Background

Accurate evaluation of glomerular filtration rates (GFRs) is of critical importance in clinical practice. A previous study showed that models based on artificial neural networks (ANNs) could achieve a better performance than traditional equations. However, large-sample cross-sectional surveys have not resolved questions about ANN performance.

Methods

A total of 1,180 patients that had chronic kidney disease (CKD) were enrolled in the development data set, the internal validation data set and the external validation data set. Additional 222 patients that were admitted to two independent institutions were externally validated. Several ANNs were constructed and finally a Back Propagation network optimized by a genetic algorithm (GABP network) was chosen as a superior model, which included six input variables; i.e., serum creatinine, serum urea nitrogen, age, height, weight and gender, and estimated GFR as the one output variable. Performance was then compared with the Cockcroft-Gault equation, the MDRD equations and the CKD-EPI equation.

Results

In the external validation data set, Bland-Altman analysis demonstrated that the precision of the six-variable GABP network was the highest among all of the estimation models; i.e., 46.7 ml/min/1.73 m2 vs. a range from 71.3 to 101.7 ml/min/1.73 m2, allowing improvement in accuracy (15% accuracy, 49.0%; 30% accuracy, 75.1%; 50% accuracy, 90.5% [P<0.001 for all]) and CKD stage classification (misclassification rate of CKD stage, 32.4% vs. a range from 47.3% to 53.3% [P<0.001 for all]). Furthermore, in the additional external validation data set, precision and accuracy were improved by the six-variable GABP network.

Conclusions

A new ANN model (the six-variable GABP network) for CKD patients was developed that could provide a simple, more accurate and reliable means for the estimation of GFR and stage of CKD than traditional equations. Further validations are needed to assess the ability of the ANN model in diverse populations.

Background

A non-dipper blood pressure (BP) pattern is very common in chronic kidney disease (CKD) patients and affects the progression and development of cardiovascular disease. However, data on the reversed dipper BP pattern on target-organ damage in Chinese CKD patients are lacking.

Methods

A total of 540 CKD patients were enrolled. Ambulatory blood pressure monitoring (ABPM), clinical BP, ultrasonographic assessment and other clinical data were collected. Univariate and multivariate analyses were used to ascertain the relationship between ABPM results and clinical parameters.

Results

A total of 21.9% CKD patients had a reversed dipper BP pattern, 42% of patients had a non-dipper BP pattern and 36.1% of patients had a dipper BP pattern. Patients with reversed dipper BP pattern had the worst renal function and most severe cardiovascular damages among these CKD patients (p<0.05). The estimated glomerular filtration rate (eGFR) and left ventricular mass index (LVMI) correlated significantly with the rate of decline of nocturnal BP. A reversed dipper BP pattern was an independent factor affecting kidney damage and left ventricular hypertrophy. Age, lower hemoglobin level, higher 24-h systolic BP from ABPM, and higher serum phosphate levels were independent associated with a reversed dipper BP pattern after multivariate logistic regression analyses.

Conclusion

The reversed dipper BP pattern is closely related to severe renal damage and cardiovascular injuries in CKD patients, and special attention should be given to these CKD patients.

Background

Many young people experiment with cannabis, yet only a subgroup progress to dependence suggesting individual differences that could relate to factors such as genetics and behavioral traits. Dopamine receptor D2 (DRD2) and proenkephalin (PENK) genes have been implicated in animal studies with cannabis exposure. Whether polymorphisms of these genes are associated with cannabis dependence and related behavioral traits is unknown.

