Auditory Nerve Fiber Responses to Combined Acoustic and Electric Stimulation

Persons with a prosthesis implanted in a cochlea with residual acoustic sensitivity can, in some cases, achieve better speech perception with “hybrid” stimulation than with either acoustic or electric stimulation presented alone. Such improvements may involve “across auditory-nerve fiber” processes within central nuclei of the auditory system and within-fiber interactions at the level of the auditory nerve. Our study explored acoustic–electric interactions within feline auditory nerve fibers (ANFs) so as to address two goals. First, we sought to better understand recent results that showed non-monotonic recovery of the electrically evoked compound action potential (ECAP) following acoustic masking (Nourski et al. 2007, Hear. Res. 232:87–103). We hypothesized that post-masking changes in ANF temporal properties and responsiveness (spike rate) accounted for the ECAP results. We also sought to describe, more broadly, the changes in ANF responses that result from prior acoustic stimulation. Five response properties—spike rate, latency, jitter, spike amplitude, and spontaneous activity—were examined. Post-masking reductions in spike rate, within-fiber jitter and across-fiber variance in latency were found, with the changes in temporal response properties limited to ANFs with high spontaneous rates. Thus, our results suggest how non-monotonic ECAP recovery occurs for ears with spontaneous activity, but cannot account for that pattern of recovery when there is no spontaneous activity, including the results from the presumably deafened ears used in the Nourski et al. (2007) study. Finally, during simultaneous (electric+acoustic) stimulation, the degree of electrically driven spike activity had a strong influence on spike rate, but did not affect spike jitter, which apparently was determined by the acoustic noise stimulus or spontaneous activity.     

The structural diversity of heterocycle-fused potassium cyclopentadienides

Cyclopentadienides of d- and f-elements are highly important complexes with undoubted potential for practical applications. Annelation of a heterocyclic fragment with an η⁵-ring results in substantial improvement of the catalytic properties of these compounds, called “heterocenes”; the investigation of metal coordination with these specific ligands is a highly important problem. We prepared potassium derivatives 5–8 of heterocycle-annelated cyclopentadienes with different structures – derivatives of cyclopenta[1,2-b:4,3-b′]dithiophene (1), indeno[2,1-b]indole (2), indeno[1,2-b]indole (3), and indeno[1,2-b]indolizine (4) and studied the crystal and molecular structures of these salts by X-ray diffraction. We found that heterocycle-fused cyclopentadienides demonstrate remarkable diversity in metal–ligand coordination modes and crystal packing, with formation of two-dimensional polymeric (5), linear polymeric (6), tetrameric (7) and monomeric (8) structures. The NMR spectral data and results of DFT modeling indicate an increase in electron density in the cyclopentadienyl fragment, and this effect was found to be larger in the derivative of the new indolizine ligand precursor 4. The results of our study will be used in the design of next-generation catalysts of α-olefin polymerization.

Heterocycle-fused cyclopentadienides of potassium demonstrate remarkable diversity in metal–ligand coordination and crystal packing.     

Chemo-informatic strategy for imaging mass spectrometry-based hyperspectral profiling of lipid signatures in colorectal cancer

