Domains in Action: Understanding Ddi1's Diverse Functions in the Ubiquitin-Proteasome System.

The ubiquitin-proteasome system (UPS) is a pivotal cellular mechanism responsible for the selective degradation of proteins, playing an essential role in proteostasis, protein quality control, and regulating various cellular processes, with ubiquitin marking proteins for degradation through a complex, multi-stage process. The shuttle proteins family is a very unique group of proteins that plays an important role in the ubiquitin-proteasome system. Ddi1, Dsk2, and Rad23 are shuttle factors that bind ubiquitinated substrates and deliver them to the 26S proteasome. Besides mediating the delivery of ubiquitinated proteins, they are also involved in many other biological processes. Ddi1, the least-studied shuttle protein, exhibits unique physicochemical properties that allow it to play non-canonical functions in the cells. It regulates cell cycle progression and response to proteasome inhibition and defines MAT type of yeast cells. The Ddi1 contains UBL and UBA domains, which are crucial for binding to proteasome receptors and ubiquitin respectively, but also an additional domain called RVP. Additionally, much evidence has been provided to question whether Ddi1 is a classical shuttle protein. For many years, the true nature of this protein remained unclear. Here, we highlight the recent discoveries, which shed new light on the structure and biological functions of the Ddi1 protein.

Artificial Intelligence in Medical Imaging: Analyzing the Performance of ChatGPT and Microsoft Bing in Scoliosis Detection and Cobb Angle Assessment.

Open-source artificial intelligence models (OSAIM) find free applications in various industries, including information technology and medicine. Their clinical potential, especially in supporting diagnosis and therapy, is the subject of increasingly intensive research. Due to the growing interest in artificial intelligence (AI) for diagnostic purposes, we conducted a study evaluating the capabilities of AI models, including ChatGPT and Microsoft Bing, in the diagnosis of single-curve scoliosis based on posturographic radiological images. Two independent neurosurgeons assessed the degree of spinal deformation, selecting 23 cases of severe single-curve scoliosis. Each posturographic image was separately implemented onto each of the mentioned platforms using a set of formulated questions, starting from 'What do you see in the image?' and ending with a request to determine the Cobb angle. In the responses, we focused on how these AI models identify and interpret spinal deformations and how accurately they recognize the direction and type of scoliosis as well as vertebral rotation. The Intraclass Correlation Coefficient (ICC) with a 'two-way' model was used to assess the consistency of Cobb angle measurements, and its confidence intervals were determined using the F test. Differences in Cobb angle measurements between human assessments and the AI ChatGPT model were analyzed using metrics such as RMSEA, MSE, MPE, MAE, RMSLE, and MAPE, allowing for a comprehensive assessment of AI model performance from various statistical perspectives. The ChatGPT model achieved 100% effectiveness in detecting scoliosis in X-ray images, while the Bing model did not detect any scoliosis. However, ChatGPT had limited effectiveness (43.5%) in assessing Cobb angles, showing significant inaccuracy and discrepancy compared to human assessments. This model also had limited accuracy in determining the direction of spinal curvature, classifying the type of scoliosis, and detecting vertebral rotation. Overall, although ChatGPT demonstrated potential in detecting scoliosis, its abilities in assessing Cobb angles and other parameters were limited and inconsistent with expert assessments. These results underscore the need for comprehensive improvement of AI algorithms, including broader training with diverse X-ray images and advanced image processing techniques, before they can be considered as auxiliary in diagnosing scoliosis by specialists.

Artificial Intelligence in Scoliosis Classification: An Investigation of Language-Based Models.

