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In this study, berberine nanoparticles (BerNPs) were prepared using a wet-milling method with zirconium balls to enhance bioavailability and expand potential applications. The particle size and physicochemical properties of the BerNPs were analyzed using field-emission scanning electron microscopy (FE-SEM), UV–vis spectroscopy, X-ray diffraction, and Fourier-transform infrared spectroscopy. The broth dilution method was used to determine the antimicrobial activity of the BerNPs against Streptococcus mutans (S. mutans). The impact of the BerNPs on the cell surface of S. mutans was evaluated through FE-SEM analysis, focusing on its ability to inhibit biofilm formation. The results demonstrated that BerNPs were produced with an average particle size of 40–65 nm. The chemical structure of BerNPs remained consistent with that of berberine, with no modifications occurring during nanoparticle preparation. The BerNPs exhibited the ability to inhibit S. mutans, with minimum inhibitory concentration and minimum bactericidal concentration values of 78.1 and 312.5 µg/mL, respectively. BerNPs caused significant damage to S. mutans cells, disrupting the cell membrane structure, and leading to cell lysis and death. Additionally, BerNPs effectively inhibited the biofilm formation of S. mutans. In summary, BerNPs demonstrated a potent inhibitory effect on the activities of S. mutans at selectively applied concentrations.

With regard to the research and application of power converters, scientists have focused on finding structures and researching control solutions for multilevel multiphase power converters (MMC). Connecting cells in series, parallel (2 Dimension-2D) to the MMC allows easy adjustment of the power and output voltage. The design of MMCs must ensure that the switching voltage is less than the switching voltage limit of the insulated gate bipolar transistor (IGBT), and that the 2D structure can easily adjust the voltage at each level by adding or removing several cells in series. A 2D structure can be designed for a wide power range, which can be quickly achieved by adjusting the number of cells (or multicell branches) in parallel. Currently, the use of 2D structures has only a few published studies on the aspect of DC/DC modulation. This study implements a decentralized carrier phase angle shift algorithm for multicell power converters coupled in series and parallel to supply single-phase alternating current (AC) loads. This paper proposes and verifies an algorithm to ensure that the carrier phase angles of cells in the 2D structure are evenly alternating, thereby improving the algorithm to balance the alternating current between parallel branches connecting the load. Reviews, analyses, and assessments were verified on a 2D structure simulation model including six parallel branches, each of which has six cells in Matlab/Simulink software, and verified by an experimental model including four branches, each of which has four cells using digital signal processing (DSP) TMS320F28379D as the controller.

A wide-spatial coverage, low-profile, pattern reconfigurable, millimeter-wave antenna array designed for Vehicle-to-Everything (V2X) communication systems, crucial for fifth-generation wireless networks. The array features a hybrid structure and beam-scanning capabilities, ensuring extensive spatial coverage in the n257 band. Utilizing PIN diode-controlled strips, the antenna enables vertical beam tilting up to ±40° on a car with less than 1 dB gain variation. Furthermore, the subarray achieves beam scanning at angles of ±32° while maintaining a gain exceeding 8 dBi. The overall circular antenna array, incorporating director and reflector elements alongside the antenna on an additive substrate, measures $74.2 \, \text {mm} \times 74.2 \, \text {mm} \times 2.2 \, \text {mm}$ , highlighting its compact design. During simulation, the array demonstrates isolation levels surpassing 20 dB and exhibits a broad $-10 \, \text {dB}$ impedance bandwidth spanning $6570 \, \text {MHz}~(24.36$ – $30.93 \, \text {GHz}$ ). The antenna array can operate in three distinct modes—(a) endfire −z, (b) endfire, and (c) endfire +z—depending on the ON/OFF state of the diodes. In each mode, the radiation performances is verified with and without the car model. To validate the simulated results, an antenna array is fabricated, and measurements encompassing beam scanning, S-parameters, and communication are conducted. The obtained results from the physical implementation align with the simulation, confirming the effectiveness of the proposed V2X antenna array for 5G wireless communication systems.

Purpose – This study explores the effect of local budget retention rate changes (RER) on total factor productivity (TFP) and its components in Vietnam. Design/methodology/approach – The study employs a two-system generalized method of moments (GMM) estimator and data from 2012 to 2019 across all 63 provinces/cities of Vietnam. Findings – The study finds that local budget retention rates significantly influence public investment, affecting scale and allocation efficiency. The reallocation of budgets between regions and from the central government to local levels incurs certain costs, often resulting in economically robust provinces experiencing reductions in their retention rates. Practical implications – Recognizing the challenges of immediate structural budget changes due to cultural and historical factors, the study suggests a more gradual policy approach. It emphasizes the importance of policy predictability, as abrupt reductions in the retention rate lead to higher costs than gradual reductions, thus implementing budget policies with a clearer timeline. This study provides insight into local budget allocation regimes and their impact on productivity in transitioning countries. Originality/value – First, the study provides fresh evidence of the impact of retention rate changes on TFP and its components in Vietnam. Second, the study provides insights into the mechanisms of the nexus of increased budget spending, capital efficiency and, most importantly, attaining improvement in education. We also offer further insights into inefficient budget allocation agents in Vietnam, especially in large cities, which should alert scholars to explore this topic further in the future.

Abstract Survivors of COVID-19 are susceptible to diminished health-related quality of life (HRQoL) and adverse psychological health, which may be exacerbated by their experiences of fear and the impact of the pandemic itself. This study aims to identify distinct fear and impact patterns related to the COVID-19 pandemic among survivors through latent profile analysis (LPA) and examine the associations of fear and impact patterns with post-traumatic stress symptoms (PTSS) and HRQoL. A total of 5,890 Vietnamese COVID-19 survivors completed the COVID-19 Impact Battery– Disability Scale (CIB-D), the Fear of COVID-19 Scale (FCoV-19 S), the Impact of Event Scale-Revised for PTSS, and the 36-Item Short Form Survey (SF-36) for HRQoL. Four distinct groups of fear and impact were identified: “Fearful and highly impacted” (26.8%), “moderately impacted yet not fearful” (22.9%), “less impacted and less fearful” (18.6%), and “mildly impacted and neutral” (31.7%). Survivors who were “less impacted and less fearful” exhibited significantly higher HRQoL scores (regression coefficient, B: 10.9; 95% confidence interval (CI): 10.0 − 11.7), both in terms of physical (B: 12.0; 95%CI: 11.1 − 12.9) and mental health (B: 19.4; 95%CI: 9.6 − 11.1), and lower PTSS levels (B: -24.5; 95%CI: -25.8 − -23.3) compared to those who were “highly impacted and fearful”. It is imperative to acknowledge the intricate association between fear, impact, and mental health to comprehensively address the diverse needs of this distinct population post-COVID-19. These findings provide insights for designing interventions and support mechanisms for COVID-19 survivors.

