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The development of soft computing methods has had a significant influence on the subject of autonomous intelligent agriculture. This paper offers a system for autonomous greenhouse navigation that employs a fuzzy control algorithm and a deep learning-based disease classification model for tomato plants, identifying illnesses using photos of tomato leaves. The primary novelty in this study is the introduction of an upgraded Deep Convolutional Generative Adversarial Network (DCGAN) that creates augmented pictures of disease tomato leaves from original genuine samples, considerably enhancing the training dataset. To find the optimum training model, four deep learning networks (VGG19, Inception-v3, DenseNet-201, and ResNet-152) were carefully compared on a dataset of nine tomato leaf disease classes. These models have validation accuracy of 92.32%, 90.83%, 96.61%, and 97.07%, respectively, when using the original PlantVillage dataset. The system then uses an enhanced dataset with ResNet-152 network design to achieve a high accuracy of 99.69%, as compared to the original dataset with ResNet-152's accuracy of 97.07%. This improvement indicates the use of the proposed DCGAN in improving the performance of the deep learning model for greenhouse plant monitoring and disease detection. Furthermore, the proposed approach may have a broader use in various agricultural scenarios, potentially altering the field of autonomous intelligent agriculture. [ABSTRACT FROM AUTHOR]

Neonatal intensive care unit (NICU), particularly in treating developmental and epileptic encephalopathy (DEE) and metabolic epilepsy (ME), requires a deep understanding of their complex etiologies and treatment responses. After excluding treatable cases such as infectious or autoimmune encephalitis, our focus shifted to a more challenging subgroup of 59 patients for in-depth genetic analysis using exome sequencing (ES). The ES analysis identified 40 genetic abnormalities, significantly including de novo variants. Notably, we found structural variation as duplications in regions 2q24.3, including SCN1A and SCN2A were observed in 7 cases. These genetic variants, impacting ion channels, glucose transport, transcription regulation, and kinases, play a crucial role in determining medication efficacy. More than one-third (34.2%) of patients with DEE had an unfavorable response to anti-seizure medications (ASMs) in the chronic phase. However, since the ketogenic supplementary diet showed a positive effect, more than three-quarters (80%) of these drug-resistant patients improved during a 3-month follow-up. In contrast, the ME had a lower adverse reaction rate of 9.1% (2/22) to specialized medications, yet there were 5 fatalities and 10 cases with unidentified genetic etiologies. This study suggests the potential of categorizing drug-resistant variants and that a ketogenic diet could be beneficial in managing DEE and ME. It also opens new perspectives on the mechanisms of the ketogenic diet on the discovered genetic variants. [ABSTRACT FROM AUTHOR]

Precise measurement of magnetic fields is essential for various applications, such as fundamental physics, space exploration, and biophysics. Although recent progress in quantum engineering has assisted in creating advanced quantum magnetometers, there are still ongoing challenges in improving their efficiency and noise resistance. This study focuses on using symmetric graph state resources for quantum magnetometry to enhance measurement precision by analyzing the estimation theory under time-homogeneous and time-inhomogeneous noise models. The results show a significant improvement in estimating both single and multiple Larmor frequencies. In single Larmor frequency estimation, the quantum Fisher information spans a spectrum from the standard quantum limit to the Heisenberg limit within a periodic range of the Larmor frequency, and in the case of multiple Larmor frequencies, it can exceed the standard quantum limit for both noisy cases. This study highlights the potential of graph state-based methods for improving magnetic field measurements under noisy environments. [ABSTRACT FROM AUTHOR]

Retinal pigment epithelial (RPE) cells play a crucial role in the health of the retina, and their dysfunction is associated with various ocular diseases. The transplantation of RPE cells has been proposed as a potential treatment for numerous degenerative diseases, including geographic atrophy from macular degeneration. However, current models to induce RPE damage in animal models prior to transplantation involve mechanical scraping, chemical administration, or laser photocoagulation techniques, which can damage the overlying neurosensory retina. This study aims to investigate the feasibility and efficacy of nanosecond duration laser treatment to safely remove large areas of RPE cells without causing damage to the adjacent tissue or affecting the retinal architecture. Twelve pigmented rabbits were treated with a nanosecond laser on each eye at a laser energy ranging from 200 to 800 nJ with a treated area of 5 × 5 mm2. Human induced pluripotent stem cells-differentiated to RPE (hiPSC-RPE) cells labeled with indocyanine green (ICG), an FDA approved dye, were transplanted subretinally into the damaged RPE areas at day 14 post-laser treatment. The RPE atrophy and hiPSC-RPE cell survival was evaluated and monitored over a period of 14 days using color photography, fluorescein angiography (FA), photoacoustic microscopy (PAM), and optical coherence tomography (OCT) imaging. All treated eyes demonstrated focal RPE loss with a success rate of 100%. The injured RPE layers and the transplanted hiPSC-RPE cells were visualized in three dimensions using PAM and OCT. By performing PAM at an optical wavelength of 700 nm, the location of hiPSC-RPE cells were identified and distinguished from the surrounding RPE cells, and the induced PA signal increased up to 18 times. Immunohistochemistry results confirmed the grafted hiPSC-RPE replaced regions of RPE damage. This novel technique has the potential to serve as an animal model of RPE degeneration, to improve models of RPE transplantation, and may help accelerate translation of this therapeutic strategy for clinical use. [ABSTRACT FROM AUTHOR]

Alzheimer's disease (AD) is a prevalent neurodegenerative disorder afflicting the elderly population worldwide. The identification of potential gene candidates for AD holds promises for diagnostic biomarkers and therapeutic targets. Employing a comprehensive strategy, this study integrated transcriptomic data from diverse data sources, including microarray and single-cell datasets from blood and tissue samples, enabling a detailed exploration of gene expression dynamics. Through this thorough investigation, 19 notable candidate genes were found with consistent expression changes across both blood and tissue datasets, suggesting their potential as biomarkers for AD. In addition, single cell sequencing analysis further highlighted their specific expression in excitatory and inhibitory neurons, the primary functional units in the brain, underscoring their relevance to AD pathology. Moreover, the functional enrichment analysis revealed that three of the candidate genes were downregulated in synaptic signaling pathway. Further validation experiments significantly showed reduced levels of rabphilin-3A (RPH3A) in 3xTg-AD model mice, implying its role in disease pathogenesis. Given its role in neurotransmitter exocytosis and synaptic function, further investigation into RPH3A and its interactions with neurotrophic proteins may provide valuable insights into the complex molecular mechanisms underlying synaptic dysfunction in AD. [ABSTRACT FROM AUTHOR]

Nontuberculous mycobacteria (NTM) infection diagnosis remains a challenge due to its overlapping clinical symptoms with tuberculosis (TB), leading to inappropriate treatment. Herein, we employed noninvasive metabolic phenotyping coupled with comprehensive statistical modeling to discover potential biomarkers for the differential diagnosis of NTM infection versus TB. Urine samples from 19 NTM and 35 TB patients were collected, and untargeted metabolomics was performed using rapid liquid chromatography-mass spectrometry. The urine metabolome was analyzed using a combination of univariate and multivariate statistical approaches, incorporating machine learning. Univariate analysis revealed significant alterations in amino acids, especially tryptophan metabolism, in NTM infection compared to TB. Specifically, NTM infection was associated with upregulated levels of methionine but downregulated levels of glutarate, valine, 3-hydroxyanthranilate, and tryptophan. Five machine learning models were used to classify NTM and TB. Notably, the random forest model demonstrated excellent performance [area under the receiver operating characteristic (ROC) curve greater than 0.8] in distinguishing NTM from TB. Six potential biomarkers for NTM infection diagnosis, including methionine, valine, glutarate, 3-hydroxyanthranilate, corticosterone, and indole-3-carboxyaldehyde, were revealed from univariate ROC analysis and machine learning models. Altogether, our study suggested new noninvasive biomarkers and laid a foundation for applying machine learning to NTM differential diagnosis. [ABSTRACT FROM AUTHOR]

