Tuning Molecular Motion Enhances Intrinsic Fluorescence in Peptide Amphiphile Nanofibers.

Peptide amphiphiles (PAs) are highly tunable molecules that were recently found to exhibit aggregation-induced emission (AIE) when they self-assemble into nanofibers. Here, we leverage decades of molecular design and self-assembly study of PAs to strategically tune their molecular motion within nanofibers to enhance AIE, making them a highly useful platform for applications such as sensing, bioimaging, or materials property characterization. Since AIE increases when aggregated molecules are rigidly and closely packed, we altered the four most closely packed amino acids nearest to the hydrophobic core by varying the order and composition of glycine, alanine, and valine pairs. Of the six PA designs studied, C16VVAAK2 had the highest quantum yield at 0.17, which is a more than 10-fold increase from other PA designs including the very similar C16AAVVK2, highlighting the importance of precise amino acid placement to anchor rigidity closest to the core. We also altered temperature to increase AIE. C16VVAAK2 exhibited an additional 4-fold increase in maximum fluorescence intensity when the temperature was raised from 5 to 65 °C. As the temperature increased, the secondary structure transitioned from ß-sheet to random coil, indicating that further packing an already aligned molecular system makes it even more readily able to transfer energy between the electron-rich amides. This work both unveils a highly fluorescent AIE PA system design and sheds insights into the molecular orientation and packing design traits that can significantly enhance AIE in self-assembling systems.

Pertussis seasonal variation in Northern Vietnam: the evidence from a tertiary hospital.

BACKGROUND: Pertussis is a highly contagious and dangerous respiratory disease that threatens children's health in many countries, including Vietnam, despite vaccine coverage. From 2015 to 2018, Vietnam experienced an increasing number of pertussis patients. Therefore, this study aimed to investigate the trend and examine the seasonal variations of pertussis in North Vietnam. METHODS: Data were collected from medical records of all under-5-year-old inpatients admitted to the National Children's Hospital in Hanoi, Vietnam (VNCH) 2015-2018. A descriptive analysis was performed to describe the distribution of incident cases by year and season. Linear multivariable regression was conducted to investigate the association between the incidence of cases and seasonality adjusted by age and vaccination status. RESULTS: We identified 1063 laboratory-confirmed patients during 2015-2018, including 247 (23.2%) severe patients. The number of pertussis patients admitted to VNCH per 1000 hospitalizations was 3.2 in 2015, compared to 1.9, 3.1, and 2.1 in 2016, 2017, and 2018, respectively. Outbreaks occurred biennially; however, there was no significant difference in the number of severe patients over this period. Most cases occurred in the hot season (509 patients, or nearly half of the study population). With the adjustment of the vaccination rate and average age, the risk of pertussis-associated hospitalization in the mild season and the hot season was 21% (95% CI [0.12; 0.3]) and 15% (95% CI [0.05; 0.25]) higher than that in the warm season, respectively. The rate of hospitalizations was high in the mild season (28.9%) and the warm season (30.8%), nearly twice as much as that in the hot season; nevertheless, the death rate was only striking high in the mild season, about 5-6 times as much as those in the other seasons. CONCLUSION: The pertussis incidence in Northern Vietnam varied between seasons, peaking in the hot season (April-July). However, severe patients and deaths increased in the mild season (December-March). Interventions, for example, communication activities on pertussis and vaccination, are of immense importance in lowering the prevalence of pertussis. In addition, early diagnoses and early warnings performed by health professionals should be encouraged.

Two New Benzoquinone Derivatives from Vietnamese Knema globularia Stems.

The chemical investigation of the stems of Knema globularia led to the isolation of two new benzoquinones derivatives, embenones A and B (1 and 2), along with three known compounds (3-5). The structures of the isolated compounds were determined using spectroscopic techniques, including HRESIMS, 1D and 2D NMR, in conjunction with comparison to existing literature data. Compounds 1 and 2 represent new carbon skeletons in nature. Furthermore, all isolated compounds were evaluated for their α-glucosidase inhibitory activity, with compounds 1-3 exhibiting superior potency relative to the positive control (acarbose, IC50 331 µM). Their IC50 values ranged from 1.40 to 96.1 µM.

Non-Heme Iron Enzymes Catalyze Heterobicyclic and Spirocyclic Isoquinolone Core Formation in Piperazine Alkaloid Biosynthesis.