Mass spectrometry imaging (MSI) provides the opportunity to investigate tumor biology from an entirely novel biochemical perspective and could lead to the identification of a new pool of cancer biomarkers. Effective clinical translation of histology-driven MSI in systems oncology requires precise colocalization of morphological and biochemical features as well as advanced methods for data treatment and interrogation. Currently proposed MSI workflows are subject to several limitations, including nonoptimized raw data preprocessing, imprecise image coregistration, and limited pattern recognition capabilities. Here we outline a comprehensive strategy for histology-driven MSI, using desorption electrospray ionization that covers (i) optimized data preprocessing for improved information recovery; (ii) precise image coregistration; and (iii) efficient extraction of tissue-specific molecular ion signatures for enhanced biochemical distinction of different tissue types. The proposed workflow has been used to investigate region-specific lipid signatures in colorectal cancer tissue. Unique lipid patterns were observed using this approach according to tissue type, and a tissue recognition system using multivariate molecular ion patterns allowed highly accurate (>98%) identification of pixels according to morphology (cancer, healthy mucosa, smooth muscle, and microvasculature). This strategy offers unique insights into tumor microenvironmental biochemistry and should facilitate compilation of a large-scale tissue morphology-specific MSI spectral database with which to pursue next-generation, fully automated histological approaches.Mass spectrometry imaging (MSI) of biological tissue sections can provide topographically localized biochemical information to supplement conventional histopathological classification systems (1–3). Together with emerging metabolomics-based profiling approaches, MSI represents a highly promising approach in molecular systems oncology (4, 5) and is increasingly being used for the discovery of next-generation cancer biomarker panels (6, 7). Among the MSI techniques currently available, the three most commonly used are matrix-assisted laser desorption ionization (MALDI) (2, 6), secondary ion mass spectrometry (SIMS) (8, 9), and desorption electrospray ionization (DESI) (10, 11). With each of these described approaches, operating characteristics and experimental parameters can be modulated to suit specific analytical objectives and can be customized for the identification of particular biomolecular species. Here, we have opted to use the DESI technique as there are several practical advantages with this method for metabolome-wide imaging studies, primarily attributable to lack of requirement for matrix deposition and ambient ionization, which requires minimal sample preparation (11, 12).Currently MSI is likely to exert greatest influence at the prognostic and therapeutic stages of the disease continuum (Fig. 1), with three fundamental areas of application in cancer phenotyping. First, it offers a means of chemically mapping morphological regions of interest to develop next-generation prognostic and therapeutic biomarkers. Second, it permits compartmentalized assessment of the distribution and biochemical influence of chemotherapeutic agents and/or their downstream metabolites within different tissue regions, offering fresh insights into anti-cancer drug efficacy (13, 14). Third, MSI provides the opportunity to develop automated approaches for tissue classification based entirely on molecular ion patterns. Such automated, “machine-learned” strategies will lessen the logistical and financial burden being placed on pathology services in the modern cancer-screening era, while simultaneously ensuring quality control by minimizing interobserver variability (15).Open in a separate windowFig. 1.MS-based imaging technology in clinical settings.Until now the routine clinical application of MSI approaches has been restricted by inherent time/cost demands and associated heavy analytical workload. However, recent advances in MS technology combined with the richness of generated molecular information should ensure the widespread adoption of MSI technologies in the near- to midterm. The major impediment to this progress currently centers on the choice of chemo-informatics workflow. The standard approach applied to MSI datasets involves a series of steps designed to reduce bioanalytical complexities for improved information recovery, followed by pattern recognition analysis and molecular pattern interpretation. Conventional workflows, integrated into software packages such as BioMap (Novartis), SpectViewer (CEA), DataCubeExplorer (AMOLF), and Mirion (JLU) or within commercial packages from instrument manufacturers such as Xcalibur (Thermo Fisher Scientific) and FlexImaging (Bruker Daltonics) have capabilities limited to basic preprocessing and browsing through selected ion images. There is currently strong demand for more sophisticated chemo-informatics strategies that can streamline data processing and simultaneously maximize disease-relevant molecular information capture. In broad terms, these strategies involve (i) raw analytical signal preprocessing for improved information recovery; (ii) imaging informatics for correlation of MSI and histological information; and (iii) pattern recognition analysis for topographically localized biochemical feature extraction. These steps will influence one another and thus need to be considered within an integrated bioinformatics solution (16).Typically, data preprocessing methods involve peak detection or “binning” and filtering of solvent/matrix or noise-related peaks (17–19), followed by a normalization step. At present, the most widely applied approach involves integrating MSI spectra within a predefined “bin” size (typically ∼0.01 Da). This reduces mass detection accuracy and introduces biologically irrelevant spectral features, making unambiguous assignment of chemical species more difficult. In the case of normalization, the total ion current (TIC) scaling factor is frequently cited in the literature as an