Personalized neurorehabilitative precision medicine: from data to therapies (MWKNeuroReha) - a multi-centre prospective observational clinical trial to predict long-term outcome of patients with acute motor stroke.

BACKGROUND: Stroke is one of the most frequent diseases, and half of the stroke survivors are left with permanent impairment. Prediction of individual outcome is still difficult. Many but not all patients with stroke improve by approximately 1.7 times the initial impairment, that has been termed proportional recovery rule. The present study aims at identifying factors predicting motor outcome after stroke more accurately than before, and observe associations of rehabilitation treatment with outcome. METHODS: The study is designed as a multi-centre prospective clinical observational trial. An extensive primary data set of clinical, neuroimaging, electrophysiological, and laboratory data will be collected within 96 h of stroke onset from patients with relevant upper extremity deficit, as indexed by a Fugl-Meyer-Upper Extremity (FM-UE) score ≤ 50. At least 200 patients will be recruited. Clinical scores will include the FM-UE score (range 0-66, unimpaired function is indicated by a score of 66), Action Research Arm Test, modified Rankin Scale, Barthel Index and Stroke-Specific Quality of Life Scale. Follow-up clinical scores and applied types and amount of rehabilitation treatment will be documented in the rehabilitation hospitals. Final follow-up clinical scoring will be performed 90 days after the stroke event. The primary endpoint is the change in FM-UE defined as 90 days FM-UE minus initial FM-UE, divided by initial FM-UE impairment. Changes in the other clinical scores serve as secondary endpoints. Machine learning methods will be employed to analyze the data and predict primary and secondary endpoints based on the primary data set and the different rehabilitation treatments. DISCUSSION: If successful, outcome and relation to rehabilitation treatment in patients with acute motor stroke will be predictable more reliably than currently possible, leading to personalized neurorehabilitation. An important regulatory aspect of this trial is the first-time implementation of systematic patient data transfer between emergency and rehabilitation hospitals, which are divided institutions in Germany. TRIAL REGISTRATION: This study was registered at ClinicalTrials.gov ( NCT04688970 ) on 30 December 2020.

Machine learning identifies ICU outcome predictors in a multicenter COVID-19 cohort.

BACKGROUND: Intensive Care Resources are heavily utilized during the COVID-19 pandemic. However, risk stratification and prediction of SARS-CoV-2 patient clinical outcomes upon ICU admission remain inadequate. This study aimed to develop a machine learning model, based on retrospective & prospective clinical data, to stratify patient risk and predict ICU survival and outcomes. METHODS: A Germany-wide electronic registry was established to pseudonymously collect admission, therapeutic and discharge information of SARS-CoV-2 ICU patients retrospectively and prospectively. Machine learning approaches were evaluated for the accuracy and interpretability of predictions. The Explainable Boosting Machine approach was selected as the most suitable method. Individual, non-linear shape functions for predictive parameters and parameter interactions are reported. RESULTS: 1039 patients were included in the Explainable Boosting Machine model, 596 patients retrospectively collected, and 443 patients prospectively collected. The model for prediction of general ICU outcome was shown to be more reliable to predict "survival". Age, inflammatory and thrombotic activity, and severity of ARDS at ICU admission were shown to be predictive of ICU survival. Patients' age, pulmonary dysfunction and transfer from an external institution were predictors for ECMO therapy. The interaction of patient age with D-dimer levels on admission and creatinine levels with SOFA score without GCS were predictors for renal replacement therapy. CONCLUSIONS: Using Explainable Boosting Machine analysis, we confirmed and weighed previously reported and identified novel predictors for outcome in critically ill COVID-19 patients. Using this strategy, predictive modeling of COVID-19 ICU patient outcomes can be performed overcoming the limitations of linear regression models. Trial registration "ClinicalTrials" (clinicaltrials.gov) under NCT04455451.

The Drosophila foraging gene human orthologue PRKG1 predicts individual differences in the effects of early adversity on maternal sensitivity.

There is variation in the extent to which childhood adverse experience affects adult individual differences in maternal behavior. Genetic variation in the animal foraging gene, which encodes a cGMP-dependent protein kinase, contributes to variation in the responses of adult fruit flies, Drosophila melanogaster, to early life adversity and is also known to play a role in maternal behavior in social insects. Here we investigate genetic variation in the human foraging gene (PRKG1) as a predictor of individual differences in the effects of early adversity on maternal behavior in two cohorts. We show that the PRKG1 genetic polymorphism rs2043556 associates with maternal sensitivity towards their infants. We also show that rs2043556 moderates the association between self-reported childhood adversity of the mother and her later maternal sensitivity. Mothers with the TT allele of rs2043556 appeared buffered from the effects of early adversity, whereas mothers with the presence of a C allele were not. Our study used the Toronto Longitudinal Cohort (N=288 mother-16 month old infant pairs) and the Maternal Adversity and Vulnerability and Neurodevelopment Cohort (N=281 mother-18 month old infant pairs). Our findings expand the literature on the contributions of both genetics and gene-environment interactions to maternal sensitivity, a salient feature of the early environment relevant for child neurodevelopment.

