Recent patents on biotechnology最新文献

Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of COVID-19, has a highly variable clinical course, ranging from mild symptoms to severe systemic complications. Understanding the molecular basis of disease severity is essential for improving diagnostic and therapeutic strategies.

Objective: In this study, we performed transcriptome analysis of peripheral blood mononuclear cells (PBMCs) from patients with mild and severe COVID-19 to identify differentially expressed mRNAs and long noncoding RNAs (lncRNAs), and to construct a regulatory network including microRNAs (miRNAs).

Methods: Transcriptome analysis of peripheral blood mononuclear cells (PBMCs) from patients with mild and severe COVID-19 was performed to identify differentially expressed mRNAs and long noncoding RNAs (lncRNAs), and to construct a regulatory network including microRNAs (miRNAs) using Cytoscape.

Results: A total of 674 mRNAs and 215 lncRNAs were differentially expressed between severe and mild cases, with key pathways enriched in cytokine-cytokine receptor interaction and immunological synapse signaling. The lncRNAs NEAT1 and MALAT1 were identified as regulatory hubs and were broadly expressed across multiple immune and organ tissues. Predicted miRNAs (experimentally supported in interaction databases) were associated with inflammation- and cancer-related signaling pathways, including PI3K-Akt, JAK/STAT, and TNF.

Discussion: Our findings are consistent with recent patents (e.g., US2022/0298584A1, EP3892280A3, WO2023147669A1) that propose the use of noncoding RNAs and cytokines as biomarkers for COVID-19 diagnosis and severity assessment.

Conclusion: Our findings are consistent with recent patents (e.g., "US20220298584A1", "EP3892280A3", "WO2023147669A1") that propose the use of noncoding RNAs and cytokines as biomarkers for COVID-19 diagnosis and severity assessment. This integrative transcriptomic analysis highlights the regulatory role of noncoding RNAs in COVID-19 progression, exemplified by the central hub lncRNAs NEAT1 and MALAT1, which interact with inflammation- associated miRNAs and mRNA targets to modulate cytokine signaling. These findings offer specific transcriptomic biomarkers with potential for clinical application and therapeutic targeting.

Introduction: Biodiesel from animal waste provides an alternative source of fuel. It is eco-friendly and cheaper than conventional fuel obtained through the distillation of crude oil. Biodiesel is similar to petroleum diesel and can be used alone or blended with fossil diesel as an energy source. This study provides insight into the use of waste animal fats for biodiesel production.

Methods: The data were retrieved from different sources, including PubMed, Google Scholar, and other scientific websites. Scope of the study can be clearly understood from the facts revealed from patent work.

Results: The use of waste animal fats provides a renewable and eco-friendly alternative to petroleum diesel. Both homogeneous and heterogeneous catalysis methods have proven effective for processing WAFs, with KOH and NaOH commonly used in concentrations ranging from 1% to 2%. Increasing the catalyst concentration within a certain range can enhance biodiesel yield. However, the use of acid catalysts for transesterification of WAFs is time-intensive and requires a high alcohol-to-fat ratio. Despite these advantages, challenges remain in catalyst reuse for certain reactions and in managing complex selectivity combinations. Lipases in water-poor environments are also employed for transesterification.

Discussion: The fatty acid profiles of both animal and vegetable sources have been found suitable for biodiesel production. Although it is a cheap source for generating fuel, using specific reaction media such as acyl acceptors and employing a combination of two enzymes on a specialized support can help further reduce costs.

Conclusion: Currently, biodiesel is widely used in developed countries such as the US and Germany, but its adoption remains limited in developing nations. Optimizing transesterification methods-including the use of heterogeneous or homogeneous catalysis- and incorporating innovative technologies such as microwave-assisted enzymes can further enhance biodiesel yield and efficiency.

Fibrinolytic enzymes have garnered significant attention from researchers due to their immense potential in the medical field. As research continues to advance, the outcomes have become increasingly fruitful. The generation of applicable knowledge is usually accompanied by its protection through patent applications. This article compiles all patents related to "fibrinolytic enzyme" from Google Patents and the European Patent Office's Espacenet database, analyzing their core information, including publication year, application country, patent status, source of the fibrinolytic enzyme, and its various biochemical features. By combining relevant patent protection with current literature research, this article provides a novel and forward-looking summary of the current research status in the field of fibrinolytic enzymes.

Introduction: Nanoemulsions (NEs) are a biphasic systems formed by two immiscible liquids: (1) oil-in-water or (2) water-in-oil emulsions. These systems exhibit unique physicochemical properties due to their small particle size, making them more versatile compared to other emulsion systems. Thus, this research aimed to produce and evaluate oil-in-water nanoemulsions.

Methods: NE's were prepared using Squalene, grape seed, and avocado oils, combined with soy lecithin or soy phosphatidylcholine as emulsifiers. The selection of oils considered both regulatory aspects and patent restrictions. Formulations were produced by microfluidization, and their physicochemical properties, such as particle size, polydispersity index, and zeta potential, were assessed at day one (D0) and day 7 (D7), under storage at 4°C, 25°C, and 40°C.

