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A medical disorder known as diabetic retinopathy (DR) affects people who suffer from diabetes. Many people are visually impaired due to DR. Primary cause of DR in patients is high blood sugar, and it affects blood vessels available in the retinal cell. The recent advancement in deep learning and computer vision methods, and their automation applications can recognize the presence of DR in retinal cells and vessel images. Authors have proposed an attention-based hybrid model to recognize diabetes in early stage to prevent harmful clauses. Proposed methodology uses DenseNetl21 architecture for convolution learning and then, the feature vector will be enhanced with channel and spatial attention model. The proposed architecture also simulates binary and multiclass classification to recognize the infection and the spreading of disease. Binary classification recognizes DR images either positive or negative, while multiclass classification represents an infection on a scale of 0-4. Simulation of the proposed methodology has achieved 98.57% and 99.01% accuracy for multiclass and binary classification, respectively. Simulation of the study also explored the impact of data augmentation to make the proposed model robust and generalized. Attention-based deep learning model has achieved remarkable accuracy to detect diabetic infection from retinal cellular images. Key words: deep learning, computer vision, diabetic retinopathy, disease detection, cellular images attention model, Introduction Early illness detection improves the effectiveness of therapy in the healthcare sector. Disease detection from cellular must need to prevent infection. Diabetes is an illness that increases when insufficient [...]

: Objective: To identify the optimal AUSDRISK threshold score to screen for pre?diabetes and diabetes. Methods: A total of 406 adult patients not diagnosed with diabetes were screened in General Practices (GP) between May and October 2019. All patients received a point of care (POC) HbA1c test. HbA1c test results were categorised into diabetes (?6.5% or ?48 mmol/mol), pre?diabetes (5.7?6.4% or 39?47 mmol/mol), or normal ( Results: Of these patients, 9 (2%) had undiagnosed diabetes and 60 (15%) had pre?diabetes. A Receiver Operator Characteristic (ROC) curve was constructed to predict the presence of pre?diabetes and diabetes; the area under the ROC curve was 0.72 (95%CI 0.65?0.78) indicating modest predictive ability. The optimal threshold cut point for AUSDRISK score was 17 (sensitivity 76%, specificity 61%, + likelihood ratio (LR) 1.96, ? likelihood ratio of 0.39) while the accepted cut point of 12 performed less well (sensitivity 94%, specificity 23%, +LR=1.22 ?LR+0.26). Conclusions: The AUSDRISK tool has the potential to be used as a screening tool for pre?diabetes/diabetes in GP practices. A cut point of ?17 would potentially identify 75% of all people at risk and three in 10 sent for further testing would be positive for prediabetes or diabetes. Implications for public health: Routine case?finding in high?risk patients will enable GPs to intervene early and prevent further public health burden from the sequelae of diabetes., Pre?diabetes is a condition where a person's fasting glucose is elevated but has not reached the diabetes threshold and it is a significant risk factor for the development of type [...]

The global burden of diabetes is rapidly increasing, from 451 million people in 2019 to 693 million by 2045.sup.1. The insidious onset of type 2 diabetes delays diagnosis and increases morbidity.sup.2. Given the multifactorial vascular effects of diabetes, we hypothesized that smartphone-based photoplethysmography could provide a widely accessible digital biomarker for diabetes. Here we developed a deep neural network (DNN) to detect prevalent diabetes using smartphone-based photoplethysmography from an initial cohort of 53,870 individuals (the 'primary cohort'), which we then validated in a separate cohort of 7,806 individuals (the 'contemporary cohort') and a cohort of 181 prospectively enrolled individuals from three clinics (the 'clinic cohort'). The DNN achieved an area under the curve for prevalent diabetes of 0.766 in the primary cohort (95% confidence interval: 0.750-0.782; sensitivity 75%, specificity 65%) and 0.740 in the contemporary cohort (95% confidence interval: 0.723-0.758; sensitivity 81%, specificity 54%). When the output of the DNN, called the DNN score, was included in a regression analysis alongside age, gender, race/ethnicity and body mass index, the area under the curve was 0.830 and the DNN score remained independently predictive of diabetes. The performance of the DNN in the clinic cohort was similar to that in other validation datasets. There was a significant and positive association between the continuous DNN score and hemoglobin A1c (P [less than or equal to] 0.001) among those with hemoglobin A1c data. These findings demonstrate that smartphone-based photoplethysmography provides a readily attainable, non-invasive digital biomarker of prevalent diabetes. A deep neural network applied to smartphone-based vascular imaging can detect diabetes, opening new possibilities for non-invasive diagnosis., Author(s): Robert Avram [sup.1] , Jeffrey E. Olgin [sup.1] , Peter Kuhar [sup.2] , J. Weston Hughes [sup.3] , Gregory M. Marcus [sup.1] , Mark J. Pletcher [sup.4] , Kirstin [...]

