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Abstract In mammals, NMDA receptor antagonists have been linked to the emergence of high-frequency oscillations (HFO, 130–180 Hz) in cortical and subcortical brain regions. The extent to which transmission of this rhythm is dependent on feedforward (bottom-up) or feedback (top-down) mechanisms is unclear. Previously, we have shown that the olfactory bulb (OB), known to orchestrate oscillations in many brain regions, is an important node in the NMDA receptor-dependent HFO network. Since the piriform cortex (PC) receives major input from the OB, and can modulate OB activity via feedback projections, it represents an ideal site to investigate transmission modalities. Here we show, using silicon probes, that NMDA receptor antagonist HFO are present in the PC associated with current dipoles, although of lower power than the OB. Granger causality and peak-lag analyses implicated the OB as the driver of HFO in the PC. Consistent with this, reversible inhibition of the OB resulted in a reduction of HFO power both locally and in the PC. In contrast, inhibition of the PC had minimal impact on OB activity. Collectively, these findings point to bottom-up mechanisms in mediating the transmission of NMDA receptor antagonist-HFO, at least in olfactory circuits.

The article presents the concepts of control systems that use methods of automatic analysis and interpretation of signals. These issues are presented through the description of three control strategies: simple closed-loop control, control using a process of classification, and using a signal understanding technique. The systems based on the discussed concepts are illustrated with examples of controlling a milling machine and an autonomous vehicle. In addition, in more detail, a task of learning human motor activities is described. This task, due to the nature of the controlled object, which is a human being, is extremely difficult. The article shows that the advanced control process, in which the control algorithm is selected and its parameters are adapted to the current situation, may be implemented through the use of the classification process and machine learning methods in general. Changing the algorithm is also possible using signal understanding techniques. These techniques, utilizing models of the objects, allow to predict the long-term effects of the control process. The ability to build control systems that operate in the above manner is of huge practical importance. The aim of this article is to describe the methods of automatic signal interpretation used in control processes and identify the main problems related to their use. The key problems refer to the acquisition of expert knowledge by the system. In order for this knowledge to be effectively transferred, the methods used in the system should have a high level of explainability. Showing the essential nature of this feature is the main outcome of this work.

Slavic populations, such as those in Poland, are considered to have a low prevalence of giant cell arteritis (GCA), although epidemiological data are sparse. The study aimed to compare the reported frequency of GCA in various regions of Poland and analyze the differences between them. We conducted a multicenter, retrospective study of all GCA patients included in the POLVAS registry—the first large multicenter database of patients with vasculitis in Poland. The data from the POLVAS registry were compared with the reported prevalence provided by national insurers from the corresponding regions. A 10-fold increase in the diagnostic rates of GCA was observed in Poland between 2008 and 2019, reaching 8.38 per 100,000 population > 50 years old. It may be attributed to increased interest accompanied by improved diagnostic modalities with the introduction of ultrasound-based, fast-track diagnostic pathways in some centers. However, regional inequities are present, resulting in 10-fold differences (from 2.57 to 24.92) in reported prevalence between different regions. Corticosteroid (CS) monotherapy was the main stem of treatment. Further cooperation and education are needed to minimize regional inequities. This observational study suggests some potential for further increase of the recognizability of GCA and wider use of other than CS monotherapy treatment regimens. We hope that the Polish experience might be interesting and serve as some guidance for the populations where GCA is underdiagnosed.

Antineutrophil cytoplasmic antibody (ANCA)-associated vasculitides (AAVs) are a group of rare diseases with a chronic and relapsing course. Recent treatment guidelines offer many therapeutic options depending mainly on the type of diagnosis and disease manifestations. Areas that remain under discussion include whether all patients diagnosed with AAV belong to a homogeneous group with a similar prognosis at baseline or if the type and duration of remission-inducing treatment should depend on factors other than just diagnosis and disease severity. The aim of this review is to present the recent literature on the tools available to use while evaluating the risk of relapse in patients upon presentation as well as potential biomarkers of proceeding flare in patients upon remission.