Glioblastoma (GBM) is a highly aggressive and deadly brain cancer. Temozolomide (TMZ) is the standard chemotherapeutic agent for GBM, but the majority of patients experience recurrence and invasion of tumor cells. We investigated whether TMZ treatment of GBM cells regulates matrix metalloproteinases (MMPs), which have the main function to promote tumor cell invasion. TMZ effectively killed GL261, U343, and U87MG cells at a concentration of 500 µM, and surviving cells upregulated MMP9 expression and its activity but not those of MMP2. TMZ also elevated levels of MMP9 mRNA and MMP9 promoter activity. Subcutaneous graft tumors survived from TMZ treatment also exhibited increased expression of MMP9 and enhanced gelatinolytic activity. TMZ-mediated MMP9 upregulation was specifically mediated through the phosphorylation of p38 and JNK. This then stimulates AP-1 activity through the upregulation of c-Fos and c-Jun. Inhibition of the p38, JNK, or both pathways counteracted the TMZ-induced upregulation of MMP9 and AP-1. This study proposes a potential adverse effect of TMZ treatment for GBM: upregulation of MMP9 expression potentially associated with increased invasion and poor prognosis. This study also provides valuable insights into the molecular mechanisms by which TMZ treatment leads to increased MMP9 expression in GBM cells. [ABSTRACT FROM AUTHOR]

Sustainable cellulose-based hydrogels are used in medicine and environmental science. Hydrogels’ porosity makes them excellent adsorbents and stable substrates for immobilizing photocatalysts to remove organic dyes. Despite their potential, the implementation of hydrogels for this purpose is still limited due to their high synthesis temperature and low cellulose content. To overcome these challenges, this study develops cellulose-based hydrogels, which have a high cellulose content and can be easily synthesized under ambient conditions. Containing a higher cellulose concentration than previous hydrogels, the synthesized hydrogels are more stable and can be reused numerous times in treatment operations. The hydrogel properties were investigated using Fourier transform infrared spectroscopy, X-ray diffraction and thermal analysis. Scanning electronic microscopy revealed that TiO2 nanoparticles were homogeneously distributed throughout the hydrogel's matrices. In addition, transparent hydrogels allow light to pass through, making them suitable substrates to remove organic dye. The results showed that the hydrogel with TiO2 was able to degrade nearly 90% of organic dye within 180 min. Furthermore, the hydrogel with the embedded catalyst exhibits the potential for reusability with a regeneration efficiency of 80.01% after five runs. These findings suggest that this novel hydrogel is a promising candidate for water pollution remediation. [ABSTRACT FROM AUTHOR]

The global threat of antibiotic resistance has increased the importance of the detection of antibiotics. Conventional methods to detect antibiotics are time-consuming and require expensive specialized equipment. Here, we present a simple and rapid biosensor for detecting ampicillin, a commonly used antibiotic. Our method is based on the fluorescent properties of chitosan-coated Mn-doped ZnS micromaterials combined with the β-lactamase enzyme. The biosensors exhibited the highest sensitivity in a linear working range of 13.1–72.2 pM with a limit of detection of 8.24 pM in deionized water. In addition, due to the biological specificity of β-lactamase, the proposed sensors have demonstrated high selectivity over penicillin, tetracycline, and glucose through the enhancing and quenching effects at wavelengths of 510 nm and 614 nm, respectively. These proposed sensors also showed promising results when tested in various matrices, including tap water, bottled water, and milk. Our work reports for the first time the cost-effective (Mn:ZnS)Chitosan micromaterial was used for ampicillin detection. The results will facilitate the monitoring of antibiotics in clinical and environmental contexts. [ABSTRACT FROM AUTHOR]

This study investigated Vietnamese people's behavior and future intention to purchase medicines and functional foods online and their associated factors. From March to May 2023, a Google Form questionnaire was distributed via social networks and online platforms. Convenience and snowballing sampling methods were employed to recruit 1,305 Vietnamese people. In the past year, 50.3% of participants purchased at least one kind of medicine and/or functional foods online (medicines: 27.6%, functional foods: 45.1%). Among 656 buyers, nearly a third bought these products more than three times and only 5.9% felt dissatisfied with their previous experiences. This purchasing behavior was more prevalent among females, those married, having higher education levels, usually shopping online, having longer time of Internet use per day, and seeking health information on the Internet (p < 0.001). In addition, 77.5% of participants intended to purchase these products online in the future and 61.2% would introduce this kind of online purchase to other people. The purchase intention was significantly associated with the participants' previous experiences, area, contracting chronic diseases, and using the Internet for self-medication, while factors associated with the introducing intention included their education level, occupation, and previous experiences in online purchases (p < 0.001). [ABSTRACT FROM AUTHOR]

Many strategies have been developed to produce high levels of biologically active recombinant proteins in plants for biopharmaceutical purposes. However, the production of an active form of human iduronate-2-sulfatase (hIDS) for the treatment of Hunter syndrome by enzyme replacement therapy (ERT) is challenging due to the requirement for cotranslational modification by a formylglycine-producing enzyme encoded by sulfatase modifying factor 1 (hSUMF1) at the Cys84 residue, which converts it to C(alpha)-formylglycine. In this study, we have shown that hIDS can be highly expressed in N. benthamiana by using different constructs. Among them, BiP-GB1-L-dCBD1-2L-8xHis-L-6xHis-3L-EK-hIDS-HDEL (GB1-CBD1-hIDS) showed a high expression level when transiently co-expressed with the turnip crinkle virus gene silencing suppressor P38 and GB1-fused human calreticulin (GB1-CRT1) as a folding enhancer. The hSUMF1 was co-expressed with hIDS for cotranslational modification. The full-length recombinant proteins were purified using Ni2+-NTA affinity resin followed by enterokinase treatment to obtain tag-free hIDS. The N-terminal fragment was removed using microcrystalline cellulose (MCC) beads. The purified active form of hIDS can successfully cleave the sulfate group from an artificial substrate, 4-nitrocatechol sulfate, at a similar level to commercial hIDS expressed in animal cells. These results suggest that plants could be a promising platform for the production of recombinant hIDS. [ABSTRACT FROM AUTHOR]

This report describes the development and characterization of a comprehensive collection of CHO cell glycosylation mutants with significant potential for advancing glycobiology and biotechnology. EPO-Fc and trastuzumab, two model molecules, were produced using these mutants to assess the effects of mutated glycogenes, and LC-MS/MS analysis was employed to quantitatively analyse their N-glycans. EPO-Fc exhibited exclusively homogeneous Man9 glycans only when nearly all α-mannosidases in the genome were inactivated, except lysosomal MAN2B1. Some mutants lacking GnT-I activity produce mostly Man5 N-glycans, while their O-glycan and glycolipid profiles can differ due to other mutations in the cell. GnT-II deficiency prevents GnT-V from adding GlcNAc to the core N-glycan, resulting in branches attaching solely to the α1,3-linked mannose, leaving the α1,6-linked mannose free. The mutant-produced antibody's single-branched glycan contains more sialic acid than the dual-branched glycans produced in CHO-K1 cells. Trastuzumab produced in these mutants provided insights into how Fc N-glycans impact the antibody's interaction with FcγR1 and FcγR2a, FcγR3a, and their influence on antibody-dependent cellular cytotoxicity (ADCC). In the study of Fc glycans in Fc-FcγR1 and FcγR2a interactions, we observed a consistent glycan-related impact on binding to both receptors, indicating a common interaction mechanism between Fc glycans and both FcγRI and FcγRIIa. CHO mutants produced trimeric gp120 demonstrated distinct reactivity with multiple broadly neutralizing anti-HIV antibodies, confirming the involvement of gp120 glycans in interactions with specific broadly neutralizing antibodies. Finally, one of the mutants produced human β-glucocerebrosidase with uniform Man5 N-glycans, showcasing its potential for glycoengineered production and enhancement in therapeutic efficacy. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic affected countries across the globe, demanding drastic public health policies to mitigate the spread of infection, which led to economic crises as a collateral damage. In this work, we investigate the impact of human mobility, described via international commercial flights, on COVID-19 infection dynamics on a global scale. We developed a graph neural network (GNN)-based framework called Dynamic Weighted GraphSAGE (DWSAGE), which operates over spatiotemporal graphs and is well-suited for dynamically changing flight information updated daily. This architecture is designed to be structurally sensitive, capable of learning the relationships between edge features and node features. To gain insights into the influence of air traffic on infection spread, we conducted local sensitivity analysis on our model through perturbation experiments. Our analyses identified Western Europe, the Middle East, and North America as leading regions in fueling the pandemic due to the high volume of air traffic originating or transiting through these areas. We used these observations to propose air traffic reduction strategies that can significantly impact controlling the pandemic with minimal disruption to human mobility. Our work provides a robust deep learning-based tool to study global pandemics and is of key relevance to policymakers for making informed decisions regarding air traffic restrictions during future outbreaks. [ABSTRACT FROM AUTHOR]

