Determination of Critical Dimensions of Microchannels to Ensure the Electrokinetic Biomolecule Preconcentration: Analytical and Numerical Studies.

Preconcentration of biomolecules based on ion concentration polarization (ICP) has been splendidly applied to various biomedical and chemical processes. However, in many circumstances, biomolecule preconcentration could not occur due to the lack of full studies on the preconcentration mechanism, especially on the effect of microchannel dimensions. In this work, we provide analytical studies on the critical dimensions (minimum and maximum) of microchannels for the preconcentration of biomolecules. These formulas are verified with the numerical results by fully solving the coupled governing equations: Poisson-Nernst-Planck and Navier-Stokes experiments with appropriate boundary conditions and assumptions. In addition, we examine the impact of operational parameters, such as electric potentials and critical external pressures, on the formation of the preconcentration. Moreover, two important results are provided for the first time, including the position of the preconcentrated biomolecule region and the concentration enhancement factor of the biomolecules. These analytical and numerical results are consistent with experimental observations and, therefore, could provide sharp insight into the mechanism of biomolecule preconcentration and give useful guidelines to better design and optimize ICP-based microfluidic preconcentration devices.

Multiphysics analytical and numerical studies of biomolecule preconcentration utilizing ion concentration polarization: a case study of convergent microchannels.

A convergent sector in microfluidic devices utilizing ion concentration polarization (ICP) can help increase the preconcentration rate and the concentration enhancement factor (CEF) of biomolecules. In this work, we present a detailed study of the nozzle-like-squeeze effect of a convergent channel on the preconcentration of biomolecules. By numerically solving coupled Nernst-Planck-Poisson-Navier-Stokes governing equations for the 2D channel model, we report the first study on the critical width of a convergent region in the channel to retain the advantage of the nozzle-like-squeeze effect in speeding up preconcentration and augmenting CEF. In addition, we investigated the impact of the location and the dimensions of a convergent sector on the mechanism of biomolecule preconcentration. The location of an ion-selective membrane was also determined to ensure that biomolecules are focused on the convergent region of the channel. Moreover, we introduce analytical studies to compare and verify simulation findings. Specifically, the formulas for the critical dimensions of a convergent channel, location of a preconcentrated biomolecule plug, and position of an ion-selective membrane are presented. Furthermore, important working parameters, including electric potentials and hydrostatic pressures, were examined to scrutinize their effect on convergent concentrators. These detailed analytical solutions and numerical simulation results are consistent with experimental observations, providing deep insights into the ICP phenomenon and the preconcentration mechanism of biomolecules in convergent microfluidic concentration devices.

Prediction of Changes in Functional Outcomes During the First Year After Inpatient Stroke Rehabilitation: A Longitudinal Study.

OBJECTIVE: To identify meaningful changes in patients in 3 functional domains (basic mobility [BM], daily activity [DA], and applied cognition [AC]) after discharge from inpatient stroke rehabilitation and to identify the predictors of 1-year functional improvement. DESIGN: A longitudinal, multicenter, prospective cohort study. SETTING: The acute care wards of 3 hospitals in the Greater Taipei area of Taiwan. PARTICIPANTS: Five hundred patients with stroke in acute care wards (mean age=60±12.2 years, 62% men, N=500). INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURE(S): The Mandarin version of the Activity Measure for Post-Acute Care (AM-PAC) short forms were assessed at discharge and 3-, 6-, and 12-month follow-up. The minimal detectable change (MDC) was used to categorize changes in the scores as improved and unimproved at the 4 time points. RESULTS: The mean scores of the AM-PAC BM and DA subscales substantially increased over the first 3 months after discharge (86% of participants exhibited improvement) and slightly increased during the subsequent 9 months (5∼26% of participants exhibited improvement). However, the mean score of the AC subscale decreased within the first 3 months and increased over the subsequent 9 months (22-23% of participants exhibited improvement). The BM, AC scores at discharge were the dominant predictors of subsequent functional improvement (P<.05). Patients with a higher functional stage at discharge were more likely to experience significant improvement. CONCLUSION: This study established the capacity of the AM-PAC to predict functional improvement in 3 domains during the early, middle, and late stages of recovery. The findings can assist clinicians in identifying patients at risk of unfavorable long-term functional recovery and providing such patients with tailored interventions during the early stage of rehabilitation.

