St. Catherine Hospital

ABSTRACTImportanceCancers of unknown primary origin (CUPs) represent a significant diagnostic and therapeutic challenge in the field of oncology. With the limitations of current diagnostic tools in these cases, novel approaches must be brought forward to improve treatment outcomes for these patients.ObjectiveThe objective of this study was to develop a machine-learning-based software for primary cancer site identification (OncoOrigin), based on genetic data acquired from tumor DNA sequencing.DesignBy design, this was anin silicodiagnostic study.SettingThis study was conducted using data from the cBioPortal database (accessed on 21 September 2024) and several data processing and machine-learning Python libraries.ParticipantsThis study involved over 20,000 tumor samples with information on patient age, sex, and the presence of genetic variants in over 600 genes.Main Outcomes and MeasuresThe main outcome of interest in this study was machine-learning-based discrimination between cancer type classes, based on the provided data. Model quality was assessed by train set cross-validation and evaluation on a segregated test set. Finally, the optimal model was incorporated with a graphical user interface into the OncoOrigin software. Feature importances for class discrimination were also determined on the optimal model.ResultsOut of the four tested machine-learning estimators, the XGBoostClassifier-based model proved superior on test set evaluation, with a top-2 accuracy of 0.91 and ROC-AUC of 0.97. Class sensitivity values for prostate cancer, breast cancer, melanoma, and colorectal cancer were over 0.85, while all class specificity values were equal to or higher than 0.95. The top 3 significant features were patient sex, and genetic alterations in theAPCandKRASgenes.Conclusions and RelevanceIn this study, we have successfully developed a machine-learning-based software for primary cancer site identification with high-quality evaluation metrics. Through simple clinical implementation, such a tool has the potential to significantly improve the diagnostics and treatment outcomes for patients suffering from CUP.KEY POINTSQuestionCan a machine-learning-based tool (OncoOrigin) accurately predict the primary cancer site from tumor DNA sequencing data in patients with cancers of unknown primary origin (CUP)?FindingsIn thisin silicostudy, the XGBoostClassifier model demonstrated high predictive performance, achieving a top-2 accuracy of 0.91 and ROC-AUC of 0.97 for the classification of ten cancer types using genetic data from over 20,000 tumor samples.MeaningThe OncoOrigin software shows potential for improving the diagnosis and treatment of CUP by providing accurate primary cancer site identification based on genetic data.

From the beginning of life, a complex immune-biochemical dialogue is established in the brain, influenced by maternal experiences and the Social Unconscious. Trauma leaves traces in memory, either by its explicit or implicit transcription, psychologically experienced either as a conscious event or as an unconscious, blind and violent disorder, especially when the traumatic quantity overwhelms the Psychic Apparatus. The group factors interacting among different countries and cultures will be explored in relation to trauma‘s treatment and transformation in the group. Trauma‘s maintenance and transformation through generations, creates wounds in time, space, boundaries, transgenerationally influencing our genetic, ethical and national heritage. Psychotherapeutic factors like Agapi (Love), acceptance, containing, holding, gratitude, equal human-rights, transcultural and trans-religious-dialogue, corrective emotional experience and forgiving process are group parameters with impact in trauma’s healing after alteration of the Brain Plasticity. The forgiving process served as a marker in the evaluation of trauma‘s transformation by investigating the relationship between forgiveness, likelihood forgiveness and transgression related interpersonal motivations using Pearson’s correlation coefficient.

BackgroundReactive arthritis and septic arthritis rarely present concomitantly in the same joint and patient. Reactive arthritis presenting after coronavirus disease 2019 is also exceedingly rare, with less than 30 cases reported thus far. Less common pathogens such as Clostridium difficile have been reported to cause reactive arthritis, especially in patients with a positive human leukocyte antigen B27, and therefore should be considered in diagnostic algorithms. The aim of this case report is to highlight the difficulties and precautions in discerning and diagnosing patients presenting with sudden swelling of the knee.Case presentationWe report the case of a 70-year-old Caucasian male with a recent history of coronavirus disease 2019 upper respiratory infection and diarrhea and negating trauma, who presented with a swollen and painful knee. Pain and swelling worsened and inflammatory parameters increased after an intraarticular corticosteroid injection. The patient was therefore treated with arthroscopic lavage and intravenous antibiotics for suspected septic arthritis. Synovial fluid and synovium samples were taken and sent for microbiological analysis. Synovial fluid cytology showed increased leukocytes at 10,980 × 106/L, while polymerase chain reaction and cultures came back sterile. Clostridium difficile toxin was later detected from a stool sample and the patient was treated with oral vancomycin. The patient was tested for the presence of human leukocyte antigen B27, which was positive. We present a review of the literature about the challenges of distinguishing septic from reactive arthritis, and about the mechanisms that predispose certain patients to this rheumatological disease.ConclusionsIt is still a challenge to differentiate between septic and reactive arthritis of the knee, and it is even more challenging to identify the exact cause of reactive arthritis. This case report of a human leukocyte antigen-B27-positive patient highlights the necessity of contemplating different, less common causes of a swollen knee joint as a differential diagnosis of an apparent septic infection, especially in the coronavirus disease 2019 era. Treating the patient for septic arthritis prevented any possible complications of such a condition, while treating the C. difficile infection contributed to the substantial relief of symptoms.

