Search Results (147)

Physics concepts are considered an essential component of STEM (science, technology, engineering, and mathematics) education and fundamental for economic and technological development in the world. However, there can be student academic underperformance, such as the school environment, learning media and infrastructure, student interest and emotions, as well as social and economic development factors in communities. These problems are even more acute in rural areas of developing countries, where poverty is high and teachers often lack the necessary technological skills. The aim of this study was to evaluate the impact of a low-cost STEM tool focused on motivation in learning, in terms of five variables of interest in physics in rural areas, as well as the durability of the tools used to learn 12 physics concepts. A quasi-experimental study was conducted with the participation of 78 high school students, with an average age of 15.82 years, in a rural area of Guerrero, Mexico. The results showed that using the STEM tool significantly increased students’ interest in learning methodology, active participation, and attitude towards physics, facilitating the teacher’s work. In addition, the 3D construction kit used in the experimentation, besides being low-cost, proved to be affordable and durable, making it ideal for use in rural areas. Full article

The architecture, engineering, and construction (AEC) industry faces challenges related to inefficiencies and fragmentation that highlight the need for advanced construction technologies and drive interest in innovative solutions such as the platform approach to design. This study assessed platform-based building design through (1) interviews with practitioners from China, Jordan, and the UK, which helped to define the platform approach in the AEC industry and the challenges involved, and (2) a residential building design simulation conducted to evaluate the potential of the platform approach. The simulated design’s materials costs, energy efficiency, and construction time were compared with those of the traditional building design. The results of the comparison corroborate the interview findings concerning practitioners’ perspectives on platform definition, benefits, challenges, and implementation. The findings also demonstrate the potential of the platform approach to enhance productivity and scalability through modularization, kit-of-parts configuration, and standardization. This research bridges the gap between theory and practice by supporting shareholder perspectives on building design and construction with the results of a simulated platform approach to a real-world design project. This research addresses the urgent need to better understand and test the platform approach to achieve material, energy, and construction time savings through collaborative and practice-informed design. Full article

One of the key elements in the analysis of gene expression and its post-translational regulation is miRNAs. Degradome-seq analyses are performed to analyze the cleavage of target RNAs in the transcriptome. This work presents the first degradome-seq library preparation protocol that enables successful construction of libraries, even from highly degraded RNA samples with RIN below 3, thus significantly expanding the possibilities for research when working with low-quality material. The developed protocol improves the efficiency of library preparation in degradome-seq analysis used to identify miRNA targets, reduces library preparation time, and lowers the cost of purchasing reagents by using reagents from the RNA-seq library preparation kit and proprietary-designed primers. A crucial feature of this new protocol is optimizing the purification step for short library fragments, which increases the yield of correctly sized fragments compared to previously used methods. This is achieved by implementing an original method involving tube-spin purification with gauze and precipitation using sodium acetate with glycogen, greatly enhancing recovery efficiency—a factor especially critical when working with degraded RNA. Cloning to a plasmid and sequencing of the inserted fragment verified the correctness of the library preparation using the developed protocol. This protocol represents a groundbreaking tool for degradome research, enabling the construction and sequencing of degradome libraries, even from degraded samples previously considered unsuitable for such analyses. This is due to the use of residues from the sRNA-seq library kit. It noticeably reduces the cost of library construction. The precision of the excised fragment after electrophoresis was performed during the procedure to isolate fragments of the correct length, which was improved using additional size markers. Compared to previously used methods, optimizing the purification method of degradome-seq libraries allowed an increase in the yield of fragments obtained. Full article

