Single-cell meta-analysis of cigarette smoking lung atlas

Single-cell RNA-seq (scRNA-seq) technologies have been broadly utilized to reveal the molecular mechanisms of respiratory diseases and physiology at single-cell resolution. Here, we constructed a cigarette smoking lung atlas by integrating data from 8 public datasets, including 104 lung scRNA-seq samples with patient state information. The cigarette smoking lung atlas generated by this single-cell meta-analysis (scMeta-analysis) revealed early carcinogenesis events and defined the alterations of single-cell gene expression, cell population, fundamental properties of biological pathways, and cell-cell interactions induced by cigarette smoking. In addition, we developed two novel scMeta-analysis methods incorporating clinical metadata: VARIED (Visualized Algorithms of Relationships In Expressional Diversity) and AGED (Aging-related Gene Expressional Differences). VARIED analysis revealed the expressional diversity associated with smoking carcinogenesis in each cell population. AGED analysis revealed differences in gene expression related to both aging and smoking states. Our scMeta-analysis provided new insights into the effects of smoking and into cellular diversity in the human lung at single-cell resolution.

Concentration of Circulating Cell-Free DNA in the Peripheral Blood Plasma of Patients with Acute Endogenous and Exogenous Etiology Psychoses

Introduction: cell-free plasma DNA (cfDNA) is used as a marker refl ecting the level of apoptosis in the human body under stress. Acute psychosis caused by endogenous (schizophrenia) and exogenous (alcohol intoxication) factors in the patient’s body is associated with oxidative stress. Presumably, cfDNA concentration in the blood plasma of patients with acute psychoses of endogenous and exogenous etiology is increased. The purpose of the study: comparative analysis of the cfDNA concentration in the blood plasma of treated and untreated patients with paranoid schizophrenia during the disease exacerbation, patients with alcoholic psychosis and healthy volunteers. Patients and methods: the concentration of cfDNA was determined in the blood plasma samples of 476 people: control group (n = 95); patients with schizophrenia in the acute stage of the disease (n = 334); patients with alcoholic psychosis (n = 47). Results: the concentrations of cfDNA in the plasma of patients with schizophrenia (median 931 ng/ml) is 2.2 times higher than in the control group (median 428 ng/ml) and 1.8 times higher than in the patients with alcoholic psychosis (504 ng/ml). For the patients with schizophrenia with high PANSS, we found the highest values of the cfDNA concentration in the blood plasma during psychosis, which indicates a more pronounced systemic process, which is accompanied by the cell death level increase. Conclusions: the concentration of cfDNA in the blood plasma could be used as a biochemical marker that refl ects the severity of the schizophrenia patient’ state upon admission to the hospital.

Dexmedetomidine Induces Low Patient State Indices While Preventing the Development of Postoperative Delirium in Older Patients Undergoing General Anesthesia - A Secondary Analysis of a Randomized Controlled Trial (NEUPRODEX)

Background: Dexmedetomidine may have a delirium preventive effect in high-risk surgical patients. Accurate frontal EEG-guided anesthesia can decrease the incidence of postoperative delirium by avoiding too deep anesthesia. Aim of our study is to evaluate the incidence of postoperative delirium under intraoperative frontal EEG neuromonitoring during general anesthesia with dexmedetomidine.Methods: A secondary analysis of a single-center, randomized, double-blinded, placebo-controlled trial. Patients > 60 years were included with either abdominal or cardiac surgery, receiving intraoperative dexmedetomidine or placebo. Delirium incidence was measured up to the fifth postoperative day. Anesthetic depth was measured as Patient State Index (PSi™) every 15 minutes during surgery using EEG-based neuromonitoring.Results: Of the 60 patients included, the incidence of postoperative delirium was significantly reduced in the dexmedetomidine group (n=28) vs. the control group (n=32) (p=0.031). A PSi less than 25 at least once was seen in 85.2% of the verum group and 58.1% of the placebo group (p=0.024). The mean (SD) PSi value in the dexmedetomidine group was 28.17 (10.35) and 33.55 (11.31) in the placebo group using mixed-model ANOVA.Conclusions: Intraoperative Dexmedetomidine reduces the incidence of postoperative delirium in older patients at risk, although presenting with lower intraoperative PSi levels.