This study explores the effects of dietary supplementation with passion fruit peel pectin (Passiflora edulis) and red yeast cell walls (Sporidiobolus pararoseus) on growth performance, immunity, intestinal morphology, gene expression, and gut microbiota of Nile tilapia (Oreochromis niloticus). Nile tilapia with an initial body weight of approximately 15 ± 0.06 g were fed four isonitrogenous (29.09–29.94%), isolipidic (3.01–4.28%), and isoenergetic (4119–4214 Cal/g) diets containing 0 g kg−1 pectin or red yeast cell walls (T1 - Control), 10 g kg−1 pectin (T2), 10 g kg−1 red yeast (T3), and a combination of 10 g kg−1 pectin and 10 g kg−1 red yeast (T4) for 8 weeks. Growth rates and immune responses were assessed at 4 and 8 weeks, while histology, relative immune and antioxidant gene expression, and gut microbiota analysis were conducted after 8 weeks of feeding. The results showed that the combined supplementation (T4) significantly enhanced growth performance metrics, including final weight, weight gain, specific growth rate, and feed conversion ratio, particularly by week 8, compared to T1, T2, and T3 (P < 0.05). Immunological assessments revealed increased lysozyme and peroxidase activities in both skin mucus and serum, with the T4 group showing the most pronounced improvements. Additionally, antioxidant and immune-related gene expression, including glutathione peroxidase (GPX), glutathione reductase (GSR), and interleukin-1 (IL1), were upregulated in the gut, while intestinal morphology exhibited improved villus height and width. Gut microbiota analysis indicated increased alpha and beta diversity, with a notable rise in beneficial phyla such as Actinobacteriota and Firmicutes in the supplemented groups. These findings suggest that the combined use of pectin and red yeast cell walls as prebiotics in aquaculture can enhance the health and growth of Nile tilapia, offering a promising alternative to traditional practices. Further research is needed to determine optimal dosages for maximizing these benefits. [ABSTRACT FROM AUTHOR]

To enhance the effectiveness of the Advanced Persistent Threat (APT) detection process, this research proposes a new approach to build and analyze the behavior profiles of APT attacks in network traffic. To achieve this goal, this study carries out two main objectives, including (i) building the behavior profile of APT IP in network traffic using a new intelligent computation method; (ii) analyzing and evaluating the behavior profile of APT IP based on a deep graph network. Specifically, to build the behavior profile of APT IP, this article describes using a combination of two different data mining methods: Bidirectional Long Short-Term Memory (Bi) and Attention (A). Based on the obtained behavior profile, the Dynamic Graph Convolutional Neural Network (DGCNN) is proposed to extract the characteristics of APT IP and classify them. With the flexible combination of different components in the model, the important information and behavior of APT attacks are demonstrated, not only enhancing the accuracy of detecting attack campaigns but also reducing false predictions. The experimental results in the paper show that the method proposed in this study has brought better results than other approaches on all measurements. In particular, the accuracy of APT attack prediction results (Precision) reached from 84 to 91%, higher than other studies of over 7%. These experimental results have proven that the proposed BiADG model for detecting APT attacks in this study is proper and reasonable. In addition, those experimental results have not only proven the effectiveness and superiority of the proposed method in detecting APT attacks but have also opened up a new approach for other cyber-attack detections such as distributed denial of service, botnets, malware, phishing, etc. [ABSTRACT FROM AUTHOR]

It is well known that the roughness of a wall plays a crucial role in determining the passive earth pressure that is exerted on a rigid wall. While the effects of positive wall roughness have been extensively studied in the past few decades, the study of passive earth pressure with negative wall friction is rarely found in the literature. This study aims to provide a precise solution for negative friction walls under passive wall conditions. The research is initiated by adopting a radial stress field for the cohesionless backfill and employs the concept of stress self-similarity. The problem is then formulated in a way that a statically admissible stress field be developed throughout an analyzed domain using a two-step numerical framework. The framework involves the successful execution of numerical integration, which leads to the exploration of the statically admissible stress field in cohesionless backfills under negative wall friction. This, in turn, helps to shed light on the mechanism of load transfer in such situations so that reliable design charts and tables be provided for practical uses. The study continues with a soft computing model that leads to more robust and effective designs for earth-retaining structures under various negative wall frictions and sloping backfills. [ABSTRACT FROM AUTHOR]

Recent advances in AI and intelligent vehicle technology hold the promise of revolutionizing mobility and transportation through advanced driver assistance systems (ADAS). Certain cognitive factors, such as impulsivity and inhibitory control have been shown to relate to risky driving behavior and on-road risk-taking. However, existing systems fail to leverage such factors in assistive driving technologies adequately. Varying the levels of these cognitive factors could influence the effectiveness and acceptance of ADAS interfaces. We demonstrate an approach for personalizing driver interaction via driver safety interfaces that are are triggered based on the inference of the driver's latent cognitive states from their driving behavior. To accomplish this, we adopt a data-driven approach and train a recurrent neural network to infer impulsivity and inhibitory control from recent driving behavior. The network is trained on a population of human drivers to infer impulsivity and inhibitory control from recent driving behavior. Using data collected from a high-fidelity vehicle motion simulator experiment, we demonstrate the ability to deduce these factors from driver behavior. We then use these inferred factors to determine instantly whether or not to engage a driver safety interface. This approach was evaluated using leave-one-out cross validation using actual human data. Our evaluations reveal that our personalized driver safety interface that captures the cognitive profile of the driver is more effective in influencing driver behavior in yellow light zones by reducing their inclination to run through them. [ABSTRACT FROM AUTHOR]

Youth screen media activity is a growing concern, though few studies include objective usage data. Through the longitudinal, U.S.-based Adolescent Brain Cognitive Development (ABCD) Study, youth (mage = 14; n = 1415) self-reported their typical smartphone use and passively recorded three weeks of smartphone use via the ABCD-specific Effortless Assessment Research System (EARS) application. Here we describe and validate passively-sensed smartphone keyboard and app use measures, provide code to harmonize measures across operating systems, and describe trends in adolescent smartphone use. Keyboard and app-use measures were reliable and positively correlated with one another (r = 0.33) and with self-reported use (rs = 0.21–0.35). Participants recorded a mean of 5 h of daily smartphone use, which is two more hours than they self-reported. Further, females logged more smartphone use than males. Smartphone use was recorded at all hours, peaking on average from 8 to 10 PM and lowest from 3 to 5 AM. Social media and texting apps comprised nearly half of all use. Data are openly available to approved investigators (https://nda.nih.gov/abcd/). Information herein can inform use of the ABCD dataset to longitudinally study health and neurodevelopmental correlates of adolescent smartphone use. [ABSTRACT FROM AUTHOR]

Usher syndrome type 2A (USH2A) is a genetic disorder characterized by retinal degeneration and hearing loss. To better understand the pathogenesis and progression of this syndrome, animal models such as USH2A knockout (USH2AKO) rabbits have been developed. In this study, we employed multimodal imaging techniques, including photoacoustic microscopy (PAM), optical coherence tomography (OCT), fundus autofluorescence (FAF), fluorescein angiography (FA), and indocyanine green angiography (ICGA) imaging to evaluate the retinal changes in the USH2AKO rabbit model. Twelve New Zealand White rabbits including USH2AKO and wild type (WT) were used for the experiments. Multimodal imaging was implemented at different time points over a period of 12 months to visualize the progression of retinal changes in USH2AKO rabbits. The results demonstrate that ellipsoid zone (EZ) disruption and degeneration, key features of Usher syndrome, began at the age of 4 months old and persisted up to 12 months. The EZ degeneration areas were clearly observed on the FAF and OCT images. The FAF images revealed retinal pigment epithelium (RPE) degeneration, confirming the presence of the disease phenotype in the USH2AKO rabbits. In addition, PAM images provided high-resolution and high image contrast of the optic nerve and the retinal microvasculature, including retinal vessels, choroidal vessels, and capillaries in three-dimensions. The quantification of EZ fluorescent intensity using FAF and EZ thickness using OCT provided comprehensive quantitative data on the progression of degenerative changes over time. This multimodal imaging approach allowed for a comprehensive and non-invasive assessment of retinal structure, microvasculature, and degenerative changes in the USH2AKO rabbit model. The combination of PAM, OCT, and fluorescent imaging facilitated longitudinal monitoring of disease progression and provided valuable insights into the pathophysiology of USH2A syndrome. These findings contribute to the understanding of USH2A syndrome and may have implications for the development of diagnostic and therapeutic strategies for affected individuals. The multimodal imaging techniques employed in this study offer a promising platform for preclinical evaluation of potential treatments and may pave the way for future clinical applications in patients with Usher syndrome. [ABSTRACT FROM AUTHOR]