Abstract Background Quantification of Amyloid beta (Aβ) oligomers in plasma enables early diagnosis of Alzheimer’s Disease (AD) and improves our understanding of underlying pathologies. However, quantification necessitates an extremely sensitive and selective technology because of very low Aβ oligomer concentrations and possible interference from matrix components. Methods In this report, we developed and validated a surface-based fluorescence distribution analysis (sFIDA) assay for quantification of Aβ oligomers in plasma. Results The blood-based sFIDA assay delivers a sensitivity of 1.8 fM, an inter- and intra-assay variation below 20% for oligomer calibration standards and no interference with matrix components. Quantification of Aβ oligomers in 359 plasma samples from the DELCODE cohort reveals lower oligomer concentrations in subjective cognitive decline and AD patients than healthy Control participants. Conclusions Correlation analysis between CSF and plasma oligomer concentrations indicates an impaired clearance of Aβ oligomers that is dependent on the ApoE ε4 status.

Abstract Increasing the use of renewable energy in microgrids (MGs) offers environmental and economic benefits. However, the unpredictable and intermittent nature of available resources poses challenges for optimal MG scheduling. Hybrid AC–DC microgrids provide a solution, seamlessly integrating renewables while reducing energy losses and improving power grid reliability. Additionally, incentive‐based demand response programs promote flexible energy consumption, further mitigating the variability of renewable generation and enhancing grid stability. This paper investigates the challenges and potential of high renewable penetration in hybrid AC–DC MGs, analysing the role of demand response programs in system optimization. The microgrid's energy management is modelled using MILP, while a Stackelberg game represents the demand response program. These models are integrated to optimize energy management and demand response jointly. Simulations demonstrate the cost‐saving benefits of this integrated framework, achieved through coordinated flexible resource scheduling and incentive‐based demand response programming.

ABSTRACT Aims/Introduction Blood glucose meters are commonly used at the bedside, but most of the meters used in Hung Vuong Hospital (Ho Chi Minh City, Vietnam) are built for self‐monitoring and might not be suitable for determining glucose levels in patients. In this study, we aimed to validate the performance of six frequently used meters in our hospital using the Clinical & Laboratory Standards Institute (CLSI) standard, and investigate the hematocrit impact on the accuracy of these meters. Materials and Methods A total of 135 pregnant women who underwent a 75‐g oral glucose tolerance test consented to participate in the study at Hung Vuong Hospital. Whole blood glucose levels were measured in duplicate using meters, and hematocrit levels were measured using an Alinity h‐series analyzer. Within 5 min, plasma glucose levels were measured twice in a row using the Cobas c502 reference analyzer. For accuracy and precision, the hematocrit effect was assed using CLSI POCT12‐A3. Results Out of six evaluated meters, three meters qualified. For CLSI criterion at glucose concentration of 5.55 mmol/L, Accu‐Chek Inform II, Accu‐Chek Performa and OneTouch VerioVue achieved 97.31%, 98.08% and 99.62%, respectively. For CLSI criterion at 4.17 mmol/L, these three achieved 100%. Accu‐Chek Inform II and Accu‐Chek Performa showed an inverse correlation between glucose level and hematocrit with slopes of −0.500 (95% confidence interval −0.678 to −0.322) and −0.396 (95% confidence interval −0.569 to −0.224), whereas OneTouch VerioVue was not affected by hematocrit, with a slope of 0.207 (95% confidence interval −0.026 to 0.440). Conclusions Blood glucose meters' measurements can be affected by hematocrit, and might provide readings not within an acceptable bias. Medical organizations need to verify or validate before using on patients.

Abstract Background Misfolding and aggregation of amyloid β (Aβ), along with neurofibrillary tangles consisting of aggregated Tau species, are pathological hallmarks of Alzheimer’s disease (AD) onset and progression. In this study, we hypothesized the clearance of Aβ aggregates from the brain and body into the gut. Methods To investigate this, we used surface-based fluorescence intensity distribution analysis (sFIDA) to determine the Aβ aggregate concentrations in feces from 26 AD patients and 31 healthy controls (HC). Results Aβ aggregates were detectable in human feces and their concentrations were elevated in AD patients compared to HC (specificity 90.3%, sensitivity 53.8%). Conclusion Thus, fecal Aβ aggregates constitute a non-invasive biomarker candidate for diagnosing AD. Whether digestion-resistant Aβ aggregates in feces are secreted via the liver and bile or directly from the enteric neuronal system remains to be elucidated.

Abstract The advancement of Photovoltaic technology has undergone rapid acceleration in recent years. Nonetheless, the most significant drawback of Photovoltaic is its intermittence, making it an obvious source of power fluctuation. This study proposes a novel scheme for real‐time or intraday PV power forecasting by adopting two predictive models, namely, White‐box and Combination. The White‐box model is implemented employing mathematical calculations and statistics called Exceedance Probability. Meanwhile, the Combination model is an aggregation of several predictive models' outputs including the White‐box model and benchmark ones by dynamically adjusting the weight coefficient of each model based on their forecasting accuracy. The experimental results, which are verified on two PV systems corresponding to two case studies located at Vietnam and Australia, indicate that the two proposed models outperform other referenced models as nMAPE improves approximately 40% and 38% in terms of the first and second case study, respectively. In particular, the White‐box model shows superiority by updating the forecast every 10 min, which can adapt to the fluctuation of weather conditions whereas the Combination one yields acceptable precision, indicating its flexible application.

Printed circuit boards (PCBs) are an important component of electronic devices. Therefore, ensuring the quality of such PCBs in the manufacturing process is crucial. Especially, cracks or scratches appearing on the PCB surface pose a significant hurdle, due to their minuscule size, making them the most challenging to address. In this work, we present a real-time automated algorithm for defects inspection of printed circuit boards (PCBs) in different lighting conditions. First, the Oriented FAST and Rotated BRIEF (ORB) algorithm extracts features from the input images, then the Brute-force matching method matches these features with the ORB features template. Next, the input images are calibrated to match the size and orientation of the template data by the RANSAC (Random Sample Consensus) algorithm. Finally, the defective areas on the PCB surface are segmented by using the U-NET (i.e., a type of convolutional neural network (CNN)) model. The proposed algorithm is tested in three different lighting conditions: low light, normal light, and high light conditions. Experimental studies are conducted on a representative PCB to evaluate the defect detection capacity of the proposed algorithm and the experimental results show that the proposed system works well in the three different lighting conditions with an accuracy of up to 97%, the detection speed is 12 frames per second (FPS).

