Search Results (803)

Glucocorticoids (GS) are widely used in multiple medical indications due to their anti-inflammatory, immunosuppressive, and antiproliferative effects. Despite their effectiveness in treating respiratory, skin, joint, renal, and neoplastic diseases, they dysregulate glucose metabolism, leading to steroid-induced diabetes (SID) or a significant increase of glycemia in people with previously diagnosed diabetes. The risk of adverse event development depends on the prior therapy, the duration of the treatment, the form of the drug, and individual factors, i.e., BMI, genetics, and age. Unfortunately, SID and steroid-induced hyperglycemia (SIH) are often overlooked, because the fasting blood glucose level, which is the most commonly used diagnostic test, is insufficient for excluding both conditions. The appropriate control of post-steroid hyperglycemia remains a major challenge in everyday clinical practice. Recently, the most frequently used antidiabetic strategies have been insulin therapy with isophane insulin or multiple injections in the basal–bolus regimen. Alternatively, in patients with lower glycemia, sulphonylureas or glinides were used. Taking into account the pathogenesis of post-steroid-induced hyperglycemia, the initiation of therapy with glucagon-like peptide 1 (GLP-1) analogs and dipeptidyl peptidase 4 (DPP-4) inhibitors should be considered. In this article, we present a universal practical diagnostic algorithm of SID/SIH in patients requiring steroids, in both acute and chronic conditions, and we present a new pharmacotherapy algorithm taking into account the use of all currently available antidiabetic drugs. Full article

Studies have shown that corn (Zea mays L.) proteins, mainly α-zein, have the potential to act on therapeutic targets related to non-communicable chronic diseases, such as high blood pressure and type 2 diabetes. Enzymatic hydrolysis of proteins present in foods can result in a great diversity of peptides with different structures and possible bioactivities. A review of recent scientific research papers was performed to show evidence of the bioactive properties of corn peptides by in vitro assays. The α-zein amino acid sequences were identified in the UniProtKB protein database and then analyzed in the BIOPEP database to simulate enzymatic digestion and verify the potential biological action of the resulting peptides. The peptides found in the BIOPEP database were categorized according to the probability of presenting biological action using the PeptideRanker database. The aim was to use existing data to identify in silico the potential for obtaining biologically active peptides from α-zein, the main storage protein of corn. The analysis showed that the majority of peptide fragments were related to the inhibition of angiotensin-converting enzyme, followed by the inhibition of dipeptidyl peptidase IV and dipeptidyl peptidase III. Many drugs used to treat high blood pressure and type 2 diabetes work by inhibiting these enzymes, suggesting that corn peptides could be potential alternative agents. In vitro studies found that the primary bioactivity observed was antioxidative action. Both in vitro and in silico approaches are valuable for evaluating the bioactive properties resulting from protein hydrolysis, such as those found in α-zein. However, conducting in vitro studies based on prior in silico evaluation can be more efficient and cost-effective. Full article

This work addresses the optimized planning of survivable optical 5G Xhaul access networks employing passive Wavelength Division Multiplexing (WDM) technologies. Specifically, it focuses on the reliability of optical transmission paths connecting remote radio sites to a central hub ensured by using a novel, cost-effective, flexible, and dedicated path protection (DPP-F) scheme, protecting against single-link failures. The proposed DPP-F network protection approach allows for switching of individual wavelengths or the complete multiplexed WDM signal, flexibly applying the best switching option according to given traffic demands. Concurrently, it enables traffic aggregation on the transmission paths from the end and intermediate nodes to minimize the overall network deployment cost. The problem of selecting primary (working) and backup (protection) paths, together with the selection of the best switching and traffic aggregation options, is modeled and solved as a mixed-integer linear programming (MILP) optimization problem. To evaluate the cost savings achieved with DPP-F, we compare it with two reference DPP schemes based on switching the entire multiplexed WDM signal (DPP-M) and individual wavelengths (DPP-W). Numerical experiments conducted across a wide range of network scenarios reveal, among other things, that DPP-F’s performance is at least as good as that of the reference methods, bringing significant cost savings (from several to tens of percent) in most of the analyzed network scenarios. Full article

