Developing a pragmatic consensus procedure supporting the ICH S1B(R1) weight of evidence carcinogenicity assessment

The ICH S1B carcinogenicity global testing guideline has been recently revised with a novel addendum that describes a comprehensive integrated Weight of Evidence (WoE) approach to determine the need for a 2-year rat carcinogenicity study. In the present work, experts from different organizations have joined efforts to standardize as much as possible a procedural framework for the integration of evidence associated with the different ICH S1B(R1) WoE criteria. The framework uses a pragmatic consensus procedure for carcinogenicity hazard assessment to facilitate transparent, consistent, and documented decision-making and it discusses best-practices both for the organization of studies and presentation of data in a format suitable for regulatory review. First, it is acknowledged that the six WoE factors described in the addendum form an integrated network of evidence within a holistic assessment framework that is used synergistically to analyze and explain safety signals. Second, the proposed standardized procedure builds upon different considerations related to the primary sources of evidence, mechanistic analysis, alternative methodologies and novel investigative approaches, metabolites, and reliability of the data and other acquired information. Each of the six WoE factors is described highlighting how they can contribute evidence for the overall WoE assessment. A suggested reporting format to summarize the cross-integration of evidence from the different WoE factors is also presented. This work also notes that even if a 2-year rat study is ultimately required, creating a WoE assessment is valuable in understanding the specific factors and levels of human carcinogenic risk better than have been identified previously with the 2-year rat bioassay alone.

Treatment of Olfactory Disorders After SARS - CoViD 2 Virus Infection

OBJECTIVE

The benefit of a nasal corticosteroid in the treatment of persistent post-infectious smell disorders is not as clear in previous studies as is assumed for olfactory training. This study would therefore like to describe the treatment strategies using the example of a persistent olfactory dysfunction as a result of a proven infection with SARS-CoViD-2-virus.

METHODS

Twenty patients (average age of 33.9 ± 11.9 years) with hyposmia were included in this study from December 2020 to July 2021. Every second patient received additionally a nasal corticosteroid. The two resulting randomized groups of equal size were screened with the TDI test, a 20-item taste powder test for the assessment of retronasal olfaction and otorhinolaryngological examination. The patients were asked to train twice daily using a standardized odor training kit and followed up after 2 months and 3 months, respectively.

RESULTS

We documented a significant overall improvement in olfactory ability over the investigation period in both groups. While the TDI score steadily increased on average under the combination therapy, the rise under olfactory training alone was initially steeper. This short-term interaction effect over mean two months was not statistically significant. According to Cohen, however, a moderate effect (eta2 = 0.055, Cohen`s d = 0.5) can still be assumed. This effect could be explained by a possibly higher compliance at the beginning of the sole olfactory training due to the lack of further drug treatment offers. When the training intensity decreases, the recovery of the sense of smell stagnates. Adjunctive therapy ultimately outweighs this short-term benefit.

CONCLUSIONS

The results reinforce the recommendation of early and consistent olfactory training on patients with dysosmia due to COVID-19. For continuous improvement of the sense of smell, an accompanying topical treatment seems at least to be worth consideration. The results should be optimized with larger cohorts and using new objective olfactometric methods.

Postoperative serum C-reactive protein dynamics after pharyngolaryngectomy with jejunal free-flap reconstruction

INTRODUCTION

Pharyngolaryngectomy with jejunal free-flap (JFF) reconstruction can be offered for locally advanced hypopharyngeal cancer. However, the procedure carries significant morbidity. Postoperative serial serum C-reactive protein (CRP) has been shown to be a marker predicting postoperative complications, and the aim of this study was to describe the dynamics and value of CRP in this patient group.

METHODS

Retrospective analysis of pharyngolaryngectomies with JFF reconstruction was performed in our institution. Daily postoperative CRP values were analysed within the first 14 days, as were complications.

RESULTS

Twenty-one cases were included. Total morbidity was 57.1% including 14.3% (temporary) anastomotic leaks and 14.3% flap failures. Patients in the normal group showed peak CRP levels around postoperative day 2 (2.2). Increased CRP levels on or after day 4 were associated with complications (p<0.01) with a sensitivity of 83.3% and specificity of 77.8%. In keeping with CRP kinetics from other surgical studies, peak CRP values on day 2 or 3 are expected, followed by a decline. Peaks in CRP on day 4 or later raise the suspicion of complications. CRP is not specific for any one complication but rather can help guide early appropriate clinical assessment and management.

CONCLUSIONS

The natural postoperative CRP response peaks around postoperative day 2 (2.2) and declines thereafter. Rising CRP levels after postoperative day 3 are suspicious of surgical complications (p<0.01) with positive and negative predictive values of 83.3% and 77.8%, respectively. Therefore, serial postoperative CRP can be used as an adjunct to monitor outcomes in this group.