This study investigates the impact of migration on the well-being of children under 5 in Vietnam. For the purpose of this study migration is measured by the proportion of residents who moved from one province to another five years ago, while children’s well-being is proxied by nutritional status, height and weight for age, education, and childcare. Our estimation results show that migration increases the probability of child access to food, improves their nutritional status, and enhances childcare. Interestingly, the effects of migration on the nutritional status of children under 5 tend to be greater for children who has already had a better nutritional status. We find that income is a channel through which migration affects the well-being of children. Our findings suggest that promoting migration can be an effective tool for improving the well-being of children in Vietnam.

Abstract The gap between electricity supply and demand, which is the electricity imbalance, can have negative economic impacts on retail electricity suppliers. This paper presents a methodology for designing demand response (DR) programs while mitigating the negative impacts. The DR programs require the retailers to set target electricity consumption and prices of economic incentives for customers who cooperate with the DR programs. First, the target electricity consumption is determined by solving a problem of social welfare maximization in which the objective function is the sum of economic surplus of the retailers and their customers and impacts of electricity imbalance. The optimal electricity prices or the optimal rebate levels are then calculated under the principle that rational customers act to maximize their economic surplus. Through numerical simulations, the authors confirmed that the proposed methodology mitigated the impacts of electricity imbalance. Meanwhile, results of the numerical simulations showed that in practical situations, there were cases where the retailers unable to reduce the electricity imbalance profitably. Therefore, the authors additionally discuss ways to assess the electricity imbalance, which motivates the retailers to reduce the imbalance, in such cases.

Abstract Islet amyloid polypeptide (IAPP) is co-secreted with insulin from pancreatic ß-cells. Its oligomerisation is regarded as disease driving force in type 2 diabetes (T2D) pathology. Up to now, IAPP oligomers have been detected in affected tissues. IAPP oligomer concentrations in blood have not been analysed so far. Using the IAPP single-oligomer-sensitive and monomer-insensitive surface-based fluorescence intensity distribution analysis (sFIDA) technology, levels of IAPP oligomers in blood plasma from healthy controls and people with T2D in different disease stages where determined. Subsequently, the level of IAPP oligomerisation was introduced as the ratio between the IAPP oligomers determined with sFIDA and the total IAPP concentration determined with ELISA. Highest oligomerisation levels were detected in plasma of people with T2D without late complication and without insulin therapy. Their levels stand out significantly from the control group. Healthy controls presented with the lowest oligomerisation levels in plasma. In people with T2D without complications, IAPP oligomerisation levels correlated with disease duration. The results clearly demonstrate that IAPP oligomerisation in insulin-naïve patients correlates with duration of T2D. Although a correlation per se does not identify, which is cause and what is consequence, this result supports the hypothesis that IAPP aggregation is the driving factor of T2D development and progression. The alternative and conventional hypothesis explains development of T2D with increasing insulin resistance causing exhaustion of pancreatic ß-cells due to over-secretion of insulin, and thus IAPP, too, resulting in subsequent IAPP aggregation and fibril deposition in the pancreas. Further experiments and comparative analyses with primary tissues are warranted.

Abstract Anelloviruses are nonpathogenic viruses that comprise a major portion of the human virome. Despite being ubiquitous in the human population, anelloviruses (ANVs) remain poorly understood. Basic features of the virus, such as the identity of its capsid protein and the structure of the viral particle, have been unclear until now. Here, we use cryogenic electron microscopy to describe the first structure of an ANV-like particle. The particle, formed by 60 jelly roll domain-containing ANV capsid proteins, forms an icosahedral particle core from which spike domains extend to form a salient part of the particle surface. The spike domains come together around the 5-fold symmetry axis to form crown-like features. The base of the spike domain, the P1 subdomain, shares some sequence conservation between ANV strains while a hypervariable region, forming the P2 subdomain, is at the spike domain apex. We propose that this structure renders the particle less susceptible to antibody neutralization by hiding vulnerable conserved domains while exposing highly diverse epitopes as immunological decoys, thereby contributing to the immune evasion properties of anelloviruses. These results shed light on the structure of anelloviruses and provide a framework to understand their interactions with the immune system.

Abstract Background Ensuring ongoing first-aid training for primary healthcare providers (PHPs) is one of the critical strategies for providing quality health services and contributing to achieving universal health coverage. However, PHPs have received insufficient attention in terms of training and capacity building, especially in the remote areas of low-to-middle-income countries. This study evaluated the effectiveness of a first-aid training program for PHPs on a Vietnamese island and explored their perspectives and experiences regarding first-aid implementation. Methods A mixed-methods study was conducted among 39 PHPs working in community healthcare centers. The quantitative method utilized a quasi-experimental design to evaluate participants’ first-aid knowledge at three time points: pre-training, immediately post-training, and three months post-training. Sixteen of the PHPs participated in subsequent semi-structured focus group interviews using the qualitative method. Quantitative data were analyzed using repeated measures analysis of variance (ANOVA), while qualitative data were subjected to thematic analysis. Results The quantitative results showed a significant improvement in both the overall mean first-aid knowledge scores and the subdimensions of the first-aid knowledge scores among healthcare providers post-training. There was a statistically significant difference between the baseline and immediate posttest and follow-up knowledge scores (p 0.05). Three main themes emerged from the focus group discussions: perception of first-aid in remote areas, facilitators and barriers. Participants identified barriers, including infrastructure limitations, shortage of the primary healthcare workforce, inadequate competencies, and insufficient resources. Conversely, receiving considerable support from colleagues and the benefits of communication technologies in implementing first aid were mentioned as facilitators. The training bolstered the participants’ confidence in their first-aid responses, and there was a desire for continued education. Conclusions Implementing periodic first-aid refresher training for PHPs in a nationwide resource-limited setting can contribute significantly to achieving universal health coverage goals. This approach potentially enhances the preparedness of healthcare providers in these areas to deliver timely and effective first aid during emergencies, which may lead to more consistent primary healthcare services despite various challenges.

Abstract In this paper, we would like to examine whether stable de Sitter inflationary solutions appear within power-law extensions of the Starobinsky model. In particular, we will address general constraints for the existence along with the stability of de Sitter inflationary solutions in a general case involving not only the Starobinsky $$R^2$$ R 2 term but also an additional power-law $$R^n$$ R n one. According to the obtained results, we will be able to identify which extension is more suitable for an early inflationary phase rather than a late-time cosmic acceleration phase. To be more specific, we will consider several values of n to see whether the corresponding de Sitter inflationary solutions are stable or not.

