Local Delivery of Therapeutics to the Inner Ear: The State of the Science

BACKGROUND: Advances in the understanding of the genetic and molecular etiologies of inner ear disorders have enabled the identification of therapeutic targets and innovative delivery approaches to the inner ear. As this field grows, the need for knowledge about effective delivery of therapeutics to the inner ear has become a priority. This review maps all clinical and pre-clinical research published in English in the field to date, to guide both researchers and clinicians about local drug delivery methods in the context of novel therapeutics. METHODS: A systematic search was conducted using customized strategies in Cochrane, pubmed and EMBASE databases from inception to 30/09/2018. Two researchers undertook study selection and data extraction independently. RESULTS: Our search returned 12,200 articles, of which 837 articles met the inclusion criteria. 679 were original research and 158 were reviews. There has been a steady increase in the numbers of publications related to inner ear therapeutics delivery over the last three decades, with a sharp rise over the last 2 years. The intra-tympanic route accounts for over 70% of published articles. Less than one third of published research directly assesses delivery efficacy, with most papers using clinical efficacy as a surrogate marker. CONCLUSION: Research into local therapeutic delivery to the inner ear has undergone a recent surge, improving our understanding of how novel therapeutics can be delivered. Direct assessment of delivery efficacy is challenging, especially in humans, and progress in this area is key to understanding how to make decisions about delivery of novel hearing therapeutics

Pyridine functionalized carbon nanotubes: unveiling the role of external pyridinic nitrogen sites for oxygen reduction reaction.

Pyridinic nitrogen has been recognized as the primary active site in nitrogen-doped carbon electrocatalysts for the oxygen reduction reaction (ORR), which is a critical process in many renewable energy devices. However, the preparation of nitrogen-doped carbon catalysts comprised of exclusively pyridinic nitrogen remains challenging, as well as understanding the precise ORR mechanisms on the catalyst. Herein, a novel process is developed using pyridyne reactive intermediates to functionalize carbon nanotubes (CNTs) exclusively with pyridine rings for ORR electrocatalysis. The relationship between the structure and ORR performance of the prepared materials is studied in combination with density functional theory calculations to probe the ORR mechanism on the catalyst. Pyridinic nitrogen can contribute to a more efficient 4-electron reaction pathway, while high level of pyridyne functionalization result in negative structural effects, such as poor electrical conductivity, reduced surface area, and small pore diameters, that suppressed the ORR performance. This study provides insights into pyridine-doped CNTs-functionalized for the first time via pyridyne intermediates-as applied in the ORR and is expected to serve as valuable inspiration in designing high-performance electrocatalysts for energy applications

Advances in understanding of air-sea exchange and cycling of greenhouse gases in the upper ocean

\ua9 2024 University of California Press. All rights reserved. The air–sea exchange and oceanic cycling of greenhouse gases (GHG), including carbon dioxide (CO2), nitrous oxide (N2O), methane (CH4), carbon monoxide (CO), and nitrogen oxides (NOx \ubc NO \ufe NO2), are fundamental in controlling the evolution of the Earth’s atmospheric chemistry and climate. Significant advances have been made over the last 10 years in understanding, instrumentation and methods, as well as deciphering the production and consumption pathways of GHG in the upper ocean (including the surface and subsurface ocean down to approximately 1000 m). The global ocean under current conditions is now well established as a major sink for CO2, a major source for N2O and a minor source for both CH4 and CO. The importance of the ocean as a sink or source of NOx is largely unknown so far. There are still considerable uncertainties about the processes and their major drivers controlling the distributions of N2O, CH4, CO, and NOx in the upper ocean. Without having a fundamental understanding of oceanic GHG production and consumption pathways, our knowledge about the effects of ongoing major oceanic changes—warming, acidification, deoxygenation, and eutrophication—on the oceanic cycling and air–sea exchange of GHG remains rudimentary at best. We suggest that only through a comprehensive, coordinated, and interdisciplinary approach that includes data collection by global observation networks as well as joint process studies can the necessary data be generated to (1) identify the relevant microbial and phytoplankton communities, (2) quantify the rates of ocean GHG production and consumption pathways, (3) comprehend their major drivers, and (4) decipher economic and cultural implications of mitigation solutions

Evidence-based robust optimization of pulsed laser orbital debris removal under epistemic uncertainty

An evidence-based robust optimization method for pulsed laser orbital debris removal (LODR) is presented. Epistemic type uncertainties due to limited knowledge are considered. The objective of the design optimization is set to minimize the debris lifetime while at the same time maximizing the corresponding belief value. The Dempster–Shafer theory of evidence (DST), which merges interval-based and probabilistic uncertainty modeling, is used to model and compute the uncertainty impacts. A Kriging based surrogate is used to reduce the cost due to the expensive numerical life prediction model. Effectiveness of the proposed method is illustrated by a set of benchmark problems. Based on the method, a numerical simulation of the removal of Iridium 33 with pulsed lasers is presented, and the most robust solutions with minimum lifetime under uncertainty are identified using the proposed method