Identify Primary Air Pollution Sources of BTEX by Using Positive Matrix Factorization (PMF): A Case Study of Ho Chi Minh City, Vietnam.

Ho Chi Minh City (HCMC) is one of the main socioeconomic and financial centers of Vietnam. The city also faces serious air pollution. However, the city polluted with benzene, toluene, ethylbenzene, and xylene (BTEX) has rarely been studied. We used positive matrix factorization (PMF) to analyze BTEX concentrations measured at two sampling locations to identify the main sources of BTEX in HCMC. The locations represented residential area (i.e., To Hien Thanh) and industrial area (i.e., Tan Binh Industrial Park). At the To Hien Thanh location, the average concentrations of benzene, ethylbenzene, toluene, and xylene were 6.9, 14.4, 4.9, and 12.7 µg/m3, respectively. At the Tan Binh location, the average concentrations of benzene, ethylbenzene, toluene, and xylene were 9.8, 22.6, 2.4, and 9.2 µg/m3, respectively. The results showed that PMF was a reliable model for source apportionment in HCMC. Traffic activities were the main sources of BTEX. Besides, industrial activities also contributed to BTEX emissions, especially the location near the industrial park. The majority of BTEXs at the To Hien Thanh sampling site come from traffic sources accounting for 56.2%. Activities from traffic and photochemical reactions (42.7%) and industrial sources (40.5%) were the main sources affecting BTEX emissions at the sampling site of Tan Binh Industrial Park. This study can be used as a reference for mitigation solutions to reduce the BTEX emission in HCMC.

Graphene Nanoparticles for Ultralow Friction at Extremely High Pressures and Temperatures.

This study uses the molecular dynamics approach to design graphene nanoparticles from the graphene sheets seeded randomly and investigates their lubricity. These nanoparticles are found to provide stable lubrication at extremely high pressure and temperature of up to 15 GPa and 2000 K, respectively. From the influences of both nanoparticle and graphene, the friction between the diamond slab and the nanoparticles shows ultralow values of the friction coefficient of 0.0034-0.0162 under 1-15 GPa and 300 K and 0.0065-0.0338 under 300-2000 K and 1 or 10 GPa. Providing stable lubrication and ultralow friction under these conditions is the large advantage of graphene nanoparticles.

Structural order of water molecules around polyrotaxane including PEG, α-cyclodextrin, and α-lipoic acid linker on gold surface by molecular dynamics simulations.

In materials science, water plays an important part, especially at the molecular level. It shows various properties when sorbed onto surfaces of polymers. The structure of the molecular water ensemble in the vicinity of the polymers is under discussion. In this study, we used molecular dynamics methods to analyze the structure of water in the vicinity of the polymer polyrotaxane (PR), composed of α-cyclodextrins (α-CDs), a poly(ethylene glycol) (PEG) axial chain, and α-lipoic acid linkers, at various temperatures. The distribution of water around the functional groups, hydrogen bond network, and tetrahedral order were analyzed to classify the various types of water around the polymer. We found that the tetrahedral order of water had a strained relationship from the XES experiment. Four water regions were separated from each other in the vicinity of 1 to 5 Å around PR. The intermediate and non-freezing water were formed due to the interaction between water molecules and the functional groups, such as hydroxyl, ether, and ester.

Essential Oils from the Leaves, Stem, and Roots of Blumea lanceolaria (Roxb.) Druce in Vietnam: Determination of Chemical Composition, and In Vitro, In Vivo, and In Silico Studies on Anti-Inflammatory Activity.