This study uses a quantitative approach based on a discrete choice experiment with 586 farmers in Northern Vietnam to measure how representative market and non-market factors could influence their preferences for participating in organic certification schemes. Our results suggest that a sales contract with either flexible or guaranteed prices is a significant incentive to explain their willingness to pay higher production costs to be involved in organic certification schemes. Furthermore, providing farmers with training and technical support is also essential to motivate farmers toward organic agriculture. Finally, neighborhood cooperatives and formal leaders’ participation in organic certification could encourage farmers to convert to organic agriculture.

Acerola, known for its high vitamin C content and bioactive compounds, offers numerous health benefits. Utilizing acerola juice in the formation of water-in-oil-in-water emulsion can enhance its application potential and product diversity. This study employed the block-freeze concentration and spontaneous emulsification methods. Factors affecting emulsion properties, such as emulsifier composition and concentration, water-in-oil emulsion concentration, and stirring speed, were systematically investigated, with each subsequent experiment informed by prior results. The results demonstrated the successful fabrication of water-in-oil-in-water emulsion using Tween 80 as the emulsifier at a concentration of 25%, an optimal concentration of 21%, and stirring at 700 rpm for 15 min. The resultant emulsion exhibited a small droplet size of 0.35 ± 0.01 µm with a polydispersity index of 0.33 ± 0.04. The amounts of total phenolic content, total flavonoid content, and vitamin C, along with DPPH free radical scavenging, indicated significant antioxidant capacity, with values of 5.65 ± 0.05 mgGAE/g, 8.27 ± 0.25 mgQE/100g, 9.17 ± 0.07 mgAAE/g, and 62.78% ± 0.33, respectively.

Background: Receiving hemodialysis treatment makes end-stage renal disease (ESRD) patients highly vulnerable amidst the COVID-19 pandemic. Hence, their kidney disease quality of life (KDQOL) is affected. We aimed to examine the association between fear of COVID-19 (FCoV-19) and KDQOL, and the effect modification of Health literacy (HL) on this association.Material and Methods: A survey was conducted at 8 hospitals from July 2020 to March 2021 on 972 patients. Data collection includes socio-demographic factors, clinical parameters, HL, digital healthy diet literacy (DDL), hemodialysis diet knowledge (HDK), FCoV-19, suspected COVID-19 symptoms (S-COVID-19-S), and KDQOL.Results: Higher HL scores B = 0.13 (95% CI = 0.06–0.21, p = 0.001) and HDK scores B = 0.58 (95% CI = 0.31–0.85, p = 0.001) were associated with higher KDQOL scores. Whereas, S-COVID-19-S B = −6.12 (95% CI = −7.66 to – 4.58, p = 0.001) and FCoV-19 B = −0.91 (95% CI = −1.03 to – 0.80, p = 0.001) were associated with lower KDQOL scores. Notably, higher HL scores significantly attenuate the negative impact of FCoV-19 on overall KDQOL and the kidney disease component summary.Conclusions: In hemodialysis patients, FCoV-19 and S-COVID-19-S were associated with a lower KDQOL. Health literacy significantly mitigates the negative impact of FCoV-19 on KDQOL. Strategic public health interventions to improve HL are suggested to protect patient’s KDQOL during the pandemic.

Drought ranks among the costliest of all climate-related phenomena and manifests in various forms, posing significant challenges in understanding its influence on agriculture and natural ecosystems. Mainland Southeast Asia (MSEA), a significant region of tropical agriculture and vegetation ecosystems, has become increasingly susceptible to drought hazards. In this study, we characterized and assessed vegetation dynamics and their drought impacts using correlation analysis and explainable machine learning methods under different vegetation types and elevation zones during the dry growing seasons from 2000 to 2022. Specifically, we characterized the vegetation dynamics and their trend in space and time. Next, we assessed vegetation-drought responses in consideration of meteorological, hydrological, and agricultural droughts under different land cover types and elevation characteristics. Lastly, we used an explainable machine learning method to quantify the drivers and impacts of multifaceted droughts on natural and undisturbed vegetation ecosystems. Our findings revealed that nearly 70% of the MSEA region experienced a greening trend despite large areas of vegetative damage during the drought years. Vietnam witnessed increasing vegetation condition in most observed years while the declining trend was mainly found in Cambodia and southern Laos. Vegetation-drought responses showed that tropical vegetation had a high sensitivity to drought conditions, and stronger responses were observed in rainfed crop, mixed forest, and deciduous forest at lower altitude areas. In natural and undisturbed ecosystems, short-term meteorological and agricultural drought disturbances accounted for nearly 93% of variations in tropical vegetation. Among the different examined drought indices, the 3-month Standardized Precipitation Evapotranspiration (SPEI-3) and Temperature Condition Index (TCI) were identified as the factors having the largest influence, together explaining about 55% of the observed natural undisturbed vegetation variations. These findings deepen our understanding of tropical vegetation-drought responses and the underlying drivers of natural and undisturbed ecosystems. Such insights could provide valuable information to assist national and local governments in the MSEA region in developing effective drought management and adaptation programs to safeguard tropical agricultural production and natural ecosystems amidst growing climate challenges.

This paper presents a two-port microstrip patch antenna system with compact size and high isolation for full-duplex and multiple-input-multiple-output (MIMO) applications. The proposed miniaturization approach is to employ compact microstrip patch antenna and decoupling network as well. Here, two quarter-wavelength patch antennas are arranged in the H-plane coupled configuration with element spacing of about 0.008 λ at the center operating frequency. Besides, a defected ground structure is chosen as the decoupling network, which doesn't require any additional space and contributes to significantly reducing the overall antenna dimensions. The final antenna design with compact size of 0.49 λ × 0.37 λ × 0.01 λ has operating band from 2.45 to 2.48 GHz, in which isolation is better than 30 dB and the maximum isolation is 42 dB. Besides, the proposed antenna also achieved comparable gain of 3.8 dBi and good diversity performance. In comparison with other related works, the proposed design has smallest overall size with extremely small element spacing while obtaining comparable isolation enhancement.