We report the discovery and biosynthesis of new piperazine alkaloids-arizonamides, and their derived compounds-arizolidines, featuring heterobicyclic and spirocyclic isoquinolone skeletons, respectively. Their biosynthetic pathway involves two crucial non-heme iron enzymes, ParF and ParG, for core skeleton construction. ParF has a dual function facilitating 2,3-alkene formation of helvamide, as a substrate for ParG, and oxidative cleavage of piperazine. Notably, ParG exhibits catalytic versatility in multiple oxidative reactions, including cyclization and ring reconstruction. A key amino acid residue Phe67 was characterized to control the formation of the constrained arizonamide B backbone by ParG.

An Electrochemical Aptasensor for the Detection of Freshwater Cyanobacteria.

Aphanizomenon is a genus of cyanobacteria that is filamentous and nitrogen-fixing and inhabits aquatic environments. This genus is known as one of the major producers of cyanotoxins that can affect water quality after the bloom period. In this study, an electrochemical aptasensor is demonstrated using a specific aptamer to detect Aphanizomenon sp. ULC602 for the rapid and sensitive detection of this bacterium. The principal operation of the generated aptasensor is based on the conformational change in the aptamer attached to the electrode surface in the presence of the target bacterium, resulting in a decrease in the current peak, which is measured by square-wave voltammetry (SWV). This aptasensor has a limit of detection (LOD) of OD750~0.3, with an extension to OD750~1.2 and a sensitivity of 456.8 µA·OD750-1·cm-2 without interference from other cyanobacteria. This is the first aptasensor studied that provides rapid detection to monitor the spread of this bacterium quickly in a targeted manner.

Predictive ecological niche model for Cinnamomumparthenoxylon (Jack) Meisn. (Lauraceae) from Last Glacial Maximum to future in Vietnam.

Cinnamomumparthenoxylon (Jack) Meisn. is a tree in genus Cinnamomum that has been facing global threats due to forest degradation and habitat fragmentation. Many recent studies aim to describe habitats and assess population and species genetic diversity for species conservation by expanding afforestation models for this species. Understanding their current and future potential distribution plays a major role in guiding conservation efforts. Using five modern machine-learning algorithms available on Google Earth Engine helped us evaluate suitable habitats for the species. The results revealed that Random Forest (RF) had the highest accuracy for model comparison, outperforming Support Vector Machine (SVM), Classification and Regression Trees (CART), Gradient Boosting Decision Tree (GBDT) and Maximum Entropy (MaxEnt). The results also showed that the extremely suitable ecological areas for the species are mostly distributed in northern Vietnam, followed by the North Central Coast and the Central Highlands. Elevation, Temperature Annual Range and Mean Diurnal Range were the three most important parameters affecting the potential distribution of C.parthenoxylon. Evaluation of the impact of climate on its distribution under different climate scenarios in the past (Last Glacial Maximum and Mid-Holocene), in the present (Worldclim) and in the future (using four climate change scenarios: ACCESS, MIROC6, EC-Earth3-Veg and MRI-ESM2-0) revealed that of C.parthenoxylon would likely expand to the northeast, while a large area of central Vietnam will gradually lose its adaptive capacity by 2100.

Characterisation of the Cinnamomumparthenoxylon (Jack) Meisn (Lauraceae) transcriptome using Illumina paired-end sequencing and EST-SSR markers development for population genetics.

Cinnamomumparthenoxylon is an endemic and endangered species with significant economic and ecological value in Vietnam. A better understanding of the genetic architecture of the species will be useful when planning management and conservation. We aimed to characterize the transcriptome of C.parthenoxylon, develop novel molecular markers, and assess the genetic variability of the species. First, transcriptome sequencing of five trees (C.parthenoxylon) based on root, leaf, and stem tissues was performed for functional annotation analysis and development of novel molecular markers. The transcriptomes of C.parthenoxylon were analyzed via an Illumina HiSeqTM 4000 sequencing system. A total of 27,363,199 bases were generated for C.parthenoxylon. De novo assembly indicated that a total of 160,435 unigenes were generated (average length = 548.954 bp). The 51,691 unigenes were compared against different databases, i.e. COG, GO, KEGG, KOG, Pfam, Swiss-Prot, and NR for functional annotation. Furthermore, a total of 12,849 EST-SSRs were identified. Of the 134 primer pairs, 54 were randomly selected for testing, with 15 successfully amplified across nine populations of C.parthenoxylon. We uncovered medium levels of genetic diversity (PIC = 0.52, Na = 3.29, Ne = 2.18, P = 94.07%, Ho = 0.56 and He = 0.47) within the studied populations. The molecular variance was 10% among populations and low genetic differentiation (Fst = 0.06) indicated low gene flow (Nm = 2.16). A reduction in the population size of C.parthenoxylon was detected using BOTTLENECK (VP population). The structure analysis suggested two optimal genetic clusters related to gene flow among the populations. Analysis of molecular variance (AMOVA) revealed higher genetic variation within populations (90%) than among populations (10%). The UPGMA approach and DAPC divided the nine populations into three main clusters. Our findings revealed a significant fraction of the transcriptome sequences and these newlydeveloped novel EST-SSR markers are a very efficient tool for germplasm evaluation, genetic diversity and molecular marker-assisted selection in C.parthenoxylon. This study provides comprehensive genetic resources for the breeding and conservation of different varieties of C.parthenoxylon.