Results: The nanoemulsions produced with soy phosphatidylcholine and vegetable oils exhibited good preliminary stability, due to their small particle size. In contrast, formulations using soy lecithin as the emulsifier did not show favorable results, especially the one with grape seed oil, which showed a large particle diameter. However, none of these formulations exhibited cellular cytotoxicity.

Discussion: Emulsifier selection had a strong impact on NEs characteristics, with Soy- PC producing smaller and more uniform particles compared to soy lecithin. All NEs showed good biocompatibility in fibroblasts, indicating their safety.

Conclusion: Among the formulations, the one with phosphatidylcholine demonstrated a safer and more reliable stability profile, making it a promising candidate for application in the pharmaceutical and cosmetics industries.

Introduction: Toxoplasmosis is one of the most common parasitic infections transmitted between humans and animals, caused by the protozoan Toxoplasma gondii. This organism acts as an obligate intracellular parasite, presenting an active and rapidly proliferating form known as a tachyzoite, in addition to two durable forms: the tissue cyst and the oocyst. Due to the considerable global impact of chronic infections in various host species, especially in humans and domestic animals, creating and producing an effective vaccine for preventing and managing toxoplasmosis is critically essential. The excretory antigens of Toxoplasma gondii play a vital role in vaccine development and diagnostic processes, with the SAG2 antigen being particularly significant. At present, sophisticated bioinformatics tools are utilized to design efficient signal peptides. This research will adopt an in silico approach to evaluating different signal peptides.

Methods: The signal peptide sequence was obtained from the Signal Peptide website and Uniprot. Following this, SignalP was utilized to predict the signal peptides and determine the positions of their cleavage sites. The ProtProm tool was then employed to assess the physicochemical characteristics and solubility. Furthermore, ProtCompB was used to forecast the subcellular localization of the fusion protein.

Results: Of the 50 signal peptides analyzed, 49 were excluded based on SignalP criteria. The signal peptide with the highest aliphatic index was HDEA_ECOLI, while TORT_ECOLI exhibited the highest GRAVY value.

Discussion: Additionally, SAG2, when fused with all signal peptides, was explicitly designed for the Sec pathway, except NAPA_ECOLI, MBHT_ECOLI, CUEO_ECOLI, and OPGD_ECOLI.

Conclusion: An appropriate signal peptide was recognized for the fusion and translocation of SAG2 into the extracellular environment. While additional experimental studies are necessary for conclusive validation.

Introduction: Demand forecasting is critical for the pharmaceutical industry to ensure efficient production, inventory management, and distribution, especially in dynamic and competitive markets. This study addresses the challenges of accurate demand prediction within the Tunisian pharmaceutical sector.

Methods: The primary aim was to compare the forecasting accuracy of two methods, Holt-Winters (HW) and Multilayer Perceptron (MLP) neural networks, for three drug categories: Antiviral, Antibiotic, and Pain Relief. Additionally, the study provides actionable recommendations to enhance forecasting strategies. A 24-month (n=24) historical sales dataset (October 2020 to September 2022) from a Tunisian pharmaceutical demand forecasting company was analyzed. The analysis utilized the Holt-Winters model to incorporate seasonal adjustments and an MLP neural network to capture complex, non-linear sales patterns.

Results: Both models were evaluated using metrics such as mean squared error (MSE) to quantify prediction accuracy. The MLP neural network consistently and significantly outperformed the Holt-Winters method, demonstrating markedly lower MSE values (e.g., 0.0206 for Antivirals, compared to 30.06 for HW) and greater adaptability to demand variability across all drug categories.

Discussion: While effective for seasonal patterns, HW struggled with irregular fluctuations and complex dynamics. This study highlights the superiority of MLP neural networks for pharmaceutical demand forecasting due to their adaptability and accuracy in handling non-linear and variable data.

Conclusion: The findings provide a strong quantitative basis for Tunisian pharmaceutical companies to adopt advanced machine learning techniques for more reliable planning. However, to fully realize the potential of these techniques and address the limitations outlined in this research, future research should explore hybrid models and integrate extended datasets that incorporate external market dynamics and trends.

Introduction: Urinary Tract Infections (UTIs) caused by Escherichia coli are a major concern due to rising antimicrobial resistance. Long non-coding RNAs (lncRNAs) play crucial roles in gene regulation, but their involvement in UTIs and their implication in antimicrobial resistance mechanisms are not well understood. This study investigates the association between specific long non-coding RNAs, immune response, and antibiotic resistance in patients with infections caused by E. coli.

Methods: Quantification of specific lncRNAs (NEAT1-1, NEAT1-2, MIR3142HG, AK170409, and IL7AS) was performed using quantitative PCR. Inflammatory markers IL-1β, IRF3, and NF-κB were measured in UTI patients using ELISA kits to assess their biological response. The minimum inhibitory concentration of eleven antibiotics was determined by testing all 25 urine samples and categorized as sensitive, intermediate, or resistant.