Vancomycin is a critical antibiotic frequently utilized in clinical settings, with therapeutic drug monitoring (TDM) strongly advised to optimize treatment efficacy and mitigate the risk of adverse effects. However, current methods for measuring vancomycin levels in human plasma are hindered by long analysis times and complicated sample preparations. Thus, this study developed and validated a novel UPLC-MS/MS method for a rapid (with a running time of 3.5 min) and simple analysis of plasma vancomycin. To quantify vancomycin concentration in human plasma, we have developed and validated the UPLC-MS/MS method with high sensitivity, specificity, and accuracy, meeting the strict criteria according to the Food and Drugs Administration (FDA) guidelines for validation biological analysis methods. Vancomycin and atenolol (internal standard) underwent positive electrospray ionization (ESI+) and detection in multi-reaction monitoring (MRM) mode. The selected MRM transitions were m/z 725.66→144.16 for vancomycin and m/z 267.29→189.96 for atenolol. Plasma samples were precipitated using a simple mixture containing acetonitrile, methanol, and formic acid as a pH adjuster. The separation was performed using the Poroshell 120 Phenyl Hexyl Column (4.6 × 150 mm, 2.7 μm) maintained at 25 °C for 3.5 min. Isocratic elution with a mobile phase (methanol and 0.1% formic acid in a 40:60 v/v ratio) at a flow rate of 0.5 mL/min was employed. The method showed linearity (0.1–75 μg/mL) with a coefficient of determination above 0.9994 and a lower limit of quantification at 0.1 μg/mL. Precision, both intraday and interday, was below 10%, and accuracy ranged from 91.70% to 111.57%. System suitability, selectivity, stability, carryover, dilution, recovery, and matrix effect validation results all met acceptable criteria. The established UPLC-MS/MS method is expected to be a rapid, simple, and reliable tool for drug monitoring and pharmacokinetic studies, enhancing patient care during vancomycin administration.

Abstract The role of mitochondria peptides in the spreading of glioblastoma remains poorly understood. In this study, we investigated the mechanism underlying intracranial glioblastoma progression. Our findings demonstrate that the mitochondria-derived peptide, humanin, plays a significant role in enhancing glioblastoma progression through the intratumoral activation of the integrin alpha V (ITGAV)–TGF beta (TGFβ) signaling axis. In glioblastoma tissues, humanin showed a significant upregulation in the tumor area compared to the corresponding normal region. Utilizing multiple in vitro pharmacological and genetic approaches, we observed that humanin activates the ITGAV pathway, leading to cellular attachment and filopodia formation. This process aids the subsequent migration and invasion of attached glioblastoma cells through intracellular TGFβR signaling activation. In addition, our in vivo orthotopic glioblastoma model provides further support for the pro-tumoral function of humanin. We observed a correlation between poor survival and aggressive invasiveness in the humanin-treated group, with noticeable tumor protrusions and induced angiogenesis compared to the control. Intriguingly, the in vivo effect of humanin on glioblastoma was significantly reduced by the treatment of TGFBR1 inhibitor. To strengthen these findings, public database analysis revealed a significant association between genes in the ITGAV–TGFβR axis and poor prognosis in glioblastoma patients. These results collectively highlight humanin as a pro-tumoral factor, making it a promising biological target for treating glioblastoma.

Female students are a potential target that can help the economy develop and grow. Although women starting businesses has become popular, women still face many more challenges than men in the Vietnamese market. Some of them are autonomy, knowledge, and business motivation. Therefore, this study aims to evaluate the impact of entrepreneurship education on female students’ entrepreneurial intention through business motivation. At the same time, the research also examines the moderating role of autonomy in relationships. Data were collected from 356 female students at universities in Vietnam and analyzed using SmartPLS 4 software. The results of the study accepted all hypotheses in the model. The study found that business motivation mediates the relationship between entrepreneurship education and entrepreneurial intention. Autonomy has a moderating role in the relationships in the model. Therefore, universities need to improve entrepreneurship education and autonomy so that female students have more motivation to start businesses, thereby increasing the rate of female entrepreneurs in Vietnam.

Abstract Hypervirulent Klebsiella pneumoniae (hvKp) is a significant cause of severe invasive infections in Vietnam, yet data on its epidemiology, population structure and dynamics are scarce. We screened hvKp isolates from patients with bloodstream infections (BSIs) at a tertiary infectious diseases hospital in Vietnam and healthy individuals, followed by whole genome sequencing and plasmid analysis. Among 700 BSI-causing Kp strains, 100 (14.3%) were hvKp. Thirteen hvKp isolates were identified from 350 rectal swabs of healthy adults; none from 500 rectal swabs of healthy children. The hvKp isolates were genetically diverse, encompassing 17 sequence types (STs), predominantly ST23, ST86 and ST65. Among the 113 hvKp isolates, 14 (12.6%) carried at least one antimicrobial resistance (AMR) gene, largely mediated by IncFII, IncR, and IncA/C plasmids. Notably, the acquisition of AMR conjugative plasmids facilitated horizontal transfer of the non-conjugative virulence plasmid between K. pneumoniae strains. Phylogenetic analysis demonstrated hvKp isolates from BSIs and human carriage clustered together, suggesting a significant role of intestinal carriage in hvKp transmission. Enhanced surveillance is crucial to understand the factors driving intestinal carriage and hvKp transmission dynamics for informing preventive measures. Furthermore, we advocate the clinical use of our molecular assay for diagnosing hvKp infections to guide effective management.

This study examined the effect of low-frequency ultrasound (20 kHz, 1 and 5 min) on the physiochemical and structural properties of milk powder formulations with varying casein to whey ratios (0:100, 60:40, and 50:50) and calcium addition (30 mM). The ultrasound treatment led to changes in particle size, with an initial increase in aggregation followed by fragmentation. Calcium addition resulted in looser packing, as evidenced by a decrease in both bulk and tapped densities. DSC analysis indicated that calcium addition stabilized the protein–lactose matrix by increasing the glass transition temperature and reducing the number of thermal events. FTIR analysis revealed structural changes in proteins, with a decrease in β-sheet and β-turn and an increase in α-helix structures. These findings suggest that calcium plays a crucial role in reinforcing the structural integrity of the protein–lactose matrix, while ultrasound-induced mechanical forces lead to dynamic changes in particle size and protein conformation.