Author(s): X Ma [sup.1] [sup.2] , Y-L Zhang [sup.3] , Q Ji [sup.4] , Y Xing [sup.4] , H Pan [sup.5] , S Chen [sup.5] , J-L Tang [sup.3] , [...]

Background Colorectal cancer (CRC) incidence is increasing among young adults below screening age, despite the effectiveness of screening in older populations. Individuals with diabetes mellitus are at increased risk of early-onset CRC. We aimed to determine how many years earlier than the general population patients with diabetes with/without family history of CRC reach the threshold risk at which CRC screening is recommended to the general population. Methods and findings A nationwide cohort study (follow-up:1964-2015) involving all Swedish residents born after 1931 and their parents was carried out using record linkage of Swedish Population Register, Cancer Registry, National Patient Register, and Multi-Generation Register. Of 12,614,256 individuals who were followed between 1964 and 2015 (51% men; age range at baseline 0-107 years), 162,226 developed CRC, and 559,375 developed diabetes. Age-specific 10-year cumulative risk curves were used to draw conclusions about how many years earlier patients with diabetes reach the 10-year cumulative risks of CRC in 50-year-old men and women (most common age of first screening), which were 0.44% and 0.41%, respectively. Diabetic patients attained the screening level of CRC risk earlier than the general Swedish population. Men with diabetes reached 0.44% risk at age 45 (5 years earlier than the recommended age of screening). In women with diabetes, the risk advancement was 4 years. Risk was more pronounced for those with additional family history of CRC (12-21 years earlier depending on sex and benchmark starting age of screening). The study limitations include lack of detailed information on diabetes type, lifestyle factors, and colonoscopy data. Conclusions Using high-quality registers, this study is, to our knowledge, the first one that provides novel evidence-based information for risk-adapted starting ages of CRC screening for patients with diabetes, who are at higher risk of early-onset CRC than the general population., Author(s): Uzair Ali Khan 1,2, Mahdi Fallah 1,3,*, Kristina Sundquist 3,4,5, Jan Sundquist 3,4,5, Hermann Brenner 1,6,7, Elham Kharazmi 1,3,8 Introduction Colorectal cancer (CRC) has become the third most common [...]