acceptable means of accounting for global intensity changes in a MSI dataset (20–22). However, we have recently demonstrated that the performance of this method can be compromised by single large molecular ion peak intensities (21, 23). An additional problem inherent to MS-based analysis of complex biological mixtures is the fact that molecules present in greater intensities within a given sample will tend to exhibit larger variations when subjected to repeated measurement (23). This disruption to variance constancy across the measurement range, known in statistical terms as heteroscedasticity, represents a significant barrier to the effective application of commonly used multivariate techniques for the downstream statistical interrogation of MSI datasets (23). To date a number of different strategies have been proposed in the literature to stabilize variance across the measurement range (24), and we have recently validated several variance-stabilizing normalization techniques in the context of MS-based profiling (23).Beyond these preprocessing steps, MSI data need to be effectively “fused” with conventional histopathological information to allow the construction of large-scale molecular databases composed of region-specific molecular biomarkers and facilitate future automated histology initiatives. Precise methods for coregistration of histological and MSI data are an essential prerequisite for these applications and represent a further challenge at present. Of the software packages currently available to the MSI analyst, only the proprietary Bruker package offers image coregistration and region-of-interest molecular ion pattern extraction, with the option to further process extracted spectra in the associated statistical toolbox ClinProTools (25). However, this approach (limited to data collected on Bruker instrumentation) requires the user to manually select features on the pre- and poststaining images to conduct coregistration and can be subject to considerable error. Other less refined platforms have sought to achieve this objective by visual selection of particular regions of interest on hematoxylin and eosin (H&E)-stained optical images, followed by selection of pixels occupying similar (but not precisely aligned) geographical coordinates on corresponding MSI heat maps (22, 26). This permits only very crude colocalization of features from the two imaging modalities and may be deemed sufficient perhaps only in instances where limited variation in cell typology is seen across the tissue section (e.g., cancerous cellular regions and healthy cellular regions only). A number of image informatics methods have been recently developed to segment and to align the objects between images (27, 28). These approaches can involve rigid or nonrigid transformation, depending on object deformation characteristics. The most commonly used methods are based on extensions of the Lucas–Canade algorithm and their relative advantages and limitations have been recently described within a unifying framework (27). However, there is no standardized image coregistration protocol in the context of histology-driven MSI, and the currently used marker-based/fiducial methods may lack the precision required for detailed definition of morphology-to-chemistry interrelationships.Histology-driven, automated tissue identification further requires efficient and robust extraction of tissue-specific molecular ion patterns (19). The multidimensional nature of MSI datasets calls for effective dimensionality reduction techniques that are capable of extracting tissue-specific multivariate molecular ion patterns. Currently, the most widely used supervised dimensionality reduction technique is partial least-squares discriminant analysis (PLS-DA) (29, 30). It has been shown that PLS-based discriminant components are derived by maximizing between-class variance (Table S1) (30). A more mathematically eloquent mode of discriminant analysis is to maximize the difference between class means while simultaneously minimizing within-class variability. This is the objective of linear discriminant analysis (LDA), which maximizes the ratio of between- vs. within-class variance (31). Unfortunately, LDA cannot be directly applied in circumstances where the number of variables exceeds the number of samples, as is the case with the dataset presented here. Principal component analysis (PCA) has been commonly applied as a preprocessing step before LDA (PCA-LDA) to mitigate this problem (32). However, a problem arises here with respect to the selection of an optimal number of components. Introducing too many components into a model will increase the likelihood of LDA model overfit, whereas retaining too few can result in the loss of discriminatory information (33). In the current study, we have proposed the use of a modified maximum margin criterion (Table S1) to improve supervised feature extraction, while simultaneously avoiding arbitrary selection of the number of principal components before discriminant analysis (34).Here, we have devised a comprehensive data analysis framework with the aim of addressing the current challenges outlined above in MSI data treatment and exploration. Specifically, innovative bioinformatics solutions proposed in this study are i) variance-stabilizing normalization for improved information recovery; ii) an automated image coregistration algorithm for intuitive, precise histology-to-chemistry feature correlation; and iii) a unique method for efficient extraction of tissue-specific multivariate ion patterns. As a validation step, the outlined workflow has been applied to the investigation of tumor-surrounding lipid signatures in colorectal cancer (Movies S1 and S2). We demonstrate that this platform provides in-depth insights into tumor biochemistry by simultaneously analyzing the spatial distribution of hundreds to thousands of lipid species across different cell types. This offers potential for the development of next-generation cancer biomarkers and also may have a translational impact beyond the field of clinical histopathology in personalized pharmacotherapy and drug discovery.     

