Towards safer and efficient formulations: Machine learning approaches to predict drug-excipient compatibility.

Predicting drug-excipient compatibility is a critical aspect of pharmaceutical formulation design. In this study, we introduced an innovative approach that leverages machine learning techniques to improve the accuracy of drug-excipient compatibility predictions. Mol2vec and 2D molecular descriptors combined with the stacking technique were used to improve the performance of the model. This approach achieved a significant advancement in the predictive capacity as demonstrated by the accuracy, precision, recall, AUC, and MCC of 0.98, 0.87, 0.88, 0.93 and 0.86, respectively. Using the DE-INTERACT model as the benchmark, our stacking model could remarkably detect drug-excipient incompatibility in 10/12 tested cases, while DE-INTERACT managed to recognize only 3 out of 12 incompatibility cases in the validation experiments. To ensure user accessibility, the trained model was deployed to a user-friendly web platform (URL: https://decompatibility.streamlit.app/). This interactive interface accommodated inputs through various types, including names, PubChem CID, or SMILES strings. It promptly generated compatibility predictions alongside corresponding probability scores. However, the continual refinement of model performance is crucial before applying this model in practice.

Trapping and bypassing of suspended particulate matter, particulate nutrients and faecal indicator organisms in the river-estuary transition zone of a shallow macrotidal estuary.

Hydrodynamic controls of the transport of suspended particulate matter (SPM), particulate nutrients and faecal indicator organisms (FIOs) in the river-estuary transition zone (RETZ) of a shallow macrotidal estuary were studied on tidal and seasonal timescales. The RETZ was found to be a conduit for SPM rather than a zone of particle accumulation during spring tides, with complex size fractionation and biogeochemical exchanges of particulate nutrient/FIO compositions. The downstream RETZ was characterised by flood-dominant currents, but with ebb-dominant turbulence due to the suppression of flood tide turbulence by salinity stratification created by lateral convergence; this produced a net seaward mass transport of SPM. Without lateral convergence in the narrower upstream RETZ, flood-dominant currents and flood-dominant turbulence were experienced. Hence the RETZ exported SPM landwards from its upper end and seawards from its lower end - a process observed throughout the year during spring tides and low-to-mean river flows. During neap tides when SPM concentrations were reduced, the RETZ became a zone of minor particle accumulation as its lower end imported SPM landwards from the estuary and its upper end imported SPM seawards from the river. During a river flood event, net SPM flux was significantly increased and was seawards throughout the RETZ. SPM mass concentration and carbon, nitrogen, phosphorous, and FIO concentrations peaked due to local resuspension and advection of an ephemeral estuarine turbidity maximum (ETM). The ETM formed on the advancing flood tide due to entrainment of material from intertidal flats. Flocculation and settling occurred at high slack water. The ETM was reconstituted by entrainment on the ebb and was composed of larger flocs than on the flood. Particulate nutrients and FIOs were associated with flocs in the 10-200 µm range but not with smaller or larger flocs. SPM concentrations in the resuspension component and ETM exceeded microbial water quality standards, emphasising the need for monitoring practices that consider tidal dynamics. The results from this study showing periodic SPM export from, rather than prolonged accumulation in, the RETZ and the influence of particle size fractionation on biogeochemical fluxes in the RETZ, are likely to be transferable to many other embayment-type estuaries on macrotidal coasts.

Assessment of the distribution and ecological risks of heavy metals in coastal sediments in Vietnam's Mong Cai area.

