Quantitative gradient recalled echo (qGRE) MRI enables in vivo measurement of pre-atrophic neurodegeneration in a mouse model of Alzheimer's disease.

Robust methods are needed for preclinical evaluation of novel Alzheimer Disease (AD) therapies to accelerate drug discovery. Quantitative Gradient Recalled Echo (qGRE) MRI has shown promise to provide insight into neurodegeneration in AD prior to atrophy development in humans, highlighting areas of low neuronal density. In this study a novel qGRE method (20 echoes, TE=2-40ms) is shown to non-invasively measure the longitudinal neuronal loss in the hippocampus of a mouse model of AD tauopathy Tg4510. Tg4510 (n=10) and wild type (WT, n=6) mice underwent MRI (7T field strength) at 3-7 months old. 3D qGRE approach was used to generate brain-specific R2* maps free of magnetic field inhomogeneity artifacts. Light-sheet microscopy of the brains stained with NeuN and MBP served to visualize neuronal nuclei and myelin content respectively. Significant decrease in NeuN staining between 3mo and 5mo was observed in the hippocampus of Tg4510, validating the mouse AD model. Longitudinal analysis showed clear decreases in R2* metric of qGRE signal in the Tg4510 mice hippocampus undergoing neurodegeneration between 3 and 5 months old. Histogram analysis revealed an upward trend in patterns of low R2* value (Dark Matter, DM), and broadening of R2* distribution. These were quantified as significant increase in both DM Volume Fraction (DMVF) and R2* Standard Deviation (SD) in Tg4510 mice (p=0.004/p=0.016 DMVF/SD) but not in WT controls (p>0.25). Further monotonical increase was also observed in both metrics in time. A significant negative correlation was observed between the DMVF and myelin content (p=0.01, r=-0.76), suggesting sensitivity of the technique to the loss of myelinated axons. The presented qGRE technique, validated by histological measurements, can be readily applied as in vivo tool in preclinical models of neurodegeneration for pharmacodynamics and mechanism of action assessment.

From data to decision: Machine learning determination of aerobic and anaerobic thresholds in athletes.

Lactate analysis plays an important role in sports science and training decisions for optimising performance, endurance, and overall success in sports. Two parameters are widely used for these goals: aerobic (AeT) and anaerobic (AnT) thresholds. However, determining AeT proves more challenging than AnT threshold due to both physiological intricacies and practical considerations. Thus, the aim of this study was to determine AeT and AnT thresholds using machine learning modelling (ML) and to compare ML-obtained results with the parameters' values determined using conventional methods. ML seems to be highly useful due to its ability to handle complex, personalised data, identify nonlinear relationships, and provide accurate predictions. The 183 results of CardioPulmonary Exercise Test (CPET) accompanied by lactate and heart ratio analyses from amateur athletes were enrolled to the study and ML models using the following algorithms: Random Forest, XGBoost (Extreme Gradient Boosting), and LightGBM (Light Gradient Boosting Machine) and metrics: R2, mean absolute error (MAE), mean squared error (MSE) and root mean square error (RMSE). The regressors used belong to the group of ensemble learning algorithms that combine the predictions of multiple base models to improve overall performance and counteract overfitting to training data. Based on evaluation metrics, the following models give the best predictions: for AeT: Random Forest has an R2 value of 0.645, MAE of 4.630, MSE of 44.450, RMSE of 6.667; and for AnT: LightGBM has an R2 of 0.803, the highest among the models, MAE of 3.439, the lowest among the models, MSE of 20.953, and RMSE of 4.577. Outlined research experiments, a comprehensive review of existing literature in the field, and obtained results suggest that ML models can be trained to make personalised predictions based on an individual athlete's unique physiological response to exercise. Athletes exhibit significant variation in their AeT and AT, and ML can capture these individual differences, allowing for tailored training recommendations and performance optimization.

Novel Echocardiographic Measurements of Right Ventricular-Pulmonary Artery Coupling in Predicting the Prognosis of Precapillary Pulmonary Hypertension.

