Flood hazard potential evaluation using decision tree state-of-the-art models.

Floods occur frequently in Romania and throughout the world and are one of the most devastating natural disasters that impact people's lives. Therefore, in order to reduce the potential damages, an accurate identification of surfaces susceptible to flood phenomena is mandatory. In this regard, the quantitative calculation of flood susceptibility has become a very popular practice in the scientific research. With the development of modern computerized methods such as geographic information system and machine learning models, and as a result of the possibility of combining them, the determination of areas susceptible to floods has become increasingly accurate, and the algorithms used are increasingly varied. Some of the most used and highly accurate machine learning algorithms are the decision tree models. Therefore, in the present study focusing on flood susceptibility zonation mapping in the Trotus River basin, the following algorithms were applied: forest by penalizing attribute-weights of evidence (forest-PA-WOE), best first decision tree-WOE, alternating decision tree-WOE, and logistic regression-WOE. The best performant, characterized by a maximum accuracy of 0.981, proved to be forest-PA-WOE, whereas in terms of flood exposure, an area of over 16.22% of the Trotus basin is exposed to high and very high floods susceptibility. The performances applied models in the present work are higher than the models applied in the previous studies in the same study area. Moreover, it should be noted that the accuracy of the models is similar with the accuracies of the decision tree models achieved in the studies focused on other areas across the world. Therefore, we can state that the models applied in the present research can be successfully used in by the researchers in other case studies. The findings of this research may substantially map the flood risk areas and further aid watershed managers in limiting and remediating flood damage in the data-scarce regions. Moreover, the results of this study can be a very useful for the hazard management and planning authorities.

Gut Molecules in Cardiometabolic Diseases: The Mechanisms behind the Story.

Atherosclerotic cardiovascular disease is the most common cause of morbidity and mortality worldwide. Diabetes mellitus increases cardiovascular risk. Heart failure and atrial fibrillation are associated comorbidities that share the main cardiovascular risk factors. The use of incretin-based therapies promoted the idea that activation of alternative signaling pathways is effective in reducing the risk of atherosclerosis and heart failure. Gut-derived molecules, gut hormones, and gut microbiota metabolites showed both positive and detrimental effects in cardiometabolic disorders. Although inflammation plays a key role in cardiometabolic disorders, additional intracellular signaling pathways are involved and could explain the observed effects. Revealing the involved molecular mechanisms could provide novel therapeutic strategies and a better understanding of the relationship between the gut, metabolic syndrome, and cardiovascular diseases.

Flood susceptibility evaluation through deep learning optimizer ensembles and GIS techniques.

It is difficult to predict and model with an accurate model the floods, that are one of the most destructive risks across the earth's surface. The main objective of this research is to show the prediction power of three ensemble algorithms with respect to flood susceptibility estimation. These algorithms are: Iterative Classifier Optimizer - Alternating Decision Tree - Frequency Ratio (ICO-ADT-FR), Iterative Classifier Optimizer - Deep Learning Neural Network - Frequency Ratio (ICO-DLNN-FR) and Iterative Classifier Optimizer - Multilayer Perceptron - Frequency Ratio (ICO-MLP-FR). The first stage of the manuscript consisted of the collection and processing of the geodatabase needed in the present study. The geodatabase comprises a number of 14 flood predictors and 132 known flood locations. The Correlation-based Feature Selection (CFS) method was used in order to assess the prediction capacity of the 14 predictors in terms of flood susceptibility estimation. The training and validation of the three ensemble models constitute the next stage of the scientific workflow. Several statistical metrics and ROC curve method were involved in the evaluation of the model's performance and accuracy. According to ROC curves all the models achieved high performances since their AUC had values above 0.89. ICO-DLNN-FR proved to be the most accurate model (AUC = 0.959). The outcomes of the study can be used to guide future flood risk management and sustainable land-use planning in the designated area.

Short-Chain Fatty Acids as Bacterial Enterocytes and Therapeutic Target in Diabetes Mellitus Type 2.

