Renal cell carcinoma incidence rates and trends in young adults aged 20-39 years

Background: The burden of renal cell carcinoma (RCC) in young adults received marginal attention. We assessed contemporary gender, race and stage-specific incidence and trends of RCC among young adults (20-39 years-old) in the United States.Methods: Within Surveillance, Epidemiology, and End Results database (2000-2016), patients aged 20-39 years with histologically confirmed RCC were included. Age-standardized incidence rates (ASR per 100,000 person-years) were estimated. Temporal trends were calculated through joinpoint regression analyses to describe the average annual percent change (AAPC).Results: From 2000-2016, 7767 new RCC cases were recorded (ASR 0.6, AAPC + 5.0 %, p < 0.001). ASRs were higher in males than in females (0.7 and 0.5, respectively) and increased significantly in both genders (AAPC + 5.0 % and + 4.7 % both p < 0.001, respectively). Non-Hispanic American Indian/Alaska Native had the highest incidence (ASR 1.0) vs. non-Hispanic Asian or Pacific Islander the lowest (ASR 0.3). ASRs significantly increased in all ethnic groups. T1aNOMO and T1bNOMO stages showed the highest incidence and increase (ASR 0.3, AAPC + 5.9 %, p < 0.001 and ASR 0.1, AAPC + 5.7 %, p < 0.001, respectively). Also regional and distant stages increased (AAPC + 3.7 %, p = 0.001 and AAPC + 1.5 %, p = 0.06). The most frequent tumor characteristics were G2 (44.4 %, ASR 0.3, AAPC + 6.3 %, p < 0.001) and G1 (13.1 %, ASR 0.1, AAPC + 1.1 %, p = 0.2), as well as clear cell histology (54.8 %, ASR 0.3, AAPC + 7.6 %, p < 0.001).Conclusions: RCC in young adults is rare, but increasing. This is mainly due to T1aN0M0 tumors. Nonetheless, also regional diseases are significantly increasing. Differences between ethnic groups exist and may warrant further research

Metabolic syndrome predicts worse perioperative outcomes in patients treated with partial nephrectomy for renal cell carcinoma

OBJECTIVE: To test the association between metabolic syndrome (MetS) and its components (high blood pressure, body mass index [BMI] 65 30, altered fasting glucose, low high-density lipoprotein cholesterol and high triglycerides) on perioperative outcomes after partial nephrectomy (PN). METHODS: Within the National Inpatient Sample database (2000-2015) we identified all PN patients. First, temporal trends of MetS were reported. Second, the effect of MetS components was tested in multivariable logistic regression models predicting overall and specific perioperative complications. Third, we tested for dose-response from the concomitant effect of multiple MetS components. All models were weighted and adjusted for clustering, as well as all available patient and hospital characteristics. RESULTS: Of 25,875 patients: (1) 59.3% had high blood pressure, (2) 14.7% had BMI 65 30, (3) 21.7% had altered fasting glucose, (4) 20.2% had high triglycerides, and (5) <0.01% had low high-density lipoprotein cholesterol. One vs 2 vs 3 vs 4 MetS components were recorded in 34.9% vs 22.9% vs 8.9% vs 2.2% patients. Of all, 11.1% exhibited 65 3 components and qualified for MetS. The rates of MetS increased over time (estimated annual percentage changes: +12.0%;P <.001). The 4 tested MetS components (high blood pressure, BMI 65 30, altered fasting glucose, and high triglycerides) achieved independent predictor status in multivariable models predicting overall, cardiac, miscellaneous medical, vascular, and respiratory complications, as well as transfusions. Moreover, a statistically significant dose-response was confirmed for the same endpoints. CONCLUSION: MetS and its components consistently and strongly predict perioperative complications after PN. Moreover, the strength of the effect was directly proportional to the number of MetS components exhibited by each individual patient, even if formal MetS diagnosis of 65 3 components has not been m

Boosting Long-term Memory via Wakeful Rest: Intentional Rehearsal is not Necessary, Automatic Consolidation is Sufficient.

<div><p>People perform better on tests of delayed free recall if learning is followed immediately by a short wakeful rest than by a short period of sensory stimulation. Animal and human work suggests that wakeful resting provides optimal conditions for the consolidation of recently acquired memories. However, an alternative account cannot be ruled out, namely that wakeful resting provides optimal conditions for intentional rehearsal of recently acquired memories, thus driving superior memory. Here we utilised non-recallable words to examine whether wakeful rest boosts long-term memory, even when new memories could not be rehearsed intentionally during the wakeful rest delay. The probing of non-recallable words requires a recognition paradigm. Therefore, we first established, via Experiment 1, that the rest-induced boost in memory observed via free recall can be replicated in a recognition paradigm, using concrete nouns. In Experiment 2, participants heard 30 non-recallable non-words, presented as ‘foreign names in a bridge club abroad’ and then either rested wakefully or played a visual spot-the-difference game for 10 minutes. Retention was probed via recognition at two time points, 15 minutes and 7 days after presentation. As in Experiment 1, wakeful rest boosted recognition significantly, and this boost was maintained for at least 7 days. Our results indicate that the enhancement of memory via wakeful rest is <i>not</i> dependent upon intentional rehearsal of learned material during the rest period. We thus conclude that consolidation is <i>sufficient</i> for this rest-induced memory boost to emerge. We propose that wakeful resting allows for superior memory consolidation, resulting in stronger and/or more veridical representations of experienced events which can be detected via tests of free recall and recognition.</p></div

