A New Method to Assess Asymmetry in Fingerprints Could Be Used as an Early Indicator of Type 2 Diabetes Mellitus

Body composition as an indicator of metabolic changes in mice obtained by in vitro fertilization

To identify body systems subject to epigenetic transformation during in vitro fertilization (IVF), comparative morphological and functional studies were performed on sexually mature offspring of outbred CD1 mice, specific-pathogen-free (SPF), obtained by IVF (experiment) and natural conception (control). The studies included assessment of age-related changes in body weight and composition, energy intake and expenditure, and glucose homeostasis. To level the effects caused by the different number of newborns in the control and in the experiment, the size of the fed litters was halved in the control females. Males obtained using the IVF procedure were superior in body weight compared to control males in all age groups. As was shown by analysis of variance with experiment/control factors, gender, age (7, 10 and 20 weeks), the IVF procedure had a statistically significant and unidirectional effect on body composition. At the same time, IVF offspring outperformed control individuals in relative fat content, but were behind in terms of lean mass. The effect of the interaction of factors was not statistically significant. IVF offspring of both sexes had higher fat to lean mass ratios (FLR). Since adipose tissue contributes significantly less to total energy intake compared to muscle, the main component of lean mass, it is not surprising that at the same level of IVF locomotor activity offspring consumed less food than controls. When converted to one gram of body weight, this difference reached 19 %. One of the consequences of reduced utilization of IVF energy substrates by offspring is a decrease in their tolerance to glucose loading. The integral criterion for the effectiveness of restoring the initial glucose level is the area under the curve (AUC), the value of which was 2.5 (males) and 3.2 (females) times higher in IVF offspring compared to the corresponding control. Thus, the totality of our original and literature data shows an increase in the risk of metabolic disorders in IVF offspring, which is confirmed by epidemiological studies of a relatively young cohort of people born using assisted reproductive technologies.

A new predictor for prediabetes: Chemerin

Objective: It was aimed to investigate irisin and chemerin levels in prediabetic individuals and their value in predicting prediabetes. Method: Thirty-eight prediabetic patients aged 18-65 years (22 impaired fasting glucose (IFG), 10 impaired glucose tolerance (IGT), 6 patients with coexisting IFG and IGT) and thirty-five healthy volunteers were included in which was designed as a cross-sectional study. The basic demographic characteristics of all participants in the case and control groups were compared with the serum chemerin, irisin, creatinine, aspartate aminotransferase (AST), alanine aminotransferase (ALT), high-density lipoprotein (HDL-cholesterol), low-density lipoprotein (LDL-cholesterol), triglyceride (TG), free thyroxine (sT4), and thyroid-stimulating hormone (TSH) levels. Result: Serum chemerin level was found to be higher in the prediabetic group (p=0.03), while no significant difference was found for the irisin level between the two groups. In the multivariate logistic regression analysis, we showed that chemerin was an independent risk factor in predicting prediabetes. There was a positive correlation (p=0.01, r=0.279) between all participants' body mass index (BMI) and chemerin level and a negative correlation between irisin level and high-density lipoprotein cholesterol (HDL-C) level, and Homeostatic Model Assessment for Insulin Resistance (HOMA-IR) (p=0.04 r=-0.295, p=0.01 r=-0.407, respectively). Conclusion: Chemerin is a new generation chemokine that predicts prediabetes. Studies aimed at irisin and chemerin may provide important role to prevent the prediabetes to Type 2 diabetes progression.