Diabetes mellitus is a disease with multiple gastrointestinal symptoms (diarrhea or constipation, abdominal pain, bloating) whose pathogenesis is multifactorial. The most important of these factors is the enteric nervous system, also known as the "second brain"; a part of the peripheral nervous system capable of functioning independently of the central nervous system. Modulation of the enteric nervous system can be done by short-chain fatty acids, which are bacterial metabolites of the intestinal microbiota. In addition, these acids provide multiple benefits in diabetes, particularly by stimulating glucagon-like peptide 1 and insulin secretion. However, it is not clear what type of nutraceuticals (probiotics, prebiotics, and alimentary supplements) can be used to increase the amount of short-chain fatty acids and achieve the beneficial effects in diabetes. Thus, even if several studies demonstrate that the gut microbiota modulates the activity of the ENS, and thus, may have a positive effect in diabetes, further studies are needed to underline this effect. This review outlines the most recent data regarding the involvement of SCFAs as a disease modifying agent in diabetes mellitus type 2. For an in-depth understanding of the modulation of gut dysbiosis with SCFAs in diabetes, we provide an overview of the interplay between gut microbiota and ENS.

Variability in Sleep Timing and Dietary Intake: A Scoping Review of the Literature.

The objective of this scoping review was to summarize previous studies which examined the effect of day-to-day variability in sleep timing and social jetlag (SJL) on dietary intake. A systematic literature search was conducted in PubMed, Embase, and Clarivate Analytics Web of Science and we identified 22 records. No difference in caloric and macronutrient intake between SJL groups was observed in studies that enrolled healthy young adults. However, studies that enrolled participants with obesity and obesity-related chronic conditions reported a higher caloric intake and a higher intake of carbohydrates, total fat, saturated fats, and cholesterol in participants with SJL than in those without. Most studies reported a lower quality of diet, a delayed mealtime, and eating jetlag in participants with SJL vs. those without SJL. No correlation of day-to-day variability in sleep timing with average caloric intake was observed, but bed-time variability was negatively associated with diet quality. Methodological issues have been identified in sources assessed including study design, power calculation, population enrolled, and tools/metrics used for sleep timing variability assessment. Future well powered longitudinal studies, with clear protocols, standardized metrics, including all age groups from general population are needed to clarify the dietary intake consequences of variability in sleep timing.

The Relationships between Gut Microbiota and Diabetes Mellitus, and Treatments for Diabetes Mellitus.

Diabetes mellitus is considered to be a global epidemic. The combination of genetic susceptibility and an unhealthy lifestyle is considered to be the main trigger of this metabolic disorder. Recently, there has been increased interest in the roles of gut microbiota as a new potential contributor to this epidemic. Research, in recent years, has contributed to an in-depth characterization of the human microbiome and its associations with various diseases, including metabolic diseases and diabetes mellitus. It is known that diet can change the composition of gut microbiota, but it is unclear how this, in turn, may influence metabolism. The main objective of this review is to evaluate the pathogenetic association between microbiota and diabetes and to explore any new therapeutic agents, including nutraceuticals that may modulate the microbiota. We also look at several mechanisms involved in this process. There is a clear, bidirectional relationship between microbiota and diabetes. Current treatments for diabetes influence microbiota in various ways, some beneficial, but others with still unclear effects. Microbiota-aimed treatments have seen no real-world significant effects on the progression of diabetes and its complications, with more studies needed in order to find a really beneficial agent.

Chronic disruption of circadian rhythm with mistimed sleep and appetite - an exploratory research.

This research aimed to explore the relation of social jetlag (SJL) with perceived appetite, and hormones involved in hunger regulation in healthy subjects in free-living conditions (study registration number: ACTRN12618001182280). Eighty normally diurnally active men and women were enrolled in 4 study groups according to the presence of SJL and sleep deprivation (2 groups with SJL with or without sleep deprivations and 2 groups without SJL with or without sleep deprivation) matched 1:1:1:1 for age, gender, and body mass index. Appetite was assessed in fasting state, by measuring acylated ghrelin level and using 100 mm visual analog scales. Persons with SJL had a higher perceived appetite for pork, poultry, fish, eggs, milk, and dairy products and higher acylated ghrelin levels than those without SJL. When considering the presence of sleep deprivation, subjects with SJL, with and without sleep deprivation, reported a higher perceived appetite than group with sleep deprivation alone. They also reported later meal times for lunch and dinner, had more frequently a snack before sleep and reported eating more frequently while watching TV or playing on computer, suggesting poorer eating habits in these subjects. In conclusion, independent of sleep duration, SJL is associated with an increased appetite for caloric dense food, suggesting an increased incentive value of food in these subjects and an anticipated pleasure of ingesting these foods.

