Insulin and GLP-1 infusions demonstrate the onset of adipose-specific insulin resistance in a large fasting mammal: potential glucogenic role for GLP-1.

Prolonged food deprivation increases lipid oxidation and utilization, which may contribute to the onset of the insulin resistance associated with fasting. Because insulin resistance promotes the preservation of glucose and oxidation of fat, it has been suggested to be an adaptive response to food deprivation. However, fasting mammals exhibit hypoinsulinemia, suggesting that the insulin resistance-like conditions they experience may actually result from reduced pancreatic sensitivity to glucose/capacity to secrete insulin. To determine whether fasting results in insulin resistance or in pancreatic dysfunction, we infused early- and late-fasted seals (naturally adapted to prolonged fasting) with insulin (0.065 U/kg), and a separate group of late-fasted seals with low (10 pM/kg) or high (100 pM/kg) dosages of glucagon-like peptide-1 (GLP-1) immediately following a glucose bolus (0.5g/kg), and measured the systemic and cellular responses. Because GLP-1 facilitates glucose-stimulated insulin secretion, these infusions provide a method to assess pancreatic insulin-secreting capacity. Insulin infusions increased the phosphorylation of insulin receptor and Akt in adipose and muscle of early and late fasted seals; however the timing of the signaling response was blunted in adipose of late fasted seals. Despite the dose-dependent increases in insulin and increased glucose clearance (high dose), both GLP-1 dosages produced increases in plasma cortisol and glucagon, which may have contributed to the glucogenic role of GLP-1. Results suggest that fasting induces adipose-specific insulin resistance in elephant seal pups, while maintaining skeletal muscle insulin sensitivity, and therefore suggests that the onset of insulin resistance in fasting mammals is an evolved response to cope with prolonged food deprivation

A Deep Learning-Based Multimodal Architecture to predict Signs of Dementia

This paper proposes a multimodal deep learning architecture combining text and audio information to predict dementia, a disease which affects around 55 million people all over the world and makes them in some cases dependent people. The system was evaluated on the DementiaBank Pitt Corpus dataset, which includes audio recordings as well as their transcriptions for healthy people and people with dementia. Different models have been used and tested, including Convolutional Neural Networks (CNN) for audio classification, Transformers for text classification, and a combination of both in a multimodal ensemble. These models have been evaluated on a test set, obtaining the best results by using the text modality, achieving 90.36% accuracy on the task of detecting dementia. Additionally, an analysis of the corpus has been conducted for the sake of explainability, aiming to obtain more information about how the models generate their predictions and identify patterns in the data.We would like to thank “A way of making Europe” European Regional Development Fund (ERDF) and MCIN/AEI/10.13039/501100011033 for supporting this work under the MoDeaAS project (grant PID2019-104818RB-I00) and AICARE project (grant SPID202200X139779IV0). Furthermore, we would like to thank Nvidia for their generous hardware donation that made these experiments possible

Automated Generation of Clinical Reports Using Sensing Technologies with Deep Learning Techniques

This study presents a pioneering approach that leverages advanced sensing technologies and data processing techniques to enhance the process of clinical documentation generation during medical consultations. By employing sophisticated sensors to capture and interpret various cues such as speech patterns, intonations, or pauses, the system aims to accurately perceive and understand patient–doctor interactions in real time. This sensing capability allows for the automation of transcription and summarization tasks, facilitating the creation of concise and informative clinical documents. Through the integration of automatic speech recognition sensors, spoken dialogue is seamlessly converted into text, enabling efficient data capture. Additionally, deep models such as Transformer models are utilized to extract and analyze crucial information from the dialogue, ensuring that the generated summaries encapsulate the essence of the consultations accurately. Despite encountering challenges during development, experimentation with these sensing technologies has yielded promising results. The system achieved a maximum ROUGE-1 metric score of 0.57, demonstrating its effectiveness in summarizing complex medical discussions. This sensor-based approach aims to alleviate the administrative burden on healthcare professionals by automating documentation tasks and safeguarding important patient information. Ultimately, by enhancing the efficiency and reliability of clinical documentation, this innovative method contributes to improving overall healthcare outcomes.We would like to thank “A way of making Europe” European Regional Development Fund (ERDF) and MCIN/AEI/10.13039/501100011033 for supporting this work under the “CHAN-TWIN” project (grant TED2021-130890B-C21. HORIZON-MSCA-2021-SE-0 action number: 101086387, REMARKABLE, Rural Environmental Monitoring via ultra wide-ARea networKs And distriButed federated Learning; CIAICO/2022/132 Consolidated group project “AI4Health” funded by the Valencian government and International Center for Aging Research ICAR funded project “IASISTEM.” This work has also been supported by a Valencian government grant for PhD studies, CIACIF/2022/175 and a research initiation grant from the University of Alicante, AII23-12

Silk fibroin nanoparticles constitute a vector for controlled release of resveratrol in an experimental model of inflammatory bowel disease in rats.

