BioTech最新文献

This study evaluated the effect of ultrasonic pulse-assisted extraction on the yield and antioxidant activity of essential oils from grapefruit (Citrus paradisi) by-products using hydrodistillation and Soxhlet solvent extraction (hexane, acetone, ethanol). Ultrasound was applied at 40% amplitude for 20 min before extraction. Results showed that ultrasound significantly increased extraction yield with hexane (from 2.6 ± 0.58% to 7.6 ± 1.5%) and acetone (from 8.6 ± 0.96% to 12 ± 1.4%), while ultrasound-assisted hydrodistillation nearly doubled the yield (from 0.7 ± 0.03% to 1.5 ± 0.49%). In contrast, ultrasound decreased yield with ethanol by 3%. Antioxidant activity measured by TEAC assay was highest in acetone extracts without ultrasound (13,366.5 ± 7.66 mmol TE/g) and ethanol extracts (12,606.8 ± 0.51 mmol TE/g). However, ultrasound combined with ethanol increased DPPH scavenging activity from 1073.5 ± 1.07 µg/mL to 4933.3 ± 0.71 µg/mL and maintained high flavonoid content (9.41 ± 0.15 mg/mL) and phenolics (5.33 ± 0.09 mg/mL). Ultrasound-assisted hydrodistillation also enhanced antioxidant capacity, with DPPH values rising from 51.82 ± 5.56 µg/mL to 2413.03 ± 3.17 µg/mL. These findings demonstrate that ultrasound effectively enhances essential oil extraction and antioxidant activity depending on the solvent used, underscoring the potential of this clean technology for valorizing citrus by-products.

In bioinformatics, pathway analyses are used to interpret biological data by mapping measured molecules with known pathways to discover their functional processes and relationships. Pathway analysis has become an essential tool for interpreting large-scale omics data, translating complex gene sets into actionable experimental insights. However, issues inherent to pathway databases and misinterpretations of pathway relevance often result in "pathway fails," where findings, though statistically significant, lack biological applicability. For example, the Tumor Necrosis Factor (TNF) pathway was originally annotated based on its association with observed tumor necrosis, while it is multifunctional across diverse physiological processes in the body. This review broadly evaluates pathway analysis interpretation, including embedding-based, semantic similarity-based, and network-based approaches to clarify their ideal use-case scenarios. Each method for interpretation is assessed for its strengths, such as high-quality visualizations and ease of use, as well as its limitations, including data redundancy and database compatibility challenges. Despite advancements in the field, the principle of "garbage in, garbage out" (GIGO) shows that input quality and method choice are critical for reliable and biologically meaningful results. Methodological standardization, scalability improvements, and integration with diverse data sources remain areas for further development. By providing critical guidance with contextual examples such as TNF, we aim to help researchers align their objectives with the appropriate method. Advancing pathway analysis interpretation will further enhance the utility of pathway analysis, ultimately propelling progress in systems biology and personalized medicine.

Maternal and child health during pregnancy is an important issue in global public health, and the classification accuracy of fetal cardiotocography (CTG), as a key tool for monitoring fetal health during pregnancy, is directly related to the effectiveness of early diagnosis and intervention. Due to the serious category imbalance problem of CTG data, traditional models find it challenging to take into account a small number of categories of samples, increasing the risk of leakage and misdiagnosis. To solve this problem, this paper proposes a two-step innovation: firstly, we design a method of adaptive adjustment of misclassification loss function weights (MAAL), which dynamically identifies and increases the focus on misclassified samples based on misclassification rates. Secondly, a primary and secondary correction network model (MAC-NET) is constructed to carry out secondary correction for the misclassified samples of the primary model. Experimental results show that the method proposed in this paper achieves 99.39% accuracy on the UCI publicly available fetal health dataset, and also obtains excellent performance on other domain imbalance datasets. This demonstrates that the model is not only effective in alleviating the problem of category imbalance, but also has very high clinical utility.