Blumea lanceolaria (Roxb.) Druce, a flowering plant, is used for treating cancer and inflammatory diseases. In this study, we determined the chemical composition of the EOs extracted from the leaves (LBEO), stem (SBEO), and roots (RBEO) of B. lanceolaria and analyzed their anti-inflammation potential. Overall, 30 compounds representing 99.12%, 98.44%, and 96.89% of total EO constituents of the leaves, stem, and roots, respectively, were identified using GC-MS. ELISA, Western blotting, and qRT-PCR studies showed that LBEO, SBEO, and RBEO inhibited multiple steps in the inflammatory responses in the RAW 264.7 cell model, including NO production; TNF-α, IL-6, iNOS, and COX-2 transcription and translation; and phosphorylation of IκBα and p65 of the NF-κB pathway. In the carrageenan-induced paw edema model, all three EOs inhibited paw edema at both early and delayed phases. Molecular docking studies indicated that the main components of B. lanceolaria EOs (BEOs) targeted and inhibited major components of inflammation-related pathways, including the arachidonic acid metabolic pathway, NF-κB pathway, and MAPK pathway. We present the first study to characterize the chemical composition of BEOs and confirm their potent anti-inflammatory effects in in vitro, in vivo, and in silico analysis. These results can facilitate the development of effective anti-inflammatory drugs with limited side effects in the future.

Cultivation of Caenorhabditis elegans on new cheap monoxenic media without peptone.

The study of species biodiversity within the Caenorhabditis genus of nematodes would be facilitated by the isolation of as many species as possible. So far, over 50 species have been found, usually associated with decaying vegetation or soil samples, with many from Africa, South America and Southeast Asia. Scientists based in these regions can contribute to Caenorhabditis sampling and their proximity would allow intensive sampling, which would be useful for understanding the natural history of these species. However, severely limited research budgets are often a constraint for these local scientists. In this study, we aimed to find a more economical, alternative growth media to rear Caenorhabditis and related species. We tested 25 media permutations using cheaper substitutes for the reagents found in the standard nematode growth media (NGM) and found three media combinations that performed comparably to NGM with respect to the reproduction and longevity of C. elegans. These new media should facilitate the isolation and characterization of Caenorhabditis and other free-living nematodes for the researchers in the poorer regions such as Africa, South America, and Southeast Asia where nematode diversity appears high.

Molecular typing of conjunctivitis-causing adenoviruses in Hanoi, Vietnam from 2017 to 2019 and complete genome analysis of the most prevalent type (HAdV-8).

Adenoviral conjunctivitis is a common epidemic worldwide. In Vietnam, up to 80,000 patients are infected with adenoviral conjunctivitis annually. However, there are few investigations on the pathogenic adenoviruses that cause conjunctivitis. In total, 120 eye-swab samples were collected from patients with viral conjunctivitis symptoms in Hanoi, Vietnam from 2017 to 2019. Human adenoviruse (HAdV) was detected in 67 samples (55.83%) using polymerase chain reaction amplification of at least one of three HAdV-specific marker genes (hexon, penton, and fiber). Of the 67 HAdV samples, 46 samples could be analyzed by all three marker genes. DNA sequence analysis and phylogenetic tree building based on the three marker genes from the 46 HAdV samples revealed five different HAdV types associated with conjunctivitis in Hanoi, including HAdV-3 (4.3%), HAdV-4 (2.2%), HAdV-8 (89.1%), HAdV-37 (2.2%), and a potential recombinant type between types HAdV-8 and HAdV-3 (2.2%). This showed that HAdV-8 was the most common type identified in Hanoi. Complete genome analysis of HAdV-8 isolated from a Vietnamese patient (VN2017) using Sanger sequencing revealed 34 unique nucleotide changes, indicating that the adenovirus continuously accumulates new mutations. Hence, continuous surveillance of HAdV-8 changes in Vietnam is necessary in the future.

Enhanced Electron Transfer Mediated by Conjugated Polyelectrolyte and Its Application to Washing-Free DNA Detection.

