To investigate the risk factors associated with recurrent hemorrhage following vitrectomy surgical intervention for diabetic retinopathy (DR).

A retrospective analysis was conducted on 579 eyes diagnosed with DR necessitating surgical intervention. These cases were categorized into two groups: recurrent hemorrhage and non-recurrent hemorrhage. Comparative, random forest (RF), and regression analyses were subsequently performed to evaluate variables pertaining to patients' demographic information, clinical examination and blood test results, treatment approaches, lifestyle habits, and overall health status.

This study compared patients with recurrent and non-recurrent hemorrhages, revealing significant differences in factors such as endodiathermy, anticoagulant use, cerebrovascular diseases, smoking status, glycosylated hemoglobin levels and BMI. Patients with no recurrent hemorrhage have faster vision recovery. The univariable logistic regression analysis indicated that cerebrovascular disease (OR = 7.87, P < 0.001), anticoagulant use (OR = 16.72, P < 0.001), and elevated glycated hemoglobin levels (OR = 21.22, P < 0.001) exhibited strong associations with recurrent hemorrhage. The multivariable logistic regression analysis indicated that recurrent hemorrhage risk factors include anticoagulant use (OR = 120.77, P = 0.020) and glycated hemoglobin levels (OR = 18.41, P = 0.001).

Recurrent postoperative hemorrhage is influenced by several factors, notably the use of intraoperative endodiathermy, adjustments in ocular therapy, and management of the patient's systemic condition. In clinical practice, careful consideration of these factors is essential to mitigate postoperative hemorrhage in patients.

This study aims to analyze the application and clinical translation value of the self-evolving machine learning methods in predicting diabetic retinopathy and visualizing clinical outcomes.

A retrospective study was conducted on 300 diabetic patients admitted to our hospital between January 2022 and October 2023. The patients were divided into a diabetic retinopathy group (n=150) and a non-diabetic retinopathy group (n=150). The improved Beetle Antennae Search (IBAS) was used for hyperparameter optimization in machine learning, and a self-evolving machine learning model based on XGBoost was developed. Value analysis was performed on the predictive features for diabetic retinopathy selected through multifactor logistic regression analysis, followed by the construction of a visualization system to calculate the risk of diabetic retinopathy occurrence.

Multifactor logistic regression analysis revealed that being male, having a longer disease duration, higher systolic blood pressure, fasting blood glucose, glycosylated hemoglobin, low-density lipoprotein cholesterol, and urine albumin-to-creatinine ratio were risk factors for the development of diabetic retinopathy, while non-pharmacological treatment was a protective factor. The self-evolving machine learning model demonstrated significant performance advantages in early diagnosis and prediction of diabetic retinopathy occurrence.

The application of the self-evolving machine learning models can assist in identifying features associated with diabetic retinopathy in clinical settings, enabling early prediction of disease occurrence and aiding in the formulation of treatment plans to improve patient prognosis.

To determine the effects of aerobic exercise on the components of the metabolic syndrome in older adult diabetic patients by means of a systematic review with meta-analysis.

We used the PubMed/Medline, Scopus, Cochrane library, Web of Science databases and the Google Scholar search engine. Randomized controlled trials (RCTs) were selected according to the inclusion criteria. Two reviewers independently determined whether studies met the inclusion criteria, extracted data, and used the Cochrane risk of bias tool (RoB 2). Quantitative analyses were performed in R v 4.0.5, using random effects.

We identified 8697 studies, of which 7 RCTs were included in the qualitative synthesis. Most studies were assessed as having a high or low RoB in at least three domains. Meta-analysis showed that aerobic exercise was effective in improving glucose levels (standardized mean difference [SMD]: -1.04; 95% confidence interval [95% CI] -1.27, -0.81), systolic blood pressure (SMD: -0.79; 95% CI: -1.02, -0.56), diastolic blood pressure (SMD: -0.75; 95% CI: -0.98, -0.52), glycosylated hemoglobin (SMD: -0.57, 95% CI: -0.77, -0.37), HDL (SMD: 0.35, 95% CI: 0.15, 0.55), triglycerides (SMD: -0.26, 95% CI: -0.47, -0.06). No significant adverse effects were reported. The level of certainty of the results was low for fasting glucose, moderate for systolic and diastolic blood pressure, and very low for the other outcomes, in addition to few adverse effects. However, these results should be interpreted with caution due to the use of surrogate markers.