Mind the gap: olfactory trace conditioning in honeybees.

Trace conditioning is a form of classical conditioning, where a neutral stimulus (conditioned stimulus, CS) is associated with a following appetitive or aversive stimulus (unconditioned stimulus, US). Unlike classical delay conditioning, in trace conditioning there is a stimulus-free gap between CS and US, and thus a poststimulus neural representation (trace) of the CS is required to bridge the gap until its association with the US. The properties of such stimulus traces are not well understood, nor are their underlying physiological mechanisms. Using behavioral and physiological approaches, we studied appetitive olfactory trace conditioning in honeybees. We found that single-odor presentation created a trace containing information about odor identity. This trace conveyed odor information about the initial stimulus and was robust against interference by other odors. Memory acquisition decreased with increasing CS-US gap length. The maximum learnable CS-US gap length could be extended by previous trace-conditioning experience. Furthermore, acquisition improved when an additional odor was presented during the CS-US gap. Using calcium imaging, we tested whether projection neurons in the primary olfactory brain area, the antennal lobe, contain a CS trace. We found odor-specific persistent responses after stimulus offset. These post-odor responses, however, did not encode the CS trace, and perceived odor quality could be predicted by the initial but not by the post-odor response. Our data suggest that olfactory trace conditioning is a less reflexive form of learning than classical delay conditioning, indicating that odor traces might involve higher-level cognitive processes.

External Validation of COVID-19 Risk Scores during Three Waves of Pandemic in a German Cohort-A Retrospective Study.

Several risk scores were developed during the COVID-19 pandemic to identify patients at risk for critical illness as a basic step to personalizing medicine even in pandemic circumstances. However, the generalizability of these scores with regard to different populations, clinical settings, healthcare systems, and new epidemiological circumstances is unknown. The aim of our study was to compare the predictive validity of qSOFA, CRB65, NEWS, COVID-GRAM, and 4C-Mortality score. In a monocentric retrospective cohort, consecutively hospitalized adults with COVID-19 from February 2020 to June 2021 were included; risk scores at admission were calculated. The area under the receiver operating characteristic curve and the area under the precision-recall curve were compared using DeLong's method and a bootstrapping approach. A total of 347 patients were included; 23.6% were admitted to the ICU, and 9.2% died in a hospital. NEWS and 4C-Score performed best for the outcomes ICU admission and in-hospital mortality. The easy-to-use bedside score NEWS has proven to identify patients at risk for critical illness, whereas the more complex COVID-19-specific scores 4C and COVID-GRAM were not superior. Decreasing mortality and ICU-admission rates affected the discriminatory ability of all scores. A further evaluation of risk assessment is needed in view of new and rapidly changing epidemiological evolution.

DNA methylation mediates neural processing after odor learning in the honeybee.

DNA methyltransferases (Dnmts) - epigenetic writers catalyzing the transfer of methyl-groups to cytosine (DNA methylation) - regulate different aspects of memory formation in many animal species. In honeybees, Dnmt activity is required to adjust the specificity of olfactory reward memories and bees' relearning capability. The physiological relevance of Dnmt-mediated DNA methylation in neural networks, however, remains unknown. Here, we investigated how Dnmt activity impacts neuroplasticity in the bees' primary olfactory center, the antennal lobe (AL) an equivalent of the vertebrate olfactory bulb. The AL is crucial for odor discrimination, an indispensable process in forming specific odor memories. Using pharmacological inhibition, we demonstrate that Dnmt activity influences neural network properties during memory formation in vivo. We show that Dnmt activity promotes fast odor pattern separation in trained bees. Furthermore, Dnmt activity during memory formation increases both the number of responding glomeruli and the response magnitude to a novel odor. These data suggest that Dnmt activity is necessary for a form of homoeostatic network control which might involve inhibitory interneurons in the AL network.

DNA Methylation Adjusts the Specificity of Memories Depending on the Learning Context and Promotes Relearning in Honeybees.

