Turning waste into wealth: high-acid-value waste oil upgraded to high-performance natural ester insulating oil in one efficient process
Peer-Reviewed Publication
Updates every hour. Last Updated: 30-Oct-2026 22:16 ET (31-Oct-2026 02:16 GMT/UTC)
Aiming at the problems of severe degradation and complex impurities in high-acid-value waste cooking oil, a multi-stage coupled refining process including phosphoric acid degumming, alkali refining deacidification, activated carbon decolorization/deodorization and winterization was established. Waste cooking oil was successfully converted into natural ester insulating oil meeting power industry standards, providing a new pathway for the green and high-value utilization of kitchen waste oil.
Based on the generalized road rights theory, this study establishes an interval calculation model for photovoltaic (PV) power generation potential of expressways, covering service areas, toll stations, maintenance bases, and slopes under multi-credibility confidence levels. Taking Hunan Province in China as an example, we quantify PV potential and energy consumption matching in short-, medium- and long-term periods. Slopes are identified as the largest potential scenario, revealing the evolution from energy consumption to self-sufficiency and surplus power grid connection, supporting the deep integration of transportation and energy.
The Universitat Jaume I of Castelló has secured nearly one million euros for five projects under the competitive call for grants aimed at strengthening research careers, within the Human Resources programme of the 2024–2027 State Plan for Scientific, Technical and Innovation Research. This achievement places the UJI fourth nationally and first in the Valencian Community in terms of funding obtained in this call, behind only the Spanish National Research Council (CSIC), the University of Barcelona and the Universitat Politècnica de Catalunya, and ahead of larger universities.
The 2025 call awarded a total of 130 grants worth almost 25 million euros. Its aim is to support the consolidation of the professional careers of national and international researchers within the Spanish System for Science, Technology and Innovation (SECTI), through the creation of permanent positions and by facilitating the launch or strengthening of research lines via funding for R&D&I projects and the improvement of laboratories, facilities and scientific equipment.
Online shoppers could one day face fewer misleading fake reviews thanks to a newly tested AI-powered detection system developed by researchers at the University of East London.
With global life expectancy steadily increasing, the growing gap between lifespan and healthspan has placed the aging of the female reproductive system at the forefront of biomedical research. This process, which profoundly impacts fertility, quality of life, and long-term health, is no longer viewed simply through the lens of chronological age or menopause. Instead, a paradigm shift is underway, where aging is understood as a distinct biological process best quantified by multi-omics technologies and computational models known as "aging clocks." These tools—encompassing epigenetics, transcriptomics, proteomics, metabolomics, and microbiomics—provide a powerful, integrated framework to measure biological age, reveal tissue-specific vulnerabilities, and elucidate systemic aging patterns that chronological metrics fail to capture. While this research area is still evolving, the growing availability of high-quality datasets offers unprecedented opportunities to advance our understanding of reproductive aging, infertility, and pregnancy complications, moving towards more personalized and predictive healthcare.
Promoters are key DNA regions that control gene transcription, but their activity varies greatly across different cell types. This heterogeneity makes it difficult for existing computational methods to identify promoters reliably. A team led by Professors Zhangyu Mei and Hao Wu from Shandong University, China, has developed MuSE‑Promoter, a deep ensemble learning framework that combines multi‑scale feature fusion, transformer attention, and a learnable weighted ensemble of neural network and random forest. The system outperforms state‑of‑the‑art methods on human cell lines from different tissues and on Arabidopsis thaliana datasets, and shows excellent generalization in cross‑cell‑line and promoter–enhancer discrimination tasks.
Paligenosis defines a tightly controlled program through which terminally differentiated cells re‑enter the cell cycle and contribute to tissue repair after injury. This review systematically introduces the concept, the three sequential stages of paligenosis—mTORC1 suppression with autophagy initiation, followed by mTORC1 reactivation and stemness gene induction, and finally proliferation with lineage restoration—as well as the underlying molecular networks involving autophagy, metabolic rewiring, and epigenetic remodeling. The article then compares paligenosis with other forms of cellular plasticity such as dedifferentiation, transdifferentiation, epithelial‑mesenchymal transition, and induced pluripotency, highlighting its unique stepwise, reversible and intralineage nature. A major focus is the dual role of paligenosis: while it ensures efficient regeneration in tissues like the stomach and pancreas, its persistent or dysregulated activation under chronic stress or oncogenic signals can drive metaplasia, tumor initiation, metastasis and therapy resistance. The review closes by discussing biomarker prospects for distinguishing adaptive repair from malignant drift, and the therapeutic potential of modulating paligenotic pathways for regenerative medicine and cancer treatment.
N6-methyladenosine (m6A), the most abundant internal modification in eukaryotic mRNA, serves as a pivotal epitranscriptomic mark that dynamically regulates RNA metabolism—including stability, splicing, translation, and localization—thereby shaping cellular identity and function. This modification is installed by writer complexes (e.g., METTL3/METTL14), erased by demethylases (FTO, ALKBH5), and interpreted by reader proteins. Among these readers, YTHDF2 has emerged as a central regulator, primarily known for binding m6A-modified transcripts and promoting their decay, but recent evidence reveals a more complex role extending to m5C reading and even translational enhancement. YTHDF2 functions as a key integrator of intrinsic genetic programs and extrinsic environmental cues, critically governing hematopoietic stem cell (HSC) fate, immune cell development and activation, and tumor-immune interactions. This review synthesizes advances in understanding YTHDF2’s molecular mechanisms—spanning RNA-stability-dependent and -independent pathways—and its multifaceted roles in hematopoiesis, immunity, and cancer, highlighting its potential as a therapeutic target in immune-related diseases and malignancies.
A new approach to accurately imaging objects with complex shapes and varying degrees of "shininess" could enable high-precision applications in virtual and mixed reality settings, industrial inspection and medical imaging.