Open-source artificial intelligence models are finding free application in various industries, including computer science and medicine. Their clinical potential, especially in assisting diagnosis and therapy, is the subject of increasingly intensive research. Due to the growing interest in AI for diagnostics, we conducted a study evaluating the abilities of AI models, including ChatGPT, Microsoft Bing, and Scholar AI, in classifying single-curve scoliosis based on radiological descriptions. Fifty-six posturographic images depicting single-curve scoliosis were selected and assessed by two independent neurosurgery specialists, who classified them as mild, moderate, or severe based on Cobb angles. Subsequently, descriptions were developed that accurately characterized the degree of spinal deformation, based on the measured values of Cobb angles. These descriptions were then provided to AI language models to assess their proficiency in diagnosing spinal pathologies. The artificial intelligence models conducted classification using the provided data. Our study also focused on identifying specific sources of information and criteria applied in their decision-making algorithms, aiming for a deeper understanding of the determinants influencing AI decision processes in scoliosis classification. The classification quality of the predictions was evaluated using performance evaluation metrics such as sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), accuracy, and balanced accuracy. Our study strongly supported our hypothesis, showing that among four AI models, ChatGPT 4 and Scholar AI Premium excelled in classifying single-curve scoliosis with perfect sensitivity and specificity. These models demonstrated unmatched rater concordance and excellent performance metrics. In comparing real and AI-generated scoliosis classifications, they showed impeccable precision in all posturographic images, indicating total accuracy (1.0, MAE = 0.0) and remarkable inter-rater agreement, with a perfect Fleiss' Kappa score. This was consistent across scoliosis cases with a Cobb's angle range of 11-92 degrees. Despite high accuracy in classification, each model used an incorrect angular range for the mild stage of scoliosis. Our findings highlight the immense potential of AI in analyzing medical data sets. However, the diversity in competencies of AI models indicates the need for their further development to more effectively meet specific needs in clinical practice.

Assessment of the Functioning Profile of Patients with Lung Cancer Undergoing Lobectomy in Relation to the ICF Rehabilitation Core Set.

Lung cancer often presents with pain and breathlessness, frequently necessitating surgical procedures, such as lung lobectomy. A pivotal component of postoperative care is rehabilitation, aimed not only at improving the clinical condition but also at influencing the patient's functional profile. In a study conducted at the Clinic of Thoracic Surgery and Respiratory Rehabilitation in the Regional Multispecialist Center for Oncology and Traumatology of the Nicolaus Copernicus Memorial Hospital in Lodz, the effectiveness of rehabilitation intervention was assessed in 50 patients (n = 27 M, n = 23 F) postlobectomy due to early stage nonsmall cell lung cancer (NSCLC). The International Classification of Functioning, Disability, and Health-ICF Rehabilitation Core Set was used to evaluate the functional profile, the modified Laitinen scale for pain assessment, and the modified Borg scale for breathlessness evaluation. Additionally, lung-expansion time was monitored. The significance level of the statistical tests in this analysis was set at α = 0.05. The study employed an analysis of the normality of the distributions of the numerical variables, reporting of variable distributions, estimation of differences between groups, estimation of differences within groups, estimation of the independence of categorical variables, and regression analysis. The research confirmed that rehabilitation partially improves the functional profile of patients and reduces the sensation of breathlessness postsurgery. The study highlighted the need for future research with a larger number of participants and an extended observation period to gain a deeper understanding of the impact of rehabilitation on patients after lung lobectomy procedures.

Evaluating Scoliosis Severity Based on Posturographic X-ray Images Using a Contrastive Language-Image Pretraining Model.

Assessing severe scoliosis requires the analysis of posturographic X-ray images. One way to analyse these images may involve the use of open-source artificial intelligence models (OSAIMs), such as the contrastive language-image pretraining (CLIP) system, which was designed to combine images with text. This study aims to determine whether the CLIP model can recognise visible severe scoliosis in posturographic X-ray images. This study used 23 posturographic images of patients diagnosed with severe scoliosis that were evaluated by two independent neurosurgery specialists. Subsequently, the X-ray images were input into the CLIP system, where they were subjected to a series of questions with varying levels of difficulty and comprehension. The predictions obtained using the CLIP models in the form of probabilities ranging from 0 to 1 were compared with the actual data. To evaluate the quality of image recognition, true positives, false negatives, and sensitivity were determined. The results of this study show that the CLIP system can perform a basic assessment of X-ray images showing visible severe scoliosis with a high level of sensitivity. It can be assumed that, in the future, OSAIMs dedicated to image analysis may become commonly used to assess X-ray images, including those of scoliosis.