BACKGROUND: Currently, there are many parameters with proven prognostic significance in pulmonary hypertension (PH). Recently, the parameters defining right ventricular-pulmonary artery coupling (RVPAC) have gained clinical importance. In our study, we investigated the prognostic potential of previously known single echocardiographic parameters and new parameters reflecting RVPAC in patients with precapillary PH. OBJECTIVE: Our study aimed to evaluate the prognostic value of selected echocardiographic parameters and the neutrophil-lymphocyte ratio (NLR) in adults with precapillary PH. METHODS: This study included 39 patients (74% women; average age, 63 years) with precapillary PH: pulmonary arterial hypertension (PAH) and chronic thromboembolic PH (CTEPH). The mean follow-up period was 16.6 ± 13.3 months. Twelve patients (31%) died during the observation time. We measured several echocardiographic parameters, which reflect right ventricular function, pulmonary hemodynamics, and RVPAC. To assess disease progression and the patient's functional capacity, the World Health Organization functional class (WHO FC) was determined. The patient's physical capacity was also evaluated using the 6 min walk test (6MWT). The analysis included values of the N-terminal prohormone brain natriuretic peptide (NT-proBNP) and NLR. RESULTS: TAPSE × AcT and TAPSE/sPAP were shown to statistically and significantly correlate with PH predictors, including WHO-FC, 6MWT, and NT-proBNP. Univariate Cox proportional hazards regression analysis revealed that AcT, TAPSE, mPAP, TAPSE/sPAP, RAP, TRPG/AcT, TAPSE × AcT, and NLRs are good predictors of mortality in patients with PH. In addition, the ROC curve analysis showed that TAPSE × AcT is a better predictor of PH-related deaths than TAPSE/sPAP and TAPSE alone. In our study, patients with TAPSE × AcT values < 126.36 had shorter survival times (sensitivity = 72.7%; specificity = 80.0%). CONCLUSIONS: TAPSE × AcT is a novel, promising, and practicable echocardiographic parameter reflecting RVPAC, which is comparable to TAPSE/sPAP. Moreover, TAPSE × AcT can be a useful parameter in assessing the severity and prognosis of patients with precapillary PH.

In the Search for Biomarkers of Pulmonary Arterial Hypertension, Are Cytokines IL-2, IL-4, IL-6, IL-10, and IFN-Gamma the Right Indicators to Use?

Pulmonary arterial hypertension (PAH) is a complex disorder characterized by increased pressure in the pulmonary arteries, leading to right heart failure. While the exact mechanisms underlying PAH are not fully understood, cytokines have been implicated in the pathogenesis of the disease. Cytokines play a crucial role in regulating immune responses and inflammation. These small proteins also play a key role in shaping the immunophenotype, which refers to the specific characteristics and functional properties of immune cells, which can have a significant impact on the development of PAH. The aim of this study was to determine the immunophenotype and the concentration of selected cytokines, IL-2, IL-4, IL-6, IL-10, and IFN-gamma, in patients diagnosed with PAH (with particular emphasis on subtypes) in relation to healthy volunteers. Based on the obtained results, we can conclude that in patients with PAH, the functioning of the immune system is deregulated as a result of a decrease in the percentage of selected subpopulations of immune cells in peripheral blood and changes in the concentration of tested cytokines in relation to healthy volunteers. In addition, a detailed analysis showed that there are statistically significant differences between the PAH subtypes and the tested immunological parameters. This may indicate a significant role of the immune system in the pathogenesis of PAH.

Tricuspid Regurgitation Velocity/Tricuspid Annular Plane Systolic Excursion (TRV/TAPSE) Ratio as a Novel Indicator of Disease Severity and Prognosis in Patients with Precapillary Pulmonary Hypertension.

