Single-cell gene regulatory network prediction by explainable AI.

The molecular heterogeneity of cancer cells contributes to the often partial response to targeted therapies and relapse of disease due to the escape of resistant cell populations. While single-cell sequencing has started to improve our understanding of this heterogeneity, it offers a mostly descriptive view on cellular types and states. To obtain more functional insights, we propose scGeneRAI, an explainable deep learning approach that uses layer-wise relevance propagation (LRP) to infer gene regulatory networks from static single-cell RNA sequencing data for individual cells. We benchmark our method with synthetic data and apply it to single-cell RNA sequencing data of a cohort of human lung cancers. From the predicted single-cell networks our approach reveals characteristic network patterns for tumor cells and normal epithelial cells and identifies subnetworks that are observed only in (subgroups of) tumor cells of certain patients. While current state-of-the-art methods are limited by their ability to only predict average networks for cell populations, our approach facilitates the reconstruction of networks down to the level of single cells which can be utilized to characterize the heterogeneity of gene regulation within and across tumors.

DNA methylation-based classification of sinonasal tumors.

The diagnosis of sinonasal tumors is challenging due to a heterogeneous spectrum of various differential diagnoses as well as poorly defined, disputed entities such as sinonasal undifferentiated carcinomas (SNUCs). In this study, we apply a machine learning algorithm based on DNA methylation patterns to classify sinonasal tumors with clinical-grade reliability. We further show that sinonasal tumors with SNUC morphology are not as undifferentiated as their current terminology suggests but rather reassigned to four distinct molecular classes defined by epigenetic, mutational and proteomic profiles. This includes two classes with neuroendocrine differentiation, characterized by IDH2 or SMARCA4/ARID1A mutations with an overall favorable clinical course, one class composed of highly aggressive SMARCB1-deficient carcinomas and another class with tumors that represent potentially previously misclassified adenoid cystic carcinomas. Our findings can aid in improving the diagnostic classification of sinonasal tumors and could help to change the current perception of SNUCs.

Conditioning learning in an attentional task relates to age and ventricular expansion in a nonhuman primate (Microcebus murinus).

The grey mouse lemur (Microcebus murinus) is a promising nonhuman primate model for brain ageing and neurodegenerative diseases. Age-related cognitive decline in this model is well described, however, data on possible relations between attention and age, as they are known from humans, are missing. We tested 10 mouse lemurs in a touchscreen-based version of the 5-choice-serial-reaction-time-task (5CSRTT) on visuo-spatial attention: subjects had to interact with a briefly presented stimulus occurring unpredictably in one out of five locations on the touchscreen. Animals were trained to an 80 % performance at a four seconds stimulus presentation duration (SPD) and subsequently challenged by a SPD of two seconds. Additionally, ventricular expansion was assessed using structural magnetic resonance imaging. Trials to the 80 % criterion at four seconds SPD correlated significantly with age and with ventricular expansion, especially around the occipital lobe. Once criterion performance was reached, two seconds challenge performance was independent of age. In four subjects that were additionally challenged with 1.5, 1.0, 0.8, or 0.6 s SPDs or variable delays preceding stimulus presentation, performance linearly declined with decreasing SPD, i.e. increasing attentional demand. In conclusion, this is the first report of 5CSRTT data in mouse lemurs and demonstrates the general applicability of this task of visuo-spatial attention to this nonhuman primate model. Results further demonstrate age-related deficits in learning during acquisition of the 5CSRTT and suggest that both may be linked through age-related atrophy of occipital structures and a resulting deficit in central visual processes.

Optimization of 4-Substituted Benzenesulfonamide Scaffold To Reverse Acinetobacter baumannii Serum-Adaptive Efflux Associated Antibiotic Tolerance.

Acinetobacter baumannii is a nosocomial pathogen of urgent concern for public health due to rising rates of multidrug and pandrug resistance. In the context of environmental cues such as growth in human serum, A. baumannii is known to display adaptive efflux, in which a multitude of efflux-associated genes are upregulated, resulting in efflux-mediated drug tolerance in strains that are otherwise susceptible to antibiotic therapy. Previously, we identified a sulfonamide-containing scaffold molecule (ABEPI1) that reversed serum-associated antibiotic tolerance in A. baumannii. Herein, we present structure-activity relationship studies on 29 newly synthesized analogues. These molecules were characterized for their ability to potentiate multiple antibiotics in serum, reduce serum-associated ethidium bromide efflux and depolarize bacterial cell membranes. In addition, they were assessed for toxicity to mammalian cells. Collectively, these molecules may represent promising potential adjuvants for use in combination with new and existing antibiotics to treat A. baumannii bacterial infections.

Neurobiological substrates of animal personality and cognition in a nonhuman primate (Microcebus murinus).

INTRODUCTION: The gray mouse lemur (Microcebus murinus) is an important nonhuman primate model in biomedical research. Numerous studies investigated mouse lemur behavior and possible factors underlying interindividual variation in both, animal personality and cognitive performance. Some effects, such as an age-related decline in executive functioning, have robustly been found across laboratory colonies; however, little is known about the brain structural substrates in mouse lemurs. METHODS: Here, we provide first exploratory data linking in vivo magnetic resonance imaging of 34 mouse lemurs to performance in a standardized, touchscreen-based task on object discrimination and reversal learning as well as to animal personality under different scenarios in an open field. RESULTS: High interindividual variability in both brain morphometric and behavioral measurements was found, but only few significant correlations between brain structure and behavior were revealed: Object discrimination learning was linked to the volume of the hippocampus and to temporal lobe thickness, while reversal learning was linked to thalamic volume and the thickness of the anterior cingulate lobe. Emergence latency into the open field correlated with volume of the amygdala. General exploration-avoidance in the empty open-field arena correlated with thicknesses of the anterior cingulate lobe and fronto-parietal substructures. Neophilia, assessed as exploration of a novel object placed in the arena, among others, related to the volume of the caudate nucleus. CONCLUSION: In summary, our data suggest a prominent role of temporal structures (including the hippocampus) for learning capability, as well as thalamic and anterior cingulate structures for cognitive flexibility and response inhibition. The amygdala, the anterior cingulate lobe, and the caudate nucleus are particularly linked to animal personality in the open-field setting. These findings are congruent with the comparative psychological literature and provide a valuable basis for future studies elucidating aspects of behavioral variation in this nonhuman primate model.

Sex-specific patterns of age-related cerebral atrophy in a nonhuman primate Microcebus murinus.

Steadily aging populations result in a growing need for research regarding age-related brain alterations and neurodegenerative pathologies. By allowing a good translation of results to humans, nonhuman primates, such as the gray mouse lemur Microcebus murinus, have gained attention in this field. Our aim was to examine correlations between atrophy-induced brain alterations and age, with special focus on sex differences in mouse lemurs. For cerebral volumetric measurements, in vivo magnetic resonance imaging was performed on 59 animals (28♀♀/31♂♂) aged between 1.0 to 11.9 years. Volumes of different brain regions, cortical thicknesses, and ventricular expansions were evaluated. Analyses revealed significant brain atrophies with increasing age, particularly around the caudate nucleus, the thalamus, and frontal, parietal, and temporo-occipital regions. Especially old females showed a strong decline in cingulate cortex thickness and had higher values of ventricular expansion, whereas cortical thickness of the splenium and occipital regions decreased mainly in males. Our study, thus, provides first evidence for sex-specific, age-related brain alterations in a nonhuman primate, suggesting that mouse lemurs can help elucidating the mechanism underlying sex disparities in cerebral aging, for which there is mixed evidence in humans.