Congenital Anterior Dislocation of the Sacrococcygeal Bone in a Newborn.

We present a case of a child who was transported to the Neurosurgery Clinic from another hospital for the purpose of performing a surgical procedure of the spinal myelomeningocele. On the first day of the stay, a set of tests was performed, including an anterior-posterior (AP) projection X-ray, which clearly showed a developmental defect in the lumbar-sacral section of the spine. In the follow-up physical examination, there was a depression of the skin on the right side of the surgical scar after closing the open myelomeningocele. In the follow-up MRI of the lumbar-sacral section, an extremely rare congenital anterior dislocation of the sacrococcygeal bone was unexpectedly visualized. Despite recommendations for further diagnostics, the patient did not attend the required follow-up examinations. In the final section, we provide a general summary of the literature on rare developmental defects of the spine in children.

The NR3C1 Glucocorticoid Receptor Gene Polymorphisms May Modulate the TGF-beta mRNA Expression in Asthma Patients.

Glucocorticosteroids (GCs) are basic drugs in therapy of a number of diseases, including chronic diseases of the respiratory system. They are the most important anti-inflammatory drugs in the treatment of asthma. GCs after binding to the glucocorticoid receptor (GR) form the complex (transcription factor), which acts on promoter and regulatory parts of genes enhancing the expression of anti-inflammatory proteins and decreasing the proinflammatory protein synthesis, including numerous cytokines mediating inflammation in the course of asthma. Non-sensitivity or resistance to GCs favours an increase in the TGF-ß expression. This cytokine plays a central role in asthma inducing fibroblast differentiation and extracellular matrix synthesis. TGF-ß isoforms, 1, 2 and 3, are located on chromosome 19q13, 1q41 and 14q24, respectively. GCs reduce TGF-ß 1 and TGF-ß 2 production and significantly decrease the expression of upregulated TGF-ß 1 and TGF-ß 2 mRNA induced by exogenous TGF-ß. In asthma, TGF-ß may play a role in the development of the peribronchiolar and subepithelial fibrosis, which contributes to a significant clinical exacerbation of asthma. Therefore, it is possible that NR3C1 glucocorticoid receptor gene polymorphisms could exert varied effects on the TGF-ß mRNA expression and fibrotic process in lungs of asthmatic patients. The aim of the study was to evaluate the impact of polymorphic forms (Tth111I, BclI, ER22/23EK, N363S) of the NR3C1 gene on the level of the TGF-ß 1 mRNA expression. A total of 173 patients with asthma and 163 healthy volunteers participated in the study. Genotyping of Tth111I, BclI, ER22/23EK, and N363S polymorphisms of the NR3C1 gene was performed by using PCR-HRM and PCR-RFLP techniques. TGF-ß mRNA was assessed by real time RT-PCR. Tth111I SNP significantly (p = 0.0115) correlated with the TGF-ß 1 mRNA expression level. The significance of AA and GG genotypes of Tth111I SNP in increasing and decreasing the level of the TGF-ß 1 mRNA expression was demonstrated. Both BclI SNP and ER22/23EK SNP did not affect the expression level of the cytokine analysed. The N363S SNP AA genotype of NR3C1 gene statistically significantly influenced the increase in the level of the TGF-ß 1 mRNA expression. Thus, SNPs of NR3C1 gene play an important regulatory function in the bronchi of patients suffering from asthma. In the case of the occurrence of Tth111I and N363S polymorphic forms of the gene studied, a reduced ability of GCs to inhibit the TGF-ß 1 expression can be observed.