Background and purpose: Minimally invasive surgery for ICH has shown a significantly improved functional outcome for selected ICH patients. This study aimed to evaluate the factors influencing the outcome of supratentorial ICH patients treated with stereotactic computed tomographic (CT) guided recombinant tissue plasminogen activator (rt-PA). Methods: We retrospectively evaluated data from 80 consecutive supratentorial ICH patients between December 2017 and July 2020, analyzing their 180-day outcomes, and identifying clinical, radiological factors for good prognosis within 180 days. Results: The mean age was 55.6 years (SD 11.4). The median preoperative Glasgow Coma Scale (GCS) score was 9 (interquartile range - IQR 6–12). The mean final ICH volume was 26.5 ml (SD 27.5), with ICH volume reduction by an average of 66.7 %. Six months after the procedure, 40 patients (50 %) had favorable outcomes (modified Rankin Scale [mRS]) score 0–3). In multivariate analysis, age (odds ratio [OR] = 0.939, 95 % confidence interval (CI) = 0.894 – 0.986; p = 0.012), the GCS score before operation (OR = 1.525, 95 % CI = 1.008 – 2.309; p = 0.046), the initial midline shift (OR = 0.808, 95 % CI = 0.661 – 0.988; p = 0.038), and the residual volume hematoma (OR = 0.949, 95 % CI = 0.908 – 0.992, p = 0.020) were the significant predictors of a favorable 180-day outcome. Receiver operating characteristic curve analysis confirmed that the best cut-off point for predicting the good functional 180-day outcome was a GCS score of 9 before the procedure [area under the curve: 0.721, 95 % CI = 0.608 – 0.833, p = 0.001]. Conclusion: CT-guided thrombolysis and aspiration can be safe and effective in reducing ICH volume. A preoperation GCS score above or equal to 9 and younger age were associated with improved long-term outcomes in patients with supratentorial ICH.

Objective: To identify the efficacy and tolerability of Proteoglycan F in patients with primary knee OA.Design: A 24-week randomized, placebo-controlled, double-blind clinical trial with two arms: (1) Proteoglycan F (received 10 ​mg proteoglycan daily, for 24 weeks) and (2) control group (received placebo). Knee symptoms and joint cartilage status (evaluated by ultrasound and MRI of knee joints), quality of life, serum cytokine levels (IL-1β and TNF-α), and safety evaluation were measured before, during, and after the treatment. Results: After 24-week treatment, pain reduction (in the KOOS pain score) of at least 20% and at least 50% (NRS scale) compared to baseline in the PGF group was significantly higher than those in the control group. The PGF group had greater reductions in the total scores of subchondral bone marrow edema, and bone cocoon under cartilage on knee MRI (classification according to WORMs), which were −2.27 (-4.0; −0.51) and −1.77 (-3.08; −0.46), respectively (p ​

Background Digital Health Literacy (DHL) is crucial in navigating digital health environments, yet few studies focus on older adults. Objective Explore the associations of digital health information and resource utilization, IT-related social support, and barriers/enhancers to digital health service usage with DHL among older adults. Methods A cross-sectional study was conducted from January 2022 to April 2023, involving 417 individuals over the age of 60 who were interviewed using an instrument for collecting data on DHL, social support, barriers/enhancers influencing use of digital health resources and personal/demographic data. Multi-regression models were used to examine the associations. Results Higher DHL scores were associated with daily use of digital interaction with healthcare ( B = 0.28; 95% confidence interval [CI] = 0.07, 0.49; p = .01), daily use of other digital health resources ( B = 0.22; 95% CI = 0.05, 0.40; p = .01), ease in finding assistance for online navigation ( B = 0.27; 95% CI = 0.08, 0.45; p = .01), self-perceived digital proficiency (“usually very good at surfing the internet,” B = 0.35; 95% CI = 0.18, 0.52; p = .01), assistance from relatives/others in internet browsing ( B = 0.20; 95% CI = 0.02, 0.37; p = .02), and having access to a computer, tablet, or smartphone ( B = 0.29; 95% CI = 0.11, 0.47, p = .01). Conversely, barriers like “no access to a computer, tablet, or phone at all times” ( B = −0.19; 95% CI = −0.34, −0.04; p = .01), “difficulty understanding online content” ( B = −0.22; 95% CI = −0.36, −0.07; p = .01), and “believing to be too old for online services” ( B = −0.18; 95% CI = −0.32, −0.03; p = .02) were associated with lower DHL scores. Conclusions Engagement with digital health platforms, including making online appointments and accessing personal health records, is associated with higher DHL levels. Support from relatives or others, a modifiable attribute, is also associated with elevated DHL among older adults.

Objectives The prevalence of posttraumatic stress disorder (PTSD) has increased, particularly among individuals who have recovered from coronavirus disease 2019 (COVID-19) infection. Health literacy is considered a “social vaccine” that helps people respond effectively to the pandemic. We aimed to investigate the association between long COVID-19 and PTSD, and to examine the modifying role of health literacy in this association. Methods A cross-sectional study was conducted at 18 hospitals and health centers in Vietnam from December 2021 to October 2022. We recruited 4,463 individuals who had recovered from COVID-19 infection for at least 4 weeks. Participants provided information about their sociodemographics, clinical parameters, health-related behaviors, health literacy (using the 12-item short-form health literacy scale), long COVID-19 symptoms and PTSD (Impact Event Scale-Revised score of 33 or higher). Logistic regression models were used to examine associations and interactions. Results Out of the study sample, 55.9% had long COVID-19 symptoms, and 49.6% had PTSD. Individuals with long COVID-19 symptoms had a higher likelihood of PTSD (odds ratio [OR], 1.86; 95% confidence interval [CI], 1.63–2.12; p

Breadfruit's substantial carbohydrate content makes it a viable starch source, specifically resistant starch (RS) that helps prevent chronic diseases. This study investigated the effects of enzyme hydrolysis and microwave treatment (MT) on enriching type III RS in breadfruit. It also determined its structural and functional properties, including swelling power, solubility index, water absorption capacity, oil binding capacity, and syneresis. MT at 30 W.g-1 for 3 min resulted in the highest RS content of 74.8%, significantly surpassing pullulanase hydrolysis (1.0 U.g-1 dry basis for 12 h) at 17.3% RS. The breadfruit starch granules exhibited a regular shape, approximately 7.9 µm in length, whereas modified granules were less than 11 µm, along with observable deformation in their structural shape. In conclusion, the study demonstrates the efficacy of MT for enhancing RS content in breadfruit, highlighting its potential as a healthy functional ingredient and starch substitute.

The widespread use of virtual assistants (e.g., GPT4 and Gemini, etc.) by students in their academic assignments raises concerns about academic integrity. Consequently, various machine-generated text (MGT) detection methods, developed from metric-based and model-based approaches, were proposed and shown to be highly effective. The model-based MGT methods often encounter difficulties when dealing with source code due to disparities in semantics compared to natural languages. Meanwhile, the efficacy of metric-based MGT methods on source code has not been investigated. Moreover, the challenge of identifying machine-generated codes (MGC) has received less attention, and existing solutions demonstrate low accuracy and high false positive rates across diverse human-written codes. In this paper, we take into account both semantic features extracted from Large Language Models (LLMs) and the applicability of metrics (e.g., Log-Likelihood, Rank, Log-rank, etc.) for source code analysis. Concretely, we propose MageCode, a novel method for identifying machine-generated codes. MageCode utilizes the pre-trained model CodeT5+ to extract semantic features from source code inputs and incorporates metric-based techniques to enhance accuracy. In order to assess the proposed method, we introduce a new dataset comprising more than 45,000 code solutions generated by LLMs for programming problems. The solutions for these programming problems which were obtained from three advanced LLMs (GPT4, Gemini, and Code-bison-32k), were written in Python, Java, and C++. The evaluation of MageCode on this dataset demonstrates superior performance compared to existing baselines, achieving up to 98.46% accuracy while maintaining a low false positive rate of less than 1%.

