BACKGROUND: Acute Patient Physiologic and Laboratory Evaluation (APPLE) scores have not been reported in cats with diabetic ketoacidosis (DKA).
OBJECTIVE: In cats with DKA, APPLE scores will be significantly higher in non-survivors compared with survivors and these scores will predict mortality.
METHODS: Sixty-eight cats with DKA.
METHODS: Retrospective study. The APPLE scores, blood glucose concentration (BG), venous pH, and ketone concentrations were compared between survivors and non-survivors. Simple logistic regression was used to determine if these variables predict the binary variable of survival or non-survival, and if they did, an empirical optimal cut point for mortality prediction was calculated.
RESULTS: The APPLEfast and APPLEfull scores were significantly higher in non-survivors (30 cats; 24.6 ± 7.4 $$ 24.6\\pm 7.4 $$ and 45.2 ± 7.3 $$ 45.2\\pm 7.3 $$ , respectively) compared with survivors (38 cats; 20.9 ± 6.2 $$ 20.9\\pm 6.2 $$ and 41.7 ± 6.5 $$ 41.7\\pm 6.5 $$ ; P = .01 and P = .02, respectively). The APPLEfast (P = .03) but not the APPLEfull scores (P = .06) predicted mortality. For every 1 unit increase in the APPLEfast score, the odds of death increased by 1.08 (95% confidence interval [CI], 1.006-1.17; P = .03). Median BG was significantly higher in non-survivors (431 mg/dL; range, 260-832 mg/dL) compared with survivors (343 mg/dL; range, 256-738 mg/dL; P = .01) and BG predicted mortality (P = .02). For every 1 mg/dL increase in BG, the odds of death increased by 1.004 (95% CI, 1.0006-1.008). Empirical optimal cut points for APPLEfast and BG mortality prediction were 24.5 and 358 mg/dL, respectively.
CONCLUSIONS: The APPLEfast score and BG predict mortality in cats with DKA and can be used to stratify populations by risk of mortality in clinical trials of DKA in cats.

UNASSIGNED: Many studies have examined the role of inflammation in the development of diabetic neuropathy (DPN).
UNASSIGNED: Evaluate the relation of the serum level of Transforming Growth Factor-β and Tumor Necrosis Factor-α and development of diabetic peripheral neuropathy DPN.
UNASSIGNED: In a case-control study, randomly selected 140 diabetic patients were included, the randomly selected patients were divided equally and matched into a case group who have diabetic peripheral neuropathy and diabetic neuropathy-free patients as a control group. For both groups whole blood sample was examined to compare for (TGF-β), and (TNF-α) levels determination by ELISA technique.
UNASSIGNED: The age of the study samples ranged from 25 to 80 years with a male ratio of 1.45:1 although the sex differences between both groups were not significant. The mean levels of (TNF-α) and (TGF-β) was significantly higher among cases group than that of controls group (254.86 ± 75.9 vs158.01 ± 50.600) for TNF-α and for TGF- β (312.85 ± 62.27 vs. 217.82 ± 52.95) respectively. Both TNF-α and TGF-β have high sensitivity and specificity in detection of DPN. The sensitivity of TNF-α was 95.7% and specificity of 61.4% area under the ROC curve (AUC) of 0.870 ± 0.029, while the sensitivity of TGF-β was 91.4%, and specificity of 67.1 with good area under the ROC curve (AUC) of 0.891 ± 0.026 (P=0.000).
UNASSIGNED: TNF-α and TGF -β are significantly elevated levels in patients with DPN, these cytokines could be used as indicators for the development of DPN.