Hyperspectral imaging has gained popularity for analysing remotely sensed images in various fields such as agriculture and medical. However, existing models face challenges in dealing with the complex relationships and characteristics of spectral–spatial data due to the multi-band nature and data redundancy of hyperspectral data. To address this limitation, we propose a novel approach called DiffSpectralNet, which combines diffusion and transformer techniques. The diffusion method is able extract diverse and meaningful spectral–spatial features, leading to improvement in HSI classification. Our approach involves training an unsupervised learning framework based on the diffusion model to extract high-level and low-level spectral–spatial features, followed by the extraction of intermediate hierarchical features from different timestamps for classification using a pre-trained denoising U-Net. Finally, we employ a supervised transformer-based classifier to perform the HSI classification. We conduct comprehensive experiments on three publicly available datasets to validate our approach. The results demonstrate that our framework significantly outperforms existing approaches, achieving state-of-the-art performance. The stability and reliability of our approach are demonstrated across various classes in all datasets. [ABSTRACT FROM AUTHOR]

People living in coastal areas are frequently affected by natural disasters, such as floods and storms. This study aimed to assess the quality of life (QoL) of people living in disadvantaged coastal communes (subdivision of Vietnam) and identify their associated factors by using the World Health Organization's quality of life instrument (WHOQOL-BREF). To achieve this, a cross-sectional descriptive study was conducted on 595 individuals aged 18 years and above living in the coastal communes in Thua Thien Hue province, Vietnam, from October 2022 to February 2023. The results showed that the mean overall QoL (mean ± SD) was 61.1 ± 10.8. Among the four domains of QoL, the physical health (57.2 ± 12.3) domain had a lower score than the psychological health (61.9 ± 13.0), social relations (63.4 ± 13.4), and environment (61.9 ± 13.3) domains. The QoL score of the domains for participants affected by flooding was significantly lower than that of those not affected, except for social relations. Multivariable logistic regression showed that subjects with not good QoL had the educational background with no formal education (Odds ratio (OR) = 2.63, 95% CI 1.19–5.83), fairly poor/poor households (OR = 2.75, 95% CI 1.48–5.12), suffered Musculoskeletal diseases (OR = 1.61, 95% CI 1.02–2.56), unsatisfaction with health status (OR = 5.27, 95% CI 2.44–11.37), family conflicts (OR = 4.51, 95%CI 2.10–9.69), and low levels of social support (OR = 2.62; 95% CI 1.14–6.02). The analysis also revealed that workers (OR = 0.17, 95% CI 0.04–0.66) had a better QoL than farmer-fisherman. QoL in disadvantaged coastal communes was low, with the lowest scores in the physical health domain. Based on the socioeconomic factors associated with not good QoL identified here, it is recommended that local authorities take more appropriate and practical measures to increase support, including measures for all aspects of physical health, psychological health, social relations, and the living environment, especially for people affected by floods. [ABSTRACT FROM AUTHOR]

Persistent diarrhea is a severe gastroenteric disease with relatively high risk of pediatric mortality in developing countries. We conducted a randomized, double-blind, controlled clinical trial to evaluate the efficacy of liquid-form Bacillus clausii spore probiotics (LiveSpo CLAUSY; 2 billion CFU/5 mL ampoule) at high dosages of 4–6 ampoules a day in supporting treatment of children with persistent diarrhea. Our findings showed that B. clausii spores significantly improved treatment outcomes, resulting in a 2-day shorter recovery period (p < 0.05) and a 1.5–1.6 folds greater efficacy in reducing diarrhea symptoms, such as high frequency of bowel movement of ≥ 3 stools a day, presence of fecal mucus, and diapered infant stool scale types 4-5B. LiveSpo CLAUSY supportive treatment achieved 3 days (p < 0.0001) faster recovery from diarrhea disease, with 1.6-fold improved treatment efficacy. At day 5 of treatment, a significant decrease in blood levels of pro-inflammatory cytokines TNF-α, IL-17, and IL-23 by 3.24% (p = 0.0409), 29.76% (p = 0.0001), and 10.87% (p = 0.0036), respectively, was observed in the Clausy group. Simultaneously, there was a significant 37.97% decrease (p = 0.0326) in the excreted IgA in stool at day 5 in the Clausy group. Overall, the clinical study demonstrates the efficacy of B. clausii spores (LiveSpo CLAUSY) as an effective symptomatic treatment and immunomodulatory agent for persistent diarrhea in children. Trial registration: NCT05812820. [ABSTRACT FROM AUTHOR]

Among the congener of dioxin, 2,3,7,8-TCDD is the most toxic, having a serious long-term impact on the environment and human health. UDP-glucuronosyltransferase 1A1 (UGT1A1) plays a crucial role in the detoxification and excretion of endogenous and exogenous lipophilic compounds, primarily in the liver and gastrointestinal tract. This study aimed to investigate the association of UGT1A1 gene polymorphisms, expression levels, and enzyme concentration with Agent Orange/Dioxin exposure. The study included 100 individuals exposed to Agent Orange/Dioxin nearby Da Nang and Bien Hoa airports in Vietnam and 100 healthy controls. UGT1A1 SNP rs10929303, rs1042640 and rs8330 were determined by Sanger sequencing, mRNA expression was quantified by RT-qPCR and plasma UGT1A1 concentrations were measured by ELISA. The results showed that UGT1A1 polymorphisms at SNPs rs10929303, rs1042640 and rs8330 were associated with Agent Orange/Dioxin exposure (OR = 0.55, P = 0.018; OR = 0.55, P = 0.018 and OR = 0.57, P = 0.026, respectively). UGT1A1 mRNA expression levels and enzyme concentration were significantly elevated in individuals exposed to Agent Orange/Dioxin compared to controls (P < 0.0001). Benchmark dose (BMD) analyses showed that chronic exposure to 2,3,7,8-TCDD contamination affects the UGT1A1 mRNA and protein levels. Furthermore, UGT1A1 polymorphisms affected gene expression and enzyme concentrations in individuals exposed to Agent Orange/Dioxin. In conclusion, UGT1A1 gene polymorphisms, UGT1A gene expression levels and UGT1A1 enzyme concentrations were associated with Agent Orange/Dioxin exposure. The metabolism of 2,3,7,8-TCDD may influence UGT1A gene expression and enzyme concentrations. [ABSTRACT FROM AUTHOR]

In recent years, the use of Building Information Modeling (BIM) with Building Energy Modeling (BEM) has become the primary research focus for reducing the energy consumption of buildings in the planning and operational phases. The combination of BIM and BEM offers advantages for the various phases of a construction project. However, there are currently very few studies that can integrate multi-objective optimization algorithms into the BIM-BEM process to achieve automatic optimization and effectively manage many aspects of building development. In this study, an EnergyPlus integrated multi-objective jellyfish search (EP-MOJSO) system was developed, utilizing an optimization algorithm to find the best thermal insulation layers for an Aluminum composite material (ACM) wall. The goal is to reduce the energy consumption and total cost in a BIM-BEM environment. In the case study, the authors successfully applied the system to a real building, resulting in a 10.7% reduction in total cost and a 65 kWh/m2/year reduction in EUI. It is expected that the results of the study will open up new ways of using algorithms for multi-criteria optimization in BIM models to optimize various project factors such as energy and total cost and thus make an important contribution to sustainable building design. [ABSTRACT FROM AUTHOR]