Coastal sediments in the Mong Cai area were collected and analyzed for grain size, heavy metals, total organic carbon, and isotopes (210Pb, 226Ra, δ15N, δ13C) to assess sediment quality. The most common sediments were fine sand in surface sediment, very fine sand in core C1, and very coarse and coarse silt in core C2. The total organic carbon was highest in C2 next to the surface and lowest in C1, with content levels of 1.81%, 0.40%, and 0.31%, respectively. The chronology in C1 was 1877-2019 (142 years, 0-5 0 cm), with an average sedimentation rate of 0.71 cm/year. In C2, the chronology was 1944-2019 (75 years, 0-14 cm), with an average sedimentation rate of 0.27 cm/year. These δ13C and δ15N in the sediment reflect the source of the organic matter mix from the marine and terrigenous sediments. All studied heavy metals were lower than the ISQGs, with the exception of As in C1 and C2, which were higher. C1 showed a decline in As over time, while C2 As levels increased between 1996 and 2019. In terms of heavy metal pollution indexes, the geoaccumulation index (Igeo) showed that C1 and C2 were unpolluted to moderately polluted with As, with Li and Pb in C2; the enrichment factor (EF) was moderately enriched with As; the contamination factor (CF) was moderately contaminated (Pb, Cd, Fe, Mo, and Li) in C2 and C1 (Cd, As, Li) and considerably contaminated (As) in C2. The risk factor (ER) of As showed a moderate potential ecological risk in C2. The degree of contamination (CD) ranged from moderate to considerable (C1, C2), and the ecological risk (RI) was low. Although CD ranged from moderate (C1) to considerable (C2), most contamination was concentrated at the bottom of the cores. RI was low. The Mong Cai sediment quality does not currently affect the coastal area's ecosystem and fauna.

Occurrence of Marek's Disease in Backyard Chicken Flocks in Vietnam.

Marek's disease (MD) is a common lymphomatous and neuropathic disease of birds, especially chickens, and has caused significant losses to chicken production as a result of high mortality and morbidity. This study aims to determine the status of MD in backyard flocks in the Mekong Delta of Vietnam and to analyze clinical cases occurring during a year. The study was carried out from August 2018 to July 2019, during which time 16 suspected cases of chicken flocks with MD were observed, 40 chickens were subjected to anatomopathological examination, and PCR was performed for diagnosis of MD and determination of Marek's disease virus (MDV) serotypes. The results showed that all of the examined flocks were confirmed as experiencing MD. Nearly all cases were in an acute form with typical lesions of visceral lymphomas. Besides the presence of Marek's disease virus serotype 1 (MDV-1) from 100.0% of tested chicken flocks (16/16), nononcogenic turkey herpesvirus serotype 3 (MDV-3) was also found from 8 of 16 (50.0%) of examined chicken flocks. Morbidity and mortality at sampling time varied from 1% to 42.11% and 0.6% to 10%, respectively. Chicken flocks with MD vaccination had lower morbidity and mortality. These first findings confirm endemic MD in backyard chicken populations in Vietnam and confirm it continues to be a threat to chickens in backyard flocks and poultry production in general.

Presentación de la enfermedad de Marek en parvadas de pollos de traspatio en Vietnam. La enfermedad de Marek (MD) es una enfermedad linfoproliferativa y neuropática común de las aves, especialmente de los pollos y ha causado pérdidas significativas en la producción de pollos como resultado de la alta mortalidad y morbilidad. Este estudio tiene como objetivo determinar el estado de la enfermedad de Marek en parvadas de traspatio en el delta del Mekong en Vietnam y analizar los casos clínicos que ocurren durante un año. El estudio se llevó a cabo de agosto de 2018 a julio de 2019, tiempo durante el cual se observaron 16 casos sospechosos de parvadas de pollos con enfermedad de Marek, 40 pollos fueron sometidos a examen anatomopatológico y se les realizó PCR para el diagnóstico de enfermedad de Marek y determinación del serotipo del virus. Los resultados confirmaron que todas las parvadas examinadas presentaban enfermedad de Marek y casi todos los casos presentaban una forma aguda con lesiones típicas de linfomas viscerales, especialmente en el hígado. Además de la presencia del serotipo 1 del virus de la enfermedad de Marek (MDV-1) en el 100% de las parvadas de pollos analizadas (16/16), también se encontró el serotipo 3 del herpesvirus del pavo no oncogénico (MDV-3) en 8 de 16 (50.0 %) de las parvadas de pollo examinadas. La morbilidad y la mortalidad en el momento del muestreo variaron del 1% al 42.11% y del 0.6% al 10%, respectivamente. Las parvadas de pollos con vacunación contra la enfermedad de Marek tuvieron menor morbilidad y mortalidad. Estos primeros hallazgos confirman la presencia endémica del virus de la enfermedad de Marek en las poblaciones de pollos de traspatio en Vietnam y confirman que continúa siendo una amenaza para los pollos en parvadas de traspatio y para la producción avícola en general.

Deep learning models for forecasting dengue fever based on climate data in Vietnam.

BACKGROUND: 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. OBJECTIVE: 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. METHODS: 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). RESULTS AND DISCUSSION: 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. CONCLUSION: 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.

