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Neuronal spike patterns are the fundamental units of neural communication in the brain, which is still not fully understood. Entropy measures offer a quantitative framework to assess the variability and information content of these spike patterns. By quantifying the uncertainty and informational content of neuronal patterns, entropy measures provide insights into neural coding strategies, synaptic plasticity, network dynamics, and cognitive processes. Here, we review basic entropy metrics and then we provide examples of recent advancements in using entropy as a tool to improve our understanding of neuronal processing. It focuses especially on studies on critical dynamics in neural networks and the relation of entropy to predictive coding and cortical communication. We highlight the necessity of expanding entropy measures from single neurons to encompass multi-neuronal activity patterns, as cortical circuits communicate through coordinated spatiotemporal activity patterns, called neuronal packets. We discuss how the sequential and partially stereotypical nature of neuronal packets influences the entropy of cortical communication. Stereotypy reduces entropy by enhancing reliability and predictability in neural signaling, while variability within packets increases entropy, allowing for greater information capacity. This balance between stereotypy and variability supports both robustness and flexibility in cortical information processing. We also review challenges in applying entropy to analyze such spatiotemporal neuronal spike patterns, notably, the “curse of dimensionality” in estimating entropy for high-dimensional neuronal data. Finally, we discuss strategies to overcome these challenges, including dimensionality reduction techniques, advanced entropy estimators, sparse coding schemes, and the integration of machine learning approaches. Thus, this work summarizes the most recent developments on how entropy measures contribute to our understanding of principles underlying neural coding.

This study investigates the impact of Epstein–Barr virus (EBV) infection on children’s proteomes across different phases of the disease, utilising seventy-nine blood samples categorised into three groups: EBV-naive patients, acute infectious mononucleosis (IM) cases, and convalescents followed up for 12 months post-IM. The aim is to identify proteins influenced by EBV infection, shedding light on the chronic processes triggered by the virus. The results reveal thirty-nine proteins distinguishing between naive patients and those with IM, including actin, lumican, peroxiredoxin-2, fibulin-1, gelsolin, and alpha-2-macroglobulin, which are involved in immune responses, cell adhesion, and inflammation. Elevated oxidative stress markers like peroxiredoxin-2 in IM patients suggest potential links to EBV’s induction of reactive oxygen species. Increased levels of apolipoproteins A-I, A-IV, C-IV, and M during IM imply associations with viral infection, while complement system proteins (C1q, C1r, and C8 gamma chain) are also elevated, reflecting their role in the immune response and viral clearance. This study’s focus on children provides unique insights into EBV’s impact on young populations, emphasising proteomics’ role in uncovering protein associations and understanding the virus’s long-term consequences. However, specific relationships between identified proteins and EBV infection require further investigation.

The purpose of this study was to evaluate the use of compressible soft robotic sensors (C-SRS) in determining plantar pressure to infer vertical and shear forces in wearable technology: A ground reaction pressure sock (GRPS). To assess pressure relationships between C-SRS, pressure cells on a BodiTrakTM Vector Plate, and KistlerTM Force Plates, thirteen volunteers performed three repetitions of three different movements: squats, shifting center-of-pressure right to left foot, and shifting toes to heels with C-SRS in both anterior−posterior (A/P) and medial−lateral (M/L) sensor orientations. Pearson correlation coefficient of C-SRS to BodiTrakTM Vector Plate resulted in an average R-value greater than 0.70 in 618/780 (79%) of sensor to cell comparisons. An average R-value greater than 0.90 was seen in C-SRS comparison to KistlerTM Force Plates during shifting right to left. An autoregressive integrated moving average (ARIMA) was conducted to identify and estimate future C-SRS data. No significant differences were seen in sensor orientation. Sensors in the A/P orientation reported a mean R2 value of 0.952 and 0.945 in the M/L sensor orientation, reducing the effectiveness to infer shear forces. Given the high R values, the use of C-SRSs to infer normal pressures appears to make the development of the GRPS feasible.

The linearity of soft robotic sensors (SRS) was recently validated for movement angle assessment using a rigid body structure that accurately depicted critical movements of the foot−ankle complex. The purpose of this study was to continue the validation of SRS for joint angle movement capture on 10 participants (five male and five female) performing ankle movements in a non-weight bearing, high-seated, sitting position. The four basic ankle movements—plantar flexion (PF), dorsiflexion (DF), inversion (INV), and eversion (EVR)—were assessed individually in order to select good placement and orientation configurations (POCs) for four SRS positioned to capture each movement type. PF, INV, and EVR each had three POCs identified based on bony landmarks of the foot and ankle while the DF location was only tested for one POC. Each participant wore a specialized compression sock where the SRS could be consistently tested from all POCs for each participant. The movement data collected from each sensor was then compared against 3D motion capture data. R-squared and root-mean-squared error averages were used to assess relative and absolute measures of fit to motion capture output. Participant robustness, opposing movements, and gender were also used to identify good SRS POC placement for foot−ankle movement capture.