We conducted a large-scale online survey in February 2023 to investigate the public's perceptions of COVID-19 infection and fatality risks in Japan. We identified two key findings. First, univariate analysis comparing perceived and actual risk suggested overestimation and nonnegligible underestimation of COVID-19 risk. Second, multivariate logistic regression analyses revealed that age, income, education levels, health status, information sources, and experiences related to COVID-19 were associated with risk perceptions. Given that risk perceptions are closely correlated with daily socioeconomic activities and well-being, it is important for policy-makers and public health experts to understand how to communicate COVID-19 risk to the public effectively. [ABSTRACT FROM AUTHOR]

It has been proposed that, when processing a stream of events, humans divide their experiences in terms of inferred latent causes (LCs) to support context-dependent learning. However, when shared structure is present across contexts, it is still unclear how the "splitting" of LCs and learning of shared structure can be simultaneously achieved. Here, we present the Latent Cause Network (LCNet), a neural network model of LC inference. Through learning, it naturally stores structure that is shared across tasks in the network weights. Additionally, it represents context-specific structure using a context module, controlled by a Bayesian nonparametric inference algorithm, which assigns a unique context vector for each inferred LC. Across three simulations, we found that LCNet could (1) extract shared structure across LCs in a function learning task while avoiding catastrophic interference, (2) capture human data on curriculum effects in schema learning, and (3) infer the underlying event structure when processing naturalistic videos of daily events. Overall, these results demonstrate a computationally feasible approach to reconciling shared structure and context-specific structure in a model of LCs that is scalable from laboratory experiment settings to naturalistic settings. [ABSTRACT FROM AUTHOR]

Arboviruses transmitted by mosquitoes, including Japanese encephalitis virus (JEV), present a substantial global health threat. JEV is transmitted by mosquitoes in the genus Culex, which are common in both urban and rural areas in Vietnam. In 2020, we conducted a 1-year survey of Culex mosquito abundance in urban, suburban, and peri-urban areas of Hanoi using CDC-light traps. Mosquitoes were identified to species and sorted into pools based on species, sex, and trap location. The mosquito pools were also investigated by RT-qPCR for detection of JEV. In total, 4829 mosquitoes were collected over a total of 455 trap-nights, across 13 months. Collected mosquitoes included Culex, Aedes, Anopheles, and Mansonia species. Culex mosquitoes, primarily Cx. quinquefasciatus, predominated, especially in peri-urban areas. Most Culex mosquitoes were caught in the early months of the year. The distribution and abundance of mosquitoes exhibited variations across urban, suburban, and peri-urban sites, emphasizing the influence of environmental factors such as degree of urbanization, temperature and humidity on Culex abundance. No JEV was detected in the mosquito pools. This study establishes baseline knowledge of Culex abundance and temporal variation, which is crucial for understanding the potential for JEV transmission in Hanoi. [ABSTRACT FROM AUTHOR]

Diagnosing encapsulated follicular-patterned thyroid tumors like Invasive Encapsulated Follicular Variant of Papillary Thyroid Carcinoma (IEFVPTC), Non-invasive Follicular Thyroid Neoplasm with Papillary-like Nuclear Features (NIFTP), and Well-Differentiated Tumor of Uncertain Malignant Potential (WDT-UMP) remains challenging due to their morphological and molecular similarities. This study aimed to investigate the protein distinctions among these three thyroid tumors and discover biological tumorigenesis through proteomic analysis. We employed total shotgun proteome analysis allowing to discover the quantitative expression of over 1398 proteins from 12 normal thyroid tissues, 13 IEFVPTC, 11 NIFTP, and 10 WDT-UMP. Principal component analysis revealed a distinct separation of IEFVPTC and normal tissue samples, distinguishing them from the low-risk tumor group (NIFTP and WDT-UMP). IEFVPTC exhibited the highest number of differentially expressed proteins (DEPs) compared to the other tumors. No discriminatory proteins between NIFTP and WDT-UMP were identified. Moreover, DEPs in IEFVPTC were significantly associated with thyroid tumor progression pathways. Certain hub genes linked to the response of immune checkpoint inhibitor therapy, revealing the potential predictor of prognosis. In conclusion, the proteomic profile of IEFVPTC differs from that of low-risk tumors. These findings may provide valuable insights into tumor biology and offer a basis for developing novel therapeutic strategies for follicular-patterned thyroid neoplasms. [ABSTRACT FROM AUTHOR]

Metal artifacts notoriously pose significant challenge in computed tomography (CT), leading to inaccuracies in image formation and interpretation. Artifact reduction tools have been designed to improve cone beam computed tomography (CBCT) image quality by reducing artifacts caused by certain high-density materials. Metal artifact reduction (MAR) tools are specific algorithms that are applied during image reconstruction to minimize or eliminate artifacts degrading CBCT images. The purpose of the study is to evaluate the effect of a MAR algorithm on image quality in CBCT performed for evaluating patients before transarterial radioembolization (TARE). We retrospectively included 40 consecutive patients (aged 65 ± 13 years; 23 males) who underwent 45 CBCT examinations (Allura FD 20, XperCT Roll protocol, Philips Healthcare, Best, The Netherlands) in the setting of evaluation for TARE between January 2017 and December 2018. Artifacts caused by coils, catheters, and surgical clips were scored subjectively by four readers on a 5-point scale (1 = artifacts affecting diagnostic information to 5 = no artifacts) using a side-by-side display of uncorrected and MAR-corrected images. In addition, readers scored tumor visibility and vessel discrimination. MAR-corrected images were assigned higher scores, indicating better image quality. The differences between the measurements with and without MAR were most impressive for coils with a mean improvement of 1.6 points (95%CI [1.5 1.8]) on the 5-point likert scale, followed by catheters 1.4 points (95%CI [1.3 1.5]) and clips 0.7 points (95%CI [0.3 1.1]). Improvements for other artifact sources were consistent but relatively small (below 0.25 points on average). Interrater agreement was good to perfect (Kendall's W coefficient = 0.68–0.95) and was higher for MAR-corrected images, indicating that MAR improves diagnostic accuracy. A metal artifact reduction algorithm can improve diagnostic and interventional accuracy of cone beam CT in patients undergoing radioembolization by reducing artifacts caused by diagnostic catheters and coils, lowering interference of metal artifacts with adjacent major structures, and improving tumor visibility. [ABSTRACT FROM AUTHOR]

In response to the escalating global threat of antimicrobial resistance, our laboratory has established a phagemid packaging system for the generation of CRISPR-Cas13a-antimicrobial capsids targeting methicillin-resistant Staphylococcus aureus (MRSA). However, a significant challenge arose during the packaging process: the unintentional production of wild-type phages alongside the antimicrobial capsids. To address this issue, the phagemid packaging system was optimized by strategically incorporated silent mutations. This approach effectively minimized contamination risks without compromising packaging efficiency. The study identified the indispensable role of phage packaging genes, particularly terL-terS, in efficient phagemid packaging. Additionally, the elimination of homologous sequences between the phagemid and wild-type phage genome was crucial in preventing wild-type phage contamination. The optimized phagemid-LSAB(mosaic) demonstrated sequence-specific killing, efficiently eliminating MRSA strains carrying target antibiotic-resistant genes. While acknowledging the need for further exploration across bacterial species and in vivo validation, this refined phagemid packaging system offers a valuable advancement in the development of CRISPR-Cas13a-based antimicrobials, shedding light on potential solutions in the ongoing battle against bacterial infections. [ABSTRACT FROM AUTHOR]

Bacteria perceive light signals via photoreceptors and modulate many physiological and genetic processes. The impacts played by light, oxygen, or voltage (LOV) and blue light (BL) photosensory proteins on the virulence-related traits of plant bacterial pathogens are diverse and complex. In this study, we identified LOV protein (Pc-LOV1) from Pseudomonas cichorii JBC1 (PcJBC1) and characterized its function using LOV1-deficient mutant (JBC1Δlov1). In the dark state, the recombinant Pc-LOV1 protein showed an absorption band in UV-A region with a double peak at 340 nm and 365 nm, and within the blue-region, it exhibited a main absorption at 448 nm along with two shoulder peaks at 425 nm and 475 nm, which is a typical feature of oxidized flavin within LOV domain. The adduct-state lifetime (τrec) of Pc-LOV1 was 67.03 ± 4.34 min at 25 °C. BL negatively influenced the virulence of PcJBC1 and the virulence of JBC1Δlov1 increased irrespective of BL, indicating that Pc-LOV1 negatively regulates PcJBC1 virulence. Pc-LOV1 and BL positively regulated traits relevant to colonization on plant surface, such as adhesion to the plant tissue and biofilm formation. In contrast, swarming motility, exopolysaccharide production, and siderophore synthesis were negatively controlled. Gene expression supported the modulation of bacterial features by Pc-LOV1. Overall, our results suggest that the LOV photosensory system plays crucial roles in the adaptive responses and virulence of the bacterial pathogen PcJBC1. The roles of other photoreceptors, sensing of other wavelengths, and signal networking require further investigation. [ABSTRACT FROM AUTHOR]