BACKGROUND: Tricuspid annular plane systolic excursion (TAPSE) and tricuspid regurgitation velocity (TRV) are two echocardiographic parameters with prognostic value in patients with pulmonary hypertension (PH). When analyzed concurrently as the TRV/TAPSE ratio, they allow the ventricular-pulmonary artery coupling (RVPAC) to be assessed. This could better predict disease severity in patients with PH. OBJECTIVE: Our study aimed to evaluate the prognostic value of the TRV/TAPSE ratio echocardiographic parameter in adults with precapillary PH. METHODS: This study included 39 patients (74% women; average age, 63 years) with precapillary PH (pulmonary arterial hypertension and chronic thromboembolic PH) The mean follow-up period was 16.6 ± 13.3 months. Twelve patients (31%) died during the observation time. We measured TAPSE as a surrogate of RV contractility and TRV reflecting RV afterload, while ventricular-arterial coupling was evaluated by the ratio between these two parameters (TRV/TAPSE). To assess disease progression and the patient's functional capacity, the World Health Organization functional class (WHO FC) was determined. Patient physical capacity was also evaluated using the 6 min walk test (6MWT). The analysis included values of N-terminal prohormone brain natriuretic peptide (NT-proBNP), which were taken routinely during the follow-up visit. RESULTS: The mean calculated TRV/TAPSE ratio was 0.26 ± 0.08 m/s/mm. Upon comparison of the TRV/TAPSE ratio to the disease prognostic indicators, we observed a statistically significant correlation between TRV/TAPSE and the results of the WHO FC, 6MWT, and NT-proBNP. The TRV/TAPSE ratio is thus a good predictor of mortality in PH patients (AUC, 0.781). Patients with a TRV/TAPSE ratio > 0.30 m/s/mm had a shorter survival time, with log-rank test p < 0.0001. Additionally, ROC analysis revealed higher AUC for TRV/TAPSE than for TAPSE and TRV alone. CONCLUSIONS: TRV/TAPSE is a promising practicable echocardiographic parameter reflecting RVPAC. Moreover, TRV/TAPSE could be viable risk stratification parameter and could have prognostic value in patients with PH.

Overview of Image Datasets for Deep Learning Applications in Diagnostics of Power Infrastructure.

The power sector is one of the most important engineering sectors, with a lot of equipment that needs to be appropriately maintained, often spread over large areas. With the recent advances in deep learning techniques, many applications can be developed that could be used to automate the power line inspection process, replacing previously manual activities. However, in addition to these novel algorithms, this approach requires specialized datasets, collections that have been properly curated and labeled with the help of experts in the field. When it comes to visual inspection processes, these data are mainly images of various types. This paper consists of two main parts. The first one presents information about datasets used in machine learning, especially deep learning. The need to create domain datasets is justified using the example of the collection of data on power infrastructure objects, and the selected repositories of different collections are compared. In addition, selected collections of digital image data are characterized in more detail. The latter part of the review also discusses the use of an original dataset containing 2630 high-resolution labeled images of power line insulators and comments on the potential applications of this collection.

Basilar tip fenestration giving rise to Percheron's and mesencephalic arteries.

The basilar bifurcation region is a common site for intracranial aneurysms, as well as it gives rise to a group of perforating arteries that supply the mesencephalon and the thalamus. Complex vascular microanatomy poses a diagnostic and therapeutic challenge for neurosurgeons, neuroradiologists and neurologists. In this paper, we present a previously unreported case of basilar tip fenestration that gave rise to five perforating arteries: the artery of Percheron and four mesencephalic arteries. Due to invaluable clinical significance, the possibility of such a variant must be considered during performing various neurovascular procedures, since e.g., embolization of the fenestration misdiagnosed as an aneurysm would inevitably lead to severe neurological complications (consciousness disturbances, quadriplegia, and sensory loss). Comprehensive knowledge of the neuroanatomy and neuroembryology is crucial to safe execution of intracranial interventions.

Magnetic resonance imaging detects white adipose tissue beiging in mice following PDE10A inhibitor treatment.

Weight gain is a common harmful side effect of atypical antipsychotics used for schizophrenia treatment. Conversely, treatment with the novel phosphodiesterase-10A (PDE10A) inhibitor MK-8189 in clinical trials led to significant weight reduction, especially in patients with obesity. This study aimed to understand and describe the mechanism underlying this observation, which is essential to guide clinical decisions. We hypothesized that PDE10A inhibition causes beiging of white adipose tissue (WAT), leading to weight loss. Magnetic resonance imaging (MRI) methods were developed, validated, and applied in a diet-induced obesity mouse model treated with a PDE10A inhibitor THPP-6 or vehicle for measurement of fat content and vascularization of adipose tissue. Treated mice showed significantly lower fat fraction in white and brown adipose tissue, and increased perfusion and vascular density in WAT versus vehicle, confirming the hypothesis, and matching the effect of CL-316,243, a compound known to cause adipose tissue beiging. The in vivo findings were validated by qPCR revealing upregulation of Ucp1 and Pcg1-α genes, known markers of WAT beiging, and angiogenesis marker VegfA in the THPP-6 group. This work provides a detailed understanding of the mechanism of action of PDE10A inhibitor treatment on adipose tissue and body weight and will be valuable to guide both the use of MK-8189 in schizophrenia and the potential application of the target for weight loss indication.

