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Abstract 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 Cluster analysis can also detect abnormalities besides building a basis for identifying elements into clusters. Detecting abnormalities is a highly developed feature in the field of unsupervised learning. However, existing studies have mainly focused on discrete data, not probability density functions. This paper enables a possibilistic approach to solving the clustering for probability density functions dealing with abnormal elements. First, the data are extracted using the density function. Then, they are passed through the proposed algorithm to produce a possibilistic partition. Finally, a decision rule is established to recognize which function is abnormal. We compare the proposed algorithm with baseline algorithms in clustering PDFs, such as k-means, FCF, and Self-Updated Clustering. The results of three numerical examples applied to the image are typical for this new method. Furthermore, The proposed algorithm reaches accuracy at 100% over simulated benchmark data and outperforms baseline methods. Additionally, two last examples apply to image data reaching G-mean up from 96 to 100% (Sensitivity: 92–100% and Specificity: 100%). The proposed method can be researched and used to understand the internal structures of big data in the digital age through the probability density functions.

This study examines a cooperative non-orthogonal multiple access (NOMA) network utilizing an energy-constrained unmanned aerial vehicle (UAV) relay (UAVR) to expand coverage and improve network throughput. In order to provide energy to the UAVR, we consider the hybrid simultaneous wireless information and power transmission (SWIPT) method, which allows the UAVR to harvest energy from the source (i.e., sink node) signal. Herein, a hybrid time switching (TS)-based and power splitting (PS)-based relaying scheme is applied to improve the UAVR’s energy harvesting (EH) efficiency and the system performance. Given this context, we derive the closed-form expression of the outage probability (OP) for the sensors to evaluate the network performance. Based on the achieved analytical results, we apply the bat algorithm optimization (BAO) method to determine the optimal working point (as a fraction of received power and power allocation coefficients, and the 3-D positions of the UAVR) for the system such that the OP is minimized. The numerical analysis indicates that BAO is effective in both exploring and exploiting solutions, making it a suitable choice for similar non-convex optimization problems in continuous search spaces for cooperative NOMA IoT networks.

This study aims to assess high school students' learning outcomes, their achievement of goals and fulfilling academic requirements and how the entire teaching and learning process takes place. The study, consisting of an experimental group and a control group was conducted for pre-test and post-test comparisons of the academic performance of 88 10th grade students. 44 students were selected as the experimental group that underwent a specific teaching strategy to monitor their development of qualities and competencies in one semester, and the remaining 44 students acted as the control group. The data collected after the tests were analyzed using SPSS software (V20). The results showed that the students in the experimental group had better academic results than those in the control group. The findings of this study have implications for policy, further research as well as approaches for the assessment of students' development of qualities and competencies in Vietnam.

Deubiquitinating enzymes (DUBs) prevent ubiquitination by eliminating ubiquitin from their substrates. Deubiquitinating enzymes have important roles in a number of cell biology subfields that are highly relevant to diseases like neurodegeneration, cancer, autoimmune disorders, and long-term inflammation. Deubiquitinating enzymes feature a well-defined active site and, for the most part, catalytic cysteine, which makes them appealing targets for small-molecule drug development. Ubiquitin-specific protease 46 (USP46) is a member of the ubiquitin-specific protease family, the largest subfamily of DUBs. Over the past 10 years, some studies have steadily demonstrated the significance of USP46 in several biological processes, although it was identified later and early research progress was modest. Specifically, in the last few years, the carcinogenic properties of USP46 have become more apparent. In the current review, we provide a comprehensive overview of the current knowledge about USP46 including its characteristics, structure, inhibitors, function in diseases, especially in the nervous system, and the correlation of USP46 with cancers.

Vietnam is regarded as one of the developing countries that successfully attracts foreign direct investment (FDI). Approaching and transferring technology in FDI projects is the top priority in promoting Vietnam’s FDI attractiveness strategy. The estimated results show that FDI positively contributed to technology development, stimulating innovation in science and technology applications while improving competitiveness for domestic enterprises. However, due to the lack of R&D activities and management capabilities, it still has numerous difficulties in applying and transferring technology to Vietnam. Therefore, to enhance the efficiency of FDI on technology development, Vietnam needs to strongly implement further solutions.