Aerobic exercise was shown to have a significant improvement in the components of the metabolic syndrome in older diabetic adults, and no major adverse effects were reported. However, we recommend more RCTs with longer intervention time to establish the impact on symptoms and complications.

Motivation for the study. The motivation for this research arises from the high prevalence of metabolic syndrome and diabetes mellitus around the world. Despite their impact, there is a gap in knowledge regarding non-pharmacological interventions in older adults aimed at improving the metabolic profile of these patients. Main findings. Our results show a significant improvement in glucose, blood pressure, glycosylated hemoglobin, HDL, and triglyceride levels after the aerobic exercise intervention. In addition, no significant adverse effects were observed. Public health implications. Physical exercise is an affordable and globally available strategy. It improves the metabolic profile of older adult patients with metabolic syndrome.

Glycated hemoglobin A1c (HbA1c) is considered the most suitable for diabetes mellitus diagnosis due to its accuracy and convenience. However, the effect of HbA1c on diabetic retinopathy (DR) in the Han and Korean populations in Jilin, China, remains inconclusive.

To determine the best cut-off of HbA1c for diagnosing DR among the Chinese.

This cross-sectional study included 1933 participants from the Yanbian area of Jilin Province, China. Trained investigators employed a questionnaire-based survey, physical examination, laboratory tests, and fundus photography for the investigation. The best cut-off value for HbA1c was established via the receiver operating characteristic curve. The factors associated with HbA1c-associated risk factors were determined via linear regression.

The analysis included 887 eligible Chinese Han and Korean participants, 591 of whom were assigned randomly to the training set and 296 to the validation set. The prevalence of DR was 3.27% in the total population. HbA1c of 6.2% was the best cut-off value in the training set, while it was 5.9% in the validation set. In both Chinese Han and Korean populations, an HbA1c level of 6.2% was the best cut-off value. The optimal cut-off values of fasting blood glucose (FBG) ≥ 7 mmol/L and < 7 mmol/L were 8.1% and 6.2% respectively in Han populations, while those in Korean populations were 6.9% and 5.3%, respectively. Age, body mass index, and FBG were determined as the risk factors impacting HbA1c levels.

HbA1c may serve as a useful diagnostic indicator for DR. An HbA1c level of 6.2% may be an appropriate cut-off value for DR detection in the Chinese population.

Diabetic retinopathy (DR) represents a severe complication of diabetes mellitus, characterized by irreversible visual impairment resulting from microvascular abnormalities. Since the global prevalence of diabetes continues to escalate, DR has emerged as a prominent area of research interest. The development and progression of DR encompass a complex interplay of pathological and physiological mechanisms, such as high glucose-induced oxidative stress, immune responses, vascular endothelial dysfunction, as well as damage to retinal neurons. Recent years have unveiled the involvement of genomic and epigenetic factors in the formation of DR mechanisms. At present, extensive research explores the potential of biomarkers such as cytokines, molecular and cell therapies, antioxidant interventions, and gene therapy for DR treatment. Notably, certain drugs, such as anti-VEGF agents, antioxidants, inhibitors of inflammatory responses, and protein kinase C (PKC)-β inhibitors, have demonstrated promising outcomes in clinical trials. Within this context, this review article aims to introduce the recent molecular research on DR and highlight the current progress in the field, with a particular focus on the emerging and experimental treatment strategies targeting the immune and redox signaling pathways.

The degenerative tendency of diabetes leads to micro- and macrovascular complications due to abnormal levels of biochemicals, particularly in patients with poor diabetic control. Diabetes is supposed to be treated by reducing blood glucose levels, scavenging free radicals, and maintaining other relevant parameters close to normal ranges. In preclinical studies, numerous in vivo trials on animals as well as in vitro tests are used to assess the antidiabetic and antioxidant effects of the test substances. Since a substance that performs poorly in vitro won't perform better in vivo, the outcomes of in vitro studies can be utilized as a direct indicator of in vivo activities.