Genetic and epigenetic variations contributed by Alu retrotransposition

<p>Abstract</p> <p>Background</p> <p><it>De novo </it>retrotransposition of Alu elements has been recognized as a major driver for insertion polymorphisms in human populations. In this study, we exploited Alu-anchored bisulfite PCR libraries to identify evolutionarily recent Alu element insertions, and to investigate their genetic and epigenetic variation.</p> <p>Results</p> <p>A total of 327 putatively recent Alu insertions were identified, altogether represented by 1,762 sequence reads. Nearly all such <it>de novo </it>retrotransposition events (316/327) were novel. Forty-seven out of forty-nine randomly selected events, corresponding to nineteen genomic loci, were sequence-verified. Alu element insertions remained hemizygous in one or more individuals in sixteen of the nineteen genomic loci. The Alu elements were found to be enriched for young Alu families with characteristic sequence features, such as the presence of a longer poly(A) tail. In addition, we documented the occurrence of a duplication of the AT-rich target site in their immediate flanking sequences, a hallmark of retrotransposition. Furthermore, we found the sequence motif (TT/AAAA) that is recognized by the ORF2P protein encoded by LINE-1 in their 5'-flanking regions, consistent with the fact that Alu retrotransposition is facilitated by LINE-1 elements. While most of these Alu elements were heavily methylated, we identified an Alu localized 1.5 kb downstream of TOMM5 that exhibited a completely unmethylated left arm. Interestingly, we observed differential methylation of its immediate 5' and 3' flanking CpG dinucleotides, in concordance with the unmethylated and methylated statuses of its internal 5' and 3' sequences, respectively. Importantly, TOMM5's CpG island and the 3 Alu repeats and 1 MIR element localized upstream of this newly inserted Alu were also found to be unmethylated. Methylation analyses of two additional genomic loci revealed no methylation differences in CpG dinucleotides flanking the Alu insertion sites in the two homologous chromosomes, irrespective of the presence or absence of the insertion.</p> <p>Conclusions</p> <p>We anticipate that the combination of methodologies utilized in this study, which included repeat-anchored bisulfite PCR sequencing and the computational analysis pipeline herein reported, will prove invaluable for the generation of genetic and epigenetic variation maps.</p

Robust automated detection of microstructural white matter degeneration in Alzheimer’s disease using machine learning classification of multicenter DTI data

Diffusion tensor imaging (DTI) based assessment of white matter fiber tract integrity can support the diagnosis of Alzheimer’s disease (AD). The use of DTI as a biomarker, however, depends on its applicability in a multicenter setting accounting for effects of different MRI scanners. We applied multivariate machine learning (ML) to a large multicenter sample from the recently created framework of the European DTI study on Dementia (EDSD). We hypothesized that ML approaches may amend effects of multicenter acquisition. We included a sample of 137 patients with clinically probable AD (MMSE 20.6±5.3) and 143 healthy elderly controls, scanned in nine different scanners. For diagnostic classification we used the DTI indices fractional anisotropy (FA) and mean diffusivity (MD) and, for comparison, gray matter and white matter density maps from anatomical MRI. Data were classified using a Support Vector Machine (SVM) and a Naïve Bayes (NB) classifier. We used two cross-validation approaches, (i) test and training samples randomly drawn from the entire data set (pooled cross-validation) and (ii) data from each scanner as test set, and the data from the remaining scanners as training set (scanner-specific cross-validation). In the pooled cross-validation, SVM achieved an accuracy of 80% for FA and 83% for MD. Accuracies for NB were significantly lower, ranging between 68% and 75%. Removing variance components arising from scanners using principal component analysis did not significantly change the classification results for both classifiers. For the scanner-specific cross-validation, the classification accuracy was reduced for both SVM and NB. After mean correction, classification accuracy reached a level comparable to the results obtained from the pooled cross-validation. Our findings support the notion that machine learning classification allows robust classification of DTI data sets arising from multiple scanners, even if a new data set comes from a scanner that was not part of the training sample

Effect of anthropogenic sulphate aerosol in China on the drought in the western-to-central US

In recent decades, droughts have occurred in the western-to-central United States (US), significantly affecting food production, water supplies, ecosystem health, and the propagation of vector-borne diseases. Previous studies have suggested natural sea surface temperature (SST) forcing in the Pacific as the main driver of precipitation deficits in the US. Here, we show that the aerosol forcing in China, which has been known to alter the regional hydrological cycle in East Asia, may also contribute to reducing the precipitation in the western-to-central US through atmospheric teleconnections across the Pacific. Our model experiments show some indications that both the SST forcing and the increase in regional sulphate forcing in China play a similar role in modulating the western-to-central US precipitation, especially its long-term variation. This result indicates that regional air quality regulations in China have important implications for hydrological cycles in East Asia, as well as in the USopen1

FORMATION AND COALESCENCE OF FULLERENE IONS FROM DIRECT LASER VAPORIZATION

A series of carbon cluster ions have been created by direct laser vaporization of elementary carbons and organic compounds with different structures and compositions. The mass spectra of the carbon cluster ions were recorded in situ by a time-of-flight mass spectrometer and the experimental results showed that the formation of fullerenes and their relative abundances are closely related to the surface structure of the sample. Under direct laser vaporization, the products from a perfect (0001) surface of graphite were mainly C-60 and C-70. The surface perpendicular to the (0001) plane of graphite could not produce C-60, other fullerene ions or compounds containing six-membered aromatic carbon rings. The products of amorphous carbon and aromatic compounds included C-60 and other fullerenes, among which those with a mass twice that of C-60 were most abundant. Furthermore, C-60 and C-70 could also be aggregated from direct laser vaporization. Based on these experimental results, mechanism for formation of C-60 and other fullerenes is suggested