LRIT3 is essential to localize TRPM1 to the dendritic tips of depolarizing bipolar cells and may play a role in cone synapse formation

Mutations in LRIT3 lead to complete congenital stationary night blindness (cCSNB). The exact role of LRIT3 in ON‐bipolar cell signaling cascade remains to be elucidated. Recently, we have characterized a novel mouse model lacking Lrit3 [no b‐wave 6, (Lrit3^nob6/nob6)], which displays similar abnormalities to patients with cCSNB with LRIT3 mutations. Here we compare the localization of components of the ON‐bipolar cell signaling cascade in wild‐type and Lrit3^nob6/nob6 retinal sections by immunofluorescence confocal microscopy. An anti‐LRIT3 antibody was generated. Immunofluorescent staining of LRIT3 in wild‐type mice revealed a specific punctate labeling in the outer plexiform layer (OPL), which was absent in Lrit3^nob6/nob6 mice. LRIT3 did not co‐localize with ribeye or calbindin but co‐localized with mGluR6. TRPM1 staining was severely decreased at the dendritic tips of all depolarizing bipolar cells in Lrit3^nob6/nob6 mice. mGluR6, GPR179, RGS7, RGS11 and Gβ5 immunofluorescence was absent at the dendritic tips of cone ON‐bipolar cells in Lrit3^nob6/nob6 mice, while it was present at the dendritic tips of rod bipolar cells. Furthermore, peanut agglutinin (PNA) labeling was severely reduced in the OPL in Lrit3^nob6/nob6 mice. This study confirmed the localization of LRIT3 at the dendritic tips of depolarizing bipolar cells in mouse retina and demonstrated the dependence of TRPM1 localization on the presence of LRIT3. As tested components of the ON‐bipolar cell signaling cascade and PNA revealed disrupted localization, an additional function of LRIT3 in cone synapse formation is suggested. These results point to a possibly different regulation of the mGluR6 signaling cascade between rod and cone ON‐bipolar cells.     

Core–Shell Fe3O4@C Nanoparticles for the Organic Dye Adsorption and Targeted Magneto-Mechanical Destruction of Ehrlich Ascites Carcinoma Cells

The morphology, structure, and magnetic properties of Fe₃O₄ and Fe₃O₄@C nanoparticles, as well their effectiveness for organic dye adsorption and targeted destruction of carcinoma cells, were studied. The nanoparticles exhibited a high magnetic saturation value (79.4 and 63.8 emu/g, correspondingly) to facilitate magnetic separation. It has been shown that surface properties play a key role in the adsorption process. Both types of organic dyes—cationic (Rhodomine C) and anionic (Congo Red and Eosine)—were well adsorbed by the Fe₃O₄ nanoparticles’ surface, and the adsorption process was described by the polymolecular adsorption model with a maximum adsorption capacity of 58, 22, and 14 mg/g for Congo Red, Eosine, and Rhodomine C, correspondingly. In this case, the kinetic data were described well by the pseudo-first-order model. Carbon-coated particles selectively adsorbed only cationic dyes, and the adsorption process for Methylene Blue was described by the Freundlich model, with a maximum adsorption capacity of 14 mg/g. For the case of Rhodomine C, the adsorption isotherm has a polymolecular character with a maximum adsorption capacity of 34 mg/g. To realize the targeted destruction of the carcinoma cells, the Fe₃O₄@C nanoparticles were functionalized with aptamers, and an experiment on the Ehrlich ascetic carcinoma cells’ destruction was carried out successively using a low-frequency alternating magnetic field. The number of cells destroyed as a result of their interaction with Fe₃O₄@C nanoparticles in an alternating magnetic field was 27%, compared with the number of naturally dead control cells of 6%.     