While bulk RNA sequencing provides a comprehensive view of transcriptomes, it lacks cell type specificity. Single-cell RNA sequencing (scRNA-seq) overcomes this limitation by providing detailed insights at the individual cell level, though it involves higher costs. Deconvolution methods can estimate cell type proportions in bulk RNA-seq data, but their results may vary based on the scRNA-seq reference data and software used. This study investigates the estimation of muscle fiber type proportions through deconvolution analysis of Longissimus dorsi muscle bulk RNA-seq data from late-gestation Holstein Friesian multiparous cows. Four software tools (i.e., CIBERSORTx, Cellanneal, DeconvR-NNLS, and DeconvR-RLM) were compared using scRNA-seq reference data from Brahman and Wagyu cattle breeds, which included proportions of types I, IIa, and IIx myofibers. Kruskal-Wallis and Dunn's tests revealed that the breed of reference data significantly influenced the proportions of type IIa and IIx muscle fibers across different deconvolution methods. To the best of our knowledge, this is the first study to show that the cattle breed used in reference scRNA-seq data can substantially impact deconvolution outcomes, highlighting a critical consideration for accurate cell type proportion estimation in livestock genomics. These findings suggest that future deconvolution studies should carefully consider breed compatibility between reference and target datasets.

Gene expression analysis is crucial in understanding cellular processes, development, health, and disease. With RNA-seq outpacing microarray as the chosen platform for gene expression, is there space for array data in future profiling? This study involved 35 participants from the Adolescent Medicine Trials Network for HIV/AIDS Intervention protocol. RNA was isolated from whole blood samples and analyzed using both microarray and RNA-seq technologies. Data processing included quality control, normalization, and statistical analysis using non-parametric Mann-Whitney U tests. Differential expression analysis and pathway analysis were conducted to compare the outputs of the two platforms. The study found a high correlation in gene expression profiles between microarray and RNA-seq, with a median Pearson correlation coefficient of 0.76. RNA-seq identified 2395 differentially expressed genes (DEGs), while microarray identified 427 DEGs, with 223 DEGs shared between the two platforms. Pathway analysis revealed 205 perturbed pathways by RNA-seq and 47 by microarray, with 30 pathways shared. Both microarray and RNA-seq technologies provide highly concordant results when analyzed with consistent non-parametric statistical methods. The findings emphasize that both methods are reliable for gene expression analysis and can be used complementarily to enhance the robustness of biological insights.

Large-scale bioprocesses often suffer from spatial heterogeneities, which impact microbial performance and often lead to phenotypic population heterogeneity. To better understand these effects at the single-cell level, this study applied, for the first time, automated real-time flow cytometry (ART-FCM) to monitor L-phenylalanine production with an Escherichia coli triple reporter strain in a fed-batch process with glycerol as the carbon source. The strain was cultivated in both a well-mixed stirred-tank bioreactor (STR) and a scale-down two-compartment bioreactor (TCB), consisting of an STR and a coiled flow inverter (CFI) in bypass, to simulate spatial heterogeneities. ART-FCM enabled autonomous, high-frequency sampling every 20 min, allowing for real-time tracking of fluorescence signals linked to growth (rrnB-mEmerald), oxygen availability (narGHIJ-CyOFP1), and product formation (aroFBL-mCardinal2). The STR exhibited uniform reporter expression and higher biomass accumulation, while the TCB showed delayed product formation and pronounced phenotypic diversification depending on the set mean residence time in the CFI. Single-cell fluorescence distributions revealed that the shorter mean residence time in the CFI resulted in pronounced subpopulation formation, whereas longer exposure attenuated heterogeneity, indicating transcriptional adaptation. This finding highlights a critical aspect of scale-down studies: increased exposure duration to perturbations can enhance population robustness. Overall, this study demonstrates the relevance of ART-FCM, in combination with a multi-reporter strain, as a pioneering tool for capturing dynamic cellular behavior and correlating it to process performance, providing deeper insights into microbial heterogeneity under fluctuating bioprocess conditions.