Impact of diabetes mellitus on disease severity and patient survival in idiopathic pulmonary arterial hypertension: data from the Polish multicentre registry (BNP-PL).

BACKGROUND: Recent studies revealed that alterations in glucose and lipid metabolism in idiopathic pulmonary arterial hypertension (IPAH) are associated with disease severity and poor survival. However, data regarding the impact of diabetes mellitus (DM) on the prognosis of patients with IPAH remain scarce. The aim of our study was to determine that impact using data from a national multicentre prospective pulmonary hypertension registry. METHODS: We analysed data of adult patients with IPAH from the Database of Pulmonary Hypertension in the Polish population (BNP­PL) between March 1, 2018 and August 31, 2020. Upon admission, clinical, echocardiographic, and haemodynamic data were collected at 21 Polish IPAH reference centres. The all-cause mortality was assessed during a 30-month follow-up period. To adjust for differences in age, body mass index (BMI), and comorbidities between patients with and without DM, a 2-group propensity score matching was performed using a 1:1 pairing algorithm. RESULTS: A total of 532 patients with IPAH were included in the study and 25.6% were diagnosed with DM. Further matched analysis was performed in 136 patients with DM and 136 without DM. DM was associated with older age, higher BMI, more advanced exertional dyspnea, increased levels of N-terminal pro-brain natriuretic peptide, larger right atrial area, increased mean right atrial pressure, mean pulmonary artery pressure, pulmonary vascular resistance, and all-cause mortality compared with no DM. CONCLUSIONS: Patients with IPAH and DM present with more advanced pulmonary vascular disease and worse survival than counterparts without DM independently of age, BMI, and cardiovascular comorbidities.

Early detection of Solanum lycopersicum diseases from temporally-aggregated hyperspectral measurements using machine learning.

Some plant diseases can significantly reduce harvest, but their early detection in cultivation may prevent those consequential losses. Conventional methods of diagnosing plant diseases are based on visual observation of crops, but the symptoms of various diseases may be similar. It increases the difficulty of this task even for an experienced farmer and requires detailed examination based on invasive methods conducted in laboratory settings by qualified personnel. Therefore, modern agronomy requires the development of non-destructive crop diagnosis methods to accelerate the process of detecting plant infections with various pathogens. This research pathway is followed in this paper, and an approach for classifying selected Solanum lycopersicum diseases (anthracnose, bacterial speck, early blight, late blight and septoria leaf) from hyperspectral data captured on consecutive days post inoculation (DPI) is presented. The objective of that approach was to develop a technique for detecting infection in less than seven days after inoculation. The dataset used in this study included hyperspectral measurements of plants of two cultivars of S. lycopersicum: Benito and Polfast, which were infected with five different pathogens. Hyperspectral reflectance measurements were performed using a high-spectral-resolution field spectroradiometer (350-2500 nm range) and they were acquired for 63 days after inoculation, with particular emphasis put on the first 17 day-by-day measurements. Due to a significant data imbalance and low representation of measurements on some days, the collective datasets were elaborated by combining measurements from several days. The experimental results showed that machine learning techniques can offer accurate classification, and they indicated the practical utility of our approaches.

Patient Satisfaction with a Dedicated Infusion Pump for Subcutaneous Treprostinil to Treat Pulmonary Arterial Hypertension.

