Education Outcomes of Children Born Late Preterm: A Retrospective Whole-Population Cohort Study

Maternal and Child Health Journal - Early life exposures can have an impact on a child’s developmental trajectory and children born late preterm (34–36 weeks gestational age)...     

Differentiating poor validity from probable impairment on the medical symptom validity test: a cross-validation study

Aims: In neuropsychological evaluations, it is often difficult to ascertain whether poor performance on measures of validity is due to poor effort or malingering, or whether there is genuine cognitive impairment. Dunham and Denney created an algorithm to assess this question using the Medical Symptom Validity Test (MSVT). We assessed the ability of their algorithm to detect poor validity versus probable impairment, and concordance of failure on the MSVT with other freestanding tests of performance validity.

Methods: Two previously published datasets (n?=?153 and n?=?641, respectively) from outpatient neuropsychological evaluations were used to test Dunham and Denney’s algorithm, and to assess concordance of failure rates with the Test of Memory Malingering and the forced choice measure of the California Verbal Learning Test, two commonly used performance validity tests.

Results: In both datasets, none of the four cutoff scores for failure on the MSVT (70%, 75%, 80%, or 85%) identified a poor validity group with proportionally aligned failure rates on other freestanding measures of performance validity. Additionally, the protocols with probable impairment did not differ from those with poor validity on cognitive measures.

Conclusions: Despite what appeared to be a promising approach to evaluating failure on the easy MSVT subtests when clinical data are unavailable (as recommended in the advanced interpretation program, or advanced interpretation [AI], of the MSVT), the current findings indicate the AI remains the gold standard for doing so. Future research should build on this effort to address shortcomings in measures of effort in neuropsychological evaluations.     

Binding mode of conformations and structure-based pharmacophore development for farnesyltransferase inhibitors

Farnesyltransferase (FTase) is one of the prenyltransferase family enzymes that catalyse the transfer of 15-membered isoprenoid (farnesyl) moiety to the cysteine of CAAX motif-containing proteins including Rho and Ras family of G proteins. Inhibitors of FTase act as drugs for cancer, malaria, progeria and other diseases. In the present investigation, we have developed two structure-based pharmacophore models from protein–ligand complex (3E33 and 3E37) obtained from the protein data bank. Molecular dynamics (MD) simulations were performed on the complexes, and different conformers of the same complex were generated. These conformers were undergone protein–ligand interaction fingerprint (PLIF) analysis, and the fingerprint bits have been used for structure-based pharmacophore model development. The PLIF results showed that Lys164, Tyr166, TrpB106 and TyrB361 are the major interacting residues in both the complexes. The RMSD and RMSF analyses on the MD-simulated systems showed that the absence of FPP in the complex 3E37 has significant effect in the conformational changes of the ligands. During this conformational change, some interactions between the protein and the ligands are lost, but regained after some simulations (after 2 ns). The structure-based pharmacophore models showed that the hydrophobic and acceptor contours are predominantly present in the models. The pharmacophore models were validated using reference compounds, which significantly identified as HITs with smaller RMSD values. The developed structure-based pharmacophore models are significant, and the methodology used in this study is novel from the existing methods (the original X-ray crystallographic coordination of the ligands is used for the model building). In our study, along with the original coordination of the ligand, different conformers of the same complex (protein–ligand) are used. It concluded that the developed methodology is significant for the virtual screening of novel molecules on different targets.     

Impact of overweight and obesity on US renal cell carcinoma incidence trends (1995-2018)

In the United States, renal cell carcinoma (RCC) incidence and the prevalence of obesity, an established risk factor for RCC, have been increasing for several decades. RCC is more common among older individuals. We sought to quantify the contribution of excess adiposity to the rising incidence of RCC among individuals 60 years or older. National Institutes of Health-American Association of Retired Persons Diet and Health Study data (n = 453 859 participants, enrolled in 1995-1996, age at enrollment 50-71 years) were used to estimate multivariable-adjusted hazard ratios (HRs) for RCC across body mass index categories and HRs associated with smoking. Population attributable fractions (PAFs) were calculated using estimated HRs and annual overweight/obesity prevalence from the National Health Interview Survey (1985-2008). PAF estimates were combined with RCC incidence from Surveillance, Epidemiology and End Results-13 to calculate annual percent changes in RCC incidence attributable (and unrelated) to overweight/obesity. We found that between 1995 and 2018, among individuals aged 60 years and older, PAF for overweight/obesity increased from 18% to 29% for all RCCs. In comparison, the PAF for smoking declined from 12% to 9%. RCC incidence increased 1.8% per year (95% confidence interval [CI] 1.5%-2.1%) overall, while RCC incidence attributable to overweight/obesity increased 3.8% per year (95%CI 3.5%-4.2%) and RCC incidence unrelated to overweight/obesity increased 1.2% per year (95% CI 0.9%-1.4%). In conclusion, overweight/obesity appears to have contributed importantly to the rising incidence of RCC in the United States since the mid-1990s. Public health interventions focused on reducing overweight and obesity could help substantially in curbing this trend.