Lead (Pb) exposure poses a significant public health concern due to its neurotoxic effects. While mitochondrial dysfunction is implicated in lead neurotoxicity, the precise molecular mechanisms, particularly the role of non-coding RNA-mediated competing endogenous RNA networks, remain underexplored. SH-SY5Y neuroblastoma cells were treated with 10 μM lead acetate. Cell viability was assessed by Cell Counting Kit-8 (CCK-8). Mitochondrial ultrastructure and quantity were analyzed via transmission electron microscopy (TEM). Key mitochondrial dynamics proteins were examined by Western blot. Comprehensive transcriptome sequencing, including long non-coding RNAs (lncRNAs), circular RNAs (circRNAs), microRNAs (miRNAs) and mRNAs, was performed followed by functional enrichment and ceRNA network construction. Selected RNAs and hub genes were validated using quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR). Lead exposure significantly reduced SH-SY5Y cell viability and induced mitochondrial damage (decreased quantity, swelling, fragmentation). Western blot confirmed an imbalance in mitochondrial dynamics, as indicated by decreased mitofusin 2 (MFN2), increased total and phosphorylated dynamin-related protein 1 (DRP1). Transcriptomic analysis revealed widespread differential expression of lncRNAs, circRNAs, miRNAs, and mRNAs. Enrichment analysis highlighted mitochondrial function and oxidative stress pathways. A ceRNA network identified five key hub genes: SLC7A11, FOS, HMOX1, HGF, and NR4A1. All validated RNA and hub gene expression patterns were consistent with sequencing results. Our study demonstrates that lead exposure significantly impairs mitochondrial quantity and morphology in SH-SY5Y cells, likely via disrupted mitochondrial dynamics. We reveal the potential regulatory mechanisms of lead-induced neurotoxicity involving ceRNA networks, identifying hub genes crucial for cellular stress response. This research provides a foundational framework for developing therapeutic strategies against lead-induced neurotoxicity. Full article

Background: Cancer vaccines represent a groundbreaking advancement in cancer immunotherapy, utilizing tumor antigens to induce tumor-specific immune responses. However, challenges like tumor-induced immune resistance and technical barriers limit the widespread application of predefined antigen vaccines. Here, we investigated the potential of viral protein R (Vpr) peptides as effective candidates for constructing anonymous antigen vaccines in situ by directly injecting at the tumor site and releasing whole-tumor antigens, inducing robust anti-tumor immune responses to overcome the limitations of predefined antigen vaccines. Methods: The cytotoxic effects of Vpr peptides were evaluated using the CCK8 reagent kit. Membrane penetration ability of Vpr peptides was observed using a confocal laser scanning microscope and quantitatively analyzed using flow cytometry. EGFR levels in the cell culture supernatants of cells treated with Vpr peptides were evaluated using an ELISA. Surface exposure of CRT on the tumor cell surface was observed using a confocal laser scanning microscope and quantitatively analyzed using flow cytometry. The secretion levels of ATP from tumor cells were evaluated using an ATP assay kit. HMGB1 release was evaluated using an ELISA. Mouse (Male C57BL/6 mice aged 4 weeks) MC38 and LLC bilateral subcutaneous tumor models were established to evaluate the therapeutic effects of Vpr peptides through in situ vaccination. Proteomic analysis was performed to explore the mechanism of anti-tumor activity of Vpr peptides. Results: Four Vpr peptides were designed and synthesized, with P1 and P4 exhibiting cytotoxic effects on tumor cells, inducing apoptosis and immunogenic cell death. In mouse tumor models, in situ vaccination with Vpr peptide significantly inhibited tumor growth and activated various immune cells. High-dose P1 monotherapy demonstrated potent anti-tumor effects, activating DCs, T cells, and macrophages. Combining ISV of P1 with a CD47 inhibitor SIRPαFc fusion protein showed potent distant tumor suppression effects. Proteomic analysis suggested that Vpr peptides exerted anti-tumor effects by disrupting tumor cell morphology, movement, and adhesion, and promoting immune cell infiltration. Conclusions: The designed Vpr peptides show promise as candidates for in situ vaccination, with significant anti-tumor effects, immune activation, and favorable safety profiles observed in mouse models. In situ vaccination with Vpr-derived peptides represents a potential approach for cancer immunotherapy. Full article