The impact of a structured one-day seminar on disease-specific knowledge, lifestyle habits and disease impairment in ANCA-associated vasculitis. Results of a randomized, controlled study

OBJECTIVE

Anti-neutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) is a complex, chronic autoimmune disease, and its diagnosis triggers considerable anxiety and uncertainty for those affected. There are currently no valid data describing the impact of disease-specific patient education on the disease knowledge, subjective impairment, and changes in lifestyle habits related to AAV.

METHOD

We designed a one-day educational programme to serve AAV patients with information about their disease and its treatment. Patients were randomized into an intervention group and a waiting list control group. Increase in knowledge was measured with a multiple-choice test. The intervention group completed the questionnaire before, directly after, and 3 months after the seminar, while the waiting list control group was additionally tested 3 months before the seminar to rule out non-specific learning. Furthermore, we investigated the burden of the disease and the impact of our intervention on this burden.

RESULTS

Compared with the control group, the intervention increased the knowledge (mean ± sd score difference 2.2 ± 1.0, 95% confidence interval 0.1-4.3, p = 0.04). From the patients' point of view, their understanding of the disease had improved and the subjective impairment caused by their rheumatic disease had decreased. There was a tendency to include disease-relevant behaviour, such as nasal care or dietary recommendations, more often in everyday life.

CONCLUSION

A one-day seminar is suitable to increase the disease-specific knowledge of patients with AAV in a sustainable manner. In addition, our measure positively affected the disease-relevant behaviour.

Predicting DNA-Reactivity of N-Nitrosamines: A Quantum Chemical Approach

N-Nitrosamines (NAs) are a class of reactive organic chemicals that humans may be exposed to from environmental sources, food but also impurities in pharmaceutical preparations. Some NAs were identified as DNA-reactive mutagens and many of those have been classified as probable human carcinogens. Beyond high-potency mutagenic carcinogens that need to be strictly controlled, NAs of low potency need to be considered for risk assessment as well. NA impurities and nitrosylated products of active pharmaceutical ingredients (APIs) often arise from production processes or degradation. Most NAs require metabolic activation to ultimately become carcinogens, and their activation can be appropriately described by first-principles computational chemistry approaches. To this end, we treat NA-induced DNA alkylation as a series of subsequent association and dissociation reaction steps that can be calculated stringently by density functional theory (DFT), including α-hydroxylation, proton transfer, hydroxyl elimination, direct S_N2/S_NAr DNA alkylation, competing hydrolysis and S_N1 reactions. Both toxification and detoxification reactions are considered. The activation reactions are modeled by DFT at a high level of theory with an appropriate solvent model to compute Gibbs free energies of the reactions (thermodynamical effects) and activation barriers (kinetic effects). We study congeneric series of aliphatic and cyclic NAs to identify trends. Overall, this work reveals detailed insight into mechanisms of activation for NAs, suggesting that individual steric and electronic factors have directing and rate-determining influence on the formation of carbenium ions as the ultimate pro-mutagens and thus carcinogens. Therefore, an individual risk assessment of NAs is suggested, as exemplified for the complex API-like 4-(N-nitroso-N-methyl)aminoantipyrine which is considered as low-potency NA by in silico prediction.

Cross clinical-experimental-computational qualification of in silico drug trials on human cardiac purkinje cells for proarrhythmia risk prediction

The preclinical identification of drug-induced cardiotoxicity and its translation into human risk are still major challenges in pharmaceutical drug discovery. The ICH S7B Guideline and Q&A on Clinical and Nonclinical Evaluation of QT/QTc Interval Prolongation and Proarrhythmic Potential promotes human in silico drug trials as a novel tool for proarrhythmia risk assessment. To facilitate the use of in silico data in regulatory submissions, explanatory control compounds should be tested and documented to demonstrate consistency between predictions and the historic validation data. This study aims to quantify drug-induced electrophysiological effects on in silico cardiac human Purkinje cells, to compare them with existing in vitro rabbit data, and to assess their accuracy for clinical pro-arrhythmic risk predictions. The effects of 14 reference compounds were quantified in simulations with a population of in silico human cardiac Purkinje models. For each drug dose, five electrophysiological biomarkers were quantified at three pacing frequencies, and results compared with available in vitro experiments and clinical proarrhythmia reports. Three key results were obtained: 1) In silico, repolarization abnormalities in human Purkinje simulations predicted drug-induced arrhythmia for all risky compounds, showing higher predicted accuracy than rabbit experiments; 2) Drug-induced electrophysiological changes observed in human-based simulations showed a high degree of consistency with in vitro rabbit recordings at all pacing frequencies, and depolarization velocity and action potential duration were the most consistent biomarkers; 3) discrepancies observed for dofetilide, sotalol and terfenadine are mainly caused by species differences between humans and rabbit. Taken together, this study demonstrates higher accuracy of in silico methods compared to in vitro animal models for pro-arrhythmic risk prediction, as well as a high degree of consistency with in vitro experiments commonly used in safety pharmacology, supporting the potential for industrial and regulatory adoption of in silico trials for proarrhythmia prediction.

