BackgroundPrimary malignant or metastatic sternal tumors are uncommon. A subtotal or total sternectomy can offer a radical form of treatment. The issue is to restore the structural integrity of the chest wall.Case presentationWe report the implantation of an individualized 3D–printed titanium sternum in a patient with a sternal tumor.ConclusionsWe believe that tridimensional print technologies may also change the strategy of chest wall reconstruction.

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OBJECTIVES: This study evaluated the role of ultrasound in postoperative care after major lung resection. BACKGROUND: High accuracy of lung ultrasound imaging was proved in various medical fi elds. The experience with ultrasound after thoracic surgery is limited. METHODS: Patients scheduled for major lung resection were consecutively included in a prospective study comparing two modalities of imaging examinations, namely those employing ultrasound and X-ray in the diagnoses of pneumothorax and pleural effusion. Two examinations were performed. One after recovery from anaesthesia, the second before chest tube removal. RESULTS: Forty-eight patients underwent 87 examinations. X-ray and ultrasound examinations showed substantial and fair agreements for pneumothorax (Cohen's kappa coeffi cients 0.775 and 0.397) and slight and substantial agreements for pleural effusion (Cohen's kappa coeffi cients 0.036 and 0.611). The sensitivity bounds for pneumothorax were 45.5-58.5 % at the fi rst and 29.7-59.4 % at the second examination. Sensitivity bounds for pleural effusion were 0-86.2 % at the fi rst and 32.6-36.9 % at the second examination. Except for two cases of pneumothorax being missed by X-ray imaging, the rest of mismatches were clinically irrelevant conditions with no impact on clinical decision and patient's outcome. CONCLUSION: The use of ultrasound can reduce the number of X-ray examinations and thus lower the radiation exposure after major lung resections (Tab. 4, Ref. 30).

The authors describe a case of a 36-year-old patient who had six months’ pain of the thoracic spine and left chest. A soft slowly growing resistance was present on the dorso-lateral side of the left chest wall, in the range of the seventh to ninth rib. According to the medical history, the patient did not have any prior trauma and malignancy. A well-defined tumor of the left chest wall with calcifications, which grew to the seventh and eighth intercostal space, was present on computed tomography (CT) and magnetic resonance (MR) scans. The patient underwent resection of the tumor with the chest wall and reconstruction with polypropylene mesh. Histologically, it was a venous hemangioma, one of very rare tumors of the chest wall.

Certain post-thoracic surgery complications are monitored in a standard manner using methods that employ ionising radiation. A need to automatise the diagnostic procedure has now arisen following the clinical trial of a novel lung ultrasound examination procedure that can replace X-rays. Deep learning was used as a powerful tool for lung ultrasound analysis. We present a novel deep-learning method, automated M-mode classification, to detect the absence of lung sliding motion in lung ultrasound. Automated M-mode classification leverages semantic segmentation to select 2D slices across the temporal dimension of the video recording. These 2D slices are the input for a convolutional neural network, and the output of the neural network indicates the presence or absence of lung sliding in the given time slot. We aggregate the partial predictions over the entire video recording to determine whether the subject has developed post-surgery complications. With a 64-frame version of this architecture, we detected lung sliding on average with a balanced accuracy of 89%, sensitivity of 82%, and specificity of 92%. Automated M-mode classification is suitable for lung sliding detection from clinical lung ultrasound videos. Furthermore, in lung ultrasound videos, we recommend using time windows between 0.53 and 2.13 s for the classification of lung sliding motion followed by aggregation.