Kombucha Reduces Hyperglycemia in Type 2 Diabetes of Mice by Regulating Gut Microbiota and Its Metabolites

Kombucha, which is rich in tea polyphenols and organic acid, is a kind of acidic tea soup beverage fermented by acetic acid bacteria, yeasts, lactic acid bacteria. Kombucha has been reported to possess anti-diabetic activity, but the underlying mechanism was not well understood. In this study, a high-fat, high-sugar diet combined with streptozotocin (STZ) injection was used to induce T2DM model in mice. After four weeks of kombucha intervention, the physiological and biochemical index were measured to determine the diabetes-related indicators. High-throughput sequencing technology was used to analyze the changes in gut microbiota from the feces. The results showed that four weeks of kombucha intervention increased the abundance of SCFAs-producing bacteria and reduced the abundance of gram-negative bacteria and pathogenic bacteria. The improvement in gut microbiota reduced the damage of intestinal barrier, thereby reducing the displacement of lipopolysaccharide (LPS) and inhibiting the occurrence of inflammation and insulin resistance in vivo. In addition, the increased levels of SCFAs-producing bacteria, and thus increasing the SCFAs, improved islet β cell function by promoting the secretion of gastrointestinal hormones (GLP-1/PYY). This study methodically uncovered the hypoglycemic mechanism of kombucha through gut microbiota intervention, and the result suggested that kombucha may be introduced as a new functional drink for T2DM prevention and treatment.

Cerebral arterial architectonics and CFD simulation in mice with type 1 diabetes mellitus of different duration

Type 1 diabetes is a chronic autoimmune disease that affects tens of millions of people. Diabetes mellitus is one of the strongest factors in the development of cerebrovascular diseases. In this study we used NOD.CB17 Prkdcscid mice and the pharmacological model of type 1 diabetes mellitus of different duration to study changes in the cerebral vasculature. We used two combined approaches using magnetic resonance angiography both steady and transient CFD blood flow modeling. We identified the influence of type 1 diabetes on the architectonics and hemodynamics of the large blood vessels of the brain as the disease progresses. For the first time, we detected a statistically significant change in angioarchitectonics (the angles between the vessels of the circle of Willis, cross-sections areas of vessels) and hemodynamic (maximum blood flow rate, hydraulic resistance) in animals with diabetes duration of 2 months, that is manifested by the development of asymmetry of cerebral blood flow. The result shows the negative effect of diabetes on cerebral circulation as well as the practicability of CFD modeling. This may be of extensive interest, in pharmacological and preclinical studies.

An association between fingerprint patterns with blood group and lifestyle based diseases: a review

In the current era of the digital world, the hash of any digital means considered as a footprint or fingerprint of any digital term but from the ancient era, human fingerprint considered as the most trustworthy criteria for identification and it also cannot be changed with time even up to the death of an individual. In the court of law, fingerprint-proof is undeniably the most dependable and acceptable evidence to date. Fingerprint designs are exclusive in each human and the chance of two individuals having identical fingerprints is an exceptional case about one in sixty-four thousand million also the fingerprint minutiae patterns of the undistinguishable twins are different, and the ridge pattern of each fingertip remain unchanged from birth to till death. Fingerprints can be divided into basic four categories i.e. Loop, whorl, arch, and composites, nevertheless, there are more than 100 interleaved ridge and valleys physiognomies, called Galton’s details, in a single rolled fingerprint. Due to the immense potential of fingerprints as an effective method of identification, the present research paper tries to investigate the problem of blood group identification and analysis of diseases those arises with aging like hypertension, type 2-diabetes and arthritis from a fingerprint by analyzing their patterns correlation with blood group and age of an individual. The work has been driven by studies of anthropometry, biometric trademark, and pattern recognition proposing that it is possible to predict blood group using fingerprint map reading. Dermatoglyphics as a diagnostic aid used from ancient eras and now it is well established in number of diseases which have strong hereditary basis and is employed as a method for screening for abnormal anomalies. Apart from its use in predicting the diagnosis of disease; dermatoglyphics is also used in forensic medicine in individual identification, physical anthropology, human genetics and medicine. However, the Machine and Deep Learning techniques, if used for fingerprint minutiae patterns to be trained by Neural Network for blood group prediction and classification of common clinical diseases arises with aging based on lifestyle would be an unusual research work.