Manufacturing of adeno-associated viruses (AAV) for gene and cell therapy applications has increased significantly and spurred development of improved mammalian and insect cell-based production systems. We developed a baculovirus-based insect cell production system—the SGMO Helper—with a novel gene architecture and greater flexibility to modulate the expression level and content of individual Rep and Cap proteins. In addition, we incorporated modifications to the AAV6 capsid sequence that improves yield, capsid integrity, and potency. Production of recombinant AAV 6 (rAAV6) using the SGMO Helper had improved yields compared to the Bac-RepCap helper from the Kotin lab. SGMO Helper-derived rAAV6 is resistant to a previously described proteolytic cleavage unique to baculovirus-insect cell production systems and has improved capsid ratios and potency, in vitro and in vivo, compared with rAAV6 produced using Bac-RepCap. Next-generation sequencing sequence analysis demonstrated that the SGMO Helper is stable over six serial passages and rAAV6 capsids contain comparable amounts of non-vector genome DNA as rAAV6 produced using Bac-RepCap. AAV production using the SGMO Helper is scalable using bioreactors and has improved yield, capsid ratio, and in vitro potency. Our studies demonstrate that the SGMO Helper is an improved platform for AAV manufacturing to enable delivery of cutting-edge gene and cell therapies.

Spontaneous idiopathic vulvar edema during the second trimester is a rare condition. The approach to managing this condition involves relieving symptoms, identifying underlying causes, and implementing appropriate treatment. Managing such cases during pregnancy is challenging because of concerns for potential adverse fetal outcomes. Conservative management expects the condition to be relieved spontaneously postpartum, whereas invasive treatment offers a more rapid resolution. Treatment choices are controversial because each method has its pros and cons and influences the delivery process to a certain extent. Surgical drainage becomes a viable option when patients are not responsive to medications. We report a case of spontaneous massive vulvar edema in a 22-year-old primigravida in her 23rd week of pregnancy. After ruling out other notable causes of vulvar edema, we decided to intervene using an invasive procedure because she complained of progressive symptoms and discomfort. Subsequently, the edema subsided postprocedure, and the patient experienced successful labor with no complications. This report aims to alert clinicians that drainage attempts should be considered in pregnant patients with worsening symptoms.

Metanephric adenoma presents as a rare benign tumor in children with differentiated diagnoses: Wilms tumor or renal cell carcinoma. When confronted with small renal tumors, whether they fall into one of these three diagnostic categories, tumor resection surgery with laparoscopic partial nephrectomy is considered a viable and effective operative approach. Herein, we report the case of an 11-year-old female patient initially diagnosed with stage T1a renal cell carcinoma with postoperative pathology results confirming metanephric adenoma. Successfully treated with laparoscopic partial nephrectomy, the patient showed no signs of recurrence or metastasis during follow-up.

Cây Dầu lai có củ (Jatropha podagrica Hook. – Euphorbiaceae) được dùng trong y học cổ truyền để chữa bệnh táo bón, nhiễm trùng da, vàng da, và sốt. Thành phần hóa học chủ yếu là các hợp chất nhóm flavonoid, coumarin, acid phenol, diterpenoid, peptide, và steroid. Một số nghiên cứu đã cho biết các tác dụng dược lý tiềm năng của cây Dầu lai có củ như hoạt tính kháng khuẩn, kháng ung thư, chống oxy hóa, ức chế sự phát triển của côn trùng, ức chế thần kinh cơ và hạ huyết áp. Cho đến nay, Dược điển Việt Nam V vẫn chưa có chuyên luận về dược liệu Dầu lai có củ. Do đó, mục tiêu của nghiên cứu này là xác định các đặc điểm thực vật học của cây Dầu lai có củ. Đặc điểm hình thái, vi phẫu, bột dược liệu của lá, thân và rễ được mô tả chi tiết. Kết quả của nghiên cứu này hữu ích cho việc xác định và kiểm nghiệm dược liệu cũng như xây dựng chuyên luận Dầu lai có củ trong Dược điển Việt Nam.