Martian CO2 Ice Observation at High Spectral Resolution With ExoMars/TGO NOMAD

The Nadir and Occultation for MArs Discovery (NOMAD) instrument suite aboard ExoMars/Trace Gas Orbiter spacecraft is mainly conceived for the study of minor atmospheric species, but it also offers the opportunity to investigate surface composition and aerosols properties. We investigate the information content of the Limb, Nadir, and Occultation (LNO) infrared channel of NOMAD and demonstrate how spectral orders 169, 189, and 190 can be exploited to detect surface CO₂ ice. We study the strong CO₂ ice absorption band at 2.7 μm and the shallower band at 2.35 μm taking advantage of observations across Martian Years 34 and 35 (March 2018 to February 2020), straddling a global dust storm. We obtain latitudinal-seasonal maps for CO₂ ice in both polar regions, in overall agreement with predictions by a general climate model and with the Mars Express/OMEGA spectrometer Martian Years 27 and 28 observations. We find that the narrow 2.35 μm absorption band, spectrally well covered by LNO order 189, offers the most promising potential for the retrieval of CO₂ ice microphysical properties. Occurrences of CO₂ ice spectra are also detected at low latitudes and we discuss about their interpretation as daytime high altitude CO₂ ice clouds as opposed to surface frost. We find that the clouds hypothesis is preferable on the basis of surface temperature, local time and grain size considerations, resulting in the first detection of CO₂ ice clouds through the study of this spectral range. Through radiative transfer considerations on these detections we find that the 2.35 μm absorption feature of CO₂ ice clouds is possibly sensitive to nm-sized ice grains.

Rational Design of Highly Potent, Selective, and Bioavailable SGK1 Protein Kinase Inhibitors for the Treatment of Osteoarthritis

The serine/threonine kinase SGK1 is an activator of the β-catenin pathway and a powerful stimulator of cartilage degradation that is found to be upregulated under genomic control in diseased osteoarthritic cartilage. Today, no oral disease-modifying treatments are available and chronic treatment in this indication sets high requirements for the drug selectivity, pharmacokinetic, and safety profile. We describe the identification of a highly selective druglike 1H-pyrazolo[3,4-d]pyrimidine SGK1 inhibitor 17a that matches both safety and pharmacokinetic requirements for oral dosing. Rational compound design was facilitated by a novel hSGK1 co-crystal structure, and multiple ligand-based computer models were applied to guide the chemical optimization of the compound ADMET and selectivity profiles. Compounds were selected for subchronic proof of mechanism studies in the mouse femoral head cartilage explant model, and compound 17a emerged as a druglike SGK1 inhibitor, with a highly optimized profile suitable for oral dosing as a novel, potentially disease-modifying agent for osteoarthritis.

Application of Deep Neural Network Models in Drug Discovery Programs

In silico driven optimization of compound properties related to pharmacokinetics, pharmacodynamics, and safety is a key requirement in modern drug discovery. Nowadays, large and harmonized datasets allow to implement deep neural networks (DNNs) as a framework for leveraging predictive models. Nevertheless, various available model architectures differ in their global applicability and performance in lead optimization projects, such as stability over time and interpretability of the results. Here, we describe and compare the value of established DNN-based methods for the prediction of key ADME property trends and biological activity in an industrial drug discovery environment, represented by microsomal lability, CYP3A4 inhibition and factor Xa inhibition. Three architectures are exemplified, our earlier described multilayer perceptron approach (MLP), graph convolutional network-based models (GCN) and a vector representation approach, Mol2Vec. From a statistical perspective, MLP and GCN were found to perform superior over Mol2Vec, when applied to external validation sets. Interestingly, GCN-based predictions are most stable over a longer period in a time series validation study. Apart from those statistical observations, DNN prove of value to guide local SAR. To illustrate this important aspect in pharmaceutical research projects, we discuss challenging applications in medicinal chemistry towards a more realistic picture of artificial intelligence in drug discovery.