BACKGROUND: The impact of missing data on individual continuous glucose monitoring (CGM) data is unknown but can influence clinical decision-making for patients.
OBJECTIVE: We aimed to investigate the consequences of data loss on glucose metrics in individual patient recordings from continuous glucose monitors and assess its implications on clinical decision-making.
METHODS: The CGM data were collected from patients with type 1 and 2 diabetes using the FreeStyle Libre sensor (Abbott Diabetes Care). We selected 7-28 days of 24 hours of continuous data without any missing values from each individual patient. To mimic real-world data loss, missing data ranging from 5% to 50% were introduced into the data set. From this modified data set, clinical metrics including time below range (TBR), TBR level 2 (TBR2), and other common glucose metrics were calculated in the data sets with and that without data loss. Recordings in which glucose metrics deviated relevantly due to data loss, as determined by clinical experts, were defined as expert panel boundary error (εEPB). These errors were expressed as a percentage of the total number of recordings. The errors for the recordings with glucose management indicator <53 mmol/mol were investigated.
RESULTS: A total of 84 patients contributed to 798 recordings over 28 days. With 5%-50% data loss for 7-28 days recordings, the εEPB varied from 0 out of 798 (0.0%) to 147 out of 736 (20.0%) for TBR and 0 out of 612 (0.0%) to 22 out of 408 (5.4%) recordings for TBR2. In the case of 14-day recordings, TBR and TBR2 episodes completely disappeared due to 30% data loss in 2 out of 786 (0.3%) and 32 out of 522 (6.1%) of the cases, respectively. However, the initial values of the disappeared TBR and TBR2 were relatively small (<0.1%). In the recordings with glucose management indicator <53 mmol/mol the εEPB was 9.6% for 14 days with 30% data loss.
CONCLUSIONS: With a maximum of 30% data loss in 14-day CGM recordings, there is minimal impact of missing data on the clinical interpretation of various glucose metrics.
BACKGROUND: ClinicalTrials.gov NCT05584293; https://clinicaltrials.gov/study/NCT05584293.

BACKGROUND: Blood glucose management around exercise is challenging for youth with type 1 diabetes (T1D). Previous research has indicated interventions including decision-support aids to better support youth to effectively contextualize blood glucose results and take appropriate action to optimize glucose levels during and after exercise. Mobile health (mHealth) apps help deliver health behavior interventions to youth with T1D, given the use of technology for glucose monitoring, insulin dosing, and carbohydrate counting.
OBJECTIVE: We aimed to develop a novel prototype mHealth app to support exercise management among youth with T1D, detail the application of a co-design process and design thinking principles to inform app design and development, and identify app content and functionality that youth with T1D need to meet their physical activity goals.
METHODS: A co-design approach with a user-centered design thinking framework was used to develop a prototype mHealth app \"acT1ve\" during the 18-month design process (March 2018 to September 2019). To better understand and respond to the challenges among youth with diabetes when physically active, 10 focus groups were conducted with youth aged 13-25 years with T1D and parents of youth with T1D. Thereafter, we conducted participatory design workshops with youth to identify key app features that would support individual needs when physically active. These features were incorporated into a wireframe, which was critically reviewed by participants. A beta version of \"acT1ve\" was built in iOS and android operating systems, which underwent critical review by end users, clinicians, researchers, experts in exercise and T1D, and app designers.
RESULTS: Sixty youth with T1D, 14 parents, 6 researchers, and 10 clinicians were engaged in the development of \"acT1ve.\" acT1ve included key features identified by youth, which would support their individual needs when physically active. It provided advice on carbohydrates and insulin during exercise, information on hypoglycemia treatment, pre- and postexercise advice, and an educational food guide regarding exercise management. \"acT1ve\" contained an exercise advisor algorithm comprising 240 pathways developed by experts in diabetes and exercise research. Based on participant input during exercise, acT1ve provided personalized insulin and carbohydrate advice for exercise lasting up to 60 minutes. It also contains other features including an activity log, which displays a complete record of the end users\' activities and associated exercise advice provided by the app\'s algorithm for later reference, and regular reminder notifications for end users to check or monitor their glucose levels.
CONCLUSIONS: The co-design approach and the practical application of the user-centered design thinking framework were successfully applied in developing \"acT1ve.\" The design thinking processes allowed youth with T1D to identify app features that would support them to be physically active, and particularly enabled the delivery of individualized advice. Furthermore, app development has been described in detail to help guide others embarking on a similar project.
BACKGROUND: Australian New Zealand Clinical Trials Registry ACTRN12619001414101; https://tinyurl.com/mu9jvn2d.

