While complex inflammatory-like alterations are observed around the amyloid plaques of Alzheimer disease (AD), little is known about the molecular changes and cellular interactions that characterize this response. We investigate here in an AD mouse model the transcriptional changes occurring in tissue domains of 100 µm diameter around the amyloid plaques using spatial transcriptomics. We demonstrate early alterations in a gene co-expression network enriched for myelin and oligodendrocyte genes (OLIG), while a multicellular gene coexpression network of Plaque-Induced Genes (PIGs) involving the complement system, oxidative stress, lysosomes and inflammation is prominent in the later phase of the disease. We confirm the majority of the observed alterations at the cellular level using in situ sequencing on mouse and human brain sections. Genome-wide spatial transcriptomic analysis provides an unprecedented approach to untangle the dysregulated cellular network in the vicinity of pathogenic hallmarks of AD and other brain diseases.

The field of spatial transcriptomics is rapidly expanding, and with it the repertoire of available technologies. However, several of the transcriptome-wide spatial assays do not operate on a single cell level, but rather produce data comprised of contributions from a – potentially heterogeneous – mixture of cells. Still, these techniques are attractive to use when examining complex tissue specimens with diverse cell populations, where complete expression profiles are required to properly capture their richness. Motivated by an interest to put gene expression into context and delineate the spatial arrangement of cell types within a tissue, we here present a model-based probabilistic method that uses single cell data to deconvolve the cell mixtures in spatial data. To illustrate the capacity of our method, we use data from different experimental platforms and spatially map cell types from the mouse brain and developmental heart, which arrange as expected.

Brain maps are essential for integrating information and interpreting the structure-function relationship of circuits and behavior. We aimed to generate a systematic classification of the adult mouse brain based purely on the unbiased identification of spatially defining features by employing whole-brain spatial transcriptomics. We found that the molecular information was sufficient to deduce the complex and detailed neuroanatomical organization of the brain. The unsupervised (non-expert, data-driven) classification revealed new area- and layer-specific subregions, for example in isocortex and hippocampus, and new subdivisions of striatum. The molecular atlas further supports the characterization of the spatial identity of neurons from their single-cell RNA profile, and provides a resource for annotating the brain using a minimal gene set—a brain palette. In summary, we have established a molecular atlas to formally define the spatial organization of brain regions, including the molecular code for mapping and targeting of discrete neuroanatomical domains.

Brain maps are essential for integrating information and interpreting the structure-function relationship of circuits and behavior. We aimed to generate a systematic classification of the adult mouse brain organization based on unbiased extraction of spatially-defining features. Applying whole-brain spatial transcriptomics, we captured the gene expression signatures to define the spatial organization of molecularly discrete subregions. We found that the molecular code contained sufficiently detailed information to directly deduce the complex spatial organization of the brain. This unsupervised molecular classification revealed new area-and layer-specific subregions, for example in isocortex and hippocampus, and a new division of striatum.

Summary Alzheimer disease (AD) is a devastating neurological disease associated with progressive loss of mental skills and cognitive and physical functions whose etiology is not completely understood. Here, our goal was to simultaneously uncover novel and known molecular targets in the structured layers of the hippocampus and olfactory bulbs that may contribute to early hippocampal synaptic deficits and olfactory dysfunction in AD mice. Spatially resolved transcriptomics was used to identify high-confidence genes that were differentially regulated in AD mice relative to controls. A diverse set of genes that modulate stress responses and transcription were predominant in both hippocampi and olfactory bulbs. Notably, we identify Bok, implicated in mitochondrial physiology and cell death, as a spatially downregulated gene in the hippocampus of mouse and human AD brains. In summary, we provide a rich resource of spatially differentially expressed genes, which may contribute to understanding AD pathology.

MAPK phosphatases (MKPs) are dual specificity phosphatases that dephosphorylate and thereby inactivate MAPKs. In the present study, we provide evidence that platelet-derived growth factor BB (PDGF-BB) regulates MKP3 (DUSP6), which is considered to be a phosphatase highly selective for Erk. Intriguingly, we observed that Mek is positively regulated by MKP3, whereas Erk itself is negatively regulated. In addition, we found that activation of PDGF receptor ␣ or ␤ leads to a rapid proteasomal degradation of MKP3 in a manner that requires Mek activation; this feed-forward mechanism was found to be essential for efficient Erk phosphorylation. We could also demonstrate that PDGF-BB stimulation induces phosphorylation of MKP3 at Ser-174 and Ser-300; phosphorylation of Ser-174 is involved in PDGF-induced MKP3 degradation, since mutation of this site stabilized MKP3. Moreover, activated Erk induces mkp3 expression, leading to restoration of MKP3 levels after 1-2 h and a concomitant dephosphorylation of Erk in cells with activated PDGFR␣. Reducing the MKP3 level by small interfering RNA leads to an increased Erk activation and mitogenic response to PDGF-BB. In conclusion, MKP3 is an important regulator of PDGF-induced Erk phosphorylation acting in both a rapid positive feed-forward and a later negative feed-back loop.

Introduction. Patients' adherence to long-term therapies is low. It translates into reduced quality of life and significant deterioration of health economics. Identification of potential barriers of medication-related adherence is a starting point allowing implementation of more advanced interventions directed to adherence improvement. Aim. The purpose of our study was to create and validate a simple instrument used to assess patients' adherence to recommended medications. Material and methods. The Adherence Scale in Chronic Diseases is a self-reported questionnaire with 8 items and with proposed 5 sets of answers. The total score in the Adherence Scale in Chronic Diseases ranges from 0 to 32 points. Three levels of adherence were considered (low: scores of 0 to 20; medium 21 to 25; high > 26). The validation of the questionnaire was conducted in accordance with the validation procedure. Assessment of the internal consistency was performed using a-Cronbach coefficient. In order to conduct the factor analysis, we assessed: the determinant of correlation matrix, Kaiser-Mayer-Olkin (K-M-O) statistic and the Bartlett's test of sphericity. Factor analysis was conducted using principal component analysis with Oblimin rotation. The Kaiser criterion and scree plot were used in order to determine components of the questionnaire. Adherence levels were determined based on the percentiles. Results. Grand total of 413 patients with a cardiovascular disease were included in the study. The reliability and homogeneity of the questionnaire were confirmed by a-Cronbach coefficient (0.739). Factor analysis showed that in this questionnaire we can extract two components. The analysis of factor loadings indicated excluding item 2 from the questionnaire. After exclusion of the mentioned item, we repeated the validation procedure. For such a new dataset, according to the Kaiser criterion, only one component was extracted. Conclusions. The Adherence Scale in Chronic Diseases is a practical, reliable, consistent and well validated instrument for identifying specific obstacles to medication adherence. Its simplicity causes that it can be successfully applied in daily practice by health care professionals. Our survey has the potential to improve patient-health care professional communication and relationship.

The readiness for hospital discharge of patients after acute myocardial infarction: a new self-reported questionnaire ABSTRACT Introduction. Medical care providers are responsible for adequate preparation of patients for discharge from the hospital. The purpose of this study was to validate a new self-reported questionnaire assessing the readiness of patients for hospital discharge. The scoring less than 44 points for the entire questionnaire indicates low readiness, obtaining between 44 and 57 points indicates medium readiness, and scores over 57 points are classified as high readiness for discharge from hospital.Conclusions. The validation procedure revealed that RHD MIS is a reliable and homogeneous tool to measure the readiness of patients for hospital discharge. The set of items divided into three subscales allows subjective and objective evaluation of the patient's knowledge and expectations. Further investigation is needed to assess the potential impact of RHD MIS scoring on long-term outcome.