Unplanned hospital readmission is a safety and quality healthcare measure, conferring significant costs to the healthcare system. Elderly individuals, particularly, are at high risk of readmissions, often due to issues related to medication management. Pharmacists play a pivotal role in addressing medication-related concerns, which can potentially reduce readmissions. This retrospective single-centre cohort study, conducted from November 2022 to February 2023 in an emergency department, aimed to determine if integrating emergency medicine pharmacists into Emergency Department care models reduces unplanned hospital readmissions within 28 days and to identify the interventions they employ. The inclusion criteria included patients aged ≥ 65, taking ≥ 3 medications, and presenting with falls, cognition changes, or reduced mobility and were planned for discharge to home from the emergency department. Collaborating with the Emergency Department Aged Care Service Emergency Team, a pharmacist provided comprehensive medication management consultations, discharge liaison services, and other pharmacy related interventions to eligible participants whenever the pharmacist was available. Patients who met the eligibility criteria but did not receive pharmacist interventions due to the pharmacist's unavailability served as the control group. This method was chosen to ensure that the control group consisted of comparable patients who only differed in terms of receiving the pharmacist intervention. The study included 210 participants, with 120 receiving pharmacist interventions and 90 acting as controls. The results revealed a significant reduction in unplanned hospital readmissions among participants who received pharmacist interventions (10.0%, n = 12) compared to controls (22.2%, n = 20), with a notable difference of 12.2% (95% confidence interval 2.4–23.4%, p = 0.01). A total of 107 interventions were documented, emphasising medication selection recommendations (28.0%) and identification of adverse drug reactions/drug-drug interactions (21.5%) as primary areas of focus. These findings suggest that integrating skilled pharmacists into Emergency Department Aged Care Service Emergency Team (ASET) lowered the rate of unplanned hospital readmission within 28 days resulting in improved hospital performance metric outcomes. This highlights the potential role of pharmacists in addressing medication-related issues and enhancing the quality and safety of healthcare delivery, particularly for elderly patients transitioning from the ED to home care settings. [ABSTRACT FROM AUTHOR]

Apis mellifera filamentous virus (AmFV) is a double-stranded DNA virus that infects Apis mellifera bees. To our knowledge, this is the first comprehensive study aiming to detect and analyse the genetic diversity and prevalence of AmFV in Korean honeybee colonies. Phylogenetic analysis based on baculovirus repeat open reading frame–N gene (Bro–N) sequences revealed that AmFV isolates from the Republic of Korea (ROK) fell into two distinct lineages, with genetic origins in Switzerland and China, with nucleotide similarities of 98.3% and 98.2%, respectively. Our prevalence analysis demonstrated a noteworthy infection rate of AmFV in 545 honeybee colonies, reaching 33.09% in 2022 and increasing to 44.90% by 2023. Intriguingly, we also detected AmFV in Varroa destructor mites, highlighting their potential role as vectors and carriers of AmFV. The presence of AmFV was correlated with an increased infection rate of sacbrood virus, deformed wing virus, Lake Sinai virus 2, black queen cell virus, and Nosema ceranae in honeybee colonies. These findings provide valuable insight into the prevalence and potential transmission mechanisms of AmFV in honeybee colonies in the ROK. The results of this study may be instrumental in the effective management of viral infections in honeybee apiaries. [ABSTRACT FROM AUTHOR]

Ultrasound (US) has gained popularity as a guidance modality for percutaneous needle insertions because it is widely available and non-ionizing. However, coordinating scanning and needle insertion still requires significant experience. Current assistance solutions utilize optical or electromagnetic tracking (EMT) technology directly integrated into the US device or probe. This results in specialized devices or introduces additional hardware, limiting the ergonomics of both the scanning and insertion process. We developed the first ultrasound (US) navigation solution designed to be used as a non-permanent accessory for existing US devices while maintaining the ergonomics during the scanning process. A miniaturized EMT source is reversibly attached to the US probe, temporarily creating a combined modality that provides real-time anatomical imaging and instrument tracking at the same time. Studies performed with 11 clinical operators show that the proposed navigation solution can guide needle insertions with a targeting accuracy of about 5 mm, which is comparable to existing approaches and unaffected by repeated attachment and detachment of the miniaturized tracking solution. The assistance proved particularly helpful for non-expert users and needle insertions performed outside of the US plane. The small size and reversible attachability of the proposed navigation solution promises streamlined integration into the clinical workflow and widespread access to US navigated punctures. [ABSTRACT FROM AUTHOR]

Colloidal quantum dots (QDs) are attracting research interest because of their unique optical properties that result from the quantum confinement effect. ZnSe QDs, which are II–VI semiconductors, offer a wide direct bandgap (2.7 eV), making them promising for applications such as light-emitting diodes, photodetectors, and biomedical labeling. In the present work, colloidal ZnSe (QDs) were synthesized by the hot-injection method with a Zn:Se ratio of 1:1. The optical properties of ZnSe QDs obtained at different reaction times were investigated by spectrophotometric UV–vis absorption and emission measurements. The as-synthesized ZnSe QDs exhibit blue excitonic emission, and no defect emission was detected. Transmission electron micrographs indicated that the QDs have a spherical morphology with dimensions ranging from 3.69 to 4.53 nm. In particular, the Brus model was applied to demonstrate a correlation between the QD sizes and the optical bandgaps obtained from Tauc plots. [ABSTRACT FROM AUTHOR]

Cassava root rot disease caused by the fungal pathogens Fusarium solani and Lasiodiplodia theobromae produces severe damages on cassava production. This research was conducted to produce and assess silver nanoparticles (AgNPs) synthesized by Trichoderma harzianum for reducing root rot disease. The results revealed that using the supernatants of T. harzianum on a silver nitrate solution changed it to reddish color at 48 h, indicating the formation of AgNPs. Further characterization was identified using dynamic light scattering (DLS) and scanning electron microscope (SEM). DLS supported that the Z-average size is at 39.79 nm and the mean zeta potential is at − 36.5 mV. SEM revealed the formation of monodispersed spherical shape with a diameter between 60–75 nm. The antibacterial action of AgNPs as an antifungal agent was demonstrated by an observed decrease in the size of the fungal colonies using an increasing concentration of AgNPs until the complete inhibition growth of L. theobromae and F. solani at > 58 µg mL−1 and at ≥ 50 µg mL−1, respectively. At in vitro conditions, the applied AgNPs caused a decrease in the percentage of healthy aerial hyphae of L. theobromae (32.5%) and of F. solani (70.0%) compared to control (100%). The SR-FTIR spectra showed the highest peaks in the first region (3000–2800 cm−1) associated with lipids and fatty acids located at 2962, 2927, and 2854 cm−1 in the AgNPs treated samples. The second region (1700–1450 cm−1) consisting of proteins and peptides revealed the highest peaks at 1658, 1641, and 1548 cm−1 in the AgNPs treated samples. The third region (1300–900 cm−1), which involves nucleic acid, phospholipids, polysaccharides, and carbohydrates, revealed the highest peaks at 1155, 1079, and 1027 cm−1 in the readings from the untreated samples. Finally, the observed root rot severity on cassava roots treated with AgNPs (1.75 ± 0.50) was significantly lower than the control samples (5.00 ± 0.00). [ABSTRACT FROM AUTHOR]