OBJECTIVES: Few have compared socio-economic disparities in screening tests for cancer with recommended tests for other chronic diseases. We examined whether receipt of testing for colorectal, cervical and breast cancer, as well as diabetes and high cholesterol, differs by neighbourhood-level socio-economic and recent immigrant status. METHODS: We conducted a population-based retrospective cohort study of patients identified as screen-eligible in 2009 living in Ontario, Canada. Postal codes were used to assign residents to a dissemination area (DA). Using Canadian census data, DAs were stratified by income quintile and proportion of recent immigrants. Prevalence of screening for cancer (colorectal, cervical, breast), diabetes, and high cholesterol, using administrative data, and prevalence ratios (least/most advantaged) were calculated. RESULTS: The cohort comprised 7,652,592 people. Receipt of screening for colorectal cancer (women 61.6%; men 55.1%) and breast cancer (59.9%) were the lowest and diabetes (women 72.9%; men 61.4%) and high cholesterol (women 82.4%; men 70.3%) were the highest. We found disparities in the receipt of all tests, with the lowest uptake and largest disparities for cancer screening among those living in both low-income and high-immigration DAs: colorectal--women 48.6%; RR 0.77; 95% CI (0.74-0.79) and men 40.6%; RR 0.71 (0.68-0.74); cervical--52.0%; RR 0.80 (0.78-0.81) and breast 45.7%; RR 0.74 (0.72-0.77). CONCLUSION: People living in low-income and high-immigration DAs had the lowest screening participation for all tests, although disparities were highest for cancer. An organized integrated chronic disease screening strategy leveraging the higher diabetes and high cholesterol screening participation may increase screening for cancer and other chronic diseases in never- and underscreened populations. KEY WORDS: Health care disparities; early detection of cancer; dyslipidemia; diabetes OBJECTIFS : Peu d'etudes comparent les disparites socioeconomiques dans le recours aux tests de depistage du cancer et aux tests recommandes pour depister d'autres maladies chroniques. Nous avons cherche a determiner si le recours aux tests de depistage du cancer colorectal, du col uterin et du sein, ainsi que du diabete et de l'hypercholesterolemie, differe selon le niveau socioeconomique du quartier et le statut d'immigrant recent. METHODE : Nous avons mene une etude de cohortes populationnelle retrospective aupres de patients vivant en Ontario (Canada) identifies comme etant admissibles au depistage en 2009. Les codes postaux ont servi a affecter chaque resident a une aire de diffusion (AD). A l'aide des donnees du Recensement du Canada, les AD ont ete stratifiees selon le quintile de revenu et la proportion d'immigrants recents. Nous avons calcule la prevalence du depistage du cancer (colorectal, du col uterin, du sein), du diabete et de l'hypercholesterolemie a l'aide de donnees administratives, ainsi que les ratios de prevalence (moins/mieux nantis). RESULTATS : La cohorte comptait 7 652 592 personnes. La participation au depistage du cancer colorectal (femmes 61,6%; hommes 55,1%) et du cancer du sein (59,9%) etait la plus faible, et la participation au depistage du diabete (femmes 72,9%; hommes 61,4%) et de l'hypercholesterolemie (femmes 82,4%; hommes 70,3%) etait la plus elevee. Nous avons constate des disparites dans le recours a tous les tests, la participation la plus faible et les plus grandes disparites dans le depistage du cancer etant observes chez les residents des AD a faible revenu et a forte immigration : cancer colorectal--femmes 48,6%; RT 0,77; IC de 95% (0,74-0,79) et hommes 40,6%; RT 0,71 (0,68-0,74); cancer du col uterin--52,0%; RT 0,80 (0,78-0,81) et cancer du sein 45,7 %; RT 0,74 (0,72-0,77). CONCLUSIONS : Les residents des AD a faible revenu et a forte immigration affichaient la plus faible participation au depistage pour l'ensemble des tests, mais avec des disparites plus prononcees pour le depistage du cancer. Une strategie structuree et integree de depistage des maladies chroniques misant sur la participation plus elevee au depistage du diabete et de l'hypercholesterolemie pourrait accroitre le depistage du cancer et d'autres maladies chroniques dans les populations jamais ou insuffisamment depistees. MOTS CLES : disparites d'acces aux soins; depistage precoce du cancer; dyslipidemies; diabete, Screening for cancer (or cancer precursors) and other chronic diseases in asymptomatic people is intended to separate healthy persons from those who may be at sufficient increased risk of a [...]

Fluorescent microbeads hold great promise for in vivo continuous glucose monitoring with wireless transdermal transmission and long-lasting activity. The full potential of fluorescent microbeads has yet to be realized due to insufficient intensity for transdermal transmission and material toxicity. This paper illustrates the highly-sensitive, biostable, long-lasting, and injectable fluorescent microbeads for in vivo continuous glucose monitoring. We synthesized a fluorescent monomer composed of glucose-recognition sites, a fluorogenic site, spacers, and polymerization sites. The spacers are designed to be long and hydrophilic for increasing opportunities to bind glucose molecules; consequently, the fluorescent monomers enable high-intensive responsiveness to glucose. We then fabricated injectable-sized fluorescent polyacrylamide hydrogel beads with high uniformity and high throughput. We found that our fluorescent beads provide sufficient intensity to transdermally monitor glucose concentrations in vivo. The fluorescence intensity successfully traced the blood glucose concentration fluctuation, indicating our method has potential uses in highly-sensitive and minimally invasive continuous blood glucose monitoring. fluorescent hydrogel | microfluidics | diboronic acid | continuous glucose monitoring | diabetes mellitus doi/ 10.1073/pnas.1006911107