This study investigates the cytotoxic properties of metal complexes incorporating thio-uracil derivatives, specifically 2,4-dithiouracil and 6-propyl-2-thiouracil. The research focuses on the cytotoxic effects of Cu(II) and Pd(II) complexes with 6-propyl-2-thiouracil, as well as mixed-ligand transition metal Cu(II) and Au(III) complexes of 2,4-dithiouracil with 2-thiouracil and uracil. Cytotoxic activity was assessed against human cervical carcinoma cells (HeLa) and normal kidney cells from the African green monkey. The results demonstrated that incorporating Cu(II) and Au(III) into the compound structures significantly enhanced their cytotoxic effects. Notably, all tested complexes exhibited a stronger inhibitory effect on cancer cell proliferation compared to normal cells, with the palladium(II) complex of 6-propyl-2-thiouracil showing the lowest CD₅₀ value against the tumor cell line (0.00064 mM), which were 149 times lower than that of the ligand (0.0955 mM). These findings suggest that thio-uracil-based metal complexes, particularly those containing palladium (II) and gold(III), hold significant potential for further development as anticancer agents.

Science has made significant progress in detecting reactive oxygen species (ROS) in tobacco smoke, which is an important step for precision cancer therapy. An important advance is also the understanding that superoxide can be produced by electrophilic molecules. The dual action of hydrogen peroxide, directly or via electrophilic molecules, in the development of oxidative stress allows for the identification of target proteins that can potentially stop unwanted signals in cancer development. However, despite advances in proteomics, reliable inhibitors to stop ROS-associated cancer progression have not yet been proposed for the treatment of tobacco cigarette smokers. This is likely due to an imperfect understanding of the diversity of molecular mechanisms of anti-ROS action. Fluorescent protein detection in living cells, called in-gel, offers a direct route to a better understanding of the rapid interaction of ROS and electrophilic compounds with targeted proteins. It seemed that the traditional paradigm of pharmaceutical innovation "one drug, one disease" did not solve the problem of tobacco smoking causing cancer. However, among the various therapeutic treatments for tobacco smokers, the best way to combat cancer today is smoking cessation, which fits into the "one-cure" paradigm.

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.

Vanilla is a highly valuable spice in multiple industries worldwide. However, it faces a serious problem due to a disease known as root and stem rot, caused by the fungus Fusarium oxysporum f. sp. vanillae. Little is known about the pathogenicity mechanisms this fungus employs to establish the disease, making it imperative to elucidate mechanisms such as the presence of pathogenicity effectors in its genome. The aim of the present study was to determine the presence of the SIX gene family in the genome of three strains of F. oxysporum associated with root rot: two pathogenic strains and one non-pathogenic endophyte strain. Additionally, the complete effectorome of these strains was predicted and compared to exclude effectors present in the endophytic strain. Our results show that only the SIX9 gene is present in the strains associated with the disease, regardless of their pathogenic nature. Furthermore, no variation was observed in the SIX9 gene among these strains, suggesting that SIX9 is not involved in pathogenicity. Instead, we identified 339 shared effectors among the three strains, including the non-pathogenic strain, strongly suggesting that these genes are not relevant for establishing root rot but may play a role in endophytic colonization. The highly virulent strain IXF41 exhibited eight exclusive pathogenicity effectors, while the moderately virulent strain IXF50 had four. Additionally, one effector was identified as shared between these two strains but absent in the endophytic strain. These effectors and their promoters were characterized, revealing the presence of several cis-regulatory elements responsive to plant hormones. Overall, our findings provide novel insights into the genomic determinants of virulence in F. oxysporum f. sp. vanillae, offering a foundation for future functional studies and the development of targeted disease management strategies.