Although the use of the tyrosine kinase inhibitors (TKIs) has been proved that it can save live in a cancer treatment, the currently used drugs bring in many undesirable side-effects. Therefore, the search for new drugs and an evaluation of their efficiency are intensively carried out. Recently, a series of eighteen imidazole[1,5-a]pyridine derivatives were synthetized by us, and preliminary analyses pointed out their potential to be an important platform for pharmaceutical development owing to their promising actions as anticancer agents and enzyme (kinase, HIV-protease,…) inhibitors. In the present theoretical study, we further analyzed their efficiency in using a realistic scenario of computational drug design. Our protocol has been developed to not only observe the atomistic interaction between the EGFR protein and our 18 novel compounds using both umbrella sampling and steered molecular dynamics simulations, but also determine their absolute binding free energies. Calculated properties of the 18 novel compounds were in detail compared with those of two known drugs, erlotinib and osimertinib, currently used in cancer treatment. Inspiringly the simulation results promote three imidazole[1,5-a]pyridine derivatives as promising inhibitors into a further step of clinical trials. [ABSTRACT FROM AUTHOR]

Canine kobuvirus (CaKoV) is a pathogen associated with canine gastrointestinal disease (GID). This study examined 327 rectal swabs (RS), including 113 from Vietnam (46 healthy, 67 with GID) and 214 from Thailand (107 healthy and 107 with GID). CaKoV was detected in both countries, with prevalences of 28.3% (33/113) in Vietnam and 7.9% (17/214) in Thailand. Additionally, CaKoV was found in both dogs with diarrhea and healthy dogs. CaKoV was mainly found in puppies under six months of age (30.8%). Co-detection with other canine viruses were also observed. The complete coding sequence (CDS) of nine Vietnamese and four Thai CaKoV strains were characterized. Phylogenetic analysis revealed a close genetic relationship between Vietnamese and Thai CaKoV strains, which were related to the Chinese strains. CDS analysis indicated a distinct lineage for two Vietnamese CaKoV strains. Selective pressure analysis on the viral capsid (VP1) region showed negative selection, with potential positive selection sites on B-cell epitopes. This study, the first of its kind in Vietnam, provides insights into CaKoV prevalence in dogs of different ages and healthy statuses, updates CaKoV occurrence in Thailand, and sheds light on its molecular characteristics and immune evasion strategies. [ABSTRACT FROM AUTHOR]

The photorefractive properties of triphenylamine polymer-based composites with various composition ratios were investigated via optical diffraction, response time, asymmetric energy transfer, and transient photocurrent. The composite consisted of a photoconductive polymer of poly((4-diphenylamino)benzyl acrylate), a photoconductive plasticizer of (4-diphenylamino)phenyl)methanol, a sensitizer of [6,6]-phenyl-C61-butyric acid methyl ester, and a nonlinear optical dye of (4-(azepan-1-yl)-benzylidene)malononitrile. The photorefractive properties and related quantities were dependent on the composition, which was related to the glass transition temperature of the photorefractive polymers. The quantum efficiency (QE) of photocarrier generation was evaluated from the initial slope of the transient photocurrent. Transient photocurrents were measured and showed two unique peaks: one in the range of 10−4 to 10−3 s and the other in the range of 10−1 to 1 s. The transient photocurrents was well simulated (or reproduced) by the expanded two-trapping site model with two kinds of photocarrier generation and recombination processes and two different trapping sites. The obtained photorefractive quantity of trap density was significantly related to the photoconductive parameters of QE. [ABSTRACT FROM AUTHOR]

The article presents an active fault-tolerant control scheme with an integral terminal sliding mode controller for the UAV systems. This scheme effectively addresses saturation issues, disturbances, and sensor and actuator faults. Initially, the quadcopter UAV's model is represented in state space form. Subsequently, an augmented system incorporating auxiliary states from sensor faults is developed. An adaptive sliding mode observer is proposed for estimating the actuator and sensor faults. The integral terminal sliding mode fault-tolerant control, designed for altitude and attitude regulation, relies on fault estimation data. In contrast, a cascade proportional-integral-derivative (PID) controller is employed for position control. Simulation results demonstrate the superiority of the proposed method over existing control algorithms. [ABSTRACT FROM AUTHOR]

After stroke rehabilitation, patients need to reintegrate back into their daily life, workplace and society. Reintegration involves complex processes depending on age, sex, stroke severity, cognitive, physical, as well as socioeconomic factors that impact long-term outcomes post-stroke. Moreover, post-stroke quality of life can be impacted by social risks of inadequate family, social, economic, housing and other supports needed by the patients. Social risks and barriers to successful reintegration are poorly understood yet critical for informing clinical or social interventions. Therefore, the aim of this work is to predict social risk at rehabilitation discharge using sociodemographic and clinical variables at rehabilitation admission and identify factors that contribute to this risk. A Gradient Boosting modelling methodology based on decision trees was applied to a Catalan 217-patient cohort of mostly young (mean age 52.7), male (66.4%), ischemic stroke survivors. The modelling task was to predict an individual’s social risk upon discharge from rehabilitation based on 16 different demographic, diagnostic and social risk variables (family support, social support, economic status, cohabitation and home accessibility at admission). To correct for imbalance in patient sample numbers with high and low-risk levels (prediction target), five different datasets were prepared by varying the data subsampling methodology. For each of the five datasets a prediction model was trained and the analysis involves a comparison across these models. The training and validation results indicated that the models corrected for prediction target imbalance have similarly good performance (AUC 0.831–0.843) and validation (AUC 0.881 - 0.909). Furthermore, predictor variable importance ranked social support and economic status as the most important variables with the greatest contribution to social risk prediction, however, sex and age had a lesser, but still important, contribution. Due to the complex and multifactorial nature of social risk, factors in combination, including social support and economic status, drive social risk for individuals. [ABSTRACT FROM AUTHOR]

Developing collaborative research platforms for quantum bit control is crucial for driving innovation in the field, as they enable the exchange of ideas, data, and implementation to achieve more impactful outcomes. Furthermore, considering the high costs associated with quantum experimental setups, collaborative environments are vital for maximizing resource utilization efficiently. However, the lack of dedicated data management platforms presents a significant obstacle to progress, highlighting the necessity for essential assistive tools tailored for this purpose. Current qubit control systems are unable to handle complicated management of extensive calibration data and do not support effectively visualizing intricate quantum experiment outcomes. In this paper, we introduce Qubit Control Storage and Visualization (QubiCSV), a platform specifically designed to meet the demands of quantum computing research, focusing on the storage and analysis of calibration and characterization data in qubit control systems. As an open-source tool, QubiCSV facilitates efficient data management of quantum computing, providing data versioning capabilities for data storage and allowing researchers and programmers to interact with qubits in real time. The insightful visualization are developed to interpret complex quantum experiments and optimize qubit performance. QubiCSV not only streamlines the handling of qubit control system data but also improves the user experience with intuitive visualization features, making it a valuable asset for researchers in the quantum computing domain. [ABSTRACT FROM AUTHOR]

Elevated body mass index (BMI) has been linked to severe influenza illness and impaired vaccine immunogenicity, but the relationship between BMI and clinical vaccine effectiveness (VE) is less well described. This secondary analysis of data from a test-negative study of outpatients with acute respiratory illness assessed BMI and VE against medically attended, PCR-confirmed influenza over seven seasons (2011–12 through 2017–18). Vaccination status was determined from electronic medical records (EMR) and self-report; BMI was estimated from EMR-documented height and weight categorized for adults as obesity (≥ 30 kg/m2), overweight (25–29 kg/m2), or normal and for children based on standardized z-scales. Current season VE by virus type/subtype was estimated separately for adults and children. Pooled VE for all seasons was calculated as 1—adjusted odds ratios from logistic regression with an interaction term for BMI and vaccination. Among 28,089 adults and 12,380 children, BMI category was not significantly associated with VE against outpatient influenza for any type/subtype. Adjusted VE against A/H3N2, A/H1N1pdm09, and B in adults ranged from 16–31, 46–54, and 44–57%, and in children from 29–34, 57–65, and 50–55%, respectively, across the BMI categories. Elevated BMI was not associated with reduced VE against laboratory confirmed, outpatient influenza illness. [ABSTRACT FROM AUTHOR]