The objective of the present study is to provide research scholars with a comprehensive overview of laboratory methods and procedures for a few selected diabetic biomarkers and related parameters.

The search was conducted on scientific database portals such as ScienceDirect, PubMed, Google Scholar, BASE, DOAJ, etc. Conclusion: The development of new biomarkers is greatly facilitated by modern technology such as cell culture research, lipidomics study, microRNA biomarkers, machine learning techniques, and improved electron microscopies. These biomarkers do, however, have some usage restrictions. There is a critical need to find more accurate and sensitive biomarkers. With a few modifications, these biomarkers can be used with or even replace conventional markers of diabetes.

A growing life expectancy may result in a chronic medical condition and multimorbidity because the aging process leads to a decrease in cognitive and physiological function. These risks may affect the quality of life of geriatrics. The present study aims to determine the correlation between cognitive status (in terms of SIRT1, a nicotinamide adenine dinucleotide (NAD+)-dependent class III deacetylase) and metabolic function (in terms of the lipid profile, kidney function, and blood glucose) in geriatric patients. The differences in the parameters of metabolic function in the participants' cognitive status were determined by using the Indonesian version of the Montreal Cognitive Assessments (MoCA-Ina). The elderly participants (n = 120) were recruited at three sites in Indonesia from March to October 2022. Our study demonstrated a negative correlation between the cognitive status of geriatric patients and their metabolic function, represented by the MoCA-Ina score with a linear regression equation of y = 0.27 - 2.4 ×10-3x. Higher levels of LDL-C, cystatin C, and HbA1c were found in the Severe-Moderate Cognitive Impairment group. Determining the SIRT1 levels may be beneficial in predicting both the cognitive and metabolic status of geriatrics because this protein is among numerous metabolic sensors in the hypothalamus.

Nutraceuticals have been important for more than two decades for their safety, efficacy, and outstanding effects. Diabetes is a major metabolic syndrome, which may be improved using nutritional pharmaceuticals. Some microalgae species, such as spirulina, stand out by providing biomass with exceptional nutritional properties. Spirulina has a wide range of pharmacological effects, mostly related to phycocyanin. Phycocyanin is a protein compound with antidiabetic properties, known as a nutraceutical.

This review delves into phycocyanin applications in diabetes and its complications and ascertains the mechanisms involved.

Scopus, PubMed, Cochrane Library, Web of Science, and ProQuest databases were systematically reviewed (up to April 30, 2023), in which only animal and cellular studies were found.

According to animal studies, the administration of phycocyanin affected biochemical parameters (primary outcome) related to diabetes. These results showed an increase in fasting insulin serum and a decrease in fasting blood glucose, glycosylated serum protein, and glycosylated hemoglobin. In cellular studies, though, phycocyanin prevented methylglyoxal and human islet amyloid polypeptide-induced dysfunction in β-cells and induced apoptosis through different molecular pathways (secondary outcome), including activation of Nrf2, PI3K/Akt, and suppression of JNK and p38. Also, phycocyanin exerted its antidiabetic effect by affecting the pathways regulating hepatic glucose metabolism.

Thus, based on the available information and literature, targeting these pathways by phycocyanin may unleash an array of benefits, including positive outcomes of the antidiabetic effects of phycocyanin as a nutraceutical.

This systematic review was registered in the International Prospective Register of Systematic Reviews (PROSPERO) at the National Institute of Health. The registration number is CRD42022307522.

Type 2 diabetes mellitus (T2DM) is a chronic, metabolic disorder in which concomitant insulin resistance and β-cell impairment lead to hyperglycemia, influenced by genetic and environmental factors. T2DM is associated with long-term complications that have contributed to the burden of morbidity and mortality worldwide. The objective of this manuscript is to conduct an Exome-Wide Association Study (EWAS) on T2DM Emirati individuals to improve our understanding on diabetes-related complications to improve early diagnostic methods and treatment strategies.

This cross-sectional study recruited 310 Emirati participants that were stratified according to their medically diagnosed diabetes-related complications: diabetic retinopathy, diabetic neuropathy, diabetic nephropathy, and cardiovascular complications. The Illumina's Infinium Exome-24 array was used and 39,840 SNPs remained for analysis after quality control.