Diabetic wounds, a prevalent diabetes complication, pose significant challenges in treatment. MicroRNA-engineered exosomes (miR-exo) are a promising new treatment for diabetic wounds; however, their mechanism remains to be completely understood. Therefore, we aimed to conduct a meta-analysis to evaluate the efficacy of miR-exo treatment in the management of diabetic wounds. To achieve this aim, academic databases, including PubMed, Embase, Web of Science, and the Cochrane Library, were searched for papers published before July 4, 2023. Outcome indicators (e.g., rate of wound healing, neovascular count, rate of re-epithelialization, deposition of collagen, breadth of scar, and inflammatory factors) were assessed. Six studies (total of 72 animals) met inclusion criteria and were analyzed. The amalgamated data revealed that miR-exo treatment exhibited superior results compared to those of control therapy. miR-exo treatment significantly enhanced the rate of wound healing, increased the number of neovascular formations, accelerated the rate of re-epithelialization, increased collagen deposition, reduced scar width, while significantly downregulating the expression of inflammatory factors. Our findings indicate that miR-exo treatment augments overall diabetic wound healing, especially when administered in conjunction with innovative dressings. To ascertain the optimal parameters for miR-exo treatment in managing diabetic wounds, future studies must encompass rigorous, large-scale, double-blinded clinical trials while incorporating long-term follow-up assessments for enhanced reliability and accuracy.

This study employs the Technology Acceptance Model to investigate the factors influencing Saudi Arabian diabetic patients\' intention to use digital health services. There is an urgent need to investigate the possibilities of digital health services in managing diabetes given the startlingly rapidly increasing prevalence rate of diabetes in KSA. The study examines the variables affecting patients\' acceptance and desire to use digital health tools to manage their diabetes. The study employs the Technology Acceptance Model to ascertain the crucial factors that impact patients\' opinions regarding the usefulness and ease of use of digital healthcare technologies. The proposed model extends the traditional Technology Acceptance Model by adding two new constructs, perceived privacy and trust. These constructs were examined by analyzing the intentions of 600 respondents through online surveys. The study\'s conclusions showed that attitudes toward using digital health services for KSA diabetic patients are greatly influenced by every component of the extended Technology Acceptance Model. The study\'s conclusions add to the body of knowledge already in existence and offer insightful information to decision-makers hoping to improve digital health services.

The active form of discoidin domain receptors (DDRs) is expressed in cell surface and regulated post-translationally by glucose. The DDR2 and DDR1 transfected in HEK293 cells were expressed mainly in their active forms with sizes of 130 and 120 kDa, respectively. DDRs were observed predominantly as 100 kDa proteins in glucose-depleted culture conditions. However, transfection of endothelial growth factor receptor (EGFR) in HEK293 cells resulted in the expression of only one form regardless of glucose concentration. Vascular smooth muscle cells, HT1080s, and MDA-MB-231 cancer cells expressed DDRs in their active forms in high glucose concentrations, which did not occur with EGFR. In diabetic rats, DDRs were expressed at high levels in arterial tissue but EGFR was not highly expressed. Taken together, these results suggest that DDRs expression depends on glucose concentration it may cooperate in the development of atherosclerosis and kidney fibroblasts, promoting nephropathy in diabetic rats.