Objective. To characterize the eosinophilic granulomatosis with polyangiitis (EGPA) population from the POLVAS registry depending on ANCA status and diagnosis onset, including their comparison with the granulomatosis with polyangiitis (GPA) subset with elevated blood eosinophilia (min. 400/μl) (GPA HE) to develop a differentiating strategy. Methods. A retrospective analysis of the POLVAS registry. Results. The EGPA group comprised 111 patients. The ANCA-positive subset (n = 45 [40.54%]) did not differ from the ANCA-negative one in clinics. Nevertheless, cardiovascular manifestations were more common in ANCA-negative patients than in those with anti-myeloperoxidase (MPO) antibodies (46.97% vs. 26.92%, p = 0.045). Patients diagnosed before 2012 (n = 70 [63.06%]) were younger (median 41 vs. 49 years, p

Abstract Background The cellular inflammatory pattern of nonsteroidal anti‐inflammatory drug–exacerbated respiratory disease (N‐ERD) is heterogeneous. However, data on the heterogeneity of non‐eosinophilic asthma (NEA) with aspirin hypersensitivity are scanty. By examination of N‐ERD patients based on clinical data and eicosanoid biomarkers we aimed to identify NEA endotypes potentially guiding clinical management. Methods Induced sputum was collected from patients with N‐ERD. Sixty six patients (49.6% of 133 N‐ERD) with NEA were included in the hierarchical cluster analysis based on clinical and laboratory data. The quality of clustering was evaluated using internal cluster validation with different indices and a practical decision tree was proposed to simplify stratification of patients. Results The most frequent NEA pattern was paucigranulocytic (PGA; 75.8%), remaining was neutrophilic asthma (NA; 24.2%). Four clusters were identified. Cluster #3 included the highest number of NEA patients (37.9%) with severe asthma and PGA pattern (96.0%). Cluster #1 (24.2%) included severe only asthma, with a higher prevalence of NA (50%). Cluster #2 (25.8%) comprised well‐controlled mild or severe asthma (PGA; 76.5%). Cluster #4 contained only 12.1% patients with well‐controlled moderate asthma (PGA; 62.5%). Sputum prostaglandin D2 levels distinguished cluster #1 from the remaining clusters with an area under the curve of 0.94. Conclusions Among identified four NEA subtypes, clusters #3 and #1 represented N‐ERD patients with severe asthma but a different inflammatory signatures. All the clusters were discriminated by sputum PGD2 levels, asthma severity, and age of patients. The heterogeneity of non‐eosinophilic N‐ERD suggests a need for novel targeted interventions.

Objectives: To present a personalized approach in three cases of treatment-resistant, locoregionally aggressive forms of cANCA-positive granulomatosis with polyangiitis (GPA) and skull base involvement. Methods: Three patients with GPA and skull base involvement were described alongside a critical review of the current literature. Results: All presented patients suffered from GPA with an inflammatory tumor at the skull base, alongside cerebellopontine angle involvement, cranial nerve palsies, cerebellar disorders, concomitant hearing loss, and severe otalgia. Symptoms were associated with progressive granulomatous destruction of the temporal bone, laryngopharynx, and central nervous system infiltration. Treatment with cyclophosphamide and high doses of glucocorticoid steroids were ineffective but subsequent therapy with rituximab was successful in the presented cases. The literature review showed that the course of the disease with skull base involvement is associated with poorer clinical and radiological responses to standard pharmacotherapies. Conclusion: Granulomatous inflammation localized in the skull base is associated with a more aggressive disease progression and is less likely to respond to pharmacotherapy. Standard induction therapy with cyclophosphamide and glucocorticoid steroids may be ineffective. A better response may be achieved by using rituximab and concomitant local treatment with glucocorticoid steroid injections.

Abstract Wake-related ketamine-dependent high frequency oscillations (HFO) can be recorded in local field potentials (LFP) from cortical and subcortical regions in rodents. The mechanisms underlying their generation and occurrence in higher mammals are unclear. Unfortunately, anesthetic doses of pure ketamine attenuate HFO, which has precluded their investigation under anesthesia. Here, we show ketamine-xylazine (KX) anesthesia is associated with a prominent 80–130 Hz rhythm in the olfactory bulb (OB) of rats, whereas 30–65 Hz gamma power is diminished. Simultaneous LFP and thermocouple recordings revealed the 80–130 Hz rhythm was dependent on nasal respiration. This rhythm persisted despite surgical excision of the piriform cortex. Silicon probes spanning the dorsoventral aspect of the OB revealed this rhythm was strongest in ventral areas and associated with microcurrent sources about the mitral layer. Pharmacological microinfusion studies revealed dependency on excitatory-inhibitory synaptic activity, but not gap junctions. Finally, a similar rhythm occurred in the OB of KX-anesthetized cats, which shared key features with our rodent studies. We conclude that the activity we report here is driven by nasal airflow, local excitatory-inhibitory interactions, and conserved in higher mammals. Additionally, KX anesthesia is a convenient model to investigate further the mechanisms underlying wake-related ketamine-dependent HFO.