Dew point pressure (DPP) emerges as a pivotal factor crucial for forecasting reservoir dynamics regarding condensate-to-gas ratio and addressing production/completion hurdles, alongside calibrating EOS models for integrated simulation. However, DPP presents challenges in terms of predictability. Acknowledging these complexities, we introduce a state-of-the-art approach for DPP estimation utilizing advanced machine learning (ML) techniques. Our methodology is juxtaposed against published empirical correlation-based methods on two datasets with limited sizes and diverse inputs. With superior performance over correlation-based estimators, our ML approach demonstrates adaptability and resilience even with restricted training datasets, spanning various fluid classifications. We acquired condensate PVT data from publicly available sources and GeoMark RFDBASE, encompassing dew point pressure (the target variable), as well as compositional data (mole percentages of each component), temperature, molecular weight (MW), and specific gravity (SG) of heptane plus, which served as input variables. Before initiating the study, thorough assessments of measurement quality and results using statistical methods were conducted leveraging domain expertise. Subsequently, advanced ML techniques were employed to train predictive models with cross-validation to mitigate overfitting to the limited datasets. Our models were juxtaposed against the foremost published DDP estimators utilizing empirical correlation-based methods, with correlation-based estimators also trained on the underlying datasets for equitable comparison. To improve outcomes, pseudo-critical properties and artificial proxy features were utilized, leveraging generalized input data. Full article

Epsilon toxin (ETX), a potential agent of biological and toxic warfare, causes the death of many ruminants and threatens human health. It is crucial to understand the toxic mechanism of such a highly lethal and rapid course toxin. In this study, we detected the effects of ETX on the proteome and phosphoproteome of MDCK cells after 10 min and 30 min. A total of 44 differentially expressed proteins (DEPs) and 588 differentially phosphorylated proteins (DPPs) were screened in the 10 min group, while 73 DEPs and 489 DPPs were screened in the 30 min group. ETX-induced proteins and phosphorylated proteins were mainly located in the nucleus, cytoplasm, and mitochondria, and their enrichment pathways were related to transcription and translation, virus infection, and intercellular junction. Meanwhile, the protein–protein interaction network screened out several hub proteins, including SRSF1/2/6/7/11, SF3B1/2, NOP14/56, ANLN, GTPBP4, THOC2, and RRP1B. Almost all of these proteins were present in the spliceosome pathway, indicating that the spliceosome pathway is involved in ETX-induced cell death. Next, we used RNAi lentiviruses and inhibitors of several key proteins to verify whether these proteins play a critical role. The results confirmed that SRSF1, SF3B2, and THOC2 were the key proteins involved in the cytotoxic effect of ETX. In addition, we found that the common upstream kinase of these key proteins was SRPK1, and a reduction in the level of SRPK1 could also reduce ETX-induced cell death. This result was consistent with the phosphorylated proteomics analysis. In summary, our study demonstrated that ETX induces phosphorylation of SRSF1, SF3B2, THOC2, and SRPK1 proteins on the spliceosome pathway, which inhibits normal splicing of mRNA and leads to cell death. Full article

Cardiovascular diseases (CVDs) significantly exacerbate the severity and mortality of COVID-19. We aimed to investigate whether GWAS-significant SNPs correlate with CVDs in severe COVID-19 patients. DNA samples from 199 patients with severe COVID-19 hospitalized in intensive care units were genotyped using probe-based PCR for 10 GWAS SNPs previously implicated in severe COVID-19 outcomes. SNPs rs17713054 SLC6A20-LZTFL1 (risk allele A, OR = 2.14, 95% CI 1.06–4.36, p = 0.03), rs12610495 DPP9 (risk allele G, OR = 1.69, 95% CI 1.02–2.81, p = 0.04), and rs7949972 ELF5 (risk allele T, OR = 2.57, 95% CI 1.43–4.61, p = 0.0009) were associated with increased risk of coronary artery disease (CAD). SNPs rs7949972 ELF5 (OR = 2.67, 95% CI 1.38–5.19, p = 0.003) and rs61882275 ELF5 (risk allele A, OR = 1.98, 95% CI 1.14–3.45, p = 0.01) were linked to a higher risk of cerebral stroke (CS). No associations were observed with AH. Bioinformatics analysis revealed the involvement of GWAS-significant loci in atherosclerosis, inflammation, oxidative stress, angiogenesis, and apoptosis, which provides evidence of their role in the molecular mechanisms of CVDs. This study provides novel insights into the associations between GWAS-identified SNPs and the risk of CAD and CS. Full article

