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.     

Blur adaptation: clinical and refractive considerations

The human visual system is amenable to a number of adaptive processes; one such process, or collection of processes, is the adaptation to blur. Blur adaptation can be observed as an improvement in vision under degraded conditions, and these changes occur relatively rapidly following exposure to blur. The potential important future directions of this research area and the clinical implications of blur adaptation are discussed.     

Lifitegrast clinical efficacy for treatment of signs and symptoms of dry eye disease across three randomized controlled trials

Objective: Report efficacy findings from three clinical trials (one phase 2 and two phase 3 [OPUS-1, OPUS-2]) of lifitegrast ophthalmic solution 5.0% for treatment of dry eye disease (DED).

Research design and methods: Three 84-day, randomized, double-masked, placebo-controlled trials. Adults (≥18 years) with DED were randomized (1:1) to lifitegrast 5.0% or matching placebo. Changes from baseline to day 84 in signs and symptoms of DED were analyzed.

Main outcome measures: Phase 2, pre-specified endpoint: inferior corneal staining score (ICSS; 0–4); OPUS-1, coprimary endpoints: ICSS and visual-related function subscale (0–4 scale); OPUS-2, coprimary endpoints: ICSS and eye dryness score (EDS, VAS; 0–100).

Results: Fifty-eight participants were randomized to lifitegrast 5.0% and 58 to placebo in the phase 2 trial; 293 to lifitegrast and 295 to placebo in OPUS-1; 358 to lifitegrast and 360 to placebo in OPUS-2. In participants with mild-to-moderate baseline DED symptomatology, lifitegrast improved ICSS versus placebo in the phase 2 study (treatment effect, 0.35; 95% CI, 0.05–0.65; p?=?0.0209) and OPUS-1 (effect, 0.24; 95% CI, 0.10–0.38; p?=?0.0007). Among more symptomatic participants (baseline EDS ≥40, recent artificial tear use), lifitegrast improved EDS versus placebo in a post hoc analysis of OPUS-1 (effect, 13.34; 95% CI, 2.35–24.33; nominal p?=?0.0178) and in OPUS-2 (effect, 12.61; 95% CI, 8.51–16.70; p?<?0.0001).

Limitations: Trials were conducted over 12 weeks; efficacy beyond this period was not assessed.

Conclusions: Across three trials, lifitegrast improved ICSS in participants with mild-to-moderate baseline symptomatology in two studies, and EDS in participants with moderate-to-severe baseline symptomatology in two studies. Based on the overall findings from these trials, lifitegrast shows promise as a new treatment option for signs and symptoms of DED.     

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.