Identification and association of the single nucleotide polymorphisms, C-509T, C+466T and T+869C, of the TGF-ß1 gene in patients with asthma and their influence on the mRNA expression level of TGF-ß1.

Transforming growth factor-ß1 (TGF-ß1) is an important fibrogenic and immunomodulatory cytokine participating in the pathogenesis of a number of illnesses related to the growth, differentiation and migration of cells. It also plays a key role in inflammation, atherosclerosis, vascular inflammation and asthma. The aim of the present study was to evaluate the association between the expression of the TGF-ß1 gene and its genetic polymorphisms, and the disease phenotype. The study comprised 173 patients with asthma, as well as 163 healthy volunteers as a control group. The gender profiles of the groups were similar (p=0.8415). Genotyping was performed by polymerase chain reaction (PCR)-high resolution melting (HRM). The results were verified by sequencing. Gene expression was evaluated by RT-PCR. This study evaluated the role and frequency of genetic polymorphisms (C-509T, C+466T and T+869C) of the TGF-ß1 gene in the study group (patients with asthma) and the control group (healthy volunteers). The results obtained for the patients and healthy controls were as follows: C-509T single nucleotide polymorphism (SNP) (controls, TT/CT/CC-0.4444/0.5309/0.0247; patients, TT/CT/CC-0.3699/0.6012/0.0289), C+466T SNP (controls, TT/CT/CC-1.000/0.000/0.000; patients, TT/CT/CC-1.000/0.000/0.000) and T+869C SNP (controls, TT/CT/CC-1.000/0.000/0.000; patients, TT/CT/CC-1.000/0.000/0.000). Only the C-509T polymorphism was found to play a significant role in the pathogenesis of asthma, as well as a risk factor in the loss of the clinical control of the disease [TT vs. CC/CT, odds ratio (OR) 2.38; confidence interval (CI) 1.22-4.66; p=0.0103]. A significant difference was noted between the study and control groups with regard to the mRNA expression of TGF-ß1 (p=0.0133). A higher level of expression of the TGF-ß1 gene correlated with the time of diagnosis of patients over 16 years of age (p=0.0255). This study demonstrates that the C-509T SNP is a significant clinical risk factor for asthma and that the TGF-ß1 cytokine contributes to the progression of the illness.

Identification and association of TGFß-1 expression in patients with asthma in a Polish population - Lodz metropolitan area study.

OBJECTIVE: Interaction of genotype and environment results in a specific phenotype of the clinical course of asthma. TGFß-1 gene belongs to the important group of genes involved in the regulation of proliferation, differentiation, adhesion, and migration of a variety of cell types. TGFß-1 is inhibitory for B and T cells, as well as IgE production. In particular, it is engaged in inflammation of the bronchi and airway remodeling in asthma, which processes are critical in the pathogenesis of the disease. The aim of this study was to evaluate the correlation between the level of expression of TGFß-1 and the severity of asthma. METHODS: The study included 39 participants (20 healthy subjects and 19 patients with asthma). Each sample was analysed by using real time PCR. RESULTS: There was statistical associations between the control group and the group of patients (p = 0,00007). It was demonstrated strong correlation between healthy and patients with severe asthma according GINA guidelines (p = 0,017). It was found the strong statistical correlation between healthy and patients with severe corticosteroid dependent asthma (p = 0,013). Correlations were observed between levels of asthma severity according to the ATS guidelines and controls. The influence of the level of TGFß-1 mRNA expression and the severity of asthma (ATS) in the FEV1 (%) parameter value was found. CONCLUSION: It was found that an important role is played by TGFß-1 in the pathogenesis of asthma.

Effect of glucocorticoid receptor gene polymorphisms on asthma phenotypes.