Purpose: We aimed to evaluate the intestinal anti-inflammatory properties of silk fibroin nanoparticles, around 100 nm in size, when loaded with the stilbene compound resveratrol, in an experimental model of rat colitis. Methods: Nanoparticles were loaded with resveratrol by adsorption. The biological effects of the resveratrol-loaded nanoparticles were tested both in vitro, in a cell culture of RAW 264.7 cells (mouse macrophages), and in vivo, in the trinitrobenzenesulfonic acid model of rat colitis, when administered intracolonically. Results: The resveratrol liberation in 1× phosphate-buffered saline (PBS; pH 7.4) was characterized by fast liberation, reaching the solubility limit in 3 hours, which was maintained over a period of 80 hours. The in vitro assays revealed immunomodulatory properties exerted by these resveratrol-loaded nanoparticles since they promoted macrophage activity in basal conditions and inhibited this activity when stimulated with lipopolysaccharide. The in vivo experiments showed that after evaluation of the macroscopic symptoms, inflammatory markers, and intestinal barrier function, the fibroin nanoparticles loaded with resveratrol had a better effect than the single treatments, being similar to that produced by the glucocorticoid dexamethasone. Conclusion: Silk fibroin nanoparticles constitute an attractive strategy for the controlled release of resveratrol, showing immunomodulatory properties and intestinal anti-inflammatory effects

Simultaneous angiotensin receptor blockade and glucagon-like peptide-1 receptor activation ameliorate albuminuria in obese insulin-resistant rats.

Insulin resistance increases renal oxidant production by upregulating NADPH oxidase 4 (Nox4) expression contributing to oxidative damage and ultimately albuminuria. Inhibition of the renin-angiotensin system (RAS) and activation of glucagon-like peptide-1 (GLP-1) receptor signalling may reverse this effect. However, whether angiotensin receptor type 1 (AT1) blockade and GLP-1 receptor activation improve oxidative damage and albuminuria through different mechanisms is not known. Using insulin-resistant Otsuka Long-Evans Tokushima Fatty (OLETF) rats, we tested the hypothesis that simultaneous blockade of AT1 and activation of GLP-1r additively decrease oxidative damage and urinary albumin excretion (Ualb V) in the following groups: (a) untreated, lean LETO (n = 7), (b) untreated, obese OLETF (n = 9), (c) OLETF + angiotensin receptor blocker (ARB; 10 mg olmesartan/kg/d; n = 9), (d) OLETF + GLP-1 mimetic (EXE; 10 µg exenatide/kg/d; n = 7) and (e) OLETF + ARB +exenatide (Combo; n = 6). Mean kidney Nox4 protein expression and nitrotyrosine (NT) levels were 30% and 46% greater, respectively, in OLETF compared with LETO. Conversely, Nox4 protein expression and NT were reduced to LETO levels in ARB and EXE, and Combo reduced Nox4, NT and 4-hydroxy-2-nonenal levels by 21%, 27% and 27%, respectively. At baseline, Ualb V was nearly double in OLETF compared with LETO and increased to nearly 10-fold greater levels by the end of the study. Whereas ARB (45%) and EXE (55%) individually reduced Ualb V, the combination completely ameliorated the albuminuria. Collectively, these data suggest that AT1 blockade and GLP-1 receptor activation reduce renal oxidative damage similarly during insulin resistance, whereas targeting both signalling pathways provides added benefit in restoring and/or further ameliorating albuminuria in a model of diet-induced obesity

Association of acid phosphatase locus 1*C allele with the risk of cardiovascular events in rheumatoid arthritis patients

Introduction: Acid phosphatase locus 1 (ACP1) encodes a low molecular weight phosphotyrosine phosphatase implicated in a number of different biological functions in the cell. The aim of this study was to determine the contribution of ACP1 polymorphisms to susceptibility to rheumatoid arthritis (RA), as well as the potential contribution of these polymorphisms to the increased risk of cardiovascular disease (CV) observed in RA patients. Methods: A set of 1,603 Spanish RA patients and 1,877 healthy controls were included in the study. Information related to the presence/absence of CV events was obtained from 1,284 of these participants. All individuals were genotyped for four ACP1 single-nucleotide polymorphisms (SNPs), rs10167992, rs11553742, rs7576247, and rs3828329, using a predesigned TaqMan SNP genotyping assay. Classical ACP1 alleles (*A, *B and *C) were imputed with SNP data. Results: No association between ACP1 gene polymorphisms and susceptibility to RA was observed. However, when RA patients were stratified according to the presence or absence of CV events, an association between rs11553742*T and CV events was found (P = 0.012, odds ratio (OR) = 2.62 (1.24 to 5.53)). Likewise, the ACP1*C allele showed evidence of association with CV events in patients with RA (P = 0.024, OR = 2.43). Conclusions: Our data show that the ACP1*C allele influences the risk of CV events in patients with R

Biological Activity and Implications of the Metalloproteinases in Diabetic Foot Ulcers

Inadequate metabolic control predisposes diabetic patient to a series of complications on account of diabetes mellitus (DM). Among the most common complications of DM is neuropathy, which causes microvascular damage by hyperglycemia in the lower extremities which arrives characterized by a delayed closing. The global prevalence of diabetic neuropathy (DN) was 66% of people with diabetes in 2015, representing the principal cause of total or partial lower extremities amputation, with 22.6% of the patients with DN. Matrix metalloproteinases (MMPs) are involved in healing. The function that these mainly play is the degradation during inflammation that has as consequence the elimination of the extracellular matrix (ECM), the disintegration of the capillary membrane to give way to angiogenesis and cellular migration for the remodeling of damaged tissue. The imbalance in MMPs may increase the chronicity of a wound, what leads to chronic foot ulcers and amputation. This chapter focuses on the role of MMPs in diabetic wound healing