Stromal Reprogramming Optimizes KRAS-Specific Chemotherapy Inducing Antitumor Immunity in Pancreatic Cancer.

Pancreatic ductal adenocarcinoma (PDAC) is a clinically challenging cancer and is often characterized with rich stroma and mutated KRAS, which determines the tumor microenvironment (TME) and therapy response. Turning immunologically "cold" PDAC into "hot" is an unmet need to improve the therapeutic outcome. Herein, we propose a programmable strategy by sequential delivery of pirfenidone (PFD) and nanoengineered KRAS specific inhibitor (AMG510) and gemcitabine (GEM) liposomes.

Deciphering the maize gene ZmGF14-3: implications for plant height based on co-expression networks.

The evolutionary analysis showed that the GF14 family was conserved, however, there was limited evidence linking GF14s to plant height. In our investigations, we discovered a co-expression relationship between ZmGF14s and functionally characterized genes linked to plant height. In the co-expression network, we identified ZmGF14-3, a gene expression exhibiting a positive correlation with plant height in three maize varieties, we postulated that this gene could be intimately linked to plant height development.

Polydopamine-Mediated Metal-Organic Frameworks Modification for Improved Biocompatibility.

Engineered nanomaterials are promising in biomedical application. However, insufficient understanding of their biocompatibility at the cellular and organic levels prevents their widely biomedical applications. Metal-organic frameworks (MOFs) have attracted increasing attention in recent years.

Semi-rational engineering membrane binding domain of L-amino acid deaminase from for enhanced α-ketoisocaproate.

α-Keto acids are important raw materials for pharmaceuticals and functional foods, which could be produced from cheap feed stock by whole cell biocatalysts containing L-amino acid deaminases (L-AADs). However, the production capacity is limited by the low activity of L-AADs. The L-AAD mediated redox reaction employs the electron transport chain to transfer electrons from the reduced FADH to O, implying that the interaction between L-AAD and the cell membrane affects its catalytic activity.

A rapid selection strategy for umami peptide screening based on machine learning and molecular docking.

Umami peptides have been the focus of umami studies in recent years because of their high nutritional value and flavor activity. However, the existing screening methods of umami peptides were cumbersome, complex, time-consuming and laborious, and it was difficult to achieve high-throughput screening. In this study, a novel umami peptide rapid screening model was designed and by using lamb bone aqueous extract as raw material, through the step-by-step screening of peptidomics, machine learning methods, and molecular docking technology.

A strategy for screening novel umami dipeptides based on common feature pharmacophore and molecular docking.

To shorten the complex and tedious process of traditional umami peptide identification, a novel model based on common feature pharmacophore (HipHop, a ligand molecule-based screening method) and molecular docking (a receptor protein-based screening method) was established for umami peptide screening. In this study, HipHop was used to perform a preliminary screening of peptides. Dipeptides with potential umami activity were docked into the umami taste receptor T1R1/T1R3 for a second screening.

Research progress in the screening and evaluation of umami peptides.

Umami is an important element affecting food taste, and the development of umami peptides is a topic of interest in food-flavoring research. The existing technology used for traditional screening of umami peptides is time-consuming and labor-intensive, making it difficult to meet the requirements of high-throughput screening, which limits the rapid development of umami peptides. The difficulty in performing a standard measurement of umami intensity is another problem that restricts the development of umami peptides.