Investigation of Inaccuracies in the Assessment of Ventricular Late Potentials Using 12-lead ECG Recordings

Introduction. Ventricular late potentials (VLP) are predictors of cardiac disorders such as sudden death syndrome, myocardial infarction and ventricular tachyarrhythmias. Therefore, VLP assessment allows the severity and possible dangerous consequences of such disorders to be predicted.Aim. To determine errors associated with VLP assessment by high-resolution 12-lead ECG recordings.Materials and methods. VLPs were determined by the modulus of the cardiac electrical vector using signals from orthogonal leads. The conversion error was assessed using synchronous ECG recordings of 12-channel and orthogonal leads, the method of digital filtering (to reduce noise and interference) and the method of identifying characteristic points of the QRS complex and VLPs.Results. The conversion of 12-lead ECG signals into orthogonal signals results in errors associated with the assessment of both the modulus of the cardiac electrical vector and all VLP indicators. The Kors transformation was shown to provide the minimum errors when assessing the cardiac electrical vector modulus in the QRS area, with the errors related to the VRMS assessment not exceeding 0.084 %. The estimation of the QRSd and LAS errors should consider the nature of VLP variations and the zone of uncertainty in their assessment. The ambiguity of the results of assessing the boundaries of violations and the absence of pathologies in cardiac ventricular depolarization indicates the influence of a large number of factors on research accuracy. Errors in the assessment of these factors may result in under- and overestimation of dangerous heart rhythm disturbances and incorrect prediction of the patient' state.Conclusion. The obtained results can be used for reducing errors associated with the assessment of VLP indicators, improving the diagnostic accuracy of dangerous heart rhythm disturbances and predicting disease exacerbation due to structural and morphological disorders of the myocardium.

Per-COVID-19: A Benchmark Dataset for COVID-19 Percentage Estimation from CT-Scans

COVID-19 infection recognition is a very important step in the fight against the COVID-19 pandemic. In fact, many methods have been used to recognize COVID-19 infection including Reverse Transcription Polymerase Chain Reaction (RT-PCR), X-ray scan, and Computed Tomography scan (CT- scan). In addition to the recognition of the COVID-19 infection, CT scans can provide more important information about the evolution of this disease and its severity. With the extensive number of COVID-19 infections, estimating the COVID-19 percentage can help the intensive care to free up the resuscitation beds for the critical cases and follow other protocol for less severity cases. In this paper, we introduce COVID-19 percentage estimation dataset from CT-scans, where the labeling process was accomplished by two expert radiologists. Moreover, we evaluate the performance of three Convolutional Neural Network (CNN) architectures: ResneXt-50, Densenet-161, and Inception-v3. For the three CNN architectures, we use two loss functions: MSE and Dynamic Huber. In addition, two pretrained scenarios are investigated (ImageNet pretrained models and pretrained models using X-ray data). The evaluated approaches achieved promising results on the estimation of COVID-19 infection. Inception-v3 using Dynamic Huber loss function and pretrained models using X-ray data achieved the best performance for slice-level results: 0.9365, 5.10, and 9.25 for Pearson Correlation coefficient (PC), Mean Absolute Error (MAE), and Root Mean Square Error (RMSE), respectively. On the other hand, the same approach achieved 0.9603, 4.01, and 6.79 for PCsubj, MAEsubj, and RMSEsubj, respectively, for subject-level results. These results prove that using CNN architectures can provide accurate and fast solution to estimate the COVID-19 infection percentage for monitoring the evolution of the patient state.

Comparison of polyetheretherketone cables and stainless steel wires for sternal fixation after median sternotomy

Objective To compare the sternal fixation effect of a polyetheretherketone (PEEK) cable product and stainless steel wire after median sternotomy. Methods A multicentre retrospective clinical trial was conducted in patients that underwent median sternotomy for a range of surgical reasons. The sternum was fixed using PEEK sternal cables in the experimental group and stainless steel wires in the control group. The general patient state, product manoeuvrability, bone and wound healing state and blood test results were evaluated at seven visits during the preoperative, surgical and follow-up periods. Results A total of 108 patients (54 in each group) were included in the analysis at the final 180-day follow-up. The sternum was successfully closed using PEEK cables or steel wires in all patients and all healed well. No pathological changes were found on the X-ray imaging. Computed tomography imaging confirmed ideal fracture healing. No significant difference was found between the experimental group and the control group in outcomes. Conclusion PEEK cables are easy to implant and show desirable effectiveness in sternal fixation without any observed side-effects.