Infantile hemangiomas (IHs) are benign vascular neoplasms of childhood (prevalence 5–10%) due to the abnormal proliferation of endothelial cells. IHs are characterized by a peculiar natural life cycle enclosing three phases: proliferative (≤12 months), involuting (≥13 months), and involuted (up to 4–7 years). The mechanisms underlying this neoplastic disease still remain uncovered. Twenty-seven IH tissue specimens (15 proliferative and 12 involuting) were subjected to hematoxylin and eosin staining and a panel of diagnostic markers by immunohistochemistry. WT1, nestin, CD133, and CD26 were also analyzed. Moreover, CD31^pos/CD26^pos proliferative hemangioma–derived endothelial cells (Hem-ECs) were freshly isolated, exposed to vildagliptin (a DPP-IV/CD26 inhibitor), and tested for cell survival and proliferation by MTT assay, FACS analysis, and Western blot assay. All IHs displayed positive CD31, GLUT1, WT1, and nestin immunostaining but were negative for D2-40. Increased endothelial cell proliferation in IH samples was documented by ki67 labeling. All endothelia of proliferative IHs were positive for CD26 (100%), while only 10 expressed CD133 (66.6%). Surprisingly, seven involuting IH samples (58.3%) exhibited coexisting proliferative and involuting aspects in the same hemangiomatous lesion. Importantly, proliferative areas were characterized by CD26 immunolabeling, at variance from involuting sites that were always CD26 negative. Finally, in vitro DPP-IV pharmacological inhibition by vildagliptin significantly reduced Hem-ECs proliferation through the modulation of ki67 and induced cell cycle arrest associated with the upregulation of p21 protein expression. Taken together, our findings suggest that CD26 might represent a reliable biomarker to detect proliferative sites and unveil non-regressive IHs after a 12-month life cycle. Full article

The risk behaviors underlying the most prevalent chronic noncommunicable diseases (NCDs) encompass alcohol misuse, unhealthy diets, smoking and sedentary lifestyle behaviors. These are all linked to the altered function of the mesocorticolimbic (MCL) system. As the mesocorticolimbic circuit is central to the reward pathway and is involved in risk behaviors and mental disorders, we set out to test the hypothesis that these pathologies may be approached therapeutically as a group. To address these questions, the identification of novel targets by exploiting knowledge-based, network-based and disease similarity algorithms in two major Thomson Reuters databases (MetaBase™, a database of manually annotated protein interactions and biological pathways, and Integrity^SM, a unique knowledge solution integrating biological, chemical and pharmacological data) was performed. Each approach scored proteins from a particular approach-specific standpoint, followed by integration of the scores by machine learning techniques yielding an integrated score for final target prioritization. Machine learning identified characteristic patterns of the already known targets (control targets) with high accuracy (area under curve of the receiver operator curve was ~93%). The analysis resulted in a prioritized list of 250 targets for MCL disorders, many of which are well established targets for the mesocorticolimbic circuit e.g., dopamine receptors, monoamino oxidases and serotonin receptors, whereas emerging targets included DPP4, PPARG, NOS1, ACE, ARB1, CREB1, POMC and diverse voltage-gated Ca²⁺ channels. Our findings support the hypothesis that disorders involving the mesocorticolimbic circuit may share key molecular pathology aspects and may be causally linked to NCDs, yielding novel targets for drug repurposing and personalized medicine. Full article

Objectives: We characterized blood glucose fluctuations in patients with myotonic dystrophy type 1 (DM1). After confirming the incretin secretion capacity of patients with DM1, we intended to clarify whether dipeptidyl peptidase 4 (DPP-4) inhibitor administration was appropriate in cases of DM1 with diabetes mellitus. Methods: A 48 h continuous glucose monitoring (CGM) was performed in 29 Japanese patients with DM1. An oral glucose tolerance test (OGTT) was performed in patients with DM1 and five disease controls, and levels of blood glucose, insulin, and incretin (glucagon-like peptide-1 and gastric inhibitory polypeptide) were measured. DPP-4 inhibitors were administered to patients with diabetes mellitus complicated by DM1, and the CGM results were compared. Results: The CGM showed distinct patterns of blood glucose variability among patients classified by an OGTT pattern with significant differences in glucose parameters such as time above 140 mg/dL and mean amplitude of glycemic excursions between the groups. High sensor glucose values were observed in a certain number of patients who were classified as having normal or impaired glucose tolerance by the OGTT. The CGM confirmed the presence of low glucose levels in several patients. Incretin secretion, the target of DPP-4 inhibitors, was preserved in patients with DM1. DPP-4 inhibitor treatment resulted in lower glucose levels and improved insulin secretion in some patients. Conclusions: This is the first CGM study for DM1 patients. The CGM identified potential early abnormalities in glucose metabolism in DM1. In the future, it will be crucial to explore effective methods for harnessing CGM and assessing it quantitatively in DM1. Full article