UNASSIGNED: Diabetes mellitus is a persistent hyperglycemic condition. Thai cuisine and medicine incorporate spices: nutmeg, mace, clove buds, cardamom, cinnamon, and coriander. The in vitro impacts of these spices on anti-diabetic, antioxidant, anti-inflammatory, and total phenolic and flavonoid content were assessed.
UNASSIGNED: Alpha-amylase and alpha-glucosidase inhibition assays were conducted. Antioxidant potential was measured through DPPH and ABTS assays. Anti-inflammatory activity was determined by inhibiting nitric oxide generation in RAW 264.7 cells. Total phenolic content was quantified using the Folin Ciocalteu method, while total flavonoid content was estimated via the aluminum chloride colorimetric method.
UNASSIGNED: Ethanolic and aqueous extracts of a blend of spices (Siam cardamom, nutmeg, mace, and clove buds), denoted as 4-GlurE and 4-GlurA, displayed concentration-dependent inhibition of alpha-glucosidase, with IC50 values of 0.373 and 0.435 mg/mL, respectively. 4-GlurE and 4-GlurA exhibited antioxidant activity, by ABTS·+ radical and DPPH scavenging capabilities. 4-GlurE demonstrated anti-inflammatory potential by reducing nitric oxide generation (IC50: 43.95 ± 2.47 μg/mL). 4-GlurE and 4-GlurA possessed total phenolic content (TPC) of 122.47 ± 1.12 and 148.72 ± 0.14 mg GAE/g, respectively. 4-GlurE exhibited a higher total flavonoid content (TFC) compared to the aqueous extract (340.33 ± 4.77 and 94.17 ± 3.36 mg QE/g). Cinnamon and clove aqueous extracts were more potent than acarbose in alpha-glucosidase inhibition with the highest antioxidant activity. Polyphenol levels (TPC and TFC) exhibited strong correlations with antioxidant capacity.
UNASSIGNED: Findings are consistent with the traditional use of 4-Glur, with cinnamon, for diabetes prevention and treatment.

The process of wound healing is intricate and requires close coordination; any disruption to this process can have catastrophic results. It is hypothesized that chronic wounds that do not heal or that cease healing entirely can be caused by a combination of host factors and bacteria that are present in a wound bed or wound bed environment. There is currently a lack of understanding regarding the role that the cutaneous microbiome plays in the healing process of wounds, despite the fact that methods that do not rely on culture have revealed the role that the gut microbiome plays in human health and illness. In order to keep the host immune system in check, protect the epithelial barrier function, and ward off harmful microbes, skin commensals play a crucial role. This review compiles the research on the effects of microbiome modifications on wound healing and tissue regeneration from both clinical and pre-clinical investigations on a variety of chronic skin wounds. It is now clear that human skin commensals, symbionts, and pathogens all play a part in the inflammatory response, which in turn suggests a number of ways to treat wounds that are infected and not healing. To fully understand the function of the human skin microbiome in both short-term and long-term wound healing, additional study is required to reconcile the conflicting and contentious results of previous investigations.

BACKGROUND: The COVID-19 pandemic created unprecedented challenges for people with type 2 diabetes (T2D) and prediabetes to access in-person health care support. Primary care teams accelerated plans to implement digital health technologies (DHTs), such as remote consultations and digital self-management. There is limited evidence about whether there were inequalities in how people with T2D and prediabetes adjusted to these changes.
OBJECTIVE: This study aimed to explore how people with T2D and prediabetes adapted to the reduction in in-person health support and the increased provision of support through DHTs during the COVID-19 pandemic and beyond.
METHODS: A purposive sample of people with T2D and prediabetes was recruited by text message from primary care practices that served low-income areas. Semistructured interviews were conducted by phone or video call, and data were analyzed thematically using a hybrid inductive and deductive approach.
RESULTS: A diverse sample of 30 participants was interviewed. There was a feeling that primary care had become harder to access. Participants responded to the challenge of accessing support by rationing or delaying seeking support or by proactively requesting appointments. Barriers to accessing health care support were associated with issues with using the total triage system, a passive interaction style with health care services, or being diagnosed with prediabetes at the beginning of the pandemic. Some participants were able to adapt to the increased delivery of support through DHTs. Others had lower capacity to use DHTs, which was caused by lower digital skills, fewer financial resources, and a lack of support to use the tools.
CONCLUSIONS: Inequalities in motivation, opportunity, and capacity to engage in health services and DHTs lead to unequal possibilities for people with T2D and prediabetes to self-care and receive care during the COVID-19 pandemic. These issues can be addressed by proactive arrangement of regular checkups by primary care services and improving capacity for people with lower digital skills to engage with DHTs.