Perioperative Management of Patients with Diabetes and Cancer: Challenges and Opportunities.

BACKGROUND: Both diabetes and cancer are major global health issues that are among the leading causes of morbidity and mortality. There is a high prevalence of diabetes among cancer patients, many of whom require a surgical procedure. This review focuses on the operative complications in patients with diabetes and cancer, and the perioperative management of diabetes in cancer patients. METHODOLOGY: A literature search of articles in English-published between January 2010 and May 2024-was carried out using the databases PubMed, MEDLINE, Google Scholar, and the Cochrane Database of Systematic Reviews. The search primarily focused on the operative complications in patients with diabetes and cancer, and perioperative management strategies. RESULTS: The relationship between cancer and diabetes is complex; cancer patients have a high risk of developing diabetes, while diabetes is a risk factor for certain cancers. In addition, various cancer therapies can induce or worsen diabetes in susceptible patients. Many individuals with cancer and diabetes require surgery, and due to underlying diabetes, they may have elevated risks for operative complications. Optimal perioperative management for these patients includes managing perioperative glycemia and other comorbid illnesses, adjusting diabetic and cancer treatments, optimizing nutrition, minimizing the duration of fasting, supporting early mobilization, and providing patient education to enable self-management. CONCLUSIONS: While evidence is limited, optimal perioperative management for patients with both diabetes and cancer is necessary in order to reduce surgical complications. Future studies are needed to develop evidence-informed perioperative strategies and improve outcomes for these patients.

Structural equation modeling of a winnowed soil microbiome identifies how invasive plants re-structure microbial networks.

The development of microbial networks is central to ecosystem functioning and is the hallmark of complex natural systems. Characterizing network development over time and across environmental gradients is hindered by the millions of potential interactions among community members, limiting interpretations of network evolution. We developed a feature selection approach using data winnowing that identifies the most ecologically influential microorganisms within a network undergoing change. Using a combination of graph theory, leave-one-out analysis, and statistical inference, complex microbial communities are winnowed to identify the core organisms responding to external gradients or functionality, and then network development is evaluated against these externalities. In a plant invasion case study, the winnowed microbial network became more influential as the plant invasion progressed as a result of direct plant-microbe links rather than the expected indirect plant-soil-microbe links. This represents the first use of structural equation modeling to predict microbial network evolution, which requires identification of keystone taxa and quantification of the ecological processes underpinning community structure and function patterns.

A novel synthetic trivalent single chain variable fragment (tri-scFv) construction platform based on the SpyTag/SpyCatcher protein ligase system.

BACKGROUND: Advances in antibody engineering provide strategies to construct recombinant antibody-like molecules with modified pharmacokinetic properties. Multermerization is one strategy that has been used to produce antibody-like molecules with two or more antigen binding sites. Multimerization enhances the functional affinity (avidity) and can be used to optimize size and pharmacokinetic properties. Most multimerization strategies involve genetically fusing or non-covalently linking antibody fragments using oligomerization domains. Recent studies have defined guidelines for producing antibody-like molecules with optimal tumor targeting properties, which require intermediates size (70-120 kDa) and bi- or tri-valency. RESULTS: We described a highly modular antibody-engineering platform for rapidly constructing synthetic, trivalent single chain variable fragments (Tri-scFv) using the SpyCatcher/SpyTag protein ligase system. We used this platform to construct an anti-human epidermal growth factor receptor 3 (HER3) Tri-scFv. We generated the anti-HER3 Tri-scFv by genetically fusing a SpyCatcher to the C-terminus of an anti-HER3 scFv and ligating it to a synthetic Tri-SpyTag peptide. The anti-HER3 Tri-scFv bound recombinant HER3 with an apparent KD of 2.67 nM, which is approximately 12 times lower than the KD of monomeric anti-HER3 scFv (31.2 nM). Anti-HER3 Tri-scFv also bound endogenous cell surface expressed HER3 stronger than the monomer anti-HER3 scFv. CONCLUSION: We used the SpyTag/SpyCatcher protein ligase system to ligate anti-HER3 scFv fused to a SpyCatcher at its C-termini to a Tri-SpyTag to construct Tr-scFv. This system allowed the construction of a Tri-scFv with all the scFv antigen-binding sites pointed outwards. The anti-HER3 Tri-scFv bound recombinant and endogenously expressed HER3 with higher functional affinity (avidity) than the monomeric anti-HER3 scFv. The Tri-scFv had the size, valency, and functional affinity that are desired for therapeutic and imaging applications. Use of the SpyTag/SpyCatcher protein ligase system allows Tri-scFvs to be rapidly constructed in a simple, modular manner, which can be easily applied to scFvs or other antibody fragments targeting other antigens.