Benefit of Adjuvant Chemotherapy After Radical Cystectomy for Treatment of Urothelial Carcinoma of the Bladder in the Elderly –An International Multicenter Study

BACKGROUND: Radical cystectomy (RC) is the standard treatment for muscle invasive bladder cancer, but approximately half of all patients will ultimately succumb to disease progression despite apparent cure with extirpative surgery. Elderly patients are at especially high risk of advanced disease and may benefit from perioperative systemic therapy. OBJECTIVE: To assess the real-world benefit of adjuvant chemotherapy (AC) in patients ≥75 years old. METHODS: We retrospectively reviewed patients who underwent RC for non-metastatic urothelial carcinoma of the bladder (UCB) from 12 participating international medical institutions. Kaplan-Meier survival curves and Cox regression models were used to assess the association between age groups, administration of AC and oncological outcome parameters such as recurrence-free survival (RFS), cancer-specific survival (CSS) and overall survival (OS). RESULTS: 4,335 patients were included in the analyses, of which 820 (18.9%) were ≥75 years old. These elderly patients had a higher rate of adverse pathologic features. In an univariable subgroup analysis in patients ≥75 years with lymph node metastasis, 5-year OS was significantly higher in patients who had received AC (41% vs. 30.9%, p = 0.02). In a multivariable Cox model that was adjusted for several established outcome predictors, there was a significant favorable association between the administration of AC in elderly patients and OS, but no RFS or CSS. CONCLUSIONS: In this large observational study, the administration of AC was associated with improved OS, but not RFS or CSS, in elderly patients treated with RC for UCB. This is of clinical importance, as elderly patients are more likely to have adverse pathologic features and experience worse survival outcomes. Treatment of UCB should include both a multidisciplinary approach and a geriatric evaluation to identify patients who are most likely to tolerate and benefit from AC

Unmasking selective path integration deficits inAlzheimer’s disease risk carriers

Alzheimer’s disease (AD) manifests with progressive memory loss and spatial disorientation. Neuropathological studies suggest early AD pathology in the entorhinal cortex (EC) of young adults at genetic risk for AD (APOE4-carriers). Because the EC harbors grid cells, a likely neural substrate of path integration (PI), we examined PI performance in APOE4-carriers during a virtual navigation task. We report a selective impairment in APOE4-carriers specifically when recruitment of compensatory navigational strategies via supportive spatial cues was disabled. A separate fMRI study revealed that PI performance was associated with the strength of entorhinal grid-like representations when no compensatory strategies were available, suggesting grid cell dysfunction as a mechanistic explanation for PI deficits in APOE4-carriers. Furthermore, posterior cingulate/retrosplenial cortex was involved in the recruitment of compensatory navigational strategies via supportive spatial cues. Our results provide evidence for selective PI deficits in AD risk carriers, decades before potential disease onset

Effects of Different Correlation Metrics and Preprocessing Factors on Small-World Brain Functional Networks: A Resting-State Functional MRI Study

Graph theoretical analysis of brain networks based on resting-state functional MRI (R-fMRI) has attracted a great deal of attention in recent years. These analyses often involve the selection of correlation metrics and specific preprocessing steps. However, the influence of these factors on the topological properties of functional brain networks has not been systematically examined. Here, we investigated the influences of correlation metric choice (Pearson's correlation versus partial correlation), global signal presence (regressed or not) and frequency band selection [slow-5 (0.01–0.027 Hz) versus slow-4 (0.027–0.073 Hz)] on the topological properties of both binary and weighted brain networks derived from them, and we employed test-retest (TRT) analyses for further guidance on how to choose the “best” network modeling strategy from the reliability perspective. Our results show significant differences in global network metrics associated with both correlation metrics and global signals. Analysis of nodal degree revealed differing hub distributions for brain networks derived from Pearson's correlation versus partial correlation. TRT analysis revealed that the reliability of both global and local topological properties are modulated by correlation metrics and the global signal, with the highest reliability observed for Pearson's-correlation-based brain networks without global signal removal (WOGR-PEAR). The nodal reliability exhibited a spatially heterogeneous distribution wherein regions in association and limbic/paralimbic cortices showed moderate TRT reliability in Pearson's-correlation-based brain networks. Moreover, we found that there were significant frequency-related differences in topological properties of WOGR-PEAR networks, and brain networks derived in the 0.027–0.073 Hz band exhibited greater reliability than those in the 0.01–0.027 Hz band. Taken together, our results provide direct evidence regarding the influences of correlation metrics and specific preprocessing choices on both the global and nodal topological properties of functional brain networks. This study also has important implications for how to choose reliable analytical schemes in brain network studies