Fibronectin (FN), a primary component of the extracellular matrix (ECM), features multiple structural domains closely linked to various cellular behaviors, including migration, spreading, adhesion, and proliferation. The FN3 domain, which contains the RGD sequence, is critical in tissue repair because it enables interaction with integrin receptors on the cell surface. However, the large molecular weight of wild-type FN presents challenges for its large-scale production through heterologous expression. Therefore, this study focused on cloning the FN3 functional domain of full-length FN for expression and validation. This study selected Bacillus subtilis as the expression host due to its prominent advantages, including efficient protein secretion, absence of endotoxins, and minimal codon bias. The recombinant vector pHT43-FN3 was successfully constructed through homologous recombination technology and transformed into Bacillus subtilis WB800N. The FN3 protein was successfully expressed after induction with IPTG. Following purification of the recombinant FN protein using a His-tag nickel column, SDS-PAGE analysis showed that the molecular weight of FN3 was approximately 27.3 kDa. Western blot analysis confirmed the correct expression of FN3, and the BCA protein assay kit determined a protein yield of 5.4 mg/L. CCK8 testing demonstrated the good biocompatibility of FN3. In vitro cell experiments showed that FN3 significantly promoted cell migration at a 20 μg/mL concentration and enhanced cell adhesion at 10 μg/mL. In summary, this study successfully utilized Bacillus subtilis to express the FN3 functional domain peptide from FN protein and has validated its ability to promote cell migration and adhesion. These findings not only provide a strategy for the expression of FN protein in B. subtilis, but also establish an experimental foundation for the potential application of FN3 protein in tissue repair fields such as cutaneous wound healing and cartilage regeneration. Full article

Consumer-grade electronics are ubiquitous and can be used to manage a range of devices for various purposes. Such devices can be both mobile and stationary. They have become increasingly intelligent in operation, utilizing complex software. The circular economy is a trend in which everyday utility items are designed with recyclable and easily recyclable materials. The materials may not be durable, but they make it easy to dispose of them at the end of their life. In this paper, we extend the concept of the circular economy to the design of electronic devices using cardboard as a flat-pack surface material. We propose a small device design technique and discuss its associated issues, enabling novice users to construct, install, and calibrate custom-built electronic devices. This is in the form of a kit that includes a cardboard flat-pack, a flexible electronic circuit board, and an instruction manual. We also discuss a software design algorithm that can be used to calibrate the newly constructed device. We only consider stationary devices and investigate the proposed devices and software with a sedentary behavior monitoring application. A trial with human participants was conducted to determine the ease of contracting and initially installing the devices. The results show that the proposed approach is highly feasible for novice human users and a high degree of trust with such devices. Full article

Background/Objectives: Lipid metabolism plays a crucial role in uterine corpus endometrial carcinoma (UCEC); however, its specific mechanisms remain to be fully elucidated. This study aimed to construct a lipid-metabolism-related prognostic model and explore its association with the tumor immune microenvironment. Methods: A total of 552 UCEC and 35 normal tissue samples from The Cancer Genome Atlas (TCGA) database were analyzed to identify differentially expressed lipid-metabolism-related genes (DE-LMRGs). A prognostic risk model was established using univariate Cox analysis, least absolute shrinkage and selection operator (LASSO) regression, and multivariate Cox regression, and its clinical utility was assessed through nomogram construction. Functional enrichment analysis was performed to explore the biological pathways involved. Tumor immune infiltration patterns were evaluated using single-sample Gene Set Enrichment Analysis (ssGSEA), Estimation of Stromal and Immune Cells in Malignant Tumors using Expression Data (ESTIMATE), and Tumor Immune Dysfunction and Exclusion (TIDE) algorithms. Results: Multivariate analysis indicated that the prognostic model had robust predictive value, with AUCs of 0.701, 0.746, and 0.790 for 1-, 3-, and 5-year overall survival predictions. High-risk patients exhibited a suppressed immune microenvironment characterized by reduced immune cell infiltration, lower tumor mutation burden (TMB), and elevated TIDE scores, suggesting potential resistance to immunotherapy. Furthermore, LIPG was identified as a key hub gene through the intersection of nine machine learning algorithms, demonstrating strong associations with both cancer progression and immune infiltration. Functional validation using Cell Counting Kit-8 (CCK-8), wound healing, and transwell migration assays following small interfering RNA (siRNA) transfection demonstrated that LIPG promotes UCEC cell proliferation and migration in vitro. Conclusions: These findings highlight the critical role of lipid metabolism in UCEC progression and immune modulation, with LIPG emerging as a potential prognostic biomarker. The identified lipid-metabolism-related gene signature may provide new insights into tumor microenvironment interactions. Full article