This paper presents a multi-element multiple-input multiple-output (MIMO) antenna with self-isolation and flexible characteristics. The primary radiators of the proposed antenna consist of multiple ellipse-shaped patches arranged in an H-plane configuration. Self-decoupling is achieved by simultaneously different operating modes on the excited element (TM10 mode) and non-excited element (TM02 mode). The proposed method also shows strong extensibility. The measurements on the fabricated 4-element MIMO antenna demonstrate that the proposed decoupling method can improve the isolation by 14 dB. The antenna shows good MIMO diversity performances with respect to the envelope correlation coefficient and diversity gain. Additionally, the antenna also works effectively in when the substrate is bent, which contributes to significantly increasing the applicability of the proposed method in comparison with the other reported methods.

Abstract 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.

This paper introduces the design of a circularly polarized metasurface-based antenna array for C-band satellite applications that owns broadband operation and high gain characteristics. The single radiating element comprises a Y-shape patch and an above-placed 2 × 2 unit-cell metasurface. Further improvement in operating bandwidth and broadside gain is achieved by arranging four single elements in a 2 × 2 configuration and a sequential-phase feed network. A prototype has been fabricated and measured to validate the feasibility of the proposed antenna array. The measured operating bandwidth is 20% (4.50–5.50 GHz), which is an overlap between a −10 dB impedance bandwidth of 29.8% (4.50–5.99 GHz) and a 3 dB axial ratio bandwidth of 20% (4.50–5.50 GHz). Across this operating band, the peak broadside gain is 10.5 dBi. Compared with the recently published studies, the proposed array is a prominent design for producing a wide operating bandwidth and relatively high gains while maintaining the overall compact dimensions.

Anthrax, a widespread zoonosis in low and middle-income countries with low disease awareness and insufficient livestock vaccination coverage, has been known in Lao Cai Province in northern Vietnam for years before its apparent absence in 2009, which requires investigation as this infection is frequently reported from neighbouring provinces and countries. We aimed to describe the seasonal patterns of anthrax (1991-2008), compare livestock anthrax vaccine coverage to disease occurrence (1991- 2022), and delineate the high-risk areas to inform local disease surveillance in the province. We illustrated the seasonal pattern of anthrax and provided a comparison between livestock vaccine coverage and disease occurrence by purely spatial SaTScan (Poisson model, 25% population at risk) to detect spatial clusters of human and livestock anthrax using population derived from zonal statistics routines. The number of cases, crude cumulative incidence, and spatial clusters of human and livestock anthrax were mapped in QGIS. Results indicate peak anthrax incidence from May to October. Buffalo, domestic cattle, and horses accounted for 75% of total animal cases. Horse anthrax was more common in Lao Cai than in its neighbours and often occurred in years with human mortality. Vaccination covered less than 30% of the livestock population. We found an apparent pattern where anthrax was controlled from 1998-2003 with higher vaccine coverage (>20%) and identified spatial clusters of human and livestock anthrax in Muong Khuong, Bao Thang, and Bac Ha districts of Lao Cai. The local public health and veterinary agencies are recommended to revisit the high-risk areas and communicate with neighbouring provinces for a regional approach to anthrax surveillance and control.

ABSTRACT Siderophores are secreted ferric ion chelators used to obtain iron in nutrient-limited environmental niches, including human hosts. While all Escherichia coli express the enterobactin (Ent) siderophore system, isolates from patients with urinary tract infections additionally express the genetically distinct yersiniabactin (Ybt) siderophore system. To determine whether the Ent and Ybt systems are functionally redundant for iron uptake, we compared the growth of different isogenic siderophore biosynthetic mutants in the presence of transferrin, a human iron-binding protein. We observed that Ybt expression does not compensate for deficient Ent expression following low-density inoculation. Using transcriptional and product analysis, we found this non-redundancy to be attributable to a density-dependent transcriptional stimulation cycle in which Ybt functions as an autoinducer. These results distinguish the Ybt system as a combined quorum-sensing and siderophore system. These functions may reflect Ybt as a public good within bacterial communities or as an adaptation to confined, subcellular compartments in infected hosts. This combined functionality may contribute to the extraintestinal pathogenic potential of E. coli and related Enterobacterales.IMPORTANCEPatients with urinary tract infections are often infected with Escherichia coli strains carrying adaptations that increase their pathogenic potential. One of these adaptations is the accumulation of multiple siderophore systems, which scavenge iron for nutritional use. While iron uptake is important for bacterial growth, the increased metabolic costs of siderophore production could diminish bacterial fitness during infections. In a siderophore-dependent growth condition, we show that the virulence-associated yersiniabactin siderophore system in uropathogenic E. coli is not redundant with the ubiquitous E. coli enterobactin system. This arises not from differences in iron-scavenging activity but because yersiniabactin is preferentially expressed during bacterial crowding, leaving bacteria dependent upon enterobactin for growth at low cell density. Notably, this regulatory mode arises because yersiniabactin stimulates its own expression, acting as an autoinducer in a previously unappreciated quorum-sensing system. This unexpected result connects quorum-sensing with pathogenic potential in E. coli and related Enterobacterales.

