BACKGROUND: The triglyceride-glucose (TyG) index is associated with the development and prognosis of coronary artery disease (CAD). However, the impact of the TyG index on CAD severity across different glucose metabolism states exhibits significant disparities in previous research.
METHODS: This cross-sectional study comprised 10,433 participants from a prospective cohort. Participants were categorized into four groups based on glucose metabolism state: normal glucose regulation (NGR), prediabetes (pre-DM), diabetes mellitus (DM) without insulin prescribed (Rx), and DM with insulin Rx. The TyG index was determined by the following formula: Ln [TG (mg/dL) × FPG (mg/dL) / 2], where TG is triglycerides and FPG is fasting plasm glucose. Statistical methods such as binary logistic regression, interaction analysis, restricted cubic spline (RCS), and receiver operating characteristic (ROC) were employed to analyze the relationship between the TyG index and CAD severity across the entire population and glucose metabolism subgroups. Mediation analysis was conducted to examine the mediating effects of glycated hemoglobin (HbA1c) on these relationships. Sensitivity analysis was performed to ensure the robustness of the findings.
RESULTS: Multivariable logistic regression analysis revealed a significant positive association between the TyG index and multi-vessel CAD in the entire population (OR: 1.34; 95% CI: 1.22-1.47 per 1-unit increment). Subgroup analysis demonstrated consistent positive associations in the NGR, pre-DM, and DM non-insulin Rx groups, with the highest OR observed in the NGR group (OR: 1.67; 95% CI: 1.3-2.14 per 1-unit increment). No correlation was found in the DM with insulin Rx subgroup. RCS analyses indicated the distinct dose-response relationships across different glucose metabolism subgroups. Including the TyG index in the established model slightly improved the predictive accuracy, particularly in the NGR group. Mediation analyses showed varying mediating effects of HbA1c among different glucose metabolism subgroups. Sensitivity analysis confirmed the robustness of the aforementioned relationships in the new-onset CAD population and in individuals not using antilipidemic medications.
CONCLUSIONS: The TyG index positively associated with CAD severity across all glucose metabolism states, except for individuals receiving insulin treatment. Moreover, it might serve as a supplementary noninvasive predictor of CAD severity in addition to established factors, especially in NGR patients.

Alzheimer\'s disease (AD) and Diabetes mellitus (DM) exhibit comparable pathophysiological pathways. Genetic abnormalities in APP, PS-1, and PS-2 are linked to AD, with diagnostic aid from CSF and blood biomarkers. Insulin dysfunction, termed \"type 3 diabetes mellitus\" in AD, involves altered insulin signalling and neuronal shrinkage. Insulin influences beta-amyloid metabolism, exacerbating neurotoxicity in AD and amyloid production in DM. Both disorders display impaired glucose transporter expression, hastening cognitive decline. Mitochondrial dysfunction and Toll-like receptor 4-mediated inflammation worsen neurodegeneration in both diseases. ApoE4 raises disease risk, especially when coupled with dyslipidemia common in DM. Targeting shared pathways like insulin-degrading enzyme activation and HSP60 holds promise for therapeutic intervention. Recognizing these interconnected mechanisms underscores the imperative for developing tailored treatments addressing the overlapping pathophysiology of AD and DM, offering potential avenues for more effective management of both conditions.

The prediction of possible lead compounds from already-known drugs that may present DPP-4 inhibition activity imply a advantage in the drug development in terms of time and cost to find alternative medicines for the treatment of Type 2 Diabetes Mellitus (T2DM). The inhibition of dipeptidyl peptidase-4 (DPP-4) has been one of the most explored strategies to develop potential drugs against this condition. A diverse dataset of molecules with known experimental inhibitory activity against DPP-4 was constructed and used to develop predictive models using different machine-learning algorithms. Model M36 is the most promising one based on the internal and external performance showing values of Q2CV = 0.813, and Q2EXT = 0.803. The applicability domain evaluation and Tropsha\'s analysis were conducted to validate M36, indicating its robustness and accuracy in predicting pIC50 values for organic molecules within the established domain. The physicochemical properties of the ligands, including electronegativity, polarizability, and van der Waals volume were relevant to predict the inhibition process. The model was then employed in the virtual screening of potential DPP4 inhibitors, finding 448 compounds from the DrugBank and 9 from DiaNat with potential inhibitory activity. Molecular docking and molecular dynamics simulations were used to get insight into the ligand-protein interaction. From the screening and the favorable molecular dynamic results, several compounds including Skimmin (pIC50 = 3.54, Binding energy = -8.86 kcal/mol), bergenin (pIC50 = 2.69, Binding energy = -13.90 kcal/mol), and DB07272 (pIC50 = 3.97, Binding energy = -25.28 kcal/mol) seem to be promising hits to be tested and optimized in the treatment of T2DM. This results imply a important reduction in cost and time on the application of this drugs because all the information about the its metabolism is already available.