Age-related changes in neural functional connectivity and its behavioral relevance

<p>Abstract</p> <p>Background</p> <p>Resting-state recordings are characterized by widely distributed networks of coherent brain activations. Disturbances of the default network - a set of regions that are deactivated by cognitive tasks and activated during passive states - have been detected in age-related disorders such as Alzheimer's or Parkinson's disease but alterations in the course of healthy aging still need to be explored.</p> <p>Results</p> <p>Using magnetoencephalography (MEG), the present study investigated how age-related functional resting-state brain connectivity links to cognitive performance in healthy aging in fifty-three participants ranging in age from 18 to 89 years. A beamforming technique was used to reconstruct the brain activity in source space and the interregional coupling was investigated using partial directed coherence (PDC). We found significant age-related alterations of functional resting-state connectivity. These are mainly characterized by reduced information input into the posterior cingulum/precuneus region together with an enhanced information flow to the medial temporal lobe. Furthermore, higher inflow in the medial temporal lobe subsystem was associated with weaker cognitive performance whereas stronger inflow in the posterior cluster was related to better cognitive performance.</p> <p>Conclusion</p> <p>This is the first study to show age-related alterations in subsystems of the resting state network that are furthermore associated with cognitive performance.</p

Efficient Physical Embedding of Topologically Complex Information Processing Networks in Brains and Computer Circuits

Nervous systems are information processing networks that evolved by natural selection, whereas very large scale integrated (VLSI) computer circuits have evolved by commercially driven technology development. Here we follow historic intuition that all physical information processing systems will share key organizational properties, such as modularity, that generally confer adaptivity of function. It has long been observed that modular VLSI circuits demonstrate an isometric scaling relationship between the number of processing elements and the number of connections, known as Rent's rule, which is related to the dimensionality of the circuit's interconnect topology and its logical capacity. We show that human brain structural networks, and the nervous system of the nematode C. elegans, also obey Rent's rule, and exhibit some degree of hierarchical modularity. We further show that the estimated Rent exponent of human brain networks, derived from MRI data, can explain the allometric scaling relations between gray and white matter volumes across a wide range of mammalian species, again suggesting that these principles of nervous system design are highly conserved. For each of these fractal modular networks, the dimensionality of the interconnect topology was greater than the 2 or 3 Euclidean dimensions of the space in which it was embedded. This relatively high complexity entailed extra cost in physical wiring: although all networks were economically or cost-efficiently wired they did not strictly minimize wiring costs. Artificial and biological information processing systems both may evolve to optimize a trade-off between physical cost and topological complexity, resulting in the emergence of homologous principles of economical, fractal and modular design across many different kinds of nervous and computational networks

Graph Theoretical Analysis of Functional Brain Networks: Test-Retest Evaluation on Short- and Long-Term Resting-State Functional MRI Data

Graph-based computational network analysis has proven a powerful tool to quantitatively characterize functional architectures of the brain. However, the test-retest (TRT) reliability of graph metrics of functional networks has not been systematically examined. Here, we investigated TRT reliability of topological metrics of functional brain networks derived from resting-state functional magnetic resonance imaging data. Specifically, we evaluated both short-term (<1 hour apart) and long-term (>5 months apart) TRT reliability for 12 global and 6 local nodal network metrics. We found that reliability of global network metrics was overall low, threshold-sensitive and dependent on several factors of scanning time interval (TI, long-term>short-term), network membership (NM, networks excluding negative correlations>networks including negative correlations) and network type (NT, binarized networks>weighted networks). The dependence was modulated by another factor of node definition (ND) strategy. The local nodal reliability exhibited large variability across nodal metrics and a spatially heterogeneous distribution. Nodal degree was the most reliable metric and varied the least across the factors above. Hub regions in association and limbic/paralimbic cortices showed moderate TRT reliability. Importantly, nodal reliability was robust to above-mentioned four factors. Simulation analysis revealed that global network metrics were extremely sensitive (but varying degrees) to noise in functional connectivity and weighted networks generated numerically more reliable results in compared with binarized networks. For nodal network metrics, they showed high resistance to noise in functional connectivity and no NT related differences were found in the resistance. These findings provide important implications on how to choose reliable analytical schemes and network metrics of interest