Quantitative and qualitative analysis of the quality of life of Type 1 diabetes patients using insulin pumps and of those receiving multiple daily insulin injections

Preparation, Characterization and In vitro Evaluation of Insulin-PHBV Nanoparticles/Alginate Hydrogel Composite System for Prolonged Delivery of Insulin

PURPOSE

In the present study, biodegradable poly (3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) nanoparticles (NPs) containing insulin were loaded in sodium alginate/jeffamine (ALG/jeff) hydrogel for prolonged delivery of insulin. The main aim of this work was to fabricate an efficient insulin delivery system to improve patient adherence by decreasing the repetition of injections.

METHODS

Swelling and morphological properties and crosslinking efficiency of ALG/jeff hydrogel were assessed. The composite hydrogel was prepared by adding PHBV NPs to ALG/jeff hydrogel concurrently with crosslinking process. The morphology and loading capacity of composite hydrogel were analyzed.

RESULTS

Circular dichroism measurement demonstrated that insulin remains stable following fabrication process. The release profile exhibited 54.6 % insulin release from composite hydrogel within 31 days with minor initial burst release equated to nanoparticles and hydrogels. MTT cell viability analysis was performed by applying L-929 cell line and no cytotoxic effect was observed.

CONCLUSIONS

Favorable results clearly introduced fabricated composite hydrogel as an excellent candidate for drug delivery systems and also paves the route for prolonged delivery systems of other proteins.

Corn stigma ameliorates hyperglycemia in zebrafish and GK rats of type 2 diabetes

ETHNOPHARMACOLOGICAL RELEVANCE

Cornstigma (CS), derived from the stigma and style of gramineous plant Zeamays. The medicinal use of CS can be traced back to DianNanMateriaMedica. LingnanMedicinalPlantsCompendium records its effectiveness in ameliorating diabetes. Diabetes is a metabolic disorder characterized by hyperglycemia and the consequent chronic complications of kidney, heart, brain and other organs, which pose a significant threat to human health. CS has shown great potential in relieving hyperglycemia associated with diabetes. However, the mechanism of CS in treating diabetes remains unclear.

AIM OF THE STUDY

To explore the pathogenesis of diabetes and the mechanism of CS improving hyperglycemia in diabetes.

MATERIALS AND METHODS

We measured apigenin and luteolin contents in CS by UPLC/MS/MS method. Selecting Wistar rats as normal group, and GK rats as model group. For rats, we detected glucose and lipid metabolism indicators, including GHb, AST, ALT, U-Glu, UA, U-TP, U-ALB, and ACR after treatment. For zebrafish, we utilized alloxan and sucrose to establish the diabetes model. Measuring zebrafish blood glucose is employed to evaluate the hypoglycemic capability of CS. In order to explore the mechanism of CS in treating diabetes, we sequenced the transcriptome of zebrafish, compared differentially expressed genes of normal, diabetic, and CS-treated group, and validated multiple enrichment pathways by PCR.

RESULTS

CS can improve blood glucose levels in both GK rats and diabetic zebrafish. For rats, CS partially restored glucose and lipid metabolism indicators. Transcriptome data from zebrafish showed a close correlation with steroid biosynthesis. The RNA-Sequencing was consistent with PCR results, indicating that CS downregulated gene (fdft1,lss,cyp51) expression concerned with steroid biosynthesis pathway in the diabetes model.

CONCLUSION

CS effectively improved blood glucose levels, regulated glucose and lipid metabolism by suppressing gene expression in steroid biosynthesis pathway, and ameliorated hyperglycemia. Our research provides valuable insights for CS in the treatment of diabetes, and proposes a new strategy for selecting clinical medications for diabetes.

"You can hide it if you want to, you can let it be seen if you want to": A qualitative study of the lived experiences of Australian adults with type 1 diabetes using the Omnipod DASH® system

AIMS

Understanding the lived experience of using a tubeless insulin pump and how this differs compared to usual care (tubed insulin pump therapy (IPT) vs multiple daily injections (MDI)).

METHODS

Interviews were conducted after 12-weeks of using the Omnipod DASH Insulin Management System (Insulet, Acton, MA) and analysed using thematic analysis.

RESULTS

Fifty-eight adults (35 female; mean age 42;SD 13 years; 35 previous MDI) were interviewed. Most (84 %) wanted to continue using the device. Experiences fit two themes: 1. Taking back control of my diabetes: many previous MDI users perceived improved glycaemic control, explained by more "nuanced" control, with some reporting positive effects during exercise and sleep. Many previous MDI and IPT users endorsed positive experiences in concealing or disclosing their diabetes to others. However, some previous MDI users reported negative psychosocial experiences due to feeling continuously "attached" to their diabetes. 2. Barriers and facilitators of device acceptability: both MDI and IPT users cited wearability, alarms and the financial cost impacted their choice to continue device use. IPT users reported positive wearability experiences.

CONCLUSIONS

The tubeless pump improved diabetes management perceptions for both MDI and tubed pump users. However, participants' prior glucose management affected perceptions of its advantages and disadvantages.

