PREDICT-GTN 1: Can we improve the FIGO scoring system in gestational trophoblastic neoplasia?

Gestational trophoblastic neoplasia (GTN) patients are treated according to the eight-variable International Federation of Gynaecology and Obstetrics (FIGO) scoring system, that aims to predict first-line single-agent chemotherapy resistance. FIGO is imperfect with one-third of low-risk patients developing disease resistance to first-line single-agent chemotherapy. We aimed to generate simplified models that improve upon FIGO. Logistic regression (LR) and multilayer perceptron (MLP) modelling (n = 4191) generated six models (M1-6). M1, all eight FIGO variables (scored data); M2, all eight FIGO variables (scored and raw data); M3, nonimaging variables (scored data); M4, nonimaging variables (scored and raw data); M5, imaging variables (scored data); and M6, pretreatment hCG (raw data) + imaging variables (scored data). Performance was compared to FIGO using true and false positive rates, positive and negative predictive values, diagnostic odds ratio, receiver operating characteristic (ROC) curves, Bland-Altman calibration plots, decision curve analysis and contingency tables. M1-6 were calibrated and outperformed FIGO on true positive rate and positive predictive value. Using LR and MLP, M1, M2 and M4 generated small improvements to the ROC curve and decision curve analysis. M3, M5 and M6 matched FIGO or performed less well. Compared to FIGO, most (excluding LR M4 and MLP M5) had significant discordance in patient classification (McNemar's test P < .05); 55-112 undertreated, 46-206 overtreated. Statistical modelling yielded only small gains over FIGO performance, arising through recategorisation of treatment-resistant patients, with a significant proportion of under/overtreatment as the available data have been used a priori to allocate primary chemotherapy. Streamlining FIGO should now be the focus.     

Estimation of phase signal change in neuronal current MRI for evoke response of tactile detection with realistic somatosensory laminar network model

Magnetic field generated by neuronal activity could alter magnetic resonance imaging (MRI) signals but detection of such signal is under debate. Previous researches proposed that magnitude signal change is below current detectable level, but phase signal change (PSC) may be measurable with current MRI systems. Optimal imaging parameters like echo time, voxel size and external field direction, could increase the probability of detection of this small signal change. We simulate a voxel of cortical column to determine effect of such parameters on PSC signal. We extended a laminar network model for somatosensory cortex to find neuronal current in each segment of pyramidal neurons (PN). 60,000 PNs of simulated network were positioned randomly in a voxel. Biot–savart law applied to calculate neuronal magnetic field and additional phase. The procedure repeated for eleven neuronal arrangements in the voxel. PSC signal variation with the echo time and voxel size was assessed. The simulated results show that PSC signal increases with echo time, especially 100/80 ms after stimulus for gradient echo/spin echo sequence. It can be up to 0.1 mrad for echo time = 175 ms and voxel size = 1.48 × 1.48 × 2.18 mm³. With echo time less than 25 ms after stimulus, it was just acquired effects of physiological noise on PSC signal. The absolute value of the signal increased with decrease of voxel size, but its components had complex variation. External field orthogonal to local surface of cortex maximizes the signal. Expected PSC signal for tactile detection in the somatosensory cortex increase with echo time and have no oscillation.     

Reading the unique DNA methylation landscape of the brain: Non-CpG methylation,hydroxymethylation, and MeCP2

DNA methylation at CpG dinucleotides is an important epigenetic regulator common to virtually all mammalian cell types, but recent evidence indicates that during early postnatal development neuronal genomes also accumulate uniquely high levels of two alternative forms of methylation, non-CpG methylation and hydroxymethylation. Here we discuss the distinct landscape of DNA methylation in neurons, how it is established, and how it might affect the binding and function of protein readers of DNA methylation. We review studies of one critical reader of DNA methylation in the brain, the Rett syndrome protein methyl CpG-binding protein 2 (MeCP2), and discuss how differential binding affinity of MeCP2 for non-CpG and hydroxymethylation may affect the function of this methyl-binding protein in the nervous system.     

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.     

Dying is the Most Grown-Up Thing We Ever Do: But Do Health Care Professionals Prevent Us from Taking It Seriously?

This paper takes a somewhat slant perspective on flourishing and care in the context of suffering, death and dying, arguing that care in this context consists principally of ‘acts of work and courage that enable flourishing’. Starting with the perception that individuals, society and health care professionals have become dulled to death and the process of dying in Western advanced health systems, it suggests that for flourishing to occur, both of these aspects of life need to be faced more directly. The last days of life need to be ‘undulled’. Reflections upon the experiences of the author as carer and daughter in the face of her mother’s experience of death are used as basis for making suggestions about how care systems and professionals might better assist people in dealing with ‘the most grown up thing’ humans ever do, which is to die.     

HIV Protease: Historical Perspective and Current Research

The retroviral protease of human immunodeficiency virus (HIV) is an excellent target for antiviral inhibitors for treating HIV/AIDS. Despite the efficacy of therapy, current efforts to control the disease are undermined by the growing threat posed by drug resistance. This review covers the historical background of studies on the structure and function of HIV protease, the subsequent development of antiviral inhibitors, and recent studies on drug-resistant protease variants. We highlight the important contributions of Dr. Stephen Oroszlan to fundamental knowledge about the function of the HIV protease and other retroviral proteases. These studies, along with those of his colleagues, laid the foundations for the design of clinical inhibitors of HIV protease. The drug-resistant protease variants also provide an excellent model for investigating the molecular mechanisms and evolution of resistance.     

Nanomedicines: From Bench to Bedside and Beyond

Advancing nanomedicines from concept to clinic requires integration of new science with traditional pharmaceutical development. The medical and commercial success of nanomedicines is greatly facilitated when those charged with developing nanomedicines are cognizant of the unique opportunities and technical challenges that these products present. These individuals must also be knowledgeable about the processes of clinical and product development, including regulatory considerations, to maximize the odds for successful product registration. This article outlines these topics with a goal to accelerate the combination of academic innovation with collaborative industrial scientists who understand pharmaceutical development and regulatory approval requirements—only together can they realize the full potential of nanomedicines for patients.