The analysis revealed the associations of various genes with each complication category: 1) diabetic retinopathy was associated to SHANK3 gene in locus 22q13.33 (SNP rs9616915; p=5.18 x10-4), ZSCAN5A gene in locus 19q13.43 (SNP rs7252603; p=7.55 x10-4), and DCP1B gene in locus 12p13.33 (SNPs rs715146, rs1044950, rs113147414, rs34730825; p=7.62 x10-4); 2) diabetic neuropathy was associated to ADH4 gene in locus 4q23 (SNP rs4148883; p=1.23 x10-4), SLC11A1 gene in locus 2q35 (SNP rs17235409; p=1.85 x10-4), and MATN4 gene in locus 20q13.12 (SNP rs2072788; p=2.68 x10-4); 3) diabetic nephropathy was associated to PPP1R3A gene in locus 7q31.1 (SNP rs1799999; p=1.91 x10-4), ZNF136 gene in locus 19p13.2 (SNP rs140861589; p=2.80 x10-4), and HSPA12B gene in locus 20p13 (SNP rs6076550; p=2.86 x10-4); and 4) cardiovascular complications was associated to PCNT gene in locus 21q22.3 (SNPs rs7279204, rs6518289, rs2839227, rs2839223; p=2.18 x10-4,3.04 x10-4,4.51 x10-4,5.22 x10-4 respectively), SEPT14 gene in locus 7p11.2 (SNP rs146350220; p=2.77 x10-4), and WDR73 gene in locus 15q25.2 (SNP rs72750868; p=4.47 x10-4).

We have identified susceptibility loci associated with each category of T2DM-related complications in the Emirati population. Given that only 16% of the markers from the Illumina's Infinium Exome chip passed quality control assessment, this demonstrates that multiple variants were, either, monomorphic in the Arab population or were not genotyped due to the use of a Euro-centric EWAS array that limits the possibility of including targeted ethnic-specific SNPs. Our results suggest the alarming possibility that lack of representation in reference panels could inhibit discovery of functionally important loci associated to T2DM complications. Further effort must be conducted to improve the representation of diverse populations in genotyping and sequencing studies.

Background and Objectives: Cytokines are cell-signaling proteins whose identification may serve as inflammatory markers or early indicators for progressive disease. The aim of our study was to quantify several cytokines in aqueous humor (AH) and their correlations with biochemical parameters in diabetic eyes with non-proliferative diabetic retinopathy (NPDR). Materials and Methods: A total of 62 eyes from 62 patients were included in the study: 37 eyes from nondiabetic patients (group 1), 13 diabetic eyes with no retinopathy changes (group 2) and 12 diabetic eyes with early and moderate NPDR (group 3). AH samples were collected during uneventful cataract surgery. The cytokines IL-1β, IL-6, IL-8, IL-10, IL-12, IP-10, MCP-1, TNF-α and VEGF were quantified using multiplex bead-based immunoassay. Due to unreliable results, IL-1β, TNF-α, IL-10 and IL-12 were excluded. Concentrations were compared between groups. Biochemical parameters (fasting blood sugar, glycated hemoglobin, C-reactive protein) and the duration of diabetes were recorded. Results: VEGF levels were significantly different between groups (p = 0.001), while levels of IL-6, IL-8, IP-10 and MCP-1 were comparable across all groups (p > 0.05). IL-6 concentration correlated with VEGF in group 1 (rho = 0.651, p = 0.003) and group 3 (rho = 0.857, p = 0.007); no correlation could be proved between IL-6, IL-8, IP-10, MCP-1 or VEGF and biochemical parameters. Duration of diabetes was not correlated with the cytokine levels in groups 2 and 3. The receiver operating characteristic (ROC) curve revealed that VEGF concentrations could discriminate early and moderate NPDR from diabetes, with an area under the curve (AUC) of 0.897 (p = 0.001, 95% CI = 0.74−1.0). Conclusions: Diabetes mellitus induces significant intraocular changes in the VEGF expression in diabetic patients vs. normal subjects, even before proliferative complications appear. VEGF was increasingly expressed once the diabetes progressed from no retinopathy to early or moderate retinopathy.