Progression of Diabetic Kidney Disease and Gastrointestinal Symptoms in Patients with Type I Diabetes

(1) Background: Little research is conducted on the link between diabetic kidney disease (DKD) progression and diabetic gastroenteropathy in type 1 diabetes (T1D). (2) Methods. We performed a cross-sectional study with 100 T1D patients; 27 of them had progressive DKD, defined as an estimated glomerular filtration rate (eGFR) decline ≥3 mL/min/year or increased albuminuria stage, over a mean follow-up time of 5.89 ± 1.73 years. A newly developed score with 17 questions on gastrointestinal (GI) symptoms was used. Faecal calprotectin was measured by ELISA. Lower GI endoscopies were performed in 21 patients. (3) Results: The gastrointestinal symptom score demonstrated high reliability (Cronbach's α = 0.78). Patients with progressive DKD had higher GI symptom scores compared to those with stable DKD (p = 0.019). The former group demonstrated more frequent bowel movement disorders (p < 0.01). The scores correlated negatively with eGFR (r = -0.335; p = 0.001), positively with albuminuria (r = 0.245; p = 0.015), Hba1c (r = 0.305; p = 0.002), and diabetes duration (r = 0.251; p = 0.012). Faecal calprotectin levels did not differ between DKD groups significantly. The most commonly reported histopathological findings of enteric mucosa were infiltration with eosinophils, lymphocytes, plasmacytes, the presence of lymphoid follicles, and lymphoid aggregates. Conclusion: The progression of DKD is positively correlated with gastrointestinal symptoms; however, more research is needed to clarify the causal relationships of the gut-kidney axis in T1D.

Prediction of type 1 diabetes with machine learning algorithms based on FTIR spectral data in peripheral blood mononuclear cells

The incidence of autoimmunity is increasing, to ensure timely and comprehensive treatment, there must be a diagnostic method or markers that would be available to the general public. Fourier-transform infrared spectroscopy (FTIR) is a relatively inexpensive and accurate method for determining metabolic fingerprint. The metabolism, molecular composition and function of blood cells vary according to individual physiological and pathological conditions. Thus, by obtaining autoimmune disease-specific metabolic fingerprint markers in peripheral blood mononuclear cells (PBMC) and subsequently using machine learning algorithms, it might be possible to create a tool that will allow the diagnosis of autoimmune diseases. In this preliminary study, it was found that the peak shift at 1545 cm-1 could be considered specific for autoimmune disease type 1 diabetes (T1D), while the shifts at 1070 and 1417 cm-1 could be more attributed to the autoimmune condition per se. The prediction of T1D, despite the small number of participants in the study, showed an inverse AUC = 0.33 ± 0.096, n = 15, indicating a stable trend in the prediction of T1D based on FTIR metabolic fingerprint data in the PBMC.

One Digital Health Intervention for Monitoring Human and Animal Welfare in Smart Cities: Viewpoint and Use Case

Smart cities and digital public health are closely related. Managing digital transformation in urbanization and living spaces is challenging. It is critical to prioritize the emotional and physical health and well-being of humans and their animals in the dynamic and ever-changing environment they share. Human-animal bonds are continuous as they live together or share urban spaces and have a mutual impact on each other's health as well as the surrounding environment. In addition, sensors embedded in the Internet of Things are everywhere in smart cities. They monitor events and provide appropriate responses. In this regard, accident and emergency informatics (A&EI) offers tools to identify and manage overtime hazards and disruptive events. Such manifold focuses fit with One Digital Health (ODH), which aims to transform health ecosystems with digital technology by proposing a comprehensive framework to manage data and support health-oriented policies. We showed and discussed how, by developing the concept of ODH intervention, the ODH framework can support the comprehensive monitoring and analysis of daily life events of humans and animals in technologically integrated environments such as smart homes and smart cities. We developed an ODH intervention use case in which A&EI mechanisms run in the background. The ODH framework structures the related data collection and analysis to enhance the understanding of human, animal, and environment interactions and associated outcomes. The use case looks at the daily journey of Tracy, a healthy woman aged 27 years, and her dog Mego. Using medical Internet of Things, their activities are continuously monitored and analyzed to prevent or manage any kind of health-related abnormality. We reported and commented on an ODH intervention as an example of a real-life ODH implementation. We gave the reader examples of a "how-to" analysis of Tracy and Mego's daily life activities as part of a timely implementation of the ODH framework. For each activity, relationships to the ODH dimensions were scored, and relevant technical fields were evaluated in light of the Findable, Accessible, Interoperable, and Reusable principles. This "how-to" can be used as a template for further analyses. An ODH intervention is based on Findable, Accessible, Interoperable, and Reusable data and real-time processing for global health monitoring, emergency management, and research. The data should be collected and analyzed continuously in a spatial-temporal domain to detect changes in behavior, trends, and emergencies. The information periodically gathered should serve human, animal, and environmental health interventions by providing professionals and caregivers with inputs and "how-to's" to improve health, welfare, and risk prevention at the individual and population levels. Thus, ODH complementarily combined with A&EI is meant to enhance policies and systems and modernize emergency management.