The activity of the epigenetic writers DNA methyltransferases (Dnmts) after olfactory reward conditioning is important for both stimulus-specific long-term memory (LTM) formation and extinction. It, however, remains unknown which components of memory formation Dnmts regulate (e.g., associative vs. non-associative) and in what context (e.g., varying training conditions). Here, we address these aspects in order to clarify the role of Dnmt-mediated DNA methylation in memory formation. We used a pharmacological Dnmt inhibitor and classical appetitive conditioning in the honeybee Apis mellifera, a well characterized model for classical conditioning. We quantified the effect of DNA methylation on naïve odor and sugar responses, and on responses following olfactory reward conditioning. We show that (1) Dnmts do not influence naïve odor or sugar responses, (2) Dnmts do not affect the learning of new stimuli, but (3) Dnmts influence odor-coding, i.e., 'correct' (stimulus-specific) LTM formation. Particularly, Dnmts reduce memory specificity when experience is low (one-trial training), and increase memory specificity when experience is high (multiple-trial training), generating an ecologically more useful response to learning. (4) In reversal learning conditions, Dnmts are involved in regulating both excitatory (re-acquisition) and inhibitory (forgetting) processes.

Dnmts and Tet target memory-associated genes after appetitive olfactory training in honey bees.

DNA methylation and demethylation are epigenetic mechanisms involved in memory formation. In honey bees DNA methyltransferase (Dnmt) function is necessary for long-term memory to be stimulus specific (i.e. to reduce generalization). So far, however, it remains elusive which genes are targeted and what the time-course of DNA methylation is during memory formation. Here, we analyse how DNA methylation affects memory retention, gene expression, and differential methylation in stimulus-specific olfactory long-term memory formation. Out of 30 memory-associated genes investigated here, 9 were upregulated following Dnmt inhibition in trained bees. These included Dnmt3 suggesting a negative feedback loop for DNA methylation. Within these genes also the DNA methylation pattern changed during the first 24 hours after training. Interestingly, this was accompanied by sequential activation of the DNA methylation machinery (i.e. Dnmts and Tet). In sum, memory formation involves a temporally complex epigenetic regulation of memory-associated genes that facilitates stimulus specific long-term memory in the honey bee.

Neuroligin-associated microRNA-932 targets actin and regulates memory in the honeybee.

Increasing evidence suggests small non-coding RNAs (ncRNAs) such as microRNAs (miRNAs) control levels of mRNA expression during experience-related remodelling of the brain. Here we use an associative olfactory learning paradigm in the honeybee Apis mellifera to examine gene expression changes in the brain during memory formation. Brain transcriptome analysis reveals a general downregulation of protein-coding genes, including asparagine synthetase and actin, and upregulation of ncRNAs. miRNA-mRNA network predictions together with PCR validation suggest miRNAs including miR-210 and miR-932 target the downregulated protein-coding genes. Feeding cholesterol-conjugated antisense RNA to bees results in the inhibition of miR-210 and of miR-932. Loss of miR-932 impairs long-term memory formation, but not memory acquisition. Functional analyses show that miR-932 interacts with Act5C, providing evidence for direct regulation of actin expression by an miRNA. An activity-dependent increase in miR-932 expression may therefore control actin-related plasticity mechanisms and affect memory formation in the brain.

The speed of smell: odor-object segregation within milliseconds.

Segregating objects from background, and determining which of many concurrent stimuli belong to the same object, remains one of the most challenging unsolved problems both in neuroscience and in technical applications. While this phenomenon has been investigated in depth in vision and audition it has hardly been investigated in olfaction. We found that for honeybees a 6-ms temporal difference in stimulus coherence is sufficient for odor-object segregation, showing that the temporal resolution of the olfactory system is much faster than previously thought.

DNA methylation mediates the discriminatory power of associative long-term memory in honeybees.

Memory is created by several interlinked processes in the brain, some of which require long-term gene regulation. Epigenetic mechanisms are likely candidates for regulating memory-related genes. Among these, DNA methylation is known to be a long lasting genomic mark and may be involved in the establishment of long-term memory. Here we demonstrate that DNA methyltransferases, which induce and maintain DNA methylation, are involved in a particular aspect of associative long-term memory formation in honeybees, but are not required for short-term memory formation. While long-term memory strength itself was not affected by blocking DNA methyltransferases, odor specificity of the memory (memory discriminatory power) was. Conversely, perceptual discriminatory power was normal. These results suggest that different genetic pathways are involved in mediating the strength and discriminatory power of associative odor memories and provide, to our knowledge, the first indication that DNA methyltransferases are involved in stimulus-specific associative long-term memory formation.