Triazolopyrimidine and its analogs represent an important scaffold in medicinal chemistry research. The heterocycle of 1,2,4-triazolo[1,5-a] pyrimidine (1,2,4-TAP) serves as a bioisostere candidate for purine scaffolds, N-acetylated lysine, and carboxylic acid. This study modeled the quantitative structure–activity relationship (QSAR) of 125 congeners of 1,2,4-TAP from the ChEMBL database in the inhibition of Plasmodium falciparum using six machine learning algorithms. The most significant features among 306 molecular descriptors, including one molecular outlier, were selected using recursive feature elimination. A ratio of 20% was used to split the x- and y-matrices into 99 training and 24 test compounds. The regression models were built using machine learning sci-kit-learn algorithms (multiple linear regression (MLR), k-nearest neighbours (kNN), support vector regressor (SVR), random forest regressor (RFR) RIDGE regression, and LASSO). Model performance was evaluated using the coefficient of determination (R²), mean squared error (MSE), mean absolute error (MAE), root mean squared error (RMSE), p-values, F-statistic, and variance inflation factor (VIF). Five significant variables were considered in constructing the model (p < 0.05) with the following regression equation: pIC₅₀ = 5.90 − 0.71npr1 − 1.52pmi3 + 0.88slogP − 0.57vsurf-CW2 + 1.11vsurf-W2. On five-fold cross-validation, three algorithms—kNN (MSE = 0.46, R² = 0.54, MAE = 0.54, RMSE = 0.68), SVR (MSE = 0.33, R² = 0.67, MAE = 0.46, RMSE = 0.57), and RFR (MSE = 0.43, R² = 0.58, MAE = 0.51, RMSE = 0.66)—showed strong robustness, efficiency, and reliability in predicting the pIC₅₀ of 1,2,4-triazolo[1,5-a]pyrimidine. The models provided useful data on the functionalities necessary for developing more potent 1,2,4-TAP analogs as anti-malarial agents. Full article

In this study, a RGB based ternary-emission molecularly imprinted ratiometric fluorescence (MI-RFL) sensor was facilely constructed by using a post-imprinting mixing strategy for the sensitive detection of enrofloxacin (ENR). Upon excitation at 365 nm, the MI-RFL sensor exhibited significant emission peaks at 450, 550, and 620 nm. As the ENR concentration increased, the blue fluorescence generated by ENR in the sensing system gradually intensified, while the red and green fluorescence emitted by the quantum dots in the molecularly imprinted polymers (MIPs) was significantly quenched. Sensing conditions were systematically investigated, including the excitation wavelength, mixing ratio of red/green MIPs, the pH of the buffer solution, and the reaction time. Under the optimal conditions, the developed sensor showed a good linear relationship within the range of 0.25–4 ppm along with obvious color change, with a low detection limit of 0.134 ppm. High selectivity was also attained with an imprinting factor up to 11.65. When applied to real samples of seawater and seafood, the sensor showed good recovery rates of 94.3–126.4% and accuracy with a relative standard deviation of less than 3.97%. Furthermore, the sensor-based kit was easily fabricated and, thus, naked-eye detection of ENR was realized onsite. This study can provide a universal approach for the rapid and visual detection of ENR in complicated matrices. Full article