Social jetlag and sleep deprivation are associated with altered activity in the reward-related brain areas: an exploratory resting-state fMRI study.

OBJECTIVE: The aim of this research was to assess the effect of social jetlag (SJL) and its interaction with partial sleep deprivation on resting-state brain activity using the fractional amplitude of low-frequency fluctuation (fALFF) during free-living conditions. METHODS: A total of 28 normal weight healthy subjects were enrolled in four study groups (with SJL [with sleep deprivation and without sleep deprivation] and without SJL [with sleep deprivation and without sleep deprivation]), matched 1:1:1:1 for age, gender, and body mass index (BMI). Resting-state functional magnetic resonance imaging (fMRI) scans were collected with SIEMENS 3T scanner while subjects were in a fasting state. RESULTS: Participants with SJL had significantly higher fALFF values in right lingual gyrus and right putamen and significantly lower fALFF values in left and right inferior parietal lobe in comparison with participants without SJL and without sleep deprivation. Subjects with sleep deprivation had significantly higher fALFF in the thalamus and left superior frontal gyrus. In those with both SJL and sleep deprivation, we observed higher fALFF values in right Brodmann Area (BA)18 and lower values in left and right parietal inferior lobe. Subjects with SJL alone had significantly lower fALFF values in left frontal mid gyrus (BA6) than those with sleep deprivation alone. CONCLUSIONS: SJL was associated with altered resting-state brain activity in regions that have been shown to be involved in hedonic feeding. The effect of SJL was independent of effects induced by short sleep duration. These alterations might represent the substrate for the increased risk of obesity observed in those with SJL.

The association study of high-sensitivity C-reactive protein, pentraxin 3, nitrotyrosine, and insulin dose in patients with insulin-treated type 2 diabetes mellitus.

PURPOSE: The objective of this study was to examine the association between insulin dose and high-sensitivity C-reactive protein (hsCRP), nitrotyrosine, and pentraxin 3 in patients with insulin-treated type 2 diabetes. PATIENTS AND METHODS: Eighty patients with type 2 diabetes treated with insulin for >6 months and with stable insulin doses (±10%) within 3 months before inclusion were enrolled in this study. Medical history, including use of insulin and insulin doses, concomitant diseases and medication, and anthropometric and routine biochemical parameters were collected for each patient. hsCRP, nitrotyrosine, and pentraxin 3 were measured in fasting conditions. Comparison analysis was performed according to the distribution in tertiles of insulin dose/kg of body weight, and linear regression adjusted for confounding factors was used to examine the associations between markers of inflammation, oxidative stress, and insulin dose. RESULTS: In the comparison analysis, no statistically significant difference was found between hsCRP, nitrotyrosine, and pentraxin 3 levels across tertiles of insulin dose expressed as IU/kg of body weight (p for trend >0.05 for all comparisons) except a significantly higher hsCRP level in tertile 3 compared to tertile 1 (3.9±3.6 vs 6.1±3.8 mg/dL, p=0.035). In regression analysis, after adjustment for age, gender, smoking, body mass index, glycated hemoglobin, C-peptide, metformin, antiplatelet, and statin use, only hsCRP levels were statistically significant associated with insulin dose/kg of body weight (ß=0.237, p=0.043). CONCLUSION: In this sample of patients with type 2 diabetes treated with insulin for >6 months, hsCRP was positively associated with insulin doses. No such association was found for pentraxin 3, a more specific marker of vascular inflammation, and for nitrotyrosine as a marker of oxidative stress.

HbA1c levels are associated with severity of hypoxemia and not with apnea hypopnea index in patients with type 2 diabetes: Results from a cross-sectional study.