Automation of peptide desalting for proteomic liquid chromatography - tandem mass spectrometry by centrifugal microfluidics

For large-scale analysis of complex protein mixtures, liquid chromatography - tandem mass spectrometry (LC-MS/MS) has been proven to be one of the most versatile tools due to its high sensitivity and ability to both identify and quantify thousands of proteins in a single measurement. Sample preparation typically comprises site-specific cleavage of proteins into peptides, followed by desalting and concomitant peptide enrichment, which is commonly performed by solid phase extraction. Desalting workflows may include multiple liquid handling steps and are thus error prone and labour intensive. To improve the reproducibility of sample preparation for low amounts of protein, we present a centrifugal microfluidic disk that automates all liquid handling steps required for peptide desalting by solid phase extraction (DesaltingDisk). Microfluidic implementation was enabled by a novel centrifugal microfluidic dosing on demand structure that enabled mapping multiple washing steps onto a microfluidic disk. Evaluation of the microfluidic disk was performed by LC-MS/MS analysis of tryptic HEK-293 eukaryotic cell peptide mixtures desalted either using the microfluidic disk or a manual workflow. A comparable number of peptides were identified in the disk and manual set with 19 775 and 20 212 identifications, respectively. For a core set of 10 444 peptides that could be quantified in all injections, intensity coefficients of variation were calculated based on label-free quantitation intensities. The disk set featured smaller variability with a median CV of 9.3% compared to the median CV of 12.6% for the manual approach. Intensity CVs on protein level were lowered from 5.8% to 4.2% when using the LabDisk. Interday reproducibility for both workflows was assessed by LC-SRM/MS analysis of samples that were spiked with 11 synthetic peptides of varying hydrophobicity. Except for the most hydrophilic and hydrophobic peptides, the average CV was lowered to 3.6% for the samples processed with the disk compared to 7.2% for the manual workflow. The presented centrifugal microfluidic DesaltingDisk demonstrates the potential to improve reproducibility in the sample preparation workflow for proteomic mass spectrometry, especially for application with limited amount of sample material.

In-hospital outcomes of catheter-directed thrombolysis in patients with pulmonary embolism

Background and purpose

Catheter-directed treatment of acute pulmonary embolism (PE) is technically advancing. Recent guidelines acknowledge this treatment option for patients with overt or imminent haemodynamic decompensation, particularly when systemic thrombolysis is contraindicated or has failed. We investigated baseline characteristics and in-hospital outcomes of patients with PE who underwent catheter-directed thrombolysis (CDT) in the German nationwide inpatient cohort.

Methods

Data from hospitalizations with PE between 2005 and 2016 were collected by the Federal Office of Statistics (Statistisches Bundesamt) in Germany and included in this analysis. Patients with PE who underwent CDT were compared with patients receiving systemic thrombolysis, and those without thromboytic or other reperfusion treatment.

Results

We analyzed data from 978,094 hospitalized patients with PE. Of these, 41,903 (4.3%) patients received thrombolytic treatment (systemic thrombolysis in 4.2%, CDT in 0.1%). Among PE patients with shock, CDT was associated with lower in-hospital mortality compared to systemic thrombolysis (OR, 0.29, 95% CI 0.13–0.66, P=0.003). No intracranial bleeding occurred among PE patients with shock who received CDT. Among haemodynamically stable PE patients with right ventricular (RV) dysfunction (intermediate-risk PE), CDT also was associated with a lower risk of in-hospital mortality compared to systemic thrombolysis (OR, 0.52 [95% CI 0.38–0.70]; P&lt;0.001) or no thrombolytic treatment (0.45 [95% CI 0.33–0.62]; P&lt;0.001).

Conclusion

In the German nationwide inpatient cohort, CDT was associated with lower in-hospital mortality rates compared to systemic thrombolysis. Prospective controlled data are urgently needed to determine the true value of this treatment option in acute PE.

Funding Acknowledgement

Type of funding source: Public grant(s) – National budget only. Main funding source(s): This study was supported by the German Federal Ministry of Education and Research (BMBF 01EO1503).

Tryptic digestion of human serum for proteomic mass spectrometry automated by centrifugal microfluidics

Mass spectrometry has become an important analytical tool for protein research studies to identify, characterise and quantify proteins with unmatched sensitivity in a highly parallel manner. When transferred into clinical routine, the cumbersome and error-prone sample preparation workflows present a major bottleneck. In this work, we demonstrate tryptic digestion of human serum that is fully automated by centrifugal microfluidics. The automated workflow comprises denaturation, digestion and acidification. The input sample volume is 1.3 μl only. A triplicate of human serum was digested with the developed microfluidic chip as well as with a manual reference workflow on three consecutive days to assess the performance of our system. After desalting and liquid chromatography tandem mass spectrometry, a total of 604 proteins were identified in the samples digested with the microfluidic chip and 602 proteins with the reference workflow. Protein quantitation was performed using the Hi3 method, yielding a 7.6% lower median intensity CV for automatically digested samples compared to samples digested with the reference workflow. Additionally, 17% more proteins were quantitated with less than 30% CV in the samples from the microfluidic chip, compared to the manual control samples. This improvement can be attributed to the accurate liquid metering with all volume CVs below 1.5% on the microfluidic chip. The presented automation solution is attractive for laboratories in need of robust automation of sample preparation from small volumes as well as for labs with a low or medium throughput that does not allow for large investments in robotic systems.