The present study aimed to assess the association of 16 polymorphisms in genes encoding prothrombotic and cardiovascular risk factors with COVID‐19 disease severity: FV G1691A, FV H1299R, FII G20210A, MTHFR C677T, MTHFR A1298, factor XIII V34L, PAI‐1 4G/5G, EPCR haplotypes (A1/A2/A3), eNOS −786 T > C, eNOS G894T, LTA C804A, ACE I/D, ITGB3 PIA1/A2, ITGA2B Baka/b, β‐Fbg −455 G > A and ApoB R3500Q. The study included 30 patients with severe COVID‐19 and 49 non‐severe COVID‐19 patients. All studied polymorphisms except ITGA2B Baka/b were determined using multilocus genotyping assays CVD StripAssays (ViennaLab Diagnostics), while ITGA2B was genotyped using a real‐time PCR method based on TaqMan technology. A higher frequency of carriers of at least one ITGB3 PIA2 allele was found in severe COVID‐19 patients (p = 0.009). The distribution of genotypes was significantly different for ß‐Fbg −455 G > A (p = 0.042), with only three homozygous AA genotypes found among severe COVID‐19 patients. The association with an increased risk for severe COVID‐19 was found for ITGB3, with carriers of at least one ITGB3 PIA2 allele having a 3.5‐fold greater risk of severe COVID‐19 (p = 0.011). Genotype distribution differences were obtained for the combinations of FV H1299R and FXIII V34L (p = 0.026), ITGB3 PIA1/A2 and ITGA2B Baka/b (p = 0.024), and ACE I/D and PAI‐1 4G/5G (p = 0.046). ITGB3 polymorphism emerged as an independent risk factor for severe COVID‐19 and homozygosity for ß‐Fbg −455 G > A mutation could contribute to disease severity. The combined effect of polymorphisms in genes encoding prothrombotic and cardiovascular risk factors could further contribute to disease severity.

Sudden cardiac death (SCD) is an unexpected and dramatic event. It draws special attention especially in young, seemingly healthy athletes. Our scientific paper is based on the death of a young, 23-year-old professional footballer, who died on the football field after a two-year history of cardiac symptoms. In this study we analyzed clinical, ECG and laboratory data, as well as results of genetic testing analysis in family members. To elucidate potential genetic etiology of SCD in this family, our analysis included 294 genes related to various cardiac conditions.

Being the most common musculoskeletal progressive condition, osteoarthritis is an interesting target for research. It is estimated that the prevalence of knee osteoarthritis (OA) among adults 60 years of age or older is approximately 10% in men and 13% in women, making knee OA one of the leading causes of disability in elderly population. Today, we know that osteoarthritis is not a disease characterized by loss of cartilage due to mechanical loading only, but a condition that affects all of the tissues in the joint, causing detectable changes in tissue architecture, its metabolism and function. All of these changes are mediated by a complex and not yet fully researched interplay of proinflammatory and anti-inflammatory cytokines, chemokines, growth factors and adipokines, all of which can be measured in the serum, synovium and histological samples, potentially serving as biomarkers of disease stage and progression. Another key aspect of disease progression is the epigenome that regulates all the genetic expression through DNA methylation, histone modifications, and mRNA interference. A lot of work has been put into developing non-surgical treatment options to slow down the natural course of osteoarthritis to postpone, or maybe even replace extensive surgeries such as total knee arthroplasty. At the moment, biological treatments such as platelet-rich plasma, bone marrow mesenchymal stem cells and autologous microfragmented adipose tissue containing stromal vascular fraction are ordinarily used. Furthermore, the latter two mentioned cell-based treatment options seem to be the only methods so far that increase the quality of cartilage in osteoarthritis patients. Yet, in the future, gene therapy could potentially become an option for orthopedic patients. In the following review, we summarized all of the latest and most important research in basic sciences, pathogenesis, and non-operative treatment.

The article presents a detailed analysis of the mechanisms of involutive changes in the periorbital region, it considers the spectrum of possible aesthetic problems in this localization and methods for their prevention and correction, gives the anatomical structure of the periorbital region, describes the main types of lasers used in the periorbital region and their effectiveness, as well as protocols and complications.

Osteogenesis imperfecta (OI) or brittle bone disease is a metabolic bone disease characterized by bone fragility, low bone mass, andincreased rate of bone fractures and deformities. Clinical presentation in OI patients shows wide variability ranging from mild to severeand lethal OI types. Advances in molecular biology and studies on animal OI models found at least 16 new genes involved in OIpathogenesis. The majority of mutations are autosomal dominant aff ecting COL1A1 and COL1A2 genes responsible for collagensynthesis. The remaining 10%-15% of mutations in OI are autosomal recessive and aff ect genes involved in various metabolic boneprocesses. Progress in understanding bone metabolism and genetic engineering off ers new potential therapeutic opportunities thatare under diff erent stages of investigation.Key words: osteogenesis imperfecta, type I collagen, molecular genetics, gene therapy, stem cell