Selectively superior production of docosahexaenoic acid in Schizochytrium sp. through engineering the fatty acid biosynthetic pathways.

BACKGROUND: Schizochytrium sp. is commercially used for production of docosahexaenoic acid (DHA). Schizochytrium sp. utilizes the polyketide synthase complex (PKS) and a single type I fatty acid synthase (FAS) to synthesize polyunsaturated fatty acids and saturated fatty acids, respectively. The acyl carrier protein (ACP) domains of FAS or PKS are used to load acyl groups during fatty acids biosynthesis. Phosphopantetheinyl transferase (PPTase) transfers the pantetheine moiety from Coenzyme A to the conserved serine residue of an inactive ACP domain to produce its active form. RESULTS: In this study, in order to improve production and content of DHA, we decreased the expression of fas, strengthened the expression of the PKS pathway, and enhanced the supply of active ACP in Schizochytrium sp. ATCC20888. Weakening the expression of fas or disruption of orfA both led to growth defect and reduction of lipid yields in the resulting strains WFAS and DPKSA, indicating that both FAS and PKS were indispensable for growth and lipid accumulation. Although WFAS had a higher DHA content in total fatty acids than the wild-type strain (WT), its growth defect and low DHA yield hinders its use for DHA production. Overexpression of the orfAB, orfC, orfC-DH (truncated orfC), or ppt promoted DHA and lipid production, respectively. The yields and contents of DHA were further increased by combined overexpression of these genes. Highest values of DHA yield (7.2 g/L) and DHA content (40.6%) were achieved in a recombinant OPKSABC-PPT, ⁓56.5% and 15.3% higher than the WT values, respectively. CONCLUSIONS: This study demonstrates that genetic engineering of the fatty acid biosynthetic pathways provides a new strategy to enhance DHA production in Schizochytrium.

Photothermal Conversion of Hydrogel-Based Biomaterial.

Traditional energy from fossil fuels like petroleum and coal is limited and contributes to global environmental pollution and climate change. Developing sustainable and eco-friendly energy is crucial for addressing significant challenges such as climate change, energy dilemma and achieving the long-term development of human society. Biomass hydrogels, which are easily synthesized and modified, have diverse sources and can be designed for different applications. They are being extensively researched for their applications in artificial intelligence, flexible sensing, biomedicine, and food packaging. The article summarizes recent advances in the preparation and applications of biomass-based photothermal conversion hydrogels, discussing the light source, photothermal agents, matrix, and preparation methods in detail. It also explores the use of these hydrogels in seawater desalination, photothermal therapy, antibacterial agents, and light-activated materials, offering new ideas for developing sustainable, efficient, and advanced photothermal conversion biomass hydrogel materials. The article concludes with suggestions for future research, highlighting the challenges and prospects in this field and paving the way for developing of long-lasting, efficient energy materials.

Clustered Federated Learning in Heterogeneous Environment.

Federated learning (FL) is a distributed machine learning framework that allows resource-constrained clients to train a global model jointly without compromising data privacy. Although FL is widely adopted, high degrees of systems and statistical heterogeneity are still two main challenges, which leads to potential divergence and nonconvergence. Clustered FL handles the problem of statistical heterogeneity straightly by discovering the geometric structure of clients with various data generation distributions and getting multiple global models. The number of clusters contains prior knowledge about the clustering structure and has a significant impact on the performance of clustered FL methods. Existing clustered FL methods are inadequate for adaptively inferring the optimal number of clusters in environments with high systems' heterogeneity. To address this issue, we propose an iterative clustered FL (ICFL) framework in which the server dynamically discovers the clustering structure by successively performing incremental clustering and clustering in one iteration. We focus on the average connectivity within each cluster and give incremental clustering and clustering methods that are compatible with ICFL based on mathematical analysis. We evaluate ICFL in experiments on high degrees of systems and statistical heterogeneity, multiple datasets, and convex and nonconvex objectives. Experimental results verify our theoretical analysis and show that ICFL outperforms several clustered FL baseline methods.

A novel traffic accident detection method with comprehensive traffic flow features extraction.

With the rapidly increasing of automobiles, traffic accidents are gradually becoming more frequent. This creates a great need for effective traffic anomaly detection algorithms. Existing methods shed light on directly inferring the abnormalities from traffic flow, which is short in features extraction and representation of traffic flows. In this paper, we propose three new traffic flow features, namely the road congestion, the traffic intensity, and the traffic state instability, for more comprehensive traffic status representation and anomaly detection. Residual analysis, quadratic discrimination, multi-resolution wavelet analysis are integrated for the extraction of the aforementioned features, which will be applied for the downstream tasks of traffic anomaly detection. Experimental results reveal that accident identification based on the proposed features is more effective than the raw traffic flow, which is supposed to provide an alternative approach for further applications and studies.

A One Step Procedure toward Conductive Suspensions of Liposome-Polyaniline Complexes.

Interaction of conjugated polymers with liposomes is an attractive approach that benefits from both systems' characteristics such as electroactivity and enhanced interaction with cells. Conjugated polymer-liposome complexes have been investigated for bioimaging, drug delivery, and photothermal therapy. Their fabrication has largely been achieved by multistep procedures that require first the synthesis and processing of the conjugated polymer. Here, a new one step fabrication approach is reported based on in situ polymerization of a conjugated monomer precursor around liposomes. Polyaniline (PANI) doped with phytic acid is synthesized via oxidative polymerization in the presence of 1,2-dioleoyl-sn-glycero-3-phosphatidylcholine (DOPC) vesicles to produce a conductive aqueous suspension of Liposome-PANI complexes. PANI interacts with liposomes without disrupting the bilayer as shown using differential scanning calorimetry and fluorescence quenching studies of the hydrophobic Nile red probe. The electronic conductivity of the Liposome-PANI complexes, which stems from the doped PANI accessible on the liposome surface, is confirmed using conductive atomic force microscopy and electrochemical impedance spectroscopy. Further, short-term in vitro cell studies show that the complexes colocalize with the cell membrane without reducing cell proliferation. This study presents a novel fabrication route to conductive suspensions of conjugated polymer-liposome complexes suitable for potential applications at the biointerface.

Two strategies to engineer flexible loops for improved enzyme thermostability.

Flexible sites are potential targets for engineering the stability of enzymes. Nevertheless, the success rate of the rigidifying flexible sites (RFS) strategy is still low due to a limited understanding of how to determine the best mutation candidates. In this study, two parallel strategies were applied to identify mutation candidates within the flexible loops of Escherichia coli transketolase (TK). The first was a "back to consensus mutations" approach, and the second was computational design based on ΔΔG calculations in Rosetta. Forty-nine single variants were generated and characterised experimentally. From these, three single-variants I189H, A282P, D143K were found to be more thermostable than wild-type TK. The combination of A282P with H192P, a variant constructed previously, resulted in the best all-round variant with a 3-fold improved half-life at 60 °C, 5-fold increased specific activity at 65 °C, 1.3-fold improved kcat and a Tm increased by 5 °C above that of wild type. Based on a statistical analysis of the stability changes for all variants, the qualitative prediction accuracy of the Rosetta program reached 65.3%. Both of the two strategies investigated were useful in guiding mutation candidates to flexible loops, and had the potential to be used for other enzymes.