Airway inflammation in asthma is related to increased reactive oxygen species generation, potentially leading to tissue injury and subsequent airway remodeling. We evaluated oxidative stress in peripheral blood from asthmatic subjects (n = 74) and matched controls (n = 65), using recently developed real-time monitoring of the protein hydroperoxide (HP) formation by the coumarin boronic acid (CBA) assay. We also investigated the relation of the systemic oxidative stress response in asthma to disease severity, lung function, airway remodeling indices (lung computed tomography and histology), and blood and bronchoalveolar lavage fluid (BAL) inflammatory biomarkers. We documented enhanced systemic oxidative stress in asthma, reflected by 35% faster and 58% higher cumulative fluorescent product generation in the CBA assay (p < 0.001 for both). The dynamics of HP generation correlated inversely with lung function but not with asthma severity or histological measures of airway remodeling. HP generation was associated positively with inflammatory indices in the blood (e.g., C-reactive protein) and BAL (e.g., interleukin [IL]-6, IL-12p70, and neutrophil count). Bronchial obstruction, thicker airway walls, increased BAL IL-6, and citrullinated histone 3 in systemic circulation independently determined increased HP formation. In conclusion, a real-time CBA assay showed increased systemic HP generation in asthma. In addition, it was associated with inflammatory biomarkers, suggesting that proper disease control can also lead to a decrease in oxidative stress.

ACL injuries – next to damage to the collateral ligaments, menisci of the knee – are the most common injuries of the knee joint and very often require surgical treatment. The main aim of the treatment is to restore normal gait pattern. The objective of this study was to determine the influence of reconstructed ACL on selected gait parameters by using an accelerometer system. The study involved 34 people aged 18-54 who were divided in two groups. The first group consisted of 20 people after ACL reconstruction, aged 19-54 years old (mean 29). The second group consisted of 14 healthy people between the age of 18-45 (mean 25.36). Gait analysis in normal and fast rate was performed using the CQMotion Electronik System, MEMS type. Differences in the results were observed in the first group. In 75% of people during normal walking and in 95% during fast walking, a 5% difference between the healthy limb and the limb after ACL reconstruction was observed. The gait rate had influence on acceleration value which was observed in RMS values in both of the groups. The RMS value was different, depending on the gait rate. Accelerometric gait analysis shows that the differences in comparing rate values between limbs are not so great, however, the gait pace has influence on some gait parameters. parameters.

Laminar population analysis (LPA) is a method for analysis of electrical data recorded by linear multielectrodes passing through all lamina of cortex. Like principal components analysis (PCA) and independent components analysis (ICA), LPA offers a way to decompose the data into contributions from separate cortical populations. However, instead of using purely mathematical assumptions in the decomposition, LPA is based on physiological constraints, i.e., that the observed LFP (low-frequency part of signal) is driven by action-potential firing as observed in the MUA (multi-unit activity; high-frequency part of the signal). In the presently developed generalized laminar population analysis (gLPA) the set of basis functions accounting for the LFP data is extended compared to the original LPA, thus allowing for a better fit of the model to experimental data. This enhances the risk for overfitting, however, and we therefore tested various versions of gLPA on virtual LFP data in which we knew the ground truth. These synthetic data were generated by biophysical forward-modelling of electrical signals from network activity in the comprehensive, and well-known, thalamocortical network model developed by Traub and coworkers. The results for the Traub model imply that while the laminar components extracted by original LPA method overall are in fair agreement with the ground-truth laminar components, the results may be improved by use of gLPA method with two (gLPA-2) or even three (gLPA-3) postsynaptic LFP kernels per laminar population.