Microplastics contamination in water supply system and treatment processes.

Due to global demand, millions of tons of plastics have been widely consumed, resulting in the widespread entry of vast amounts of microplastic particles into the environment. The presence of microplastics (MPs) in water supplies, including bottled water, has undergone systematic review, assessing the potential impacts of MPs on humans through exposure assessment. The main challenges associated with current technologies lie in their ability to effectively treat and completely remove MPs from drinking and supply water. While the risks posed by MPs upon entering the human body have not yet been fully revealed, there is a predicted certainty of negative impacts. This review encompasses a range of current technologies, spanning from basic to advanced treatments and varying in scale. However, given the frequent detection of MPs in drinking and bottled water, it becomes imperative to implement comprehensive management strategies to address this issue effectively. Consequently, integrating current technologies with management options such as life-cycle assessment, circular economy principles, and machine learning is crucial to eliminating this pervasive problem.

Growth of freshwater cyanobacterium Aphanizomenon sp. ULC602 in different growing and nutrient conditions.

Aphanizomenon sp. ULC602, recently isolated in a Belgian lake, is a filamentous, nitrogen-fixing, freshwater cyanobacterium that is one of the primary producers of cyanotoxins following its bloom formation, causing water contamination. This study aims to evaluate the effects of growing conditions and essential nutrients on the growth of Aphanizomenon sp. ULC602 via its production of chlorophyll-a (Chlo-a). Our results indicated that this bacterium could grow well at temperatures ranging from 18 to 25°C with an optimal pH of 6.0-7.5 under continuous lighting. It grew slowly in the absence of a carbon source or at lower carbon concentrations. The addition of nitrogen from nitrate and urea led to a less than 50% reduction of Chlo-a content compared to the medium lacking nitrogen. The iron bioavailability significantly stimulated the Chlo-a production, but it was saturated by an iron concentration of 0.115 mM. Moreover, a decrease in Chlo-a biomass was observed under sulfur deficiency. The bacterium could not grow well in media containing various phosphorus sources. In conclusion, as the growth and consequent forming bloom of cyanobacteria can be stimulated or inhibited by environmental conditions and eutrophication, our investigation could contribute to further studies to control the blooming of the target bacterium in freshwater.

Streamlining apartment provider evaluation: A spherical fuzzy multi-criteria decision-making model.

In the context of the thriving real estate market in developing countries like Vietnam, understanding consumer preferences and effectively addressing them through a comprehensive multi-criteria decision-making (MCDM) framework is paramount for real estate providers. This study presents a two-stage MCDM model that integrates the Delphi technique and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) based on Spherical Fuzzy Sets (SFSs). Initially, the SF-Delphi technique validates critical criteria influencing customers' apartment selection in Vietnam. Secondly, the SF-TOPSIS method evaluates the top ten apartment providers. To ensure robustness and validity, a comparative analysis compares the results with those from the Intuitionistic Fuzzy TOPSIS (IF-TOPSIS) and Fuzzy TOPSIS (F-TOPSIS) methods. Subsequently, five rank correlation coefficients (Spearman, Kendall, Goodman-Kruskal, Weighted rank measure of correlation, Weighted Similarity) are used to assess the relationships between various TOPSIS techniques applied to apartment suppliers in Vietnam. The correlation coefficients demonstrate strong agreement among the TOPSIS methods, with the smallest coefficient being 0.7778, surpassing the threshold of 0.7. This high level of consistency confirms the efficacy of the proposed TOPSIS approach with different Fuzzy Sets in reliably evaluating customers' preferences for apartment suppliers. Notably, the legal aspect's prominence underscores its critical role in shaping customer choices, emphasizing the significance of considering legal factors in the context of apartment supply and demand in Vietnam. Furthermore, using SFSs makes this approach particularly suited to capture consumer perceptions within the dynamic and uncertain business environment characterized by volatility, uncertainty, complexity, and ambiguity (VUCA).