Background and Objectives: Parenteral prostacyclins are crucial in the pharmacological treatment of pulmonary arterial hypertension (PAH). Indeed, subcutaneous administration of treprostinil has been associated with considerable clinical and hemodynamic improvement, right-sided heart reverse remodeling, and long-term survival benefit. However, evidence on patient perceptions about handling a subcutaneous infusion pump for self-treatment administration and nurse views about training the patients are lacking. This study aimed to describe the perception of PAH patients and nurses regarding the use of the new portable I-Jet infusion pump for the self-administration of subcutaneous treprostinil, as well as its real-world training needs. Materials and Methods: The study is an open, observational, prospective, single-center, non-interventional study. Patients with PAH on stable therapy with subcutaneous treprostinil were invited to take part in the study at their start of use of the portable I-Jet infusion pump for the self-administration of treatment. Participants filled in a questionnaire to report their satisfaction with the use of the pump, as well as their compliance, confidence, convenience, preferences, technical issues, and perceptions of the training they received. Results: Thirteen patients completed the questionnaire after being on the pump for 2 months: 69% were females and the mean age was 51 years. The most frequent PAH etiologies were congenital heart disease (46.2%) and idiopathic PAH (38.4%). Most patients were either World Health Organization (WHO) functional class II (53.8%) or III (46.2%). Ten patients (76.9%) found the pump easy and convenient to live with. All patients declared themselves to be fully compliant and confident in using the pump (n = 13) at the end of the study follow-up. Ten patients (76.9%) would choose the new pump in the future. None of the patients made reference to technical issues that required additional hospital visits. Eight patients (61.6%) reported that learning how to use the I-Jet infusion pump was easy or very easy, and none considered that further training was needed. One trainer nurse was interviewed and confirmed the satisfaction of patients and the simplicity of usage and training. Conclusions: PAH patients were highly satisfied with the use of the new portable I-Jet infusion pump for self-administering subcutaneous treprostinil. Convenience and ease of use were valuable and commonly reported features. Moreover, the training requirement was simple. These preliminary findings support the routine use of the I-Jet infusion pump.

Detection of Power Line Insulators in Digital Images Based on the Transformed Colour Intensity Profiles.

Proper maintenance of the electricity infrastructure requires periodic condition inspections of power line insulators, which can be subjected to various damages such as burns or fractures. The article includes an introduction to the problem of insulator detection and a description of various currently used methods. Afterwards, the authors proposed a new method for the detection of the power line insulators in digital images by applying selected signal analysis and machine learning algorithms. The insulators detected in the images can be further assessed in depth. The data set used in the study consists of images acquired by an Unmanned Aerial Vehicle (UAV) during its overflight along a high-voltage line located on the outskirts of the city of Opole, Opolskie Voivodeship, Poland. In the digital images, the insulators were placed against different backgrounds, for example, sky, clouds, tree branches, elements of power infrastructure (wires, trusses), farmland, bushes, etc. The proposed method is based on colour intensity profile classification on digital images. Firstly, the set of points located on digital images of power line insulators is determined. Subsequently, those points are connected using lines that depict colour intensity profiles. These profiles were transformed using the Periodogram method or Welch method and then classified with Decision Tree, Random Forest or XGBoost algorithms. In the article, the authors described the computational experiments, the obtained results and possible directions for further research. In the best case, the proposed solution achieved satisfactory efficiency (F1 score = 0.99). Promising classification results indicate the possibility of the practical application of the presented method.

Decomposition-based framework for tumor classification and prediction of treatment response from longitudinal MRI.

Objective.In the field of radiation oncology, the benefit of MRI goes beyond that of providing high soft-tissue contrast images for staging and treatment planning. With the recent clinical introduction of hybrid MRI linear accelerators it has become feasible to map physiological parameters describing diffusion, perfusion, and relaxation during the entire course of radiotherapy, for example. However, advanced data analysis tools are required for extracting qualified prognostic and predictive imaging biomarkers from longitudinal MRI data. In this study, we propose a new prediction framework tailored to exploit temporal dynamics of tissue features from repeated measurements. We demonstrate the framework using a newly developed decomposition method for tumor characterization.Approach.Two previously published MRI datasets with multiple measurements during and after radiotherapy, were used for development and testing:T2-weighted multi-echo images obtained for two mouse models of pancreatic cancer, and diffusion-weighted images for patients with brain metastases. Initially, the data was decomposed using the novel monotonous slope non-negative matrix factorization (msNMF) tailored for MR data. The following processing consisted of a tumor heterogeneity assessment using descriptive statistical measures, robust linear modelling to capture temporal changes of these, and finally logistic regression analysis for stratification of tumors and volumetric outcome.Main Results.The framework was able to classify the two pancreatic tumor types with an area under curve (AUC) of 0.999,P< 0.001 and predict the tumor volume change with a correlation coefficient of 0.513,P= 0.034. A classification of the human brain metastases into responders and non-responders resulted in an AUC of 0.74,P= 0.065.Significance.A general data processing framework for analyses of longitudinal MRI data has been developed and applications were demonstrated by classification of tumor type and prediction of radiotherapy response. Further, as part of the assessment, the merits of msNMF for tumor tissue decomposition were demonstrated.