Direct electron transfer between a redox label and an electrode requires a short working distance (<1-2 nm), and in general an affinity biosensor based on direct electron transfer requires a finely smoothed Au electrode to support efficient target binding. Here we report that direct electron transfer over a longer working distance is possible between (i) an anionic π-conjugated polyelectrolyte (CPE) label having many redox-active sites and (ii) a readily prepared, thin polymeric monolayer-modified indium-tin oxide electrode. In addition, the long CPE label (∼18 nm for 10 kDa) can approach the electrode within the working distance after sandwich-type target-specific binding, and fast CPE-mediated oxidation of ammonia borane along the entire CPE backbone affords high signal amplification.

A quantitative chemical proteomics approach to profile the specific cellular targets of andrographolide, a promising anticancer agent that suppresses tumor metastasis.

Drug target identification is a critical step toward understanding the mechanism of action of a drug, which can help one improve the drug's current therapeutic regime and expand the drug's therapeutic potential. However, current in vitro affinity-chromatography-based and in vivo activity-based protein profiling approaches generally face difficulties in discriminating specific drug targets from nonspecific ones. Here we describe a novel approach combining isobaric tags for relative and absolute quantitation with clickable activity-based protein profiling to specifically and comprehensively identify the protein targets of andrographolide (Andro), a natural product with known anti-inflammation and anti-cancer effects, in live cancer cells. We identified a spectrum of specific targets of Andro, which furthered our understanding of the mechanism of action of the drug. Our findings, validated through cell migration and invasion assays, showed that Andro has a potential novel application as a tumor metastasis inhibitor. Moreover, we have unveiled the target binding mechanism of Andro with a combination of drug analog synthesis, protein engineering, and mass-spectrometry-based approaches and determined the drug-binding sites of two protein targets, NF-κB and actin.

An Ionic 1,4-Bis(styryl)benzene-Based Fluorescent Probe for Mercury(II) Detection in Water via Deprotection of the Thioacetal Group.

Highly sensitive and selective mercury detection in aqueous media is urgently needed because mercury poisoning usually results from exposure to water-soluble forms of mercury by inhalation and/or ingesting. An ionic conjugated oligoelectrolye (M1Q) based on 1,4-bis(styryl)benzene was synthesized as a fluorescent mercury(II) probe. The thioacetal moiety and quaternized ammonium group were incorporated for Hg2+ recognition and water solubility. A neutral Hg2+ probe (M1) was also prepared based on the same molecular backbone, and their sensor characteristics were investigated in a mixture of acetonitrile/water and in water. In the presence of Hg2+, the thioacetal group was converted to aldehyde functionality, and the resulting photoluminescence intensity decreased. In water, M1Q successfully demonstrated highly sensitive detection, showing a binding toward Hg2+ that was ~15 times stronger and a signal on/off ratio twice as high, compared to M1 in acetonitrile/water. The thioacetal deprotection by Hg2+ ions was substantially facilitated in water without an organic cosolvent. The limit of detection was measured to be 7 nM with a detection range of 10-180 nM in 100% aqueous medium.

Specificity and inhibitory mechanism of andrographolide and its analogues as antiasthma agents on NF-κB p50.

Andrographolide (1) is a diterpenoid lactone with an α,ß-unsaturated lactone group that inhibits NF-κB DNA binding. Andrographolide reacts with the nucleophilic Cys62 of NF-κB p50 through a Michael addition at the Δ(12(13)) exocylic double bond to form a covalent adduct. Using computer docking, site-directed mutagenesis, and mass spectrometry, the noncovalent interactions between andrographolide and additional binding site residues other than Cys62 were found to be essential for the covalent incorporation of andrographolide. Furthermore, the addition reaction of andrographolide on Cys62 was highly dependent on the redox conditions and on the vicinity of nearby, positively charged Arg residues in the conserved RxxRxR motif. The reaction mechanisms of several of the analogues were determined, showing that 14-deoxy-11,12-didehydroandrographolide (8) reacts with NF-κB p50 via a novel mechanism distinct from andrographolide. The noncovalent interaction and redox environment of the binding site should be considered, in addition to the electrophilicity, when designing a covalent drug. Analogues similar in structure appear to use distinct reaction mechanisms and may have very different cytotoxicities, e.g., compound 6.