A practical guide to secondary pharmacology in drug discovery

Secondary pharmacological profiling is increasingly applied in pharmaceutical drug discovery to address unwanted pharmacological side effects of drug candidates before entering the clinic. Regulators, drug makers and patients share a demand for deep characterization of secondary pharmacology effects of novel drugs and their metabolites. The scope of such profiling has therefore expanded substantially in the past two decades, leading to the implementation of broad in silico profiling methods and focused in vitro off-target screening panels, to identify liabilities, but also opportunities, as early as possible. The pharmaceutical industry applies such panels at all stages of drug discovery routinely up to early development. Nevertheless, target composition, screening technologies, assay formats, interpretation and scheduling of panels can vary significantly between companies in the absence of dedicated guidelines. To contribute towards best practices in secondary pharmacology profiling, this review aims to summarize the state-of-the art in this field. Considerations are discussed with respect to panel design, screening strategy, implementation and interpretation of the data, including regulatory perspectives. The cascaded, or integrated, use of in silico and off-target profiling allows to exploit synergies for comprehensive safety assessment of drug candidates.

Computational Investigation of Drug Phototoxicity: Photosafety Assessment, Photo-Toxophore Identification, and Machine Learning

One of the most appreciated capabilities of computational toxicology is to support the design of pharmaceuticals with reduced toxicological hazard. To this end, we have strengthened our drug photosafety assessments by applying novel computer models for the anticipation of in vitro phototoxicity and human photosensitization. These models are typically used in pharmaceutical discovery projects as part of the compound toxicity assessments and compound optimization methods. To ensure good data quality and aiming at models with global applicability we separately compiled and curated highly chemically diverse data sets from 3T3 NRU phototoxicity reports (450 compounds) and clinical photosensitization alerts (1419 compounds) which are provided as supplements. The latter data gives rise to a comprehensive list of explanatory fragments for visual guidance, termed phototoxophores, by application of a Bayesian statistics approach. To extend beyond the domain of well sampled fragments we applied machine learning techniques based on explanatory descriptors such as pharmacophoric fingerprints or, more important, accurate electronic energy descriptors. Electronic descriptors were extracted from quantum chemical computations at the density functional theory (DFT) level. Accurate UV/vis spectral absorption descriptors and pharmacophoric fingerprints turned out to be necessary for predictive computer models, which were both derived from Deep Neural Networks but also the simpler Random Decision Forests approach. Model accuracies of 83-85% could typically be reached for diverse test data sets and other company in-house data, while model sensitivity (the capability of correctly detecting toxicants) was even better, reaching 86%-90%. Importantly, a computer model-triggered response-map allowed for graphical/chemical interpretability also in the case of previously unknown phototoxophores. The photosafety models described here are currently applied in a prospective manner for the hazard identification, prioritization, and optimization of newly designed molecules.

Mechanical load exerted by PET-G aligners during mesial and distal derotation of a mandibular canine : An in vitro study

INTRODUCTION

The six force-moment (F/M) components exerted by aligners of different thickness during simulated mesiorotation and distorotation of a mandibular canine were studied.

MATERIALS AND METHODS

An acrylic mandibular model with a separated right canine mounted on a hexapod via a 3D F/M sensor was used. Duran+^® aligners (Scheu Dental, Germany) of thickness 0.5, 0.625, and 0.75 mm were fabricated on plaster models with the measurement tooth in its neutral position. The F/M values were recorded during progressive mesiorotation or distorotation of tooth 43 in 1° steps up to ±15°, corresponding to 0.5 mm displacements of the tooth's interdental contacts. Each rotation step included renewed seating of the aligner on the acrylic model. Three aligners were tested three times each for each thickness and direction of rotation.

RESULTS

The median rotational moments for the 0.5 mm aligner and 15° distorotation of tooth 43 was 27.49 Nmm (interquartile range, IQR 1.45 Nmm). The corresponding values for the 0.625 and 0.75 mm aligners were 41.04 Nmm (IQR 5.62 Nmm) and 42.48 Nmm (IQR 2.17 Nmm), respectively. The average rotational moments for distorotation were 15% higher than for mesiorotation (p = 0.01). Relatively high collateral F/M components, specifically an intrusive force and labiolingual and mesiodistal tipping moments, were observed.