SNAP-tag and Halo-tag have been employed to achieve targeted RNA editing by directing the deaminase domain of human ADAR to specific sites in the transcriptome. This targeting is facilitated by short guide RNAs (gRNAs) complementary to the target transcript, which are chemically modified with benzylguanine or chloroalkane moieties to enable covalent binding to the respective self-labeling enzymes. However, broad application of this approach has been limited by challenges such as low scalability, the requirement for specialized chemical expertise and equipment, and labor-intensive protocols. In this study, we introduce streamlined, efficient protocols for the synthesis and purification of these linkers, suitable for SNAP-tag and Halo-tag applications, without the need for advanced chemical equipment. Our methods enable linker coupling in a kit-like manner and support the high-yield production of modified gRNAs. We demonstrate that the newly synthesized linkers and gRNA designs perform similarly to previously published constructs with regard to RNA editing efficiency. Moreover, large-scale production of modified gRNAs facilitates their use in studies involving cellular uptake and in vivo experiments. Full article

Purpose: Interstitial cystitis/bladder pain syndrome (IC/BPS) is mysterious and difficult to diagnose without cystoscopic hydrodistention. This study aimed to explore non-invasive and highly reliable urine biomarkers to identify Hunner’s IC (HIC) and different non-Hunner’s IC (NHIC) subtypes. Methods: In total, 422 women with and without clinically diagnosed IC/BPS (n = 376 and 46, respectively) were retrospectively enrolled. Patients were diagnosed with HIC or NHIC by cystoscopic hydrodistention under anesthesia. Then, the maximal bladder capacity (MBC) and glomerulation grade were determined. Thirteen urine inflammatory cytokines, chemokines, and oxidative stress biomarkers based on the previously reported predictors of IC/BPS were assayed using commercial microsphere kits. The dataset was randomly divided into training (70%) and test (30%) sets for model construction and validation using logistic regression and stepwise variable selection techniques. To construct the predictive models, univariate analysis was performed to evaluate the discriminative power of each urinary biomarker, measured by the area under the curve (AUC). Biomarkers with AUC values < 0.6 were excluded from further modeling. Multivariate logistic regression was then employed, with variables selected through stepwise forward selection based on log-likelihood criteria. For dichotomization, cutoff values were determined using quartile ranges from the control group. The final model’s performance was assessed using AUC, accuracy, sensitivity, and specificity in both training and test sets. Results: By setting the screening criterion to AUC ≥ 0.60, the potential urinary biomarkers for identifying IC/BPS cases were eotaxin, monocyte chemoattractant protein-1, tumor necrosis factor-alpha (TNF-α), 8-hydroxy-2′-deoxyguanosine (8-OHdG), and 8-isoprostane. Those for identifying HIC from the IC/BPS cohort were interleukin (IL)-6, IL-8, interferon γ-inducible protein 10 (IP-10), and regulated on activation, normal T-cell expressed and secreted (RANTES). A diagnostic algorithm using a cluster of urinary biomarkers included TNF-α ≥ 0.95 pg/mL or 8-OHDG ≥ 22.34 pg/mL and 8-isoprastane ≥ 22.34 pg/mL for identifying IC/BPS from the overall cohort; for identifying HIC from the IC/BPS cohort, the urinary IP-10 ≥ 3.74 pg/mL or IP-10 ≥ 19.94 pg/mL was added. Conclusions: Using a cluster of urinary biomarkers such as TNF-α or 8-OHdG and 8-isoprostane can identify IC/BPS from a study cohort, and adding the urinary IP-10 can distinguish HIC from IC/BPS cases. Full article

The increasing volatility of the markets and the growing demand for customized products are challenges for future production to ensure maximum flexibility and adaptability. This paper introduces software-defined value stream process systems (SVPSs), a novel approach that extends the concept of software-defined manufacturing into autonomous, reconfigurable production systems. SVPSs establish a cyber–physical chain that links product features to requirements, enabling their fulfillment through modular machine and process hardware. A modular construction kit of individually combinable hardware and associated software modules is presented. These modules are coordinated via a digital process chain that enables holistic simulations, optimizations, and planning based on a Digital Twin. This system is based on software-defined manufacturing but extends it into autonomous reconfigurable machines. By enabling virtual planning and commissioning of entire production lines, the SVPS concept provides an efficient and adaptable solution to meet the demands of volatile markets. Full article