Improving human activity classification based on micro-doppler signatures of FMCW radar with the effect of noise.

Nowadays, classifying human activities is applied in many essential fields, such as healthcare, security monitoring, and search and rescue missions. Radar sensor-based human activity classification is regarded as a superior approach in comparison to other techniques, such as visual perception-based methodologies and wearable gadgets. However, noise usually exists throughout the process of extracting raw radar signals, decreasing the quality and reliability of the extracted features. This paper presents a novel method for removing white Gaussian noise from raw radar signals using a denoising algorithm before classifying human activities using a deep convolutional neural network (DCNN). Specifically, the denoising algorithm is used as a preprocessing step to remove white Gaussian noise from the input raw radar signal. After that, a lightweight Cross-Residual Convolutional Neural Network (CRCNN) with adaptable cross-residual connections is suggested for classification. The analysis results show that the denoising algorithm with a range-bin interval of 3 and a cut-threshold value of 3 achieves the best denoising effect. When the denoising algorithm was applied to the dataset, CRCNN improved the right classification rate by up to 10% compared to the recognition results achieved with the original noise-added dataset. Additionally, a comparison of the CRCNN with the denoising algorithm solution with six cutting-edge DCNNs was conducted. The experimental results reveal that the proposed model greatly outperforms the others.

Screening for Hypertension in Adults of a Northern Delta Province in Vietnam.

BACKGROUND: The proportion of people with hypertension is increasing, and those affected are relatively younger. Worldwide, it is estimated that people with high blood pressure are more than 1.5 billion people. In Vietnam, from 2002 to 2008, according to a national survey on hypertension and its risk factors within the prevention and control of cardiovascular disease program, the prevalence of hypertension was 25.1%. This is alarming because high blood pressure can cause serious complications, including death. OBJECTIVE: The study aimed to explore the blood pressure characteristics and hypertension prevalence in adults in a northern delta province of Vietnam, and describe some risk factors in hypertensive subjects screened through the program. METHODS: This was a cross-sectional study collecting data from people aged 18 years or older in 10 cantons and the city of Nam Dinh from July 15th to July 31st, 2020. Using semi-automatic OMRON sphygmomanometers, sitting blood pressure was measured three times according to standardized methods specified by the Ministry of Health and two National Vascular Societies. RESULTS: Blood pressure screening of 183,632 adults included 84,438 males, which accounted for 45.98%, with an average age of 60.36 ± 13.18 years. The estimated prevalence of hypertension was 27.20% (95% CI: 27.00% - 27.41%). The older the age, the higher the rate of hypertension in both sexes; the prevalence of hypertension over 65 years was 45.36%. Hypertension grade 1 accounted for 17.14%, followed by hypertension at grade 2 at 6.69%, and grade 3 at 1.15%; notably, the percentage of prehypertension accounted for 49.64%. The percentage of treated hypertension in Nam Dinh province was 56.85%, but the percentage of uncontrolled hypertension was 85.63%. CONCLUSION: The prevalence of hypertension in Nam Dinh province was relatively high (27.20%), although the number of treated patients was also high (56.85%); moreover, the proportion of uncontrolled hypertension remained extremely high (85.63%). Local campaigns and suitable interventions are required to detect hypertension in the early stages and increase awareness for treatment in the population.

PanKA: Leveraging population pangenome to predict antibiotic resistance.

Machine learning has the potential to be a powerful tool in the fight against antimicrobial resistance (AMR), a critical global health issue. Machine learning can identify resistance mechanisms from DNA sequence data without prior knowledge. The first step in building a machine learning model is a feature extraction from sequencing data. Traditional methods like single nucleotide polymorphism (SNP) calling and k-mer counting yield numerous, often redundant features, complicating prediction and analysis. In this paper, we propose PanKA, a method using the pangenome to extract a concise set of relevant features for predicting AMR. PanKA not only enables fast model training and prediction but also improves accuracy. Applied to the Escherichia coli and Klebsiella pneumoniae bacterial species, our model is more accurate than conventional and state-of-the-art methods in predicting AMR.