CONCLUSION

To avoid overloading of periodontal structures, derotation of lower canines should be limited to 10° per setup step, leading to rotational moments of about 15 Nmm. The mechanical behavior of the 0.625 and 0.75 mm aligners were similar; thus, it may be omitted from the aligner sequence. Further studies are required to investigate specific aligner modifications or attachments for minimizing collateral F/M components or unwanted movements, respectively, during canine derotation.

In vitro secondary pharmacological profiling: An IQ-DruSafe industry survey on current practices

INTRODUCTION

In 2015, IQ DruSafe conducted a survey of its membership to identify industry practices related to in vitro off target pharmacological profiling of small molecules.

METHODS

An anonymous survey of 20 questions was submitted to IQ-DruSafe representatives. Questions were designed to explore screening strategies, methods employed and experience of regulatory interactions related to in vitro secondary pharmacology profiling.

RESULTS

The pharmaceutical industry routinely utilizes panels of in vitro assays to detect undesirable off-target interactions of new chemical entities that are deployed at all stages of drug discovery and early development. The formats, approaches and size of panels vary between companies, in particular i) choice of assay technology; ii) test concentration (single vs. multiple concentrations) iii) rationale for targets and panels selection (taking into account organizational experience, primary target, therapeutic area, availability at service providers) iv) threshold level for significant interaction with a target and v) data interpretation. Data are generated during the early phases of drug discovery, principally before in vivo GLP studies (i.e., hit-to-lead, lead optimization, development candidate selection) and used to contextualize in vivo non-clinical and clinical findings. Data were included in regulatory documents, and around half of respondents experienced regulatory questions about the significance of the results.

CONCLUSION

While it seems that in vitro secondary pharmacological profiling is generally considered valuable across the industry, particularly as a tool in early phases of drug discovery for small molecules, there is only loose consensus on testing paradigm, the required interpretation and suitable follow up strategies to fully understand potential risk.

MRI-Based Methods for Spinal Cord Atrophy Evaluation: A Comparison of Cervical Cord Cross-Sectional Area, Cervical Cord Volume, and Full Spinal Cord Volume in Patients with Aquaporin-4 Antibody Seropositive Neuromyelitis Optica Spectrum Disorders

BACKGROUND AND PURPOSE

Measures for spinal cord atrophy have become increasingly important as imaging biomarkers in the assessment of neuroinflammatory diseases, especially in neuromyelitis optica spectrum disorders. The most commonly used method, mean upper cervical cord area, is relatively easy to measure and can be performed on brain MRIs that capture cervical myelon. Measures of spinal cord volume (eg, cervical cord volume or total cord volume) require longer scanning and more complex analysis but are potentially better suited as spinal cord atrophy measures. This study investigated spinal cord atrophy measures in a cohort of healthy subjects and patients with aquaporin-4 antibody seropositive neuromyelitis optica spectrum disorders and evaluated the discriminatory performance of mean upper cervical cord cross-sectional area compared with cervical cord volume and total cord volume.

MATERIALS AND METHODS

Mean upper cervical cord area, cervical cord volume, and total cord volume were measured using 3T MRIs from healthy subjects (n = 19) and patients with neuromyelitis optica spectrum disorders (n = 30). Group comparison and receiver operating characteristic analyses between healthy controls and patients with neuromyelitis optica spectrum disorders were performed.

RESULTS

Mean upper cervical cord area, cervical cord volume, and total cord volume measures showed similar and highly significant group differences between healthy control subjects and patients with neuromyelitis optica spectrum disorders (P < .01 for all). All 3 measures showed similar receiver operating characteristic-area under the curve values (mean upper cervical cord area = 0.70, cervical cord volume = 0.75, total cord volume = 0.77) with no significant difference between them. No associations among mean upper cervical cord cross-sectional area, cervical cord volume, or total cord volume with disability measures were found.

CONCLUSIONS

All 3 measures showed similar discriminatory power between healthy control and neuromyelitis optica spectrum disorders groups. Mean upper cervical cord area is easier to obtain compared with cervical cord volume and total cord volume and can be regarded as an efficient representative measure of spinal cord atrophy in the neuromyelitis optica spectrum disorders context.

Negative effective Li transference numbers in Li salt/ionic liquid mixtures: does Li drift in the “Wrong” direction?

Due to association with anions and an inverted drift direction in an electric field, Li⁺ cations have negative effective transference numbers.

Pedunculated, well differentiated liposarcoma of the oesophagus mimicking giant fibrovascular polyp

We present a rare case of a big oesophageal liposarcoma causing dysphagia and weight loss in a 75-year-old patient. Endoscopically, a pedunculated lesion with subtotal obstruction of the oesophageal lumen had been detected and thoracoabdominal oesophageal resection with gastric sleeve reconstruction was performed. Surprisingly, a liposarcoma of the oesophagus was revealed on histopathological analysis, showing MDM2 overexpression. Oncological follow-up has been uneventful and the patient remains in good clinical shape at 15 months after surgery.