Goat milk protein can release a variety of bioactive peptides after digestion, while most of them are digested into free amino acids or dipeptides via the GI tract. We investigated the peptide profiles of goat milk protein following in vitro gastrointestinal digestion using LC-MS/MS and identified 683 bioactive peptides, including 105 DPP-IV inhibitory peptides. Among these peptides, ILDKVGINY (IL), derived from β-lactoglobulin, was found to be high in content and resistance to digestion. Herein, we explore the effect of amino acid residue substitution at the second N-terminus on its DPP-IV inhibitory activity. Three 9 polypeptide fragments (peptide IL, IP, and II) were synthesized and subjected to molecular docking and activity analysis. The peptide IL demonstrated the highest affinity for DPP-IV with a binding energy of −8.4 kcal/mol and a moderate IC50 value of 1.431 mg/mL determined based on the Caco-2 cell model. The replacement of specific amino acid residues by Pro and Leu led to an increase in the hydrophobic force interaction between the inhibitor peptide and DPP-IV. The inhibition rates of the three peptides were significantly different (p < 0.05). Peptide II containing an Ile residue instead of Leu resulted in a significant enhancement of DPP-IV inhibitory activity, with an IC50 value of 0.577 mg/mL. The GRAVY changes in the three peptides were consistent with the trend of the inhibitory rates. Therefore, the GRAVY of peptides and branch-chain amino acids should be considered in its activity improvement. The present study revealed the presence and activity of DPP-IV inhibitory peptides in goat milk, providing important insights for further investigation of their potential food functionality and health benefits. Full article

This study investigates the production of protein hydrolysates with dipeptidyl peptidase-IV (DPP-IV) inhibitory activity from agro-industrial by-products, namely olive seed, sunflower seed, rapeseed, and lupin meals, as well as from two plant protein isolates such as pea and potato. Furthermore, the effect of simulated gastrointestinal digestion on the DPP-IV inhibitory activity of all the hydrolysates was evaluated. Overall, the lowest values of IC₅₀ (1.02 ± 0.09 – 1.24 ± 0.19 mg protein/mL) were observed for the hydrolysates with a high proportion of short-chain [< 1 kDa] peptides (i.e., olive seed, sunflower seed, and lupin) or high content of proline (i.e., rapeseed). Contrarily, the IC₅₀ of the pea and potato hydrolysates was significantly higher (1.50 ± 0.13 – 1.93 ± 0.13 mg protein/mL). In vitro digestion led to an increase in peptides <1 kDa for almost all hydrolysates (except olive and sunflower seed meals), which was noticeable for rapeseed, pea, and potato hydrolysates. Digestion did not significantly modify the DPP-IV inhibitory activity of olive, sunflower, rapeseed, and potato hydrolysates, whereas a significant decrease in IC₅₀ value was obtained for pea hydrolysate and a significant increase in IC₅₀ was obtained for lupin hydrolysate. Thus, this work shows the potential of agro-industrial by-products for the production of protein hydrolysates exhibiting DPP-IV inhibition. Full article

The Target-Based Virtual Screening approach is widely employed in drug development, with docking or molecular dynamics techniques commonly utilized for this purpose. This systematic review (SR) aimed to identify in silico therapeutic targets for treating Diabetes mellitus (DM) and answer the question: What therapeutic targets have been used in in silico analyses for the treatment of DM? The SR was developed following the guidelines of the Preferred Reporting Items Checklist for Systematic Review and Meta-Analysis, in accordance with the protocol registered in PROSPERO (CRD42022353808). Studies that met the PECo strategy (Problem, Exposure, Context) were included using the following databases: Medline (PubMed), Web of Science, Scopus, Embase, ScienceDirect, and Virtual Health Library. A total of 20 articles were included, which not only identified therapeutic targets in silico but also conducted in vivo analyses to validate the obtained results. The therapeutic targets most frequently indicated in in silico studies were GLUT4, DPP-IV, and PPARγ. In conclusion, a diversity of targets for the treatment of DM was verified through both in silico and in vivo reassessment. This contributes to the discovery of potential new allies for the treatment of DM. Full article