White blood cell (WBC) recognition is still a challenging problem because of the high variability and complexity of blood cell images. Blood cell images can vary in quality, resolution, contrast, illumination, staining, and background. Blood cells can also vary in shape, size, color, texture, and distribution. Moreover, blood cells can overlap, cluster, or deform, making them challenging to segment and identify. This paper proposed an efficient automatic illumination compensation algorithm using singular value decomposition in the cosine domain (CSVDC) to enhance WBC images in the preprocessing step. Firstly, the WBC color image is split into three color channels and then mapped to the frequency domain using the discrete cosine transform (DCT) to get their DCT coefficient matrices. Next, the compensation coefficients are constructed based on the DC terms and DCT coefficient matrices’ most significant singular values. The DCT coefficient matrices are then linearly adjusted by multiplying with the compensation coefficients. Finally, three color channels are reconstructed using the inverted DCT to get the enhanced WBC image. Experimental results for the four most common PBC_dataset_normal_DIB, Raabin-WBC, BCCD, and Munich AML Morphology datasets using state-of-art deep learning models, including VGG16, GoogLeNet, and RestNet, illustrate the effectiveness of the CSVDC algorithm. In particular, on the PBC_dataset_normal_DIB dataset, when using the ResNet, the proposed enhanced WBC images have a higher average recognition rate compared to the original, ASVDF, ASVDW, and AHOSVD images by 3.82%, 2.69%, 11.37%, and 8.62%, respectively. Experimental results show that our method dramatically improves deep learning-based WBC recognition accuracy.

Abstract Among the most prevalent neurodevelopmental disorders, Autism Spectrum Disorder (ASD) is highly diverse showing a broad phenotypic spectrum. ASD also couples with a broad range of mutations, both de novo and inherited. In this study, we used a proprietary SNP genotyping chip to analyze the genomic DNA of 250 Vietnamese children diagnosed with ASD. Our Single Nucleotide Polymorphism (SNP) genotyping chip directly targets more than 800 thousand SNPs in the genome. Our primary focus was to identify pathogenic/likely pathogenic mutations that are potentially linked to more severe symptoms of autism. We identified and validated 23 pathogenic/likely pathogenic mutations in this initial study. The data shows that these mutations were detected in several cases spanning multiple biological pathways. Among the confirmed SNPs, mutations were identified in genes previously known to be strongly associated with ASD such as SLCO1B1, ACADSB, TCF4, HCP5, MOCOS, SRD5A2, MCCC2, DCC, and PRKN while several other mutations are known to associate with autistic traits or other neurodevelopmental disorders. Some mutations were found in multiple patients and some patients carried multiple pathogenic/likely pathogenic mutations. These findings contribute to the identification of potential targets for therapeutic solutions in what is considered a genetically heterogeneous neurodevelopmental disorder.

Abstract In this paper, we investigate the validity of the so-called cosmic no-hair conjecture in the framework of anisotropic inflation models of non-canonical scalar fields non-minimally coupled to a two-form field. In particular, we focus on two typical k-inflation and Dirac–Born–Infeld inflation models, in which we find a set of exact anisotropic power-law inflationary solutions. Interestingly, these solutions are shown to be stable and attractive during an inflationary phase using the dynamical system analysis. The obtained results indicate that the non-minimal coupling between the scalar and two-form fields acts as a non-trivial source of generating stable spatial anisotropies during the inflationary phase and therefore violates the prediction of the cosmic no-hair conjecture, even when the scalar field is of non-canonical forms. In connection with the Planck 2018 data, tensor-to-scalar ratios of these anisotropic solutions are investigated. As a result, it appears that the tensor-to-scalar ratio of the anisotropic power-law inflationary solution of k-inflation model turns out to be more highly consistent with the Planck 2018 data than that of Dirac-Born-Infeld model.

Soil Erosion Susceptibility Mapping (SESM) is one of the practical approaches for managing and mitigating soil erosion. This study applied four Machine Learning (ML) models, namely the Multilayer Perceptron (MLP) classifier, AdaBoost, Ridge classifier, and Gradient Boosting classifier to perform SESM in a region of Nghe An province, Vietnam. The development of these models incorporated seven factors influencing soil erosion: slope degree, slope aspect, curvature, elevation, Normalized Difference Vegetation Index (NDVI), rainfall, and soil type. These factors were determined based on 685 identified soil erosion locations. According to SHapley Additive exPlanations (SHAP) analysis, soil type emerged as the most significant factor influencing soil erosion. Among all the developed models, the Gradient Boosting classifier demonstrated the highest prediction power, followed by the MLP classifier, Ridge classifier, and AdaBoost, respectively. Therefore, the Gradient Boosting classifier is recommended for accurate SESM in other regions too, taking into account the local geo-environmental factors. HIGHLIGHTS Soil erosion has been modeled and a soil erosion susceptibility map was generated.; Several ML models, including the MLP classifier, Ada Boost, Ridge classifier, and Gradient Boosting classifier were implemented.; Developed models were tuned using the Grid Search CV technique.; The Gradient Boosting classifier performed the best.; About 33% of the study area has a high and very high susceptibility to soil erosion occurrence.;

Medical image data often face the problem of data scarcity and costly annotation processes. To overcome this, our study introduces a novel transfer learning method for medical image classification. We present a multimodal learning framework that incorporates the pre-trained PubMedCLIP model and multimodal feature fusion. Prompts of different complexities are combined with images as inputs to the proposed model. Our findings demonstrate that this approach significantly enhances image classification tasks while reducing the burden of annotation costs. Our study underscores the potential of PubMedCLIP in revolutionizing medical image analysis through its prompt-based approach and showcases the value of multi-modality for training robust models in healthcare. Code is available at:https://github.com/HongJapan/MTL_prompt_medical.git.