Methodology/Principal Findings

Healthy young adults (18–27 years) with cannabis dependence and without a dependence diagnosis were studied (N = 50/group) in relation to a priori-determined single nucleotide polymorphisms (SNPs) of the DRD2 and PENK genes. Negative affect, Impulsive Risk Taking and Neuroticism-Anxiety temperamental traits, positive and negative reward-learning performance and stop-signal reaction times were examined. The findings replicated the known association between the rs6277 DRD2 SNP and decisions associated with negative reinforcement outcomes. Moreover, PENK variants (rs2576573 and rs2609997) significantly related to Neuroticism and cannabis dependence. Cigarette smoking is common in cannabis users, but it was not associated to PENK SNPs as also validated in another cohort (N = 247 smokers, N = 312 non-smokers). Neuroticism mediated (15.3%–19.5%) the genetic risk to cannabis dependence and interacted with risk SNPs, resulting in a 9-fold increase risk for cannabis dependence. Molecular characterization of the postmortem human brain in a different population revealed an association between PENK SNPs and PENK mRNA expression in the central amygdala nucleus emphasizing the functional relevance of the SNPs in a brain region strongly linked to negative affect.

Conclusions/Significance

Overall, the findings suggest an important role for Neuroticism as an endophenotype linking PENK polymorphisms to cannabis-dependence vulnerability synergistically amplifying the apparent genetic risk.

The use of methamphetamine (MA) has increased in recent years, and is a major health concern throughout the world. The use of MA has been associated with an increased risk of acquiring HIV-1, along with an increased probability of the acquisition of various sexually transmitted infections. In order to determine the potential effects of MA exposure in the context of an infectious agent, U937 macrophages were exposed to various combinations of MA and bacterial lipopolysaccharide (LPS). Treatment with MA alone caused significant increases in the levels of TNF-α, while treatment with both MA and LPS resulted in significant increases in TNF-α, IL-1β and the chemokine IL-8. The increases in cytokine or chemokine levels seen when cells were treated with both LPS and MA were generally greater than those increases observed when cells were treated with only LPS. Treatment with chemical inhibitors demonstrated that the signal transduction pathways including NF-kB, MAPK, and PI3-Akt were involved in mediating the increased inflammatory response. As discussed in the paper, these pathways appear to be utilized by both MA and LPS, in the induction of these inflammatory mediators. Since these pathways are involved in the induction of inflammation in response to other pathogens, this suggests that MA-exacerbated inflammation may be a common feature of infectious disease in MA abusers.

Background

Alexithymia is a personality trait characterized by deficiency in understanding, processing, or describing emotions. Recent studies have revealed that alexithymia is associated with less activation of the anterior cingulate cortex, a brain region shown to play a role in cognitive and emotional processing. However, few studies have directly investigated the cognitive domain in relation to alexithymia to examine whether alexithymic trait is related to less efficient voluntary control.

Methodology/ Principal Findings

We examined the relationship between alexithymic trait and voluntary control in a group of healthy volunteers. We used the 20-item Toronto Alexithymia Scale (TAS-20) to measure alexithymic trait. Additionally, we examined state and trait voluntary control using the revised Attention Network Test (ANT-R) and the Adult Temperament Questionnaire (ATQ), respectively. Alexithymic trait was positively correlated with the overall reaction time of the ANT-R, and negatively correlated with the Effortful Control factor of the ATQ.

Conclusions/Significance

Our results suggest that alexithymic trait is associated with less efficient voluntary control.

Voluntary control of information processing is crucial to allocate resources and prioritize the processes that are most important under a given situation; the algorithms underlying such control, however, are often not clear. We investigated possible algorithms of control for the performance of the majority function, in which participants searched for and identified one of two alternative categories (left or right pointing arrows) as composing the majority in each stimulus set. We manipulated the amount (set size of 1, 3, and 5) and content (ratio of left and right pointing arrows within a set) of the inputs to test competing hypotheses regarding mental operations for information processing. Using a novel measure based on computational load, we found that reaction time was best predicted by a grouping search algorithm as compared to alternative algorithms (i.e., exhaustive or self-terminating search). The grouping search algorithm involves sampling and resampling of the inputs before a decision is reached. These findings highlight the importance of investigating the implications of voluntary control via algorithms of mental operations.