Mitral regurgitation (MR) is associated with morphological and functional alterations of left atrium (LA) and ventricle (LV), possibly inducing LA–LV misalignment. We aimed to: (1) characterize angulation between LA and mitral annulus from conventional cine MRI data and feature-tracking (FT) contours, (2) assess their associations with functional capacity in MR patients, as assessed by oxygen consumption (peak-VO2) and minute ventilation to carbon dioxide production (VE/VCO2) slope, in comparison with MRI LA/LV strain indices. Thirty-two asymptomatic primary MR patients (56 [40; 66] years, 12 women) underwent cardiac MRI resulting in LA/LV conventional FT-derived strain indices. Then, end-diastolic angles were derived from FT LA contours: (1) α, centered on the LA centre of mass and defined by mitral valve extremities, (2) γ, centered on the mitral ring anterior/lateral side, and defined by LA centre and the other extremity of the mitral ring. Cardiopulmonary exercise testing with simultaneous echocardiography were also performed; peak-VO2 and VE/VCO2 slope were measured. While peak-VO2 and VE/VCO2 slope were not correlated to LA/LV strains, they were significantly associated with angles (α: r = 0.50, p = 0.003 and r = − 0.52, p = 0.003; γ: r = − 0.53, p = 0.002 and r = 0.52, p = 0.003; respectively), independently of age and gender (R2 ≥ 0.29, p ≤ 0.03). In primary MR, the new LA/mitral annulus angles, computed directly from standard-of-care MRI, are better correlated to exercise tolerance than conventional LA/LV strain. [ABSTRACT FROM AUTHOR]

This study aims to provide in vitro and in vivo data to support the utilization of antinuclear antibodies (ANAs) as novel tools for the diagnosis and treatment of prostate cancers. The hematological, biochemical, and histological toxicities of ANAs were assessed at the doses of 5 and 50 μg per mouse. Radiolabeling study was then conducted with ANA and 131I using the chloramine T method, and the biodistribution and treatment efficacy were subsequently investigated in a PC3 xenograft model. No changes in clinical behavior or signs of intoxication, necrosis, or malignancy were observed in ANA-treated mice. 131I-ANA was obtained in very high yield and radiochemical purity, at 94.97 ± 0.98% and 98.56 ± 0.29%, respectively. They achieved immunoreactivity fraction of 0.841 ± 0.17% with PC-3 cells. Levels of radiolabeled ANAs were 1.15–10.14 times higher in tumor tissues than in other examined organs at 24 h post-injection. The tumor growth inhibition rates were 28.33 ± 5.01% in PC3 xenografts mice treated with 131I-ANAs compared with controls and a nearly twofold improvement in median survival was observed. These results demonstrate that radioimmunotherapy of radiolabeled natural ANAs may be an effective treatment for prostate tumors. [ABSTRACT FROM AUTHOR]

Meta-heuristic algorithms distinguish themselves from conventional optimization methods owing to their intrinsic adaptability and straightforward implementation. Among them, the sine cosine algorithm (SCA) is lauded for its ability to transition seamlessly between exploration and exploitation phases throughout the optimization process. However, there exists potential for enhancing the balance that SCA maintains between exploration and exploitation. To augment the proficiency in global optimization of SCA, an innovative strategy—nSCA—that integrates the roulette wheel selection (RWS) with opposition-based learning was formulated. The robustness of nSCA was rigorously evaluated against leading-edge methods such as the genetic algorithm (GA), particle swarm optimization, moth-flame optimization, ant lion optimization, and multi-verse optimizer, as well as the foundational SCA. This evaluation included benchmarks set by both CEC 2019 and CEC 2021 test functions. Additionally, the performance of nSCA was confirmed through numerous practical optimization problems, emphasizing its effectiveness in applied settings. In all evaluations, nSCA consistently showcased superior performance compared to its evolutionary algorithm counterparts, delivering top-tier solutions for both benchmark functions and real-world optimization challenges. Given this compelling evidence, one can posit that nSCA serves as a strong candidate for addressing intricate optimization challenges found in real-world contexts, regardless of whether they are of a discrete or continuous nature. [ABSTRACT FROM AUTHOR]

The present study focuses on the problem of vehicle routing with limited capacity, with the objective of minimizing the transportation distance required to serve h clients with predetermined locations and needs. The aim is to create k trips that cover the shortest possible distance. To achieve this goal, a hybrid whale optimization algorithm (hGWOA) is proposed, which combines the whale optimization algorithm (WOA) with the grey wolf optimizer (GWO). The proposed hybrid model is comprised of two main steps. First step, the GWO's hunting mechanism is integrated transitioning to the utilization phase of WOA, and a newly devised state is introduced that is linked to GWO. In the second step, a novel technique is incorporated into the exploration mission phase to enhance the resolve after per iteration. The algorithm's performance is assessed and compared with other modern algorithms, including the GWO, WOA, ant lion optimizer (ALO), and dragonfly algorithm (DA) using 23 benchmark test functions and CEC2017 benchmark test function. The results indicate that the hybrid hGWOA method outperforms other algorithms in terms of delivery distance optimization for scenarios involving scale and complexity. These findings are corroborated through case studies related to cement delivery and a real-world scenario in Viet Nam. [ABSTRACT FROM AUTHOR]

Sarcopenia, a condition characterized by muscle mass decline, is one of the leading health problems in the elderly. This study determined the rate of sarcopenia according to criteria by Asian Working Group for Sarcopenia (AWGS) and related factors in elderly people. A community-based cross-sectional study was conducted in 632 people aged 60 years or over in Ho Chi Minh City. Data were collected through a predefined questionnaire and direct measurement. Sarcopenia was identified based on the Inbody 770 machine and AWGS criteria. The prevalence of sarcopenia was 32.0%. Participants with advanced age, low education, unemployment, low level of family economics and frailty were more likely to have sarcopenia. Among these, frailty had the highest impact on sarcopenia, with significantly higher odds of having sarcopenia found in participants with pre-frailty (OR = 4.80, 95% CI 2.75–8.38, p < 0.001) and frailty (OR = 21.16, 95% CI 8.96–49.97, p < 0.001). In contrast, BMI was inversely associated with sarcopenia. Sarcopenia is prevalent in the Vietnamese elderly. Apart from social demographic characteristics including age, education, employment and family economic status, frailty appeared to be an important risk factor. Early screening, referral, and treatment of sarcopenia among the elderly having a high risk of sarcopenia are recommended. [ABSTRACT FROM AUTHOR]

The cao vit gibbon (Nomascus nasutus) is one of the rarest primates on Earth and now only survives in a single forest patch of less than 5000 ha on the Vietnam–China border. Accurate monitoring of the last remaining population is critical to inform ongoing conservation interventions and track conservation success over time. However, traditional methods for monitoring gibbons, involving triangulation of groups from their songs, are inherently subjective and likely subject to considerable measurement errors. To overcome this, we aimed to use 'vocal fingerprinting' to distinguish the different singing males in the population. During the 2021 population survey, we complemented the traditional observations made by survey teams with a concurrent passive acoustic monitoring array. Counts of gibbon group sizes were also assisted with a UAV-mounted thermal camera. After identifying eight family groups in the acoustic data and incorporating long-term data, we estimate that the population was comprised of 74 individuals in 11 family groups, which is 38% smaller than previously thought. We have no evidence that the population has declined—indeed it appears to be growing, with new groups having formed in recent years—and the difference is instead due to double-counting of groups in previous surveys employing the triangulation method. Indeed, using spatially explicit capture-recapture modelling, we uncovered substantial measurement error in the bearings and distances from field teams. We also applied semi- and fully-automatic approaches to clustering the male calls into groups, finding no evidence that we had missed any males with the manual approach. Given the very small size of the population, conservation actions are now even more urgent, in particular habitat restoration to allow the population to expand. Our new population estimate now serves as a more robust basis for informing management actions and tracking conservation success over time. [ABSTRACT FROM AUTHOR]

Most current genotype imputation methods are reference-based, which posed several challenges to users, such as high computational costs and reference panel inaccessibility. Thus, deep learning models are expected to create reference-free imputation methods performing with higher accuracy and shortening the running time. We proposed a imputation method using recurrent neural networks integrating with an additional discriminator network, namely GRUD. This method was applied to datasets from genotyping chips and Low-Pass Whole Genome Sequencing (LP-WGS) with the reference panels from The 1000 Genomes Project (1KGP) phase 3, the dataset of 4810 Singaporeans (SG10K), and The 1000 Vietnamese Genome Project (VN1K). Our model performed more accurately than other existing methods on multiple datasets, especially with common variants with large minor allele frequency, and shrank running time and memory usage. In summary, these results indicated that GRUD can be implemented in genomic analyses to improve the accuracy and running-time of genotype imputation. [ABSTRACT FROM AUTHOR]