Shear flow of an electrically charged fluid by ion concentration polarization: scaling laws for electroconvective vortices.

We consider electroconvective fluid flows initiated by ion concentration polarization (ICP) under pressure-driven shear flow, a scenario often found in many electrochemical devices and systems. Combining scaling analysis, experiment, and numerical modeling, we reveal unique behaviors of ICP under shear flow: a unidirectional vortex structure, its height selection, and vortex advection. Determined by both the external pressure gradient and the electric body force, the dimensionless height of the sheared electroconvective vortex is shown to scale as (ϕ(2)/U(HP))(1/3), which is a clear departure from the previous diffusion-drift model prediction. To the best of our knowledge, this is the first microscopic characterization of ion concentration polarization under shear flow, and it firmly establishes electroconvection as the mechanism for an overlimiting current in realistic, large-area ion exchange membrane systems such as electrodialysis. The new scaling law has significant implications on the optimization of electrodialysis and other electrochemical systems.

Ratiometric fluorescent ion detection in water with high sensitivity via aggregation-mediated fluorescence resonance energy transfer using a conjugated polyelectrolyte as an optical platform.

A cationic conjugated polyelectrolyte was designed and synthesized based on poly(fluorene-co-phenylene) containing 5 mol% benzothiadiazole (BT) as a low energy trap and 15-crown-5 as a recognizing group for potassium ions. A potassium ion can form a sandwich-type 2:1 Lewis acid-based complex with 15-crown-5, to cause the intermolecular aggregation of polymers. This facilitates inter-chain fluorescence resonance energy transfer (FRET) to a low-energy BT segment, resulting in fluorescent signal amplification, even at dilute analyte concentrations. Highly sensitive and selective detection of K(+) ions was demonstrated in water. The linear response of ratiometric fluorescent signal as a function of [K(+) ] allows K(+) quantification in a range of nanomolar concentrations with a detection limit of ≈0.7 × 10(-9) M.

Photodegradable antimicrobial agents: towards structure optimization.

Antibiotic resistance continues to be an ominous threat facing human health globally and urgent action is required to limit the loss of human life. The pollution of antibiotics into the environment is one of the drivers behind the crisis. With this in mind, we have developed novel photodecomposable antimicrobial agents based on an ethanolamine scaffold, which upon photoirradiation decomposes into two major inactive fragments. Herein we describe our further work on the synthesis of novel ethanolamines with a particular focus on structure activity relationship, resulting in four new active compounds which photodecomposed into inactive fragments.

Effects of common full-sib families on accuracy of genomic prediction for tagging weight in striped catfish Pangasianodon hypophthalmus.

Common full-sib families (c 2 ) make up a substantial proportion of total phenotypic variation in traits of commercial importance in aquaculture species and omission or inclusion of the c 2 resulted in possible changes in genetic parameter estimates and re-ranking of estimated breeding values. However, the impacts of common full-sib families on accuracy of genomic prediction for commercial traits of economic importance are not well known in many species, including aquatic animals. This research explored the impacts of common full-sib families on accuracy of genomic prediction for tagging weight in a population of striped catfish comprising 11,918 fish traced back to the base population (four generations), in which 560 individuals had genotype records of 14,154 SNPs. Our single step genomic best linear unbiased prediction (ssGLBUP) showed that the accuracy of genomic prediction for tagging weight was reduced by 96.5%-130.3% when the common full-sib families were included in statistical models. The reduction in the prediction accuracy was to a smaller extent in multivariate analysis than in univariate models. Imputation of missing genotypes somewhat reduced the upward biases in the prediction accuracy for tagging weight. It is therefore suggested that genomic evaluation models for traits recorded during the early phase of growth development should account for the common full-sib families to minimise possible biases in the accuracy of genomic prediction and hence, selection response.