Diabetic ketoacidosis as the presenting manifestation of pancreatic adenocarcinoma with cystic features.

The common presenting symptoms of pancreatic cancer are abdominal pain, weight loss, and jaundice. Pancreatic adenocarcinoma presenting with diabetic ketoacidosis is a very rare emergent clinical condition. However, pancreatic ductal cystadenocarcinoma presenting with diabetic ketoacidosis was not reported. We describe a 60-year-old man with pancreatic cystadenocarcinoma presenting with diabetic ketoacidosis as the initial manifestation. It must be kept in mind that in diabetic ketoacidosis cases, the precipitating factor may be pancreatic ductal cystadenocarcinoma.

Epicardial Adipose Tissue Thickness in Patients With Subclinical Hypothyroidism and the Relationship Thereof With Visceral Adipose Tissue Thickness.

BACKGROUND: Subclinical hypothyroidism (SH) is associated with cardiovascular metabolic syndromes, especially dislipidemia and abdominal obesity. Visceral abdominal adipose tissue (VAAT) and epicardial adipose tissue (EAT) have the same ontogenic origin and produce many proinflammatory and proatherogenic cytokines. We evaluated EAT and VAAT thickness in patients with SH. METHODS: Forty-one patients with SH and 35 controls were included in the study. Demographical and anthropometric features of both patients and controls were recorded. Thyroid and metabolic parameters were measured. EAT was measured using 2D-transthoracic echocardiography. RESULTS: The age and gender distributions were similar in the two groups (P = 0.998 and P = 0.121, respectively). Body mass index (BMI), fat mass, waist circumference (WC), hip circumference (HC), the WC/HC ratio, and the thicknesses of VAAT and abdominal subcutaneous adipose tissue were higher in the case group than the control group (all P values < 0.01). However, both groups had similar EAT thickness (P = 0.532), which was positively correlated with BMI, fat mass, WC, HC, VAAT thickness, abdominal subcutaneous adipose tissue thickness, and serum triglyceride (TG) level (all P values < 0.01). We found no correlation between EAT thickness and thyroid-stimulating hormone (TSH) level, free thyroxine (FT4) level, or low-density lipoprotein-cholesterol (LDL-C) level, and anti-TPO level (all P values > 0.05). We found no difference between the two groups in fasting plasma glucose (FPG) level (P = 0.780), but the levels of LDL-C and TG differed significantly (P = 0.002 and P = 0.026, respectively). The serum TSH level was higher and the FT4 level was lower in the case than the control group (both P values <0.01). CONCLUSION: Increased abdominal adipose tissue thickness in patients with SH is associated with atherosclerosis. To detemine the risk of atherosclerosis in such patients, EAT measurements are valuable; such assessment is simple to perform.

Like/dislike analysis using EEG: determination of most discriminative channels and frequencies.

In this study, we have analyzed electroencephalography (EEG) signals to investigate the following issues, (i) which frequencies and EEG channels could be relatively better indicators of preference (like or dislike decisions) of consumer products, (ii) timing characteristic of "like" decisions during such mental processes. For this purpose, we have obtained multichannel EEG recordings from 15 subjects, during total of 16 epochs of 10 s long, while they were presented with some shoe photographs. When they liked a specific shoe, they pressed on a button and marked the time of this activity and the particular epoch was labeled as a LIKE case. No button press meant that the subject did not like the particular shoe that was displayed and corresponding epoch designated as a DISLIKE case. After preprocessing, power spectral density (PSD) of EEG data was estimated at different frequencies (4, 5, …, 40 Hz) using the Burg method, for each epoch corresponding to one shoe presentation. Each subject's data consisted of normalized PSD values (NPVs) from all LIKE and DISLIKE cases/epochs coming from all 19 EEG channels. In order to determine the most discriminative frequencies and channels, we have utilized logistic regression, where LIKE/DISLIKE status was used as a categorical (binary) response variable and corresponding NPVs were the continuously valued input variables or predictors. We observed that when all the NPVs (total of 37) are used as predictors, the regression problem was becoming ill-posed due to large number of predictors (compared to the number of samples) and high correlation among predictors. To circumvent this issue, we have divided the frequency band into low frequency (LF) 4-19 Hz and high frequency (HF) 20-40 Hz bands and analyzed the influence of the NPV in these bands separately. Then, using the p-values that indicate how significantly estimated predictor weights are different than zero, we have determined the NPVs and channels that are more influential in determining the outcome, i.e., like/dislike decision. In the LF band, 4 and 5 Hz were found to be the most discriminative frequencies (MDFs). In the HF band, none of the frequencies seemed offer significant information. When both male and female data was used, in the LF band, a frontal channel on the left (F7-A1) and a temporal channel on the right (T6-A2) were found to be the most discriminative channels (MDCs). In the HF band, MDCs were central (Cz-A1) and occipital on the left (O1-A1) channels. The results of like timings suggest that male and female behavior for this set of stimulant images were similar.