Changes in synaptic inputs to dI3 INs and MNs after complete transection in adult mice.

Introduction: Spinal cord injury (SCI) is a debilitating condition that disrupts the communication between the brain and the spinal cord. Several studies have sought to determine how to revive dormant spinal circuits caudal to the lesion to restore movements in paralyzed patients. So far, recovery levels in human patients have been modest at best. In contrast, animal models of SCI exhibit more recovery of lost function. Previous work from our lab has identified dI3 interneurons as a spinal neuron population central to the recovery of locomotor function in spinalized mice. We seek to determine the changes in the circuitry of dI3 interneurons and motoneurons following SCI in adult mice. Methods: After a complete transection of the spinal cord at T9-T11 level in transgenic Isl1:YFP mice and subsequent treadmill training at various time points of recovery following surgery, we examined changes in three key circuits involving dI3 interneurons and motoneurons: (1) Sensory inputs from proprioceptive and cutaneous afferents, (2) Presynaptic inhibition of sensory inputs, and (3) Central excitatory glutamatergic synapses from spinal neurons onto dI3 INs and motoneurons. Furthermore, we examined the possible role of treadmill training on changes in synaptic connectivity to dI3 interneurons and motoneurons. Results: Our data suggests that VGLUT1+ inputs to dI3 interneurons decrease transiently or only at later stages after injury, whereas levels of VGLUT1+ remain the same for motoneurons after injury. Levels of VGLUT2+ inputs to dI3 INs and MNs may show transient increases but fall below levels seen in sham-operated mice after a period of time. Levels of presynaptic inhibition to VGLUT1+ inputs to dI3 INs and MNs can rise shortly after SCI, but those increases do not persist. However, levels of presynaptic inhibition to VGLUT1+ inputs never fell below levels observed in sham-operated mice. For some synaptic inputs studied, levels were higher in spinal cord-injured animals that received treadmill training, but these increases were observed only at some time points. Discussion: These results suggest remodeling of spinal circuits involving spinal interneurons that have previously been implicated in the recovery of locomotor function after spinal cord injury in mice.

SiliFish: A desktop application to model swimming behavior in developing zebrafish (Danio rerio).

SiliFish is an open-source desktop application to model and study zebrafish swimming. Here, we explain how to define the general parameters of the model, define cell populations, place them within the spinal cord, and define their projections. We explain how to run a simulation and how to visualize the network output and single-cell activity. The choice of C# as the programming language allows higher speed performance, simulating models with larger spinal circuits in less time. For complete details on the use and execution of this protocol, please refer to Roussel et al. (2021).1.

PeSA 2.0: A software tool for peptide specificity analysis implementing positive and negative motifs and motif-based peptide scoring.

There are a vast number of molecular interactions that occur at the cellular level. Among these molecular interactions, interactions between multiple proteins are a widely studied area of research due to the importance of these interactions in cellular function and their potential in drug development. PeSA is a desktop application developed to facilitate the in vitro peptide study analysis to predict protein-protein interactions. PeSA can effortlessly generate visual outputs like motifs, bar charts, and visual matrices. Our implementation of PeSA version 2.0 includes additional tools, including the ability to further score peptide lists for consensus amongst interactions. The software is also able to design de novo peptides based on sequence motifs (sequence generator), which can be used to help design additional experiments for motif validation. Further, the efficacy of the sequence generator was validated using the lysine methyltransferase, SETD8, to identify new substrates of methylation based on motif-based predictions developed using PeSA2.0.

Healthcare Personnel's Knowledge and Management of Frequently Encountered Forensic Cases in Emergency Departments in Turkey.

BACKGROUND: Emergency department (ED) personnel frequently encounter incidents related to crime, violence, and suspicious injuries. The aim of this descriptive study was to determine the knowledge levels of ED healthcare personnel in their handling of frequently encountered forensic cases. METHODS: A cross-sectional descriptive study composed of ED healthcare personnel at all state, education and research, and university hospitals with EDs, located in Ankara, Turkey, was completed. Participants at the 15 hospitals in question were interviewed via a questionnaire developed by the researchers. RESULTS: Three hundred fifty healthcare personnel who worked agreed to participate in the study. The results show that ED healthcare personnel have less knowledge than expected of the right way to handle frequently encountered forensic cases. Very few of the healthcare professionals who participated in the study had received any training or education in the field of forensic nursing. Among participants, postgraduates, health professionals educated in forensic nursing, and healthcare staff who used additional resources to understand forensic cases, and those who had evaluated cases that presented to the ED as forensic cases, had significantly higher levels of knowledge. IMPLICATIONS: This study supports the need for professional development in forensic nursing, such as in-service training, and curriculum development for a certificate in forensic nursing to enhance the practical training of healthcare professionals who work in EDs.

PeSA: A software tool for peptide specificity analysis.

The discovery and characterization of molecular interactions is crucial towards a better understanding of complex biological processes. Particularly protein-protein interactions (i.e., PPIs), which are responsible for a variety of cellular functions from intracellular signaling to enzyme-substrate specificity, have been studied broadly over the past decades. Position-specific scoring matrices (PSSM) in particular are used extensively to help determine interaction specificity or candidate interaction motifs at the residue level. However, not all studies successfully report their results as a candidate interaction motif. In many cases, this may be due to a lack of suitable tools for simple analysis and motif generation. Peptide Specificity Analyst (PeSA) was developed with the goal of filling this information gap and providing an easy to use software to aid peptide array analysis and motif generation. PeSA utilizes two models of motif creation: (1) frequency-based using a user-defined peptide list, and (2) weight-based using experimental binding results. The ability to produce motifs effortlessly will make studying, interpreting and disseminating peptide specificity results in an effortless and straightforward process.