In assessing the bending attributes for geopolymer composites augmented with uni-directional fibers, methodologies aligned with the established American and European standards yield quantifiable values for flexural strength, denoted as σm*, and its corresponding elasticity modulus, E*. Notably, these values exhibit a pronounced dependency on the size of the testing parameters. Specifically, within a judicious range of support span L relative to specimen height H, spanning a ratio of 10 to 40, these metrics can vary by a factor between 2 and 4. By conducting evaluations across an extensive array of H/L ratios and adhering to the protocols set for comparable composites with a plastic matrix, it becomes feasible to determine the definitive flexural elastic modulus E and shear modulus G, both of which can be viewed as size-neutral material traits. A parallel methodology can be employed to deduce size-agnostic values for flexural strength, σm. The established linear relationship between the inverse practical value E* (1/E*) and the squared ratio (H/L)2 is acknowledged. However, a congruent 1/σm* relationship has been recently corroborated experimentally, aligning primarily with Tarnopolsky’s theoretical propositions. The parameter T, defined as the inverse gradient of 1/σm* about (H/L)2, is integral to these findings. Furthermore, the significance of the loading displacement rate is underscored, necessitating a tailored consideration for different scenarios.

This study presents an approach to synthesizing a mathematical model for determining the composition of geopolymer foams. The focus is on improving the accuracy of multicriteria optimization for metakaolin-based geopolymer composite composition. Experimental data on the physical and mechanical properties of geopolymers are digitized to establish the computational basis for these calculations. Optimization criteria include density, porosity, compressive strength, flexural strength, Young's modulus, volumetric heat capacity, thermal diffusivity, and thermal conductivity. In addition, parameters such as shrinkage, processability, adsorption, adhesion, and economic aspects are also considered. The proposed format aims to fine-tune the geopolymer composite formulation by using the developed model for multi-criteria analysis of technological and physical-mechanical properties of foamed geopolymer composite materials (FGCM). A synthesis of mathematical models including the main criterion, suboptimization, generalized criterion, lexicographic optimization, sorting of alternatives, interval values, and decision tree methods was used to develop methods for multi-criteria optimization of the composition of foamed geopolymers. The study additionally uses the method of criteria convolution, in which the indices of specific criteria are modified in the form of a ratio scale to clarify the limits and boundaries of changes in the composition of the geopolymer mixture. This minimizes contradictory conclusions and expert opinions and highlights the extreme values for each group of parameters. By filtering the raw information, the accuracy of estimates is improved. The exclusivity of the proposed model for determining the composition of foamed geopolymers lies in the possibility of selecting the necessary formulation by mathematical processing of digitized information of the results of measurements of physical-mechanical and operational-technological properties according to the proposed innovative algorithms and schemes. Compared to existing methods, the focus of the proposed method allows for solving problems that are inaccessible to direct observation. This is due to the discovery of hidden information about the interaction of structural and strength parameters. Combining subjective and objective elements of the choice of the optimal geopolymer formulation, the proposed methodology of information processing allows for improving the quality of determining the optimal composition of the geopolymer mixture. The results of multicriteria optimization for foamed geopolymer indicate that the optimal component composition of the geopolymer matrix, within the selected range of variation, consists of 100g metakaolin, 90g potassium activator, 5g silica fume, 100g silica sand, 7g basalt fiber, and 3g aluminum. These proportions yield the best mechanical, thermal, and technological properties.