Back to the roots? Dual cannulation strategy for ambulatory ECMO in adolescent lung transplant candidates: An alternative?

Bridging critically ill pediatric patients to lung transplantation still remains a major challenge. Although still controversial, within the last 5 years, ECMO has been increasingly used as a bridge to lung transplantation concept in adult and pediatric patients with acceptable outcomes. The outstanding developments in the field of extracorporeal devices and the introduction of awake ECMO concepts with the avoidance of mechanical ventilation have led to a real paradigm shift in the ICU management of pretransplant candidates with severe respiratory failure. Therefore, ECMO is no longer seen as a contraindication for lung transplantation at least at our center. Nevertheless, how to bridge these patients on ECMO still remains controversial. Thus, we introduced an ambulatory ECMO approach in adolescent lung transplant candidates with acute respiratory failure using a dual cannulation strategy and hereby present first results from this procedure.

Post-invasion events after infection with Staphylococcus aureus are strongly dependent on both the host cell type and the infecting S. aureus strain

Host cell invasion is a major feature of Staphylococcus aureus and contributes to infection development. The intracellular metabolically active bacteria can induce host cell activation and death but they can also persist for long time periods. In this study a comparative analysis was performed of different well-characterized S. aureus strains in their interaction with a variety of host cell types. Staphylococcus aureus (strains 6850, USA300, LS1, SH1000, Cowan1) invasion was compared in different human cell types (epithelial and endothelial cells, keratinocytes, fibroblasts, osteoblasts). The number of intracellular bacteria was determined, cell inflammation was investigated, as well as cell death and phagosomal escape of bacteria. To explain strain-dependent differences in the secretome, a proteomic approach was used. Barrier cells took up high amounts of bacteria and were killed by aggressive strains. These strains expressed high levels of toxins, and possessed the ability to escape from phagolysosomes. Osteoblasts and keratinocytes ingested less bacteria, and were not killed, even though the primary osteoblasts were strongly activated by S. aureus. In all cell types S. aureus was able to persist. Strong differences in uptake, cytotoxicity, and inflammatory response were observed between primary cells and their corresponding cell lines, demonstrating that cell lines reflect only partially the functions and physiology of primary cells. This study provides a contribution for a better understanding of the pathomechanisms of S. aureus infections. The proteomic data provide important basic knowledge on strains commonly used in the analysis of S. aureus-host cell interaction.

Combination effects of azole fungicides in male rats in a broad dose range

Two 28-day feeding studies were performed in male rats to investigate combination effects of azole fungicides in a broad dose range. Following separate administration of cyproconazole, epoxiconazole, prochloraz, propiconazole, and tebuconazole at five dose levels, the first three compounds were selected to be administered in two different mixtures at three dose levels including very low doses. Here we present the data obtained by clinical observations, pathology, histopathology, clinical chemistry and haematology. The liver was the common main target organ of all compounds and their mixtures. In addition, epoxiconazole exhibited an effect on the adrenals. Furthermore, food consumption and efficiency and body weight (gain) were affected. Adverse effects of the combinations were observed at dose levels at which the individual substances caused similar effects. No evidence of adverse effects was found at dose levels below the previously established NOAELs. Our findings indicate that the concept of dose additivity appears sufficiently protective for risk assessment of the fungicides examined. Besides toxicological testing, tissue residues of the azole compounds in liver, testis and kidney were determined revealing remarkable differences following administration of the single substances and of the mixtures.

Computational Models for Human and Animal Hepatotoxicity with a Global Application Scope

Hepatic toxicity is a key concern for novel pharmaceutical drugs since it is difficult to anticipate in preclinical models, and it can originate from pharmacologically unrelated drug effects, such as pathway interference, metabolism, and drug accumulation. Because liver toxicity still ranks among the top reasons for drug attrition, the reliable prediction of adverse hepatic effects is a substantial challenge in drug discovery and development. To this end, more effort needs to be focused on the development of improved predictive in-vitro and in-silico approaches. Current computational models often lack applicability to novel pharmaceutical candidates, typically due to insufficient coverage of the chemical space of interest, which is either imposed by size or diversity of the training data. Hence, there is an urgent need for better computational models to allow for the identification of safe drug candidates and to support experimental design. In this context, a large data set comprising 3712 compounds with liver related toxicity findings in humans and animals was collected from various sources. The complex pathology was clustered into 21 preclinical and human hepatotoxicity endpoints, which were organized into three levels of detail. Support vector machine models were trained for each endpoint, using optimized descriptor sets from chemometrics software. The optimized global human hepatotoxicity model has high sensitivity (68%) and excellent specificity (95%) in an internal validation set of 221 compounds. Models for preclinical endpoints performed similarly. To allow for reliable prediction of "truly external" novel compounds, all predictions are tagged with confidence parameters. These parameters are derived from a statistical analysis of the predictive probability densities. The whole approach was validated for an external validation set of 269 proprietary compounds. The models are fully integrated into our early safety in-silico workflow.