Acetone in the human breath is an important marker for noninvasive diagnosis of diabetes. Here, novel chemo-resistive detectors have been developed that allow rapid measurement of ultralow acetone concentrations (down to 20 ppb) with high signal-to-noise ratio in ideal (dry air) and realistic (up to 90% RH) conditions. The detector films consist of (highly sensitive) pure and Si-doped W[O.sub.3] nanoparticles (10-13 nm in diameter) made in the gas phase and directly deposited onto interdigitated electrodes. Their sensing properties (selectivity, limit of detection, response, and recovery times) have been investigated as a function of operating temperature (325-500[degrees]C), relative humidity (RH), and interfering analyte (ethanol or water vapor) concentration. It was found that Si-doping increases and stabilizes the acetone-selective [epsilon]-W[O.sub.3] phase while increasing its thermal stability and, thus, results in superior sensing performance with an optimum at about 10 mol % Si content. Furthermore, increasing the operation temperature decreased the detector response to water vapor, and above 400[degrees]C, it was ([less than or equal to] 0.7) always below the threshold (10.6) for fake diabetes detection in ideal conditions. At this temperature and at 90% RH, healthy humans ([less than or equal to] 900 ppb acetone) and diabetes patients ([greater than or equal to] 1800 ppb) can be clearly distinguished by a remarkable gap (40%) in sensor response. As a result, these solid state detectors may offer a portable and cost-effective alternative to more bulky systems for noninvasive diabetes detection by human breath analysis. 10.1021/ac902695n

A study was conducted to evaluate the efficacy and benefits of glycated hemoglobin as a more appropriate diagnostic test for diabetes as compared to the normally followed fasting glucose. Results indicated that glycated hemoglobin was far better as a predictor of risks of diabetes and cardiovascular diseases.

OBJECTIVE: To investigate the age-specific relationship between body mass index (BMI) and risk of diabetes in a Japanese general population. PARTICIPANTS AND METHODS: A cohort of Japanese men (N=19,926) and [...]

OBJECTIVES: To compare the case-finding ability of current national guidelines for screening diabetes mellitus and characterize factors that affect testing practices in an ambulatory population. PATIENTS AND METHODS: In this [...]

The case of an 81-year old man who is suffering from weight loss and odynophagia is discussed to better understand the causes, symptoms, diagnosis and treatment pf advanced HIV infection. The need and importance of early detection of HIV infection through HIV testing is highlighted.

BACKGROUND: Increasing evidence suggests that high selenium levels are associated with diabetes and other cardiometabolic risk factors. OBJECTIVES: We evaluated the association of serum selenium concentrations with fasting plasma glucose, [...]

Objectives: Raised glycosylated haemoglobin ([HbA.sub.sup.1c]) concentration is a recognized risk factor for diabetes, the incidence of which is rising worldwide. The intake of certain foods has been related to [HbA.sub.1c] concentration. The aim of this study was to investigate whether nutrient intake, sourced by these foods, was predictive of raised glycosylated haemoglobin ([HbA.sub.sup.1c]) concentration in a British cohort. Subjects: The subjects were 495 men and 570 women who were members of the Medical Research Council National Survey of Health and Development, 1946 birth cohort. Diet was assessed from 5-day records in 1982, 1989 and 1999. [HbA.sub.1c] was measured in blood samples collected in 1999. Individuals in whom concentration of [HbA.sub.1c] was [greater than or equal to] 6.3% were identified as being 'at risk' and their nutrient intake was compared with those whose concentration of [HbA.sub.1c] was within the normal range ([less than or equal to] 6.2%). Results: Lower intakes of protein, carbohydrate, non-starch polysaccharide, iron, folate, vitamin [B.sub.12] and a higher percentage energy from fat in 1989 were significantly predictive of high [HbA.sub.1c] status in 1999. In 1999, there were no nutrient intakes that were predictive of [HbA.sub.1c] status. Global tests of whether the intakes of energy, carbohydrate, sodium, iron, riboflavin and vitamin [B.sub.12] at all three time points were related to [HbA.sub.1c] status in 1999, were significant. Conclusion: An increased intake of energy, carbohydrate, sodium, iron, riboflavin and vitamin [B.sub.12] over 10 years was predictive of raised [HbA.sub.1c] status. Increased energy intake may have resulted in increase in body weight, which is a risk factor for diabetes. doi:10.1038/ejcn.2009.43; published online 24 June 2009 Keywords: diet; nutrients; glycosylated haemoglobin; NSHD, Introduction Elevated glycosylated haemoglobin ([HbA.sub.1c]) in the blood is an indicator of chronically raised blood glucose concentrations, which is used as a method of identifying people at risk of developing [...]