Gut-Lung Axis in Focus: Deciphering the Impact of Gut Microbiota on Pulmonary Arterial Hypertension.

Recent advancements in the understanding of pulmonary arterial hypertension (PAH) have highlighted the significant role of the gut microbiota (GM) in its pathogenesis. This comprehensive review delves into the intricate relationship between the GM and PAH, emphasizing the influence of gut microbial composition and the critical metabolites produced. We particularly focus on the dynamic interaction between the gut and lung, examining how microbial dysbiosis contributes to PAH development through inflammation, altered immune responses, and changes in the gut-lung axis. Noteworthy findings include variations in the ratios of key bacterial groups such as Firmicutes and Bacteroidetes in PAH and the pivotal roles of metabolites like trimethylamine N-oxide (TMAO), short-chain fatty acids (SCFAs), and serotonin in the disease's progression. Additionally, the review elucidates potential diagnostic biomarkers and novel therapeutic approaches, including the use of probiotics and fecal microbiota transplantation, which leverage the gut microbiota for managing PAH. This review encapsulates the current state of research in this field, offering insights into the potential of gut microbiota modulation as a promising strategy in PAH diagnosing and treatment.

CTLA-4 Expression Is a Promising Biomarker of Idiopathic Pulmonary Arterial Hypertension and Allows Differentiation of the Type of Pulmonary Hypertension.

Pulmonary arterial hypertension (PAH) is an increasingly frequently diagnosed disease, the molecular mechanisms of which have not been thoroughly investigated. The aim of our study was to investigate subpopulations of lymphocytes to better understand their role in the molecular pathomechanisms of various types of PAH and to find a suitable biomarker that could be useful in the differential diagnosis of PAH. Using flow cytometry, we measured the frequencies of lymphocyte subpopulations CD4+CTLA-4+, CD8+ CTLA-4+ and CD19+ CTLA-4+ in patients with different types of PAH, namely pulmonary arterial hypertension associated with congenital heart disease (CHD-PAH), pulmonary arterial hypertension associated with connective tissue disorders (CTD-PAH), chronic thromboembolic pulmonary hypertension (CTEPH) and idiopathic pulmonary arterial hypertension (iPAH), and in an age- and sex-matched control group in relation to selected clinical parameters. Patients in the iPAH group had the significantly highest percentage of CD4+CTLA-4+ T lymphocytes among all PAH groups, as compared to those in the control group (p < 0.001), patients with CTEPH (p < 0.001), CTD-PAH (p < 0.001) and CHD-PAH (p < 0.01). In iPAH patients, the percentages of CD4+CTLA-4+ T cells correlated strongly positively with the severity of heart failure New York Heart Association (NYHA) Functional Classification (r = 0.7077, p < 0.001). Moreover, the percentage of B CD19+CTLA-4+ cells strongly positively correlated with the concentration of NT-proBNP (r = 0.8498, p < 0.001). We have shown that statistically significantly higher percentages of CD4+CTLA-4+ (p ≤ 0.01) and CD8+ CTLA-4+ (p ≤ 0.001) T cells, measured at the time of iPAH diagnosis, were found in patients who died within 5 years of the diagnosis, which allows us to consider both of the above lymphocyte subpopulations as a negative prognostic/predictive factor in iPAH. CTLA-4 may be a promising biomarker of noninvasive detection of iPAH, but its role in planning the treatment strategy of PAH remains unclear. Further studies on T and B lymphocyte subsets are needed in different types of PAH to ascertain the relationships that exist between them and the disease.

A Diagnostic Method Based on Active Thermography for the Degradation Assessment of Power Plant Boiler Tubes.