Porcine circovirus type 2 (PCV2) is the main and primary causative agent of Postweaning Multisystemic Wasting Syndrome (PMWS). To date, immunoperoxidase monolayer assay (IPMA), indirect immunofluorescent assay (IFA), and enzyme linked immunosorbent assay (ELISA) are the most commonly diagnostic methods for detecting PCV2 antigens. However, these methods require specialized equipment and technical expertise and are suitable for laboratory use only. This study aims to develop an immunochromatographic strip and a magnetic chemiluminescence immunoassay for the detection of PCV2 antigens. The recombinant protein was constructed using a prokaryotic expression system, and the polyclonal antibody was obtained by animal experiments. Polystyrene microspheres are used as solid phase carriers to covalently bind to the amino groups of proteins to form immunoprobes. Monodisperse beads are covalently bound to antigens or antibodies as solid phases to bind antibodies or antigens in the liquid phase in a superior manner, thereby capturing and separating antigens and antibodies in the liquid phase. The immunochromatographic strip is qualitative detection method, this method can detect PCV2a strain, PCV2b strain, and PCV2d strain. The immunochromatographic strip had minimum detection limits of 10^2.89TCID₅₀/0.1 mL, 10^3.19TCID₅₀/0.1 mL, and 10^3.49TCID₅₀/0.1 mL for PCV2a/LG, PCV2b/SH, and PCV2d/JH. The results of testing PEDV (CV777 strain), PRV (HB2000 strain), CSFV (WH-09 strain), PRRS (JXA1-R strain), PPV (WH-1 strain), and ASFV (SD strain) were negative. The agreement between the immunochromatographic strip and the ELISA kit was 93.33% (140/150) and the Kappa was 0.866 (Kappa > 0.81). On the premise of ensuring sensitivity, the most important feature of the immunochromatographic strip is that this method can save time when testing; results can be obtained within 5 to 10 min. Magnetic chemiluminescence immunoassay is quantitative detection method; this method can detect PCV2 Cap proteins in swine serum, the linear range of this method was 0.25 ng/mL to 32 ng/mL and R² of the standard curve was 0.9993. The limit of detection (LOD) is 0.051 ng/mL and the limit of quantitation (LOQ) is 0.068 ng/mL. The agreement between the magnetic chemiluminescence immunoassay and the ELISA kit (test PCV2 Cap proteins) was 97.14% (68/70). This method took less than 30 min to achieve results, which is less than the ELISA kit. The results of this study show that immunochromatographic strip and magnetic chemiluminescence immunoassay for PCV2 antigens had great sensitivity and specificity, which lays the foundation for PCV2 clinical detection. Full article

Convolutional neural networks (CNNs) are increasingly recognized as an important and potent artificial intelligence approach, widely employed in many computer vision applications, such as facial recognition. Their importance resides in their capacity to acquire hierarchical features, which is essential for recognizing complex patterns. Nevertheless, the intricate architectural design of CNNs leads to significant computing requirements. To tackle these issues, it is essential to construct a system based on field-programmable gate arrays (FPGAs) to speed up CNNs. FPGAs provide fast development capabilities, energy efficiency, decreased latency, and advanced reconfigurability. A facial recognition solution by leveraging deep learning and subsequently deploying it on an FPGA platform is suggested. The system detects whether a person has the necessary authorization to enter/access a place. The FPGA is responsible for processing this system with utmost security and without any internet connectivity. Various facial recognition networks are accomplished, including AlexNet, ResNet, and VGG-16 networks. The findings of the proposed method prove that the GoogLeNet network is the best fit due to its lower computational resource requirements, speed, and accuracy. The system was deployed on three hardware kits to appraise the performance of different programming approaches in terms of accuracy, latency, cost, and power consumption. The software programming on the Raspberry Pi-3B kit had a recognition accuracy of around 70–75% and relied on a stable internet connection for processing. This dependency on internet connectivity increases bandwidth consumption and fails to meet the required security criteria, contrary to ZYBO-Z7 board hardware programming. Nevertheless, the hardware/software co-design on the PYNQ-Z2 board achieved an accuracy rate of 85% to 87%. It operates independently of an internet connection, making it a standalone system and saving costs. Full article