The yet uncharacterized membrane protein SA2056 belongs to the ubiquitous RND (Resistance-Nodulation-cell Division) family of transmembrane efflux transporters. The sa2056 gene is located downstream of femX, the gene encoding the essential, non-ribosomal peptidyl-transferase adding the first glycine in the staphylococcal cell wall pentaglycine interpeptide. Due to its proximity to and weak co-transcription with femX, we assumed that sa2056 may somehow be involved in peptidoglycan synthesis. Specific antibodies against SA2056 showed that this protein is expressed during growth and present in the membrane fraction of cell preparations. Using a bacterial two hybrid system, SA2056 was shown to interact (i) with itself, (ii) with FemB, which adds glycines 4 and 5 to the peptidoglycan interpeptide and (iii) with the essential penicillin binding proteins, PBP1 and PBP2, required for cell division and incorporation of the peptidoglycan into the cell wall. Unexpectedly, deletion of sa2056 led to no phenotype regarding growth, antibiotic resistances or cell morphology; nor did sa2056 deletion in combination with femB inactivation alter b-lactam and lysostaphin sensitivity and resistance, respectively, pointing to possible redundancy in the cell wall synthesis pathway. These results suggest an accessory role of SA2056 in S. aureus peptidoglycan synthesis, broadening the range of biological functions of RND proteins.

Background: Social norms have been associated with alcohol use in college populations; however, more research is needed to confirm the associations between social norms and a range of substance use behaviors during the COVID-19 pandemic. Methods: We analyzed data from the Healthy Minds Study (September 2020–December 2020), a non-probability sample administered online to college students. We used multivariable logistic regression to test for associations between respondents’ perceptions of substance use behaviors in their respective colleges and their own substance use behaviors, adjusting for age, gender, race/ethnicity, and international student status. Results: We found that those who overestimated the prevalence of alcohol use, cigarette use, cannabis use, and vaping were significantly more likely to use these substances when compared with those who did not overestimate. These associations persisted even when using different prevalence estimates of substance use, though some associations lost statistical significance when applying the survey weights to account for non-response. Conclusion: College students overestimated the prevalence of substance use in their respective colleges, even during the early stages of the pandemic when social interactions were limited, and these beliefs were associated with substance use. Future studies may test the utility of campaigns to alter perceptions of social norms and interventions that use personalized normative feedback to reduce substance use during pandemics.

Binary MgCa alloys are one of the promising and well investigated biodegradable metals and therefore a good standard for the study of novel processing routes. In this investigation, novel powder metallurgical (PM) blending and sintering methods were applied for the generation of biodegradable MgCa test specimens, using metal injection moulding (MIM). In addition to the classical PM-blending route using Ca-containing master-alloys, Ca-containing ceramics and hydrides, as there are CaO and CaH2, were used separately and in a stoichiometric mixture. In situ X-ray synchrotron radiation experiments were performed for a deeper understanding of alloy forming mechanisms during sintering. Mechanical and degradation performance was investigated by tensile testing and the monitoring of biodegradation under physiological conditions. Besides its sound strength of up to 144 MPa and degradation rate of 0.25 mm/a, the new redox alloying technique avoids the usage of any greenhouse active SF6 gas (global warming potential 22,800) during alloying, keeping the earth’s atmosphere safer. Therefore, it can be concluded that Ca-containing ceramics and hybrids are attractive alternatives to obtain, comparable to Mg-based materials, thus enabling safer processing.

Chronic kidney disease (CKD) is characterized by the progressive loss of functional nephrons. Although cardiovascular disease (CVD) complications and atherosclerosis are the leading causes of morbidity and mortality in CKD, the mechanism by which the progression of CVD accelerates remains unclear. To reveal the molecular mechanisms associated with atherosclerosis linked to CKD, we applied a shotgun lipidomics approach fortified with standard laboratory analytical methods and gas chromatography-mass spectrometry technique on selected lipid components and precursors to analyze the plasma lipidome in CKD and classical CVD patients. The MS-based lipidome profiling revealed the upregulation of triacylglycerols in CKD and downregulation of cholesterol/cholesteryl esters, sphingomyelins, phosphatidylcholines, phosphatidylethanolamines and ceramides as compared to CVD group and controls. We have further observed a decreased abundance of seven fatty acids in CKD with strong inter-correlation. In contrast, the level of glycerol was elevated in CKD in comparison to all analyzed groups. Our results revealed the putative existence of a functional causative link—the low cholesterol level correlated with lower estimated glomerular filtration rate and kidney dysfunction that supports the postulated “reverse epidemiology” theory and suggest that the lipidomic background of atherosclerosis-related to CKD is unique and might be associated with other cellular factors, i.e., inflammation.