From Microurchins to V2O5 Nanowalls: Improved Synthesis through Vanadium Powder and Fast, Selective Adsorption of Methylene Blue.

Research on synthesizing micro- and nanosized materials directly from metals has attracted considerable attention because of its simplicity, ability to synthesize in large quantities, and high uniformity. This study proposes a simple method to synthesize high-uniformity or high-density V2O5 microurchins and nanowalls directly from vanadium powder. Remarkably, the synthesis condition of 60 °C for 1 h is considered to be an optimal condition to convert metals into micro- or nano-oxides. The as-synthesized V2O5 nanowalls can adsorb nearly 90% of methylene blue in the dark in 3 min. The adsorption selectivity of these samples with several pigments is investigated.

Dragon Fruit Foliage: An Agricultural Cellulosic Source to Extract Cellulose Nanomaterials.

In this report, we focus our effort to extract cellulose nanomaterials (CNs) from an agricultural cellulosic waste, Dragon Fruit foliage (DFF). DFF was first pretreated by several mechanical treatments and then bleached by chemical treatment to obtain bleached DFF. CNs were then produced from the hydrolysis of the bleached DFF catalyzed by sulfuric acid. We obtained CNs with a small diameter (50 to 130 nm) and length (100 to 500 nm) and a height of 3 to 10 nm. The CNs have a high crystallinity (crystallinity index 84.8%), high -COOH content (0.74 mmol·g-1), good thermal stability and a good Cu (II) adsorption capacity with an adsorption maximum of ~103 mg·g-1. These findings demonstrated the great potential of converting many agricultural cellulosic wastes into valuable cellulose nanomaterials.

A simple and efficient ultrasonic-assisted electrochemical approach for scalable production of nitrogen-doped TiO2nanocrystals.

In this study, we report a facile and effective approach for large-scale production of nitrogen-doped TiO2nanocrystals (UNTs) by a combination of ultrasonic irradiation and electrochemistry at room temperature using NH4NO3electrolyte as the nitrogen source. The as-prepared UNTs were then characterized by x-ray diffraction, Raman spectroscopy, x-ray photoelectron spectroscopy, scanning electron microscopy, transmission electron microscopy, and UV-visible diffuse reflectance spectroscopy. The results indicated that the nitrogen content of UNTs reached 9.3% and bandgap energy of 2.62 eV, thus gave the high photocatalytic degradation of methylene blue under visible light irradiation. The mechanism for the formation of UNTs by ultrasonic-assisted electrochemical approach was also proposed.

MoS2 nanosheets-decorated SnO2 nanofibers for enhanced SO2 gas sensing performance and classification of CO, NH3 and H2 gases.

The effect of MoS2 nanosheet (NS) decoration on the gas-sensing properties of SnO2 nanofibers (NFs) was investigated. The decorated sensors were fabricated by facile on-chip electrospinning technique and subsequently dropping MoS2 NSs-dispersed solution. The MoS2 NS decoration resulted in enhanced the response and reduced the operating temperature of SnO2 NFs towards SO2 gas. The SnO2 NF sensor decorated with the optimum density of MoS2 NSs exhibited about 10-fold enhancement in gas response to 10 ppm SO2 at 150 °C as compared with the bare SnO2 NF sensor. Furthermore, the decorated sensors exhibited an extremely low detection limit and good selectivity for SO2 gas against other interfering gases, such as CO, NH3, and H2. The enhanced SO2 gas-sensing performance of MoS2 NSs-decorated SnO2 NFs was attributed to the chemical sensitization of MoS2 NSs and charge transfer through heterojunctions between the NSs and SnO2 nanograins. The classification of toxic gases such as CO, H2, and NH3 by the MoS2 NSs-decorated SnO2 NF sensors can achieve high accuracy with linear discriminant analysis (LDA). Our results suggest that the one-dimensional nanostructures of semiconductor metal oxides decorated with two-dimensional transition metal dichalcogenides are attractive candidates for the detection of hazardous gases.

Surface-Modified Carbon Nanotubes for Enhanced Ammonia Gas Sensitivity at Room Temperature.

