Kinetics and mechanism of sequential ring methyl C–H activation in cyclopentadienyl rhodium(iii) complexes

We have studied activation of the methyl C–H bonds in the cyclopentadienyl ligands of half-sandwich Rh(III) complexes [η5-CpXRh(N,N′)Cl]+ by observing the dependence of sequential H/D exchange on variations in CpX = Cp* (complexes 1 and 2), Me4PhCp (CpXPh, 3) or Me4PhPhCp (CpXPhPh, 4), and chelated ligand N,N′ (bpy, 1; phen, 2–4). H/D exchange was fastest in d4-MeOD (t1/2 = 10 min, 37 °C, complex 1), no H/D exchange was observed in DMSO/D2O, and d4-MeOD enhanced the rate in CD3CN. The proposed Rh(I)–fulvene intermediate was trapped by [4 + 2] Diels–Alder reactions with conjugated dienes and characterized. The Rh(I) oxidation state was confirmed by X-ray photoelectron spectroscopy (XPS). Influence of solvent on the mechanisms of activation and Diels–Alder adduct formation was modelled using DFT calculations with the CAM-B3LYP functional and CEP-31 g basis set, and influence on the reaction profile of the dimiine ligand and phenyl substituent using the larger qzvp basis set. The Rh(III)–OH intemediate is stabilised by H-bonding with methanol and a Cp* CH3 hydrogen. The Rh(I)(Me4fulvene) species, stabilised by interaction of methanol with a coordinated water, again by two H-bonds H2O–HOMe (1.49 Å) and fulvene CH2 (1.94 Å), arises from synchronous transfer of the methanol OH proton to a Rh(III)–OH ligand and Cp* methyl hydrogen to the methanol oxygen. Additionally, the observed trend in catalytic activity for complexes 1–4 was reproduced by DFT calculations. These complexes form a novel class of catalytic molecular motors with a tunable rate of operation that can be stalled in a given state. They provide a basis for elucidation of the effects of ligand design on the contributions of electronic, rotational and vibrational energies to each step in the reaction pathway at the atomic level, consideration of which will enhance the design principles for the next generation of molecular machines

Photopharmacology on Acetylcholinesterase: Novel Photoswitchable Inhibitors with Improved Pharmacological Profiles

Considerable effort has previously been invested in a light‐controlled inhibition of the enzyme acetylcholinesterase (AChE). We found that a novel azobenzene‐based bistacrine AChE inhibitor switched faster than the known dithienylethene based bistacrine and inverted the photo‐controlled interactions of the photoisomers compared to its dithienylethene congener. Furthermore, we have optimized a previously described light‐controlled tacrine‐based AChE inhibitor. Isomerization upon irradiation with UV light of the novel inhibitor was observed in aqueous medium and showed no fatigue over several cycles. The cis‐enriched form showed an 8.4‐fold higher inhibition of hAChE compared with its trans‐enriched form and was about 30‐fold more active than the reference compound tacrine with a single‐digit nanomolar inhibition. We went beyond proof‐of‐concept to discover photoswitchable AChE inhibitors with pharmacologically desirable nanomolar inhibition, “cis‐on” effect, and pronounces differences between the photoisomers

A Phase II Study to Evaluate the Safety and Efficacy of Prasinezumab in Early Parkinson's Disease (PASADENA) : Rationale, Design, and Baseline Data

Altres ajuts: F. Hoffmann-La Roche Ltd.Background: Currently available treatments for Parkinson's disease (PD) do not slow clinical progression nor target alpha-synuclein, a key protein associated with the disease. Objective: The study objective was to evaluate the efficacy and safety of prasinezumab, a humanized monoclonal antibody that binds aggregated alpha-synuclein, in individuals with early PD. Methods: The PASADENA study is a multicenter, randomized, double-blind, placebo-controlled treatment study. Individuals with early PD, recruited across the US and Europe, received monthly intravenous doses of prasinezumab (1,500 or 4,500 mg) or placebo for a 52-week period (Part 1), followed by a 52-week extension (Part 2) in which all participants received active treatment. Key inclusion criteria were: aged 40-80 years; Hoehn & Yahr (H&Y) Stage I or II; time from diagnosis ≤2 years; having bradykinesia plus one other cardinal sign of PD (e.g., resting tremor, rigidity); DAT-SPECT imaging consistent with PD; and either treatment naïve or on a stable monoamine oxidase B (MAO-B) inhibitor dose. Study design assumptions for sample size and study duration were built using a patient cohort from the Parkinson's Progression Marker Initiative (PPMI). In this report, baseline characteristics are compared between the treatment-naïve and MAO-B inhibitor-treated PASADENA cohorts and between the PASADENA and PPMI populations. Results: Of the 443 patients screened, 316 were enrolled into the PASADENA study between June 2017 and November 2018, with an average age of 59.9 years and 67.4% being male. Mean time from diagnosis at baseline was 10.11 months, with 75.3% in H&Y Stage II. Baseline motor and non-motor symptoms (assessed using Movement Disorder Society-Unified Parkinson's Disease Rating Scale [MDS-UPDRS]) were similar in severity between the MAO-B inhibitor-treated and treatment-naïve PASADENA cohorts (MDS-UPDRS sum of Parts I + II + III [standard deviation (SD)]; 30.21 [11.96], 32.10 [13.20], respectively). The overall PASADENA population (63.6% treatment naïve and 36.4% on MAO-B inhibitor) showed a similar severity in MDS-UPDRS scores (e.g., MDS-UPDRS sum of Parts I + II + III [SD]; 31.41 [12.78], 32.63 [13.04], respectively) to the PPMI cohort (all treatment naïve). Conclusions: The PASADENA study population is suitable to investigate the potential of prasinezumab to slow disease progression in individuals with early PD. Trial Registration: NCT03100149

A blood-based signature of cerebrospinal fluid A beta(1-42) status

It is increasingly recognized that Alzheimer's disease (AD) exists before dementia is present and that shifts in amyloid beta occur long before clinical symptoms can be detected. Early detection of these molecular changes is a key aspect for the success of interventions aimed at slowing down rates of cognitive decline. Recent evidence indicates that of the two established methods for measuring amyloid, a decrease in cerebrospinal fluid (CSF) amyloid beta(1-42) (A beta(1-42)) may be an earlier indicator of Alzheimer's disease risk than measures of amyloid obtained from Positron Emission Tomography (PET). However, CSF collection is highly invasive and expensive. In contrast, blood collection is routinely performed, minimally invasive and cheap. In this work, we develop a blood-based signature that can provide a cheap and minimally invasive estimation of an individual's CSF amyloid status using a machine learning approach. We show that a Random Forest model derived from plasma analytes can accurately predict subjects as having abnormal (low) CSF A beta(1-42) levels indicative of AD risk (0.84 AUC, 0.78 sensitivity, and 0.73 specificity). Refinement of the modeling indicates that only APOE epsilon 4 carrier status and four plasma analytes (CGA, A beta(1-42), Eotaxin 3, APOE) are required to achieve a high level of accuracy. Furthermore, we show across an independent validation cohort that individuals with predicted abnormal CSF A beta(1-42) levels transitioned to an AD diagnosis over 120 months significantly faster than those with predicted normal CSF A beta(1-42) levels and that the resulting model also validates reasonably across PET A beta(1-42) status (0.78 AUC). This is the first study to show that a machine learning approach, using plasma protein levels, age and APOE epsilon 4 carrier status, is able to predict CSF A beta(1-42) status, the earliest risk indicator for AD, with high accuracy