BACKGROUND: The aim of the present study was to evaluate the effect of untreated sleep apnea syndrome (SAS) on glycemic control, evaluated by HbA1c, in patients with type 2 diabetes (T2D). METHODS: The study sample consisted of 100 consecutive adult (≥18 years) patients with T2D without a prior diagnosis of sleep apnea recruited from an outpatient diabetes clinic. All patients underwent an in-hospital cardiorespiratory study using a three-channel portable sleep diagnostic tool; 64 were found to have sleep apnea, 36 were not. Information on medical history, body weight, height, sleep apnea symptoms, Epworth Sleepiness Scale scores, and HbA1c and fasting plasma glucose levels were recorded. RESULTS: After adjusting for factors known to affect HbA1c (gender, age, diabetes duration, diabetes treatment, body mass index [BMI], and waist circumference), HbA1c was higher in patients with than without SAS (8.4 % vs 7.6 %, respectively; P = 0.04). A positive correlation was found between the presence of sleep apnea and HbA1c (r = 0.24; P = 0.02). After adjusting for confounding factors (including BMI), only mean and lowest O2 saturation during sleep were significantly associated with HbA1c (ß = -0.23 [P = 0.03] and ß = -0.24 [P = 0.007], respectively). After further adjusting for waist circumference, only lowest O2 saturation during recording remained independently associated with HbA1c (ß = -0.21; P = 0.05). CONCLUSIONS: The presence of sleep apnea is associated with poorer glycemic control in patients with T2D. In patients with sleep apnea and T2D, greater levels of oxygen desaturation are associated with poorer glycemic control.

Prevalence and predictors of non-alcoholic fatty liver disease as defined by the fatty liver index in a type 2 diabetes population.

BACKGROUND AND AIMS: We aimed to study the prevalence and the predictive factors of non-alcoholic fatty liver disease (NAFLD) defined by the fatty liver index (FLI) in type 2 diabetic patients (T2DM). METHODS: Three hundred and eighty-one T2DM outpatients who regularly attended a Consulting Clinic in Cluj were retrospectivelly included. FLI, a surrogate steatosis biomarker based on body mass index (BMI), waist circumference (WC), triglycerides (TGL) and gammaglutamyl-transferase (GGT) was used to assess NAFLD in all patients. Anthropometric and biochemical parameters were measured. Hepatic steatosis (HS) was evaluated by ultrasonography. RESULTS: NAFLD-FLI (defined as FLI>60) was correlated with HS evaluated by ultrasound (r=0.28; p<0.001). NAFLD-FLI was detected in 79% of T2DM. The prevalence of obesity in NAFLD-FLI patients was 80%. Of the patients with normal alanine aminotransferase (ALAT), 73.8 % had NAFLD. At univariate analysis, NAFLD-FLI was correlated with age (r= -0.14; p=0.007), sex (r=0.20; p<0.001), LDL cholesterol (r=0.12; p=0.032), HDL cholesterol (r = -0.13; p=0.015), ALAT (r=0.20; p<0.001) and ASAT (r=0.19; p<0.001). At multiple regression analysis, sex, ALAT and LDL-cholesterol were independent predictors of NAFLD-FLI. After logistic regression model, ALAT, LDL-cholesterol, HOMA-IR were good independent predictors of NAFLD-FLI. CONCLUSIONS: NAFLD-FLI could be useful to identify NAFLD in T2DM patients. Subjects with T2DM had a high prevalence of NADLD-FLI even with normal ALAT levels. Our findings showed that sex, ALAT, LDL cholesterol and IR were significant and independent factors associated with the presence of NAFLD in T2DM subjects.

Effect of the early intensive multifactorial therapy on the cardiovascular risk in patients with newly diagnosed type 2 diabetes: an observational, prospective study.