By electron beam evaporation, noble metals (Au, Co, Pt, and Ag) with 2 and 4 nm nominal thicknesses were coated onto multi-walled carbon nanotube layers. The metals were in the form of nanoparticles mounted onto the side walls of carbon nanotubes (CNTs) to create a metal/CNT junction. The CNTs were directly grown on patterned Pt-electrode alumina substrates through chemical vapor deposition to produce a resistivity-based ammonia gas sensor. The metallic surface-modified CNT-based sensors were found sensitive to NH3 gas at room temperature. Compared with pristine CNT sensor, the response of Au/CNTs sensor increased slightly, whereas the responses of the Pt/CNTs, Co/CNTs, and Ag/CNTs increased by two, three, and more than four times, respectively.

Anaplasma marginale and A. platys Characterized from Dairy and Indigenous Cattle and Dogs in Northern Vietnam.

Anaplasma marginale and A. platys were detected and characterized (16S rDNA sequence analysis) from dairy and indigenous cattle, and the latter in domestic dogs in Vietnam. A phylogenetic tree was inferred from 26 representative strains/species of Anaplasma spp. including 10 new sequences from Vietnam. Seven of our Vietnamese sequences fell into the clade of A. marginale and 3 into A. platys, with strong nodal support of 99 and 90%, respectively. Low genetic distances (0.2-0.4%) within each species supported the identification. Anaplasma platys is able to infect humans. Our discovery of this species in cattle and domestic dogs raises considerable concern about zoonotic transmission in Vietnam. Further systematic investigations are needed to gain data for Anaplasma spp. and members of Anaplasmataceae in animal hosts, vectors and humans across Vietnam.

Magnetic iron oxide nanoparticles decorated graphene for chemoresistive gas sensing: The particle size effects.

We report a synthesis of magnetic nanoparticles chemically immobilized onto reduced graphene oxide sheets (referred to as rGO-Fe3O4 NPs) as a gas and vapor sensing platform with precisely designed particle size of 5, 10 and 20 nm to explore their influence of particle size on sensing performance. The rGO-Fe3O4 NP sensors have been investigated their responses to different gases and volatile organic compounds (VOCs) at part-per-million (ppm) levels. Results show that the Fe3O4 NPs with smaller size (5 and 10 nm) on the rGO surface led to a lower sensitivity, while particles of a size of 20 nm have a significant enhancement of sensitivity compared to the bare rGO sensor. The rGO-Fe3O4 NP20 sensor can detect trace amounts of NO2 gas and ethanol vapor at the 1 ppm and is highly selective to the NO2 and ethanol among other tested gases and VOCs, respectively. The particle size causes different distribution behaviour of NPs over rGO surface and interspaced between them, which results in deceased or increased the surface interactions between gas and graphene. The NPs themselves contained different defects level and the charge depletion layer that affect their adsorption gas/vapor molecules, which are explained for different sensing responses.

Energy Band Gap Modulation in Nd-Doped BiFeO3/SrRuO3 Heteroepitaxy for Visible Light Photoelectrochemical Activity.

The ability of band offsets at multiferroic/metal and multiferroic/electrolyte interfaces in controlling charge transfer and thus altering the photoactivity performance has sparked significant attention in solar energy conversion applications. Here, we demonstrate that the band offsets of the two interfaces play the key role in determining charge transport direction in a downward self-polarized BFO film. Electrons tend to move to BFO/electrolyte interface for water reduction. Our experimental and first-principle calculations reveal that the presence of neodymium (Nd) dopants in BFO enhances the photoelectrochemical performance by reduction of the local electron-hole pair recombination sites and modulation of the band gap to improve the visible light absorption. This opens a promising route to the heterostructure design by modulating the band gap to promote efficient charge transfer.

Synergistic Gating of Electro-Iono-Photoactive 2D Chalcogenide Neuristors: Coexistence of Hebbian and Homeostatic Synaptic Metaplasticity.