The clinical presentation of asthma results from complex gene-gene and gene-environment interactions. The natural variability of the DNA sequence within the NR3C1 gene affects the activity of glucocorticoid receptors (GCRs). The NR3C1 gene is localized on chromosome 5q31-q32. The gene coding for the GCR comprises nine exons. The structural domains of the GCR determine the biological functions of the functional domains. The observed resistance to glucocorticosteroids and the normal metabolic profile of Tth111I single nucleotide polymorphism (SNP) carriers is due to the ER22/23EK polymorphism that is present in them. BclI polymorphism significantly affects the process of alternative NR3C1 gene splicing and within that mechanism increases the sensitivity to glucocorticoids (GCs). A total of 451 subjects were enrolled in the present study, including 235 qualified to the group of bronchial asthma patients. A group of 216 healthy participants with no history of asthma or atopic conditions was qualified for the study. Genotyping was accomplished using the polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) and PCR-high resolution melting (HRM) methods. No statistically significant differences were observed in the frequency of Tth111I, BclI and ER22/23EK polymorphisms of the NR3C1 gene when comparing mild, moderate and severe asthma vs. the control group. Investigative analyses demonstrated statistically significant correlations for alleles and genotypes of Tth111I polymorphism of the NR3C1 gene between healthy subjects and patients with severe asthma characterized by a control profile corresponding to an Asthma Control Test (ACT)™ score ≥20. It was established that only the Tth111I polymorphism of the NR3C1 gene plays an important role in the pathogenesis of chronic bronchitis leading to the development of asthma with both allergic and non-allergic etiology.

The N363S and I559N single nucleotide polymorphisms of the h-GR/NR3C1 gene in patients with bronchial asthma.

Bronchial asthma is a disease of multifactorial etiology. The natural variability of the DNA sequence within the h-GR/NR3C1 gene affects both the conformation and the activity of glucocorticoid receptors. There are 2 major types of resistance to glucocorticoids (GCS)-resistant asthma failing to respond to treatment with high doses of inhaled and oral glucocorticoids. Type I GCS-resistant asthma is cytokine-induced or acquired. Type II GCS resistance involves generalized primary cortisol resistance, which affects all tissues and is likely to be associated with a mutation in the glucocorticoid receptor (GCR) gene or in genes that modulate GCR function. There are clear examples of glucocorticoid gene h-GR/NR3C1 polymorphisms that can influence responses and sensitivity to glucocorticosteroids. Among the numerous polymorphisms observed within this gene, N363S and I559N single nucleotide polymorphisms (SNPs) may play an important role in the development of bronchial asthma and in the alteration of sensitivity to GCS in severe bronchial asthma. The aim of this research project was to study the correlation between the N363S and I559N polymorphisms of the h-GR/NR3C1 gene and the occurrence of asthma in a population of Polish asthmatics. Peripheral blood was obtained from 210 healthy volunteers and 234 asthma patients. Structuralized anamnesis, spirometry and allergy skin prick tests were performed in all participants. Genotyping was carried out using the polymerase chain reaction (PCR)-restriction fragment length polymorphism (RFLP) and PCR-HRM methods. In the healthy, non-atopic population, the GG variant of the N363S polymorphism was found with a 5.7% frequency. In asthma patients, GG SNP of N363S occurred with the frequency of 6.4%. In the groups of patients with uncontrolled moderate asthma and uncontrolled severe disease, the genotype distribution for the investigated polymorphisms were as follows: N363S, AA, AG, GG occurring with 0.8750/0.0834/0.0416 frequency and I559N, TT, TA, AA occurring with 1.000/0.000/0.000 frequency. The analysis demonstrated a significantly higher frequency of the A and G variants of the N363S polymorphisms in uncontrolled moderate asthma and uncontrolled severe disease than in the healthy population. No variant-related differences in the frequency of the studied I559N polymorphism were demonstrated in healthy controls and asthma patients. In conclusion, the N363S polymorphism of the h-GR/NR3C1 gene is significantly associated with an increased sensitivity to glucococorticoids in vivo and susceptibility to the development of a moderate to severe form of uncontrolled bronchial asthma in the Polish population. This observation needs to be confirmed in a larger group of subjects.