Results: NEAT1-1, NEAT1-2, MIR3142HG, and AK170409 were significantly upregulated (p < 0.05). Inflammatory markers were significantly elevated in all samples: IL-1β at 72.36 ± 13.8 pg/mL, IRF3 at 79.36 ± 15.01 pg/mL, and NF-κB at 4.43 ± 0.82 pg/mL (p < 0.0001). NEAT1-2 and AK170409 expression correlated with distinct antibiotic response patterns (p < 0.05). Differences in biological and hematological data were observed among UTI patients with varying topographic expressions of specific long noncoding RNAs (lncRNAs).

Discussions: Specific lncRNAs may be involved in modulating immune responses and influencing antibiotic susceptibility in UTIs. Their expression patterns reflect both the severity of infection and resistance profiles, suggesting a functional role in the development of antimicrobial resistance.

Conclusion: LncRNAs are potential biomarkers for UTIs caused by E. coli. Future studies should focus on elucidating the precise role of lncRNAs in the development of antibiotic resistance in these infections.

Introduction: The production of bio-oil from microalgae is gaining attention as an alternative renewable energy source. To generate advances in this field, it is essential to identify the gaps in existing research. Overcoming this barrier necessitates addressing methodologies that can assess the existing work and develop relationships between publications, research groups, and their impact.

Methods: To chart a course toward practicality, this study employs bibliometric indicators, leveraging tools such as R Studio, VOSviewer 1.6.19, and Biblioshiny for network visualization and analysis. Drawing on the Scopus database spanning 2004-2024, a meticulous keyword strategy effectively segregated relevant papers.

Results: The findings suggest that the total number of published documents is 1005. The publication trend on this topic shows a significant increase since 2008, with a record high of 107 publications in 2022. China dominates the publication list, with thirteen universities contributing the highest. In the context of algal bio-oil, a total of 2850 authors contributed to 1005 publications.

Discussion: A three-way map displaying the relationships between journal titles, paper titles, and author keywords provides useful insights into the research landscape of the field. Algal research is growing and collaborating, despite bibliometric limitations such as time dependency and database scope. Such studies, however, offer valuable insights into the evolving bio-oil field.

Conclusion: The study aims to link sustainable economic development with technological innovation and related economic growth. Its objective is to provide researchers with information on niche research clusters, quantify emerging methodologies, facilitate collaborative networks, and identify knowledge gaps, while assisting in determining the impact of specific publication venues. In addition to analyzing key economic drivers, the study will also recommend prospective research themes to disseminate algae-based biooil production research.

Introduction: Polycyclic aromatic hydrocarbons (PAHs) are toxic petroleum byproducts in soil, exhibiting significant genotoxic properties. Microorganisms residing in contaminated soils serve as effective detoxifying agents. Among various strategies, bioremediation is an efficient biological method for detoxifying PAHs.

Method: Hundreds of soil samples were collected from the Gulf of Suez, Egypt. The isolation process utilized an enrichment culture system with phenol naphthalene (PN) (10 mg/mL) as the primary carbon source. HPLC analysis was applied to confirm PN degradation. Consequently, the bacterial strain was characterized morphologically, biochemically, and through partial sequencing of its 16S rRNA gene. Subsequently, its plasmid was purified to transfer its phenotype to Escherichia coli. Finally, a bioremediation approach was conducted to test its PAH degradation.

Results: HPLC analysis was performed to confirm PN degradation by the isolated strain. The isolated strain was identified as Lysinibacillus species AAS1 (OR044755.1) with 98.43% sequence similarity to the Lysinibacillus genus. Subsequently, E. coli transformants with the isolated plasmid were grown in the presence of PN as the primary carbon source. Finally, the bioremediation assay of the isolated strain exhibited a high efficiency in detoxifying PN.

Discussion: The novel identified Lysinibacillus species AAS1 (OR044755.1) shows promise for PAHs detoxification, which may lead to the exploration of a biological agent for the remediation of water and soil contaminated with PAHs.

Conclusion: A novel bacterial strain bearing a plasmid that can degrade PN was isolated from Egyptian petroleum waste-contaminated soil. It paved the way for further studies to isolate the whole gene(s) responsible for such degradation.

The use of microalgae in food and beverages is becoming increasingly popular as a viable way to develop products with enhanced nutritional profiles, offering positive health effects. In parallel, the plant-based food market is expanding due to the growing vegan, vegetarian, and flexitarian populations, prompting manufacturers to create innovative foods and techniques, such as the addition of microalgae to products. These functional and/or nutraceutical foods present an attractive option for consumers seeking plantbased alternatives. Although some challenges remain, this is a growing market. Furthermore, biotechnological processes are being utilized to optimize the production of microalgae with even more robust nutritional characteristics, thereby increasing their added value. This review was based on a structured literature search across major databases, applying predefined keywords and selection criteria to identify recent advances, regulatory aspects, and biotechnological developments in the field. These innovations hold significant potential to meet the rising demand for bioactive products and to propel a new era in the commercialization of microalgae-based products, a segment still underexplored in the current market.