Computational Models for Human and Animal Hepatotoxicity with a Global Application Scope

Hepatic toxicity is a key concern for novel pharmaceutical drugs since it is difficult to anticipate in preclinical models, and it can originate from pharmacologically unrelated drug effects, such as pathway interference, metabolism, and drug accumulation. Because liver toxicity still ranks among the top reasons for drug attrition, the reliable prediction of adverse hepatic effects is a substantial challenge in drug discovery and development. To this end, more effort needs to be focused on the development of improved predictive in-vitro and in-silico approaches. Current computational models often lack applicability to novel pharmaceutical candidates, typically due to insufficient coverage of the chemical space of interest, which is either imposed by size or diversity of the training data. Hence, there is an urgent need for better computational models to allow for the identification of safe drug candidates and to support experimental design. In this context, a large data set comprising 3712 compounds with liver related toxicity findings in humans and animals was collected from various sources. The complex pathology was clustered into 21 preclinical and human hepatotoxicity endpoints, which were organized into three levels of detail. Support vector machine models were trained for each endpoint, using optimized descriptor sets from chemometrics software. The optimized global human hepatotoxicity model has high sensitivity (68%) and excellent specificity (95%) in an internal validation set of 221 compounds. Models for preclinical endpoints performed similarly. To allow for reliable prediction of "truly external" novel compounds, all predictions are tagged with confidence parameters. These parameters are derived from a statistical analysis of the predictive probability densities. The whole approach was validated for an external validation set of 269 proprietary compounds. The models are fully integrated into our early safety in-silico workflow.

Faecal microbiota transplantation-A clinical view

Faecal microbiota transplantation has gained increasing attention over the last decade as various phenotypes could be transferred from a donor to a recipient in different animal models. Clinically, however, the sole indication with evidence from a randomized placebo controlled trial is refractory Clostridium difficile infection. Despite revealing successful clinical outcomes, questions concerning regulatory affairs, the identification of the best donor, the optimal mixture of the transplant as well as the preferred route of administration remain to be clarified even for this indication. Initiated by the idea that alterations in the composition of the intestinal microbiota are associated with intestinal inflammation in inflammatory bowel disease, several studies investigated whether faecal microbiota transplantation would be an equally suitable approach for these devastating disorders. Indeed, the available data indicate changes in the microbiota composition following faecal microbial transplantation depending on the degree of intestinal inflammation. Furthermore, first data even provide evidence that the transplantation of an "optimized" microbiota induces clinical remission in ulcerative colitis. However, despite these intriguing results it needs to be considered that not only "a cure of inflammation", but also risk factors and phenotypes including obesity can be transferred via faecal microbiota transplantation. Thus, a deeper understanding of the impact of a distinct microbiota composition is required before "designing" the optimal faecal microbiota transplant.

Application of omics data in regulatory toxicology: report of an international BfR expert workshop

Advances in omics techniques and molecular toxicology are necessary to provide new perspectives for regulatory toxicology. By the application of modern molecular techniques, more mechanistic information should be gained to support standard toxicity studies and to contribute to a reduction and refinement of animal experiments required for certain regulatory purposes. The relevance and applicability of data obtained by omics methods to regulatory purposes such as grouping of chemicals, mode of action analysis or classification and labelling needs further improvement, defined validation and cautious expert judgment. Based on the results of an international expert workshop organized 2014 by the Federal Institute for Risk Assessment in Berlin, this paper is aimed to provide a critical overview of the regulatory relevance and reliability of omics methods, basic requirements on data quality and validation, as well as regulatory criteria to decide which effects observed by omics methods should be considered adverse or non-adverse. As a way forward, it was concluded that the inclusion of omics data can facilitate a more flexible approach for regulatory risk assessment and may help to reduce or refine animal testing.

Discovery of N-[4-(1H-Pyrazolo[3,4-b]pyrazin-6-yl)-phenyl]-sulfonamides as Highly Active and Selective SGK1 Inhibitors

From a virtual screening starting point, inhibitors of the serum and glucocorticoid regulated kinase 1 were developed through a combination of classical medicinal chemistry and library approaches. This resulted in highly active small molecules with nanomolar activity and a good overall in vitro and ADME profile. Furthermore, the compounds exhibited unusually high kinase and off-target selectivity due to their rigid structure.