BACKGROUND: Onychomycosis is a fungal infection of the nail unit and one of the common nail diseases that occurs commonly in diabetic patients. It poses a threat of diabetic foot complications to diabetics and negatively affects the quality of life of the patients.
OBJECTIVE: The overall aim of the study was to determine the prevalence and clinical features of onychomycosis in diabetics, as well as the spectrum of causative fungi in Nigeria as compared with age and sex-matched controls.
METHODS: This was a hospital-based, comparative cross-sectional study. One hundred and fifty consecutive adult diabetics and 150 healthy controls (accompanied persons and staff) matched for age and sex were recruited from the Diabetic Clinics and the Dermatology Clinic of the University of Nigeria Teaching Hospital, Ituku-Ozalla. The participants were interviewed using a pre-tested structured questionnaire, nail scrapings were collected for fungal studies, and clippings for nail histopathology using Periodic Acid Schiff.
RESULTS: The prevalence of onychomycosis among DM subjects was 45.3% vs. 35.3% in controls, which was not statistically significant (P value 0.078). Distal-lateral subungual onychomycosis was the most common clinical type in both study groups and presented mainly with nail discolouration, onycholysis, and subungual hyperkeratosis. The most common fungi isolated were dermatophytes (Trichophyton soudanense), non-dermatophytes (Aspergillus spp.), and Candida species (Candida albicans).
CONCLUSIONS: Onychomycosis in diabetics is a very common nail disorder in the South-Eastern part of Nigeria with a high prevalence. The presence of foot ulcers was associated with onychomycosis in diabetics, and they were more likely to have non-dermatophytic onychomycosis.
BACKGROUND: L\'onychomycose est une infection fongique de l\'unité de l\'ongle et l\'une des maladies des ongles les plus courantes chez les patients diabétiques. Elle pose une menace de complications du pied diabétique et affecte négativement la qualité de vie des patients.
OBJECTIVE: L\'objectif général de l\'étude était de déterminer la prévalence et les caractéristiques cliniques de l\'onychomycose chez les diabétiques, ainsi que le spectre des champignons causaux au Nigeria par rapport à un groupe témoin apparié selon l\'âge et le sexe.
UNASSIGNED: Il s\'agissait d\'une étude transversale comparative réalisée en milieu hospitalier. Cent cinquante diabétiques adultes consécutifs et 150 témoins sains (personnes accompagnatrices et personnel) appariés selon l\'âge et le sexe ont été recrutés dans les cliniques de diabète et la clinique de dermatologie de l\'Hôpital Universitaire du Nigeria à Ituku-Ozalla. Les participants ont été interrogés à l\'aide d\'un questionnaire structuré pré-testé, des échantillons de grattage d\'ongles ont été prélevés pour des études fongiques, et des échantillons pour l\'histopathologie des ongles utilisant l\'acide périodique de Schiff.
UNASSIGNED: La prévalence de l\'onychomycose chez les sujets atteints de diabète était de 45,3 % contre 35,3 % chez les témoins, ce qui n\'était pas statistiquement significatif (valeur de p 0,078). L\'onychomycose sousunguéale distale-latérale était le type clinique le plus courant dans les deux groupes d\'étude et se manifestait principalement par une décoloration des ongles, une onycholyse et une hyperkératose sousunguéale. Les champignons les plus couramment isolés étaient les dermatophytes (Trichophyton soudanense), les non-dermatophytes (Aspergillus spp.) et les espèces de Candida (Candida albicans).
CONCLUSIONS: L\'onychomycose chez les diabétiques est un trouble des ongles très courant dans le sud-est du Nigeria avec une prévalence élevée. La présence d\'ulcères du pied était associée à l\'onychomycose chez les diabétiques, et ils étaient plus susceptibles de présenter une onychomycose non-dermatophytique.
UNASSIGNED: Onychomycose, Diabète sucré, Prévalence, Champignons, Nigeria.

OBJECTIVE: To evaluate glycemic variability (GV) using continuous glucose monitoring (CGM) in individuals with and without type 2 diabetes mellitus (T2DM) undergoing Roux-en-Y gastric bypass (RYGB).
METHODS: This prospective cohort study compared the CGM data of fourteen patients with T2DM (n = 7) and without T2DM (n = 7) undergoing RYGB. After 6 months, these patients were compared to a non-operative control group (n = 7) matched by BMI, sex, and age to the T2DM group.
RESULTS: Fourteen patients underwent RYGB, with a mean BMI of 46.9 ± 5.3 kg/m2 and an average age of 47.9 ± 8.9 years; 85% were female. After 6 months post-surgery, the total weight loss (TWL) was 27.1 ± 6.3%, with no significant differences between the groups. Patients without diabetes had lower mean interstitial glucose levels (81 vs. 94 and 98 mg/dl, p < 0.01) and lower glucose management indicator (GMI) (5.2 vs. 5.6 and 5.65%, p = 0.01) compared to the control and T2DM groups, respectively. The coefficient of variation (CV) significantly increased only in patients with diabetes (17% vs. 26.7%, p < 0.01). Both groups with (0% vs. 2%, p = 0.03) and without (3% vs. 22%, p = 0.03) T2DM experienced an increased time below range with low glucose (54-69 mg/dL). However, patients without T2DM had significantly less time in rage (70-180 mg/dL) (97% vs. 78%, p = 0.04).
CONCLUSIONS: Significant differences in CGM metrics among RYGB patients suggest an increase in glycemic variability after surgery, with a longer duration of hypoglycemia, especially in patients without T2DM.