The role of monocyte chemoattractant protein-1 (MCP-1) in diabetic nephropathy is typically viewed through the lens of inflammation, but MCP-1 might exert noninflammatory effects on the kidney cells directly. Glomerular podocytes in culture, verified to express the marker nephrin, were exposed to diabetic mediators such as high glucose or angiotensin II and assayed for MCP-1. Only transforming growth factor-[beta] (TGF-[beta]) significantly increased MCP-1 production, which was prevented by SB431542 and LY294002, indicating that signaling proceeded through the TGF-[beta] type I receptor kinase and the phosphatidylinositol 3-kinase pathway. The TGF-[beta]-induced MCP-1 was found to activate the podocyte's cysteine-cysteine chemokine receptor 2 (CCR2) and, as a result, enhance the cellular motility, cause rearrangement of the actin cytoskeleton, and increase podocyte permeability to albumin in a Transwell assay. The preceding effects of TGF-[beta] were replicated by treatment with recombinant MCP-1 and blocked by a neutralizing anti-MCP-1 antibody or a specific CCR2 inhibitor, RS102895. In conclusion, this is the first description that TGF-[beta] signaling through PI3K induces the podocyte expression of MCP-1 that can then operate via CCR2 to increase cellular migration and alter albumin permeability characteristics. The pleiotropic effects of MCP-1 on the resident kidney cells such as the podocyte may exacerbate the disease process of diabetic albuminuria. albuminuria; nephropathy; cytoskeleton; diabetes

Diabetes mellitus (DM) is associated with characteristic structural and functional changes of the myocardium, termed diabetic cardiomyopathy. As a distinct entity independent of coronary atherosclerosis, diabetic cardiomyopathy is an increasingly recognized cause of heart failure. A detailed understanding of diabetic cardiac dysfunction, using relevant animal models, is required for the effective prevention and treatment of cardiovascular complications in diabetic patients. We investigated and compared cardiac performance in rat models of type 1 DM (streptozotocin induced) and type 2 DM (Zucker diabetic fatty rats) using a pressure-volume (P-V) conductance catheter system. Left ventricular (LV) systolic and diastolic function was evaluated in vivo at different preloads, including the slope of the end-systolic P-V relation (ESPVR) and end-diastolic P-V relationship (EDPVR), preload recruitable stroke work (PRSW), maximal slope of the systolic pressure increment (dP/[dt.sub.max]), and its relation to end-diastolic volume (dP/[dt.sub.max]-EDV) as well as the time constant of LV relaxation and maximal slope of the diastolic pressure decrement. Type 1 DM was associated with decreased LV systolic pressure, dP/[dt.sub.max], slope of ESPVR and dP/[dt.sub.max]-EDV, PRSW, ejection fraction, and cardiac and stroke work indexes, indicating marked systolic dysfunction. In type 2 DM rats, systolic indexes were altered only to a lower extent and the increase of LV stiffness was more pronounced, as indicated by the higher slopes of EDPVR. Our data suggest that DM is characterized by decreased systolic performance and delayed relaxation (mainly in type 1 DM), accompanied by increased diastolic stiffness of the heart (more remarkably in type 2 DM). Based on the sophisticated method of P-V analysis, different characteristics of type 1 and type 2 diabetic cardiac dysfunction can be demonstrated. systolic dysfunction; diastolic dysfunction; systolic function; diastolic function