AbstractDuring the transformation process single nucleotide polymorphisms (SNPs) of key genes, such as p53 Arg72Pro or EGF A61G, may mediate various cellular processes. These variants may be associated with colorectal cancer risk (CRC), but conflicting findings have been reported. The purpose of this study was to determine the association of the SNPs in 5′ UTR of EGF A61G and p53 Arg72Pro and CRC in the Slovak population. The present case-control study was carried out in 173 confirmed CRC patients and 303 healthy subjects. Genotyping was performed by PCR-RFLP methods. Significant association was observed between age and CRC risk (p=0.001). Lower CRC risk was seen in younger patients carrying genotype p53 Arg72Pro (0.14; 95% CI 0.02–0.99, p=0.049). Gender-stratified analysis showed a significant inverse association of the polymorphism EGF G61G with CRC risk (0.48; 95% CI 0.2–0.9, p=0.04) only in male patients. Tumour site genotype distribution revealed that female patients with localized colon cancer were significantly associated with p53 Pro72Pro genotype (4.0; 95% CI 1.27–12.7, p=0.04) whereas the cancer of rectosigmoid junction was associated with the EGF G61G genotype (4.5; 95% CI 1.2–16.97, p=0.02). Combination of p53 Arg72Pro or EGF A61G polymorphisms were not associated with CRC risk by using logistic regression.

The global pandemic of coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is having a tremendous impact on the global economy, health care systems and the lives of almost all people in the world. The Central European country of Slovakia reached one of the highest daily mortality rates per 100,000 inhabitants in the first 3 months of 2021, despite implementing strong prophylactic measures, lockdowns and repeated nationwide antigen testing. The present study reports a comparison of the performance of the Standard Q COVID-19 antigen test (SD Biosensor) with three commercial RT-qPCR kits (vDetect COVID-19-MultiplexDX, gb SARS-CoV-2 Multiplex-GENERI BIOTECH Ltd. and Genvinset COVID-19 [E]-BDR Diagnostics) in the detection of infected individuals among employees of the Martin University Hospital in Slovakia. Health care providers, such as doctors and nurses, are classified as “critical infrastructure”, and there is no doubt about the huge impact that incorrect results could have on patients. Out of 1231 samples, 14 were evaluated as positive for SARS-CoV-2 antigen presence, and all of them were confirmed by RT-qPCR kit 1 and kit 2. As another 26 samples had a signal in the E gene, these 40 samples were re-isolated and subsequently re-analysed using the three kits, which detected the virus in 22, 23 and 12 cases, respectively. The results point to a divergence not only between antigen and RT-qPCR tests, but also within the “gold standard” RT-qPCR testing. Performance analysis of the diagnostic antigen test showed the positive predictive value (PPV) to be 100% and negative predictive value (NPV) to be 98.10%, indicating that 1.90% of individuals with a negative result were, in fact, positive. If these data are extrapolated to the national level, where the mean daily number of antigen tests was 250,000 in April 2021, it points to over 4700 people per day being misinterpreted and posing a risk of virus shedding. While mean Ct values of the samples that were both antigen and RT-qPCR positive were about 20 (kit 1: 20.47 and 20.16 for Sarbeco E and RdRP, kit 2: 19.37 and 19.99 for Sarbeco E and RdRP and kit 3: 17.47 for ORF1b/RdRP), mean Ct values of the samples that were antigen-negative but RT-qPCR-positive were about 30 (kit 1: 30.67 and 30.00 for Sarbeco E and RdRP, kit 2: 29.86 and 31.01 for Sarbeco E and RdRP and kit 3: 27.47 for ORF1b/RdRP). It confirms the advantage of antigen test in detecting the most infectious individuals with a higher viral load. However, the reporting of Ct values is still a matter of ongoing debates and should not be conducted without normalisation to standardised controls of known concentration.

MicroRNAs (miRNAs) are a class of small single-stranded non-protein-coding RNAs that play important regulatory roles in many cellular processes including cell proliferation, differentiation, growth control, and apoptosis. They regulate gene expression on the posttranscriptional level by translational repression, mRNA cleavage, or mRNA degradation in various physiological and pathological processes. In addition, some miRNAs can function as oncogenes or tumor suppressors, so they can regulate several genes that play important roles in tumorigenesis. It was found that miRNAs are directly involved in many types of cancer, including lung cancer. Lung cancer is the leading cause of cancer mortality worldwide with a substantially low survival rate. In this work, we summarize recent findings related to miRNAs mechanisms of action and the role of their dysregulated expression in lung tumorigenesis. We describe the most important miRNAs involved in lung cancer development and targets of their activity. The understanding of the miRNA regulation in cancer may help better understand the molecular mechanisms of tumorigenesis and their importance in cancerous transformation.