In vivo assessment of corneal biomechanics under a localized cross-linking treatment using confocal air-coupled optical coherence elastography

The localized application of the riboflavin/UV-A collagen cross-linking (UV-CXL) corneal treatment has been proposed to concentrate the stiffening process only in the compromised regions of the cornea by limiting the epithelium removal and irradiation area. However, current clinical screening devices dedicated to measuring corneal biomechanics cannot provide maps nor spatial-dependent changes of elasticity in corneas when treated locally with UV-CXL. In this study, we leverage our previously reported confocal air-coupled ultrasonic optical coherence elastography (ACUS-OCE) probe to study local changes of corneal elasticity in three cases: untreated, half-CXL-treated, and full-CXL-treated in vivo rabbit corneas (n = 8). We found a significant increase of the shear modulus in the half-treated (>450%) and full-treated (>650%) corneal regions when compared to the non-treated cases. Therefore, the ACUS-OCE technology possesses a great potential in detecting spatially-dependent mechanical properties of the cornea at multiple meridians and generating elastography maps that are clinically relevant for patient-specific treatment planning and monitoring of UV-CXL procedures.     

The EURO-NOTES clinical registry for natural orifice transluminal endoscopic surgery: a 2-year activity report

Background

The EURO-NOTES Clinical Registry (ECR) was established as a European database to allow the monitoring and safe introduction of Natural Orifice Transluminal Endoscopic Surgery (NOTES). The aim of this study was to analyze different techniques applied and relative results during the first 2 years of the ECR.

Methods

The ECR was designed as a voluntary database with online access. All members of the European Society for Gastrointestinal Endoscopy and the European Association for Endoscopic Surgery were requested to participate in the registry. Demographic and therapy data as well as data on the postoperative course are recorded in the ECR in an anonymous way.

Results

A total of 533 patients who underwent NOTES procedures were included in the study. Four different hybrid techniques for 435 cholecystectomies were described, registering postoperative complications in 2.8 % of patients, addition of a single trocar in 5.3 %, and conversions to laparoscopy in 0.5 %. Both flexible endoscopic and rigid laparoscopic cholecystectomy techniques proved to be safe and effective with minor differences. There was a shorter operative time in the rigid laparoscopic group. Thirty-three appendectomies were reported by transgastric and transvaginal techniques, with transvaginal techniques scoring shorter operative time and hospital stay, but with a frequent need to add more trocars. Overall complications occurred in 14.7 % of patients but they did not differ significantly among the different techniques. One transvaginal and 31 transanal sigmoidectomies were included for prolapse and diverticulitis, with four postoperative complications (12.5 %), but none needing further treatment. Twenty peroral esophageal myotomies were included with three postoperative complications (15.0 %), but none needing further treatment.

Conclusions

Five years since the introduction of NOTES into clinical practice, hybrid techniques have gained considerable clinical application. Several NOTES hybrid cholecystectomy and appendectomy techniques are practicable and safe alternatives to laparoscopic procedures. Also, sigmoidectomies and peroral esophageal myotomies were described, proving feasibility and safety. Nevertheless, the real benefit of NOTES for patients still needs to be assessed.