Emulation of brain-like signal processing with thin-film devices can lay the foundation for building artificially intelligent learning circuitry in future. Encompassing higher functionalities into single artificial neural elements will allow the development of robust neuromorphic circuitry emulating biological adaptation mechanisms with drastically lesser neural elements, mitigating strict process challenges and high circuit density requirements necessary to match the computational complexity of the human brain. Here, 2D transition metal di-chalcogenide (MoS2 ) neuristors are designed to mimic intracellular ion endocytosis-exocytosis dynamics/neurotransmitter-release in chemical synapses using three approaches: (i) electronic-mode: a defect modulation approach where the traps at the semiconductor-dielectric interface are perturbed; (ii) ionotronic-mode: where electronic responses are modulated via ionic gating; and (iii) photoactive-mode: harnessing persistent photoconductivity or trap-assisted slow recombination mechanisms. Exploiting a novel multigated architecture incorporating electrical and optical biases, this incarnation not only addresses different charge-trapping probabilities to finely modulate the synaptic weights, but also amalgamates neuromodulation schemes to achieve "plasticity of plasticity-metaplasticity" via dynamic control of Hebbian spike-time dependent plasticity and homeostatic regulation. Coexistence of such multiple forms of synaptic plasticity increases the efficacy of memory storage and processing capacity of artificial neuristors, enabling design of highly efficient novel neural architectures.

Highly Transparent and Integrable Surface Texture Change Device for Localized Tactile Feedback.

Human-machine haptic interaction is typically detected by variations in friction, roughness, hardness, and temperature, which combines to create sensation of surface texture change. Most of the current technologies work to simulate changes in tactile perception (via electrostatic, lateral force fields, vibration motors, etc.) without creating actual topographical transformations. This makes it challenging to provide localized feedback. Here, a new concept for on-demand surface texture augmentation that is capable of physically forming local topographic features in any predesigned pattern is demonstrated. The transparent, flexible, integrable device comprises of a hybrid electrode system with conductive hydrogel, silver nanowires, and conductive polymers with acrylic elastomer as the dielectric layer. Desired surface textures can be controlled by a predesigned pattern of electrodes, which operates as independent or interconnected actuators. Surface features with up to a height of 0.155 mm can be achieved with a transformation time of less than a second for a device area of 18 cm2 . High transparency levels of 76% are achieved due to the judicious choice of the electrode and the active elastomer layer. The capability of localized and controlled deformations makes this system highly useful for applications such as display touchscreens, touchpads, braille displays, on-demand buttons, and microfluidic devices.

Flexible Ionic-Electronic Hybrid Oxide Synaptic TFTs with Programmable Dynamic Plasticity for Brain-Inspired Neuromorphic Computing.

Emulation of biological synapses is necessary for future brain-inspired neuromorphic computational systems that could look beyond the standard von Neuman architecture. Here, artificial synapses based on ionic-electronic hybrid oxide-based transistors on rigid and flexible substrates are demonstrated. The flexible transistors reported here depict a high field-effect mobility of ≈9 cm2 V-1 s-1 with good mechanical performance. Comprehensive learning abilities/synaptic rules like paired-pulse facilitation, excitatory and inhibitory postsynaptic currents, spike-time-dependent plasticity, consolidation, superlinear amplification, and dynamic logic are successfully established depicting concurrent processing and memory functionalities with spatiotemporal correlation. The results present a fully solution processable approach to fabricate artificial synapses for next-generation transparent neural circuits.

Tunable photoelectrochemical performance of Au/BiFeO3 heterostructure.

Ferroelectric photoelectrodes, other than conventional semiconductors, are alternative photo-absorbers in the process of water splitting. However, the capture of photons and efficient transfer of photo-excited carriers remain as two critical issues in ferroelectric photoelectrodes. In this work, we overcome the aforementioned issues by decorating the ferroelectric BiFeO3 (BFO) surface with Au nanocrystals, and thus improving the photoelectrochemical (PEC) performance of BFO film. We demonstrate that the internal field induced by the spontaneous polarization of BFO can (1) tune the efficiency of the photo-excited carriers' separation and charge transfer characteristics in bare BFO photoelectrodes, and (2) modulate an extra optical absorption within the visible light region, created by the surface plasmon resonance excitation of Au nanocrystals to capture more photons in the Au/BFO heterostructure. This study provides key insights for understanding the tunable features of PEC performance, composed of the heterostructure of noble metals and ferroelectric materials.

Control of the Metal-Insulator Transition at Complex Oxide Heterointerfaces through Visible Light.

The coupling of the localized surface plasmon resonance of Au nanoparticles is utilized to deliver a visible-light stimulus to control conduction at the LaAlO3 /SrTiO3 interface. A giant photoresponse and the controllable metal-insulator transition are characterized at this heterointerface. This study paves a new route to optical control of the functionality at the heterointerfaces.