Proper maintenance management of power infrastructure requires inspections, in order to gather knowledge about the facility's current condition. For this purpose, periodic diagnostic tests are carried out, not only to determine the current state, but to also predict future conditions, and subsequently plan for the scope of necessary repair work. Currently, in the case of heat screens of power boilers, the diagnostic process takes many days, is very expensive, and usually does not cover the entire screen area. Therefore, it is necessary to develop new, noninvasive diagnostic methods. This study presents the concept and research for an alternative method of locating places with excessive energy boiler screen degradation that require replacement. It was assumed that the new method should be fast, require no scaffolding assembly, and permit checking of the entire screen surface; this is unlike the methods used currently, which require manual checking of selected screen tubes. The proposed method is based on active thermography, in which heat flux is forced by the liquid flowing inside the screen. Tests were carried out based on a model of an axial-symmetric system in the form of a tube, with controlled reductions in the wall thickness. An experiment was carried out many times by recording the pipe surface temperature in many characteristic places (different thicknesses of the tube walls) with a thermal imaging camera. A temperature change was forced by a controlled flow of hot or cold water. The methods of analysis were proposed and verified, allowing firstly, detection of places with a reduced wall thickness, and secondly, estimations of the wall thickness (i.e., excessive degradation). For the best-proposed model (one of the four analyzed), all of the thickness changes were detected, and the limit error of thickness obtained was 0.3 mm.

Mechanism of Spontaneous Intracerebral Hemorrhage Formation: An Anatomical Specimens-Based Study.

BACKGROUND: Despite advances in understanding various risk and prognostic factors, spontaneous intracerebral hemorrhage is connected to very high morbidity and mortality, while the therapy is mainly supportive. Understanding of the pathophysiology of initial hematoma expansion is limited due to insufficient clinical data and lack of a suitable animal model. METHODS: We injected 40 anatomic specimens of the basal ganglia with contrast medium, scanned them with a micro-computed tomography scanner and analyzed the results of radiological studies, direct and histological examinations. RESULTS: In 9 cases, micro-computed tomography and histological examinations revealed contrast medium extravasations mimicking intracerebral hematomas. The artificial hematomas spread both proximally and distally along the ruptured perforator and its branches in the perivascular spaces and detached the branches from the adjacent neural tissue leading to destruction of the tissue and secondary extravasations. Moreover, some contrast extravasations skipped to the perivascular spaces of unruptured perforators, created further extravasation sites and aggravated the expansion of the artificial hematoma. There was no subarachnoid extension of any artificial hematoma. CONCLUSIONS: We postulate that a forming basal ganglia intracerebral hematoma spreads initially in the perivascular space, detaches the branches from the neural tissue and causes secondary bleeding. It can also skip to the perivascular space of a nearby perforator. The proposed mechanism of hematoma initiation and formation explains extent of damage to the neural tissue, variability of growth in time and space, creation of secondary bleeding sites, and limited usefulness of surgical interventions. The model is reproducible, the extent of the artificial hematoma can be easily controlled, the rupture sites of the perforating arteries can be determined, and preparation of the model does not require specialized, expensive equipment apart from the micro-computed tomography scanner.

Impact of the COVID-19 Pandemic on Pulmonary Hypertension Patients: Insights from the BNP-PL National Database.

We aimed to evaluate the clinical course and impact of the SARS-CoV-2 pandemic on the rate of diagnosis and therapy in the complete Polish population of patients (pts) with pulmonary arterial hypertension (PAH-1134) and CTEPH (570 pts) treated within the National Health Fund program and reported in the national BNP-PL database. Updated records of 1704 BNP-PL pts collected between March and December 2020 were analyzed with regard to incidence, clinical course and mortality associated with COVID-19. Clinical characteristics of the infected pts and COVID-19 decedents were analyzed. The rates of new diagnoses and treatment intensification in this period were studied and collated to the proper intervals of the previous year. The incidence of COVID-19 was 3.8% (n = 65) (PAH, 4.1%; CTEPH, 3.2%). COVID-19-related mortality was 28% (18/65 pts). Those who died were substantially older and had a more advanced functional WHO class and more cardiovascular comorbidities (comorbidity score, 4.0 ± 2.1 vs. 2.7 ± 1.8; p = 0.01). During the pandemic, annualized new diagnoses of PH diminished by 25-30% as compared to 2019. A relevant increase in total mortality was also observed among the PH pts (9.7% vs. 5.9% pre-pandemic, p = 0.006), whereas escalation of specific PAH/CTEPH therapies occurred less frequently (14.7% vs. 21.6% pre-pandemic). The COVID-19 pandemic has affected the diagnosis and treatment of PH by decreasing the number of new diagnoses, escalating therapy and enhancing overall mortality. Pulmonary hypertension is a risk factor for worsened course of COVID-19 and elevated mortality.