BACKGROUND AND AIMS: We assessed if early intensive interventions improve the glycemic control and the modifiable cardiovascular diseases risk factors in Romanian patients with newly diagnosed type-2 diabetes during the first year follow-up period. PATIENTS AND METHODS: This was an observational, prospective study: 69 subjects were included in the analysis; each of them received intensive multi-factorial pharmacologic treatment and therapeutic education targeting hyperglycemia, weight, hypertension and dyslipidemia. Disease monitoring was done at months 0, 1, 3, 6 and 12 by assessment of anthropometric measurements, arterial blood pressure and biochemical parameters. The cardiovascular diseases risk factors were calculated using the United Kingdom Prospective Diabetes Study Risk Engine. RESULTS: The mean age at diagnosis was 53.61±10.66 years. All anthropometric variables (body weight, body mass index, waist circumference, visceral fat area, percentage of body fat), except for skeletal muscle mass, significantly decreased overtime. The majority of the biochemical parameters significantly decreased overtime. The non-fatal/fatal coronary heart disease risk significantly decreased at month 12 (9.74 [p<0.05] and 4.84 [p<0.05], respectively) compared to month 0 (19.66 and 11.10, respectively); a similar trend of the non-fatal/fatal stroke (risk at month 12, 8.30 [p<0.05] and 1.04 [p<0.05], respectively, while at month 0, 7.89 and 1.38, respectively) was recorded. CONCLUSIONS: Early multi-factorial treatment and intensive lifestyle interventions in patients newly diagnosed with type-2 diabetes could decrease with approximately 50% the rate of cardiovascular disease risk.

Age, abdominal obesity, and glycated hemoglobin are associated with carotid atherosclerosis in type 2 diabetes patients with nonalcoholic fatty liver disease.

AIM: The aim of this study was to evaluate the impact of clinical parameters and indices of body composition on the relation between non-alcoholic fatty liver disease (NAFLD) and carotid intima-media thickness (cIMT), in a type 2 diabetes mellitus population (T2DM). MATERIAL AND METHODS: We retrospectively enrolled 336 T2DM outpatients who regularly attended Regina Maria Clinic in Cluj. Clinical, anthropometric and biochemical parameters were measured. Ultrasonography (US) was used to assess hepatic steatosis (HS) in all patients and cIMT in 146 subjects. Body composition was assessed by bioelectric impedance (BIA, InBody 720) in all patients. RESULTS: cIMT was correlated with age (r=0.25; p=0.004), systolic blood pressure (r=0.18; p=0.041), glycated haemoglobin A1C (HbA1C, r=0.20; p=0.04), and with coronary artery disease (r=0.20; p=0.007). HS did not correlate with cIMT (r=0.04; p=0.64). cIMT was correlated with visceral fatty area (VFA, r=0.18; p=0.014) but not with other indices of body composition. Homeostasis model assessment for insulin resistance (HOMA-IR) was not correlated with cIMT (r=0.17; p=0.086). After multivariate analysis, age, HbA1c, and VFA were good independent predictors of cIMT (r=0.45; p < 0.001). CONCLUSIONS: These results are suggestive that in T2DM patients, fatty liver is not a direct mediator of early carotid atherosclerosis. Our data indicate that visceral fat accumulation and HbA1C are determinant factors of cIMT sugesting that controlling abdominal obesity and hyperglicemia might reduce atherosclerotic disease risk in NAFLD-T2DM subjects.

Amino acids from Mytilus galloprovincialis (L.) and Rapana venosa molluscs accelerate skin wounds healing via enhancement of dermal and epidermal neoformation.

Wound healing consists of re-epithelialization, contraction and formation of granulation and scar tissue. Amino acids from proteins are involved in these events, but their exact roles are not well understood. The present study was undertaken to investigate the anti-inflammatory effects of some amino acids from two molluscs, Mytilus galloprovincialis (L.) (Mediterranean mussel) and Rapana venosa (hard shell-clam) employed in induced skin burn injuries in Wistar rats. The treatment was evaluated in terms of essential amino acids composition which rendered the extracts very efficient in healing skin burns. The healing process was examined by periodic acid Schiff's, Verhoeff's Van Gieson and immunohistochemistry stains for collagen IV, CD 34 and CD 117 antibodies. According to the obtained results, as expressed by histological studies, the most abundant blood vessels, collagen fibres, basal and stem cells were found only for treated animals with amino acids from Rapana venosa extracts. The rich composition of amino acids from the two molluscs merits consideration as therapeutic agents in the treatment of skin burns.