OBJECTIVE: This study examines potential intended (attitudes, motivation and self-efficacy) and unintended (stigmatisation of diabetes) consequences of past Australian National Diabetes Week campaign videos. Further, outcomes are compared by the extent to which participants perceived their allocated video as stigmatising diabetes.
METHODS: In this cross-sectional, ten-arm study, participants (adults with or without diabetes; 1:2 ratio) were randomly allocated to view one of eight archival diabetes campaign videos (intervention), or either an active or passive control group. Post-exposure, study-specific scales measured diabetes Misconceptions and Seriousness, General and Diabetes Risk-Reduction Motivation and Self-efficacy, and perceptions of video Stigmatisation of diabetes. Scores were compared by condition (intervention vs. control) and by campaign Stigma (highest vs. lowest tertile score), separately by cohort (with or without diabetes).
RESULTS: The sample included n = 1023 without diabetes; and n = 510 with diabetes (79% type 2 diabetes). No significant differences in outcomes were observed between conditions (intervention vs. control), with one exception: a modest effect on General Self-efficacy among those without diabetes only. Those perceiving high campaign Stigma (15%), relative to low Stigma (60%), reported significantly greater diabetes Misconceptions, lower perceived Seriousness and (among those without diabetes only) lower General Motivation but higher Diabetes Risk Reduction Motivation.
CONCLUSIONS: Though limited to a single-exposure, we found little meaningful positive influence of past diabetes campaign videos on diabetes attitudes, behavioural intentions or self-efficacy. Further, campaign videos were perceived as stigmatising by a minority-a potential harmful impact. This novel study has implications for the design, implementation and evaluation of future diabetes campaigns.

暂无摘要。

Glaucoma remains the primary cause of long-term blindness. While diabetes mellitus (DM) and hypertension (HTN) are known to influence glaucoma, other factors such as age and sex may be involved. In this retrospective study, we aimed to investigate the associations between age, sex, DM, HTN, and glaucoma risk. We employed optical coherence tomography (OCT) conducted using a 200 × 200-pixel optic cube (Cirrus HD OCT 6000, version 10.0; Carl Zeiss Meditec, Dublin, CA, USA). Effects obscured by low-test signals were disregarded. Data were amassed from 1337 patients. Among them, 218 and 402 patients had DM and HTN, respectively, with 133 (10%) exhibiting both. A sex-based comparison revealed slightly greater retinal nerve fiber layer (RNFL) and ganglion cell-inner plexiform layer (GCIPL) thickness in females. Patients without DM and HTN were predominantly in their 50 s and 60 s, whereas DM and HTN were most prevalent in those in their 60 s and 70 s. Both RNFL and GCIPL thicknesses decreased with advancing age in most patients. The study revealed that older individuals were more prone to glaucoma than younger individuals, with a higher incidence among patients with DM and HTN and reduced RNFL and GCIPL thicknesses. Furthermore, early detection before advancing age could furnish valuable preventive insights.

The glucose level in the blood is measured through invasive methods, causing discomfort in the patient, loss of sensitivity in the area where the sample is obtained, and healing problems. This article deals with the design, implementation, and evaluation of a device with an ESP-WROOM-32D microcontroller with the application of near-infrared photospectroscopy technology that uses a diode array that transmits between 830 nm and 940 nm to measure glucose levels in the blood. In addition, the system provides a webpage for the monitoring and control of diabetes mellitus for each patient; the webpage is hosted on a local Linux server with a MySQL database. The tests are conducted on 120 people with an age range of 35 to 85 years; each person undergoes two sample collections with the traditional method and two with the non-invasive method. The developed device complies with the ranges established by the American Diabetes Association: presenting a measurement error margin of close to 3% in relation to traditional blood glucose measurement devices. The purpose of the study is to design and evaluate a device that uses non-invasive technology to measure blood glucose levels. This involves constructing a non-invasive glucometer prototype that is then evaluated in a group of participants with diabetes.

Diabetes has emerged as a worldwide health crisis, affecting approximately 537 million adults. Maintaining blood glucose requires careful observation of diet, physical activity, and adherence to medications if necessary. Diet monitoring historically involves keeping food diaries; however, this process can be labor-intensive, and recollection of food items may introduce errors. Automated technologies such as food image recognition systems (FIRS) can make use of computer vision and mobile cameras to reduce the burden of keeping diaries and improve diet tracking. These tools provide various levels of diet analysis, and some offer further suggestions for improving the nutritional quality of meals. The current study is a systematic review of mobile computer vision-based approaches for food classification, volume estimation, and nutrient estimation. Relevant articles published over the last two decades are evaluated, and both future directions and issues related to FIRS are explored.