The evolving landscape of educational technology has not only affected the design of teaching learning contents but also the employment of methods of delivery. In Vietnam’s language education discipline, research indicates that the integration of educational technology has significantly expanded the range of delivery modalities available to educators. However, whether the existing modalities can effectively cater to the needs of diverse learning styles remains uncertain. To bridge the research gap, this study initially seeks to assess the effectiveness of commonly utilized delivery modalities in K-12 EFL education. Thirty volunteer EFL teachers from across Vietnam, representing the north, central, and south regions, participated in in-depth interviews. These teachers teach English at primary, secondary, and high schools. The main findings include their current ICT competence levels and preferences for instructional design regarding diverse modalities of delivery. Then, grounding on an in-depth analysis of their choices and perspectives, a trichronous model is proposed and innovated to accommodate diverse learning preferences and maximize learning potential. The research findings and proposal are significant for professional development trainers and teacher educators, providing valuable insights for decision-making regarding the increasing use of technology in current EFL research and practice. This study can contribute to shaping a forward-thinking approach to EFL education in an increasingly digitalized world by addressing challenges and identifying more practical practices in language teacher education.

Does government policy intervention enhance citizens’ financial well-being, particularly when considering the increased financial soundness attributed to the private sector? This study empirically addresses this question, using data from more than 200,000 individuals worldwide. To provide causal evidence, we employ a two-stage least squares (2SLS) approach with a high-dimensional fixed-effect estimator, which captures multiple levels of control and addresses endogeneity concerns. Our findings suggest that (i) improvements in financial soundness — proxied by domestic credit development — significantly increase financial satisfaction, whereas (ii) surprisingly, government interventions, whether in the form of policies tightening or loosening, tend to erode this positive effect. This outcome may reflect either (i) ineffective interventions or (ii) the government serving as a scapegoat for a decline in subjective financial well-being. Our findings imply that to optimize public satisfaction, governments should approach interventions in the private sector with caution, thereby strengthening government legitimacy.

Construction workplaces often face unforeseen collision hazards due to a decline in auditory situational awareness among on-foot workers, leading to severe injuries and fatalities. Previous studies that used auditory signals to prevent collision hazards focused on employing a classical beamforming approach to determine equipment sounds’ Direction of Arrival (DOA). No existing frameworks implement a neural network-based approach for both equipment sound classification and localization. This paper presents an innovative framework for sound classification and localization using multichannel sound datasets artificially synthesized in a virtual three-dimensional space. The simulation synthesized 10,000 multi-channel datasets using just fourteen single sound source audiotapes. This training includes a two-staged convolutional recurrent neural network (CRNN), where the first stage learns multi-label sound event classes followed by the second stage to estimate their DOA. The proposed framework achieves a low average DOA error of 30 degrees and a high F-score of 0.98, demonstrating accurate localization and classification of equipment near workers’ positions on the site.

Drought has become one of the most devastating natural risks of agricultural production and the environment in almost all climate regions. Thus, understanding the spatiotemporal characteristics of drought and its associated impacts is crucial in drought early warning management and adaptation efforts. In this study, we used the 3-month Standardized Precipitation Index (SPI-3) obtained from Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) to investigate the space–time characteristics of drought conditions. Also, this study examined the impact of the SPI-based drought on vegetation health conditions using the Advanced Very High Resolution Radiometer (AVHRR) Normalized Difference Vegetation Index (NDVI) time-series data from 1981 to 2020. The results revealed that the region experiences drought primarily between July and September, with the most prolonged drought events lasting up to five months. Morocco suffered from more frequent droughts than other countries in the region. The Mann-Kendall test showed that the trend of drought became drier over the last decade, whereas the period from 1981 to 2010 witnessed either wetting or no trends. This study also found that the response of crops and grasslands showed higher correlation with the SPI-3 and that the response of vegetation to droughts was higher during the dry season. The findings of this study provide useful information to support local and regional drought planning and adaptation programs and enhance the understanding of drought development in the region.

Abstract Cardiovascular disease (CVD) and its risk factors seem to be linked with deteriorated graft function and persists as the major cause of mortality in kidney transplant recipients (KTRs). Diet quality is associated with CVD prevention in the healthy population, however, less study focuses on KTRs. The study aimed to determine the association between diet quality indices and lipid profile abnormalities as risk factors for CVD in KTRs. This prospective study enrolled 106 KTRs who had functioning allografts from September 2016. Lipid profiles included low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), total cholesterol (TC), and triglyceride (TG) and were based on the National Cholesterol Education Program Adult Treatment Panel III recommendations. Three-day dietary data were collected by a well-trained registered dietitian. The Alternative Healthy Eating Index-Taiwan (AHEI-Taiwan), Alternative Healthy Eating Index-2010 (AHEI-2010), and Healthy Eating Index-2015 (HEI-2015) scores were calculated and divided into quartiles and compared accordingly. KTRs’ mean LDL-C, HDL-C, TC, and TG levels were 119.8 ± 36.6 mg/dL, 52.0 ± 17.9 mg/dL, 205.8 ± 43.9 mg/dL, and 160.2 ± 121.6 mg/dL, respectively. Compared with the lowest quartile, only the highest quartile of AHEI-Taiwan had lower TC and LDL-C levels. After adjustment for age, gender, energy, Charlson comorbidity index, transplant duration, and dialysis duration, logistic regression analysis revealed that the highest quartile of AHEI-Taiwan had 82% (odds ratio [OR], 0.18; 95% confidence interval [CI] 0.04–0.72, p

Abstract Epacadostat (EPA), the most advanced IDO1 inhibitor, in combination with PD-1 checkpoint inhibitor, has failed in a recent Phase III clinical trial for treating metastatic melanoma. Here we report an EPA nanovesicle therapeutic platform (Epacasome) based on chemically attaching EPA to sphingomyelin via an oxime-ester bond highly responsive to hydrolase cleavage. Via clathrin-mediated endocytosis, Epacasome displays higher cellular uptake and enhances IDO1 inhibition and T cell proliferation compared to free EPA. Epacasome shows improved pharmacokinetics and tumour accumulation with efficient intratumoural drug release and deep tumour penetration. Additionally, it outperforms free EPA for anticancer efficacy, potentiating PD-1 blockade with boosted cytotoxic T lymphocytes (CTLs) and reduced regulatory T cells and myeloid-derived suppressor cells responses in a B16-F10 melanoma model in female mice. By co-encapsulating immunogenic dacarbazine, Epacasome further enhances anti-tumor effects and immune responses through the upregulation of NKG2D-mediated CTLs and natural killer cells responses particularly when combined with the PD-1 inhibitor in the late-stage metastatic B16-F10-Luc2 model in female mice. Furthermore, this combination prevents tumour recurrence and prolongs mouse survival in a clinically relevant, post-surgical melanoma model in female mice. Epacasome demonstrates potential to synergize with PD-1 blockade for improved response to melanoma immunotherapy.