Background: Diagnosis of acute kidney injury (AKI) relies on serum creatinine (SCr) changes. This study investigated if urinary aminopeptidases are early and predictive biomarkers of cardiac surgery-associated AKI (CSA-AKI). Methods: Glutamyl aminopeptidase (GluAp), alanyl aminopeptidase (AlaAp), dipeptidyl peptidase-4 (DPP4), proteinuria, albuminuria, N-acetyl-β-D-glucosaminidase (NAG), and neutrophile gelatinase-associated lipocalin (NGAL) were measured in urine samples from 44 patients at arrival in the intensive care unit (ICU) after cardiac surgery. Sensitivity, specificity, and positive and negative predictive value for diagnosis of stages 1, 2, and 3 of AKI were analyzed for the highest quartile of each marker. We also studied the relationship with SCr after surgery, 6- and 12-month glomerular filtration rates (GFRs), and other long-term events over the next 5 years. Results: GluAp diagnosed the maximal number of patients that developed stage 2 or 3 of AKI, increasing diagnostic sensitivity from 0% to 75%. In addition, GluAp and DPP4 were related to the decrease in GFR at 6 or 12 months after surgery. Conclusions: Urinary aminopeptidases are a potential tool for the early diagnosis of CSA-AKI, with GluAp being the most effective marker for diagnosing stage 2 or 3 of AKI at ICU admission. GluAp and DPP4 serve as predictive biomarkers for a decrease in GFR. Full article

Dipeptidyl peptidase IV (DPP-IV) inhibitors are widely used in treating type 2 diabetes due to their ability to lower blood glucose levels. However, synthetic versions often lead to gastrointestinal side effects. This study explores DPP-IV inhibitory properties in peptides from bighead carp skin. Collagen was prepared, hydrolyzed into collagen peptides, and then fractionated for DPP-IV inhibitory activity examination. The most effective fractions were identified, and their peptide sequences were determined. Molecular docking analysis identified nine peptides with potential inhibitory activity, four of which (VYP, FVA, PPGF, PGLVG) were synthesized and tested in vitro. PPGF exhibited the highest potency with an IC₅₀ of 4.63 nM, competitively binding to key DPP-IV sites, including ARG125, VAL711, TYR666, and TYR662. Other peptides showed varying effectiveness, with IC₅₀ values of 398.87 nM (VYP), 402.02 nM (FVA), and 110.20 nM (PGLVG). These findings highlight bighead carp skin peptides as potent DPP-IV inhibitors with hypoglycemic potential, suggesting a novel avenue for diabetes management using natural peptides. Moreover, this research underscores the utilization of bighead carp by-products, contributing to environmental sustainability. Full article

In this study, we aimed to explore the hypoglycemic effects of a hydrolysate on Takifugu bimaculatus skin (TBSH). The effect of the dipeptidyl peptidase-IV (DPP-IV) inhibitory activities from different TBSH fractions was investigated on basic indexes, gut hormones, blood lipid indexes, viscera, and the gut microbiota and its metabolites in rats with type 2 diabetes mellitus (T2DM). The results showed that the <1 kDa peptide fraction from TBSH (TBP) exhibited a more potent DPP-IV inhibitory effect (IC₅₀ = 0.45 ± 0.01 mg/mL). T2DM rats were induced with streptozocin, followed by the administration of TBP. The 200 mg/kg TBP mitigated weight loss, lowered fasting blood glucose levels, and increased insulin secretion by 20.47%, 25.23%, and 34.55%, respectively, rectified irregular hormonal fluctuations, lipid metabolism, and tissue injuries, and effectively remedied gut microbiota imbalance. In conclusion, TBP exerts a hypoglycemic effect in rats with T2DM. This study offers the potential to develop nutritional supplements to treat T2DM and further promote the high-value utilization of processing byproducts from T. bimaculatus. It will provide information for developing nutritional supplements to treat T2DM and further promote the high-value utilization of processing byproducts from T. bimaculatus. Full article