Over the past few years, artificial intelligence (AI) has significantly improved healthcare. Once the stuff of science fiction, AI is now widely used, even in our daily lives — often without us thinking about it. All healthcare professionals — especially executives and medical doctors — need to understand the capabilities of advanced AI tools and other breakthrough innovations. This understanding will allow them to recognize opportunities and threats emerging technologies can bring to their organizations. We hope to contribute to a meaningful public discussion about the role of this new type of AI and how our approach to healthcare and medicine can best evolve with the rapid development of this technology. Since medicine learns by example, only a few possible uses of AI in medicine are provided, which merely outline the system’s capabilities. Among the examples, it is worth highlighting the roles of AI in medical notes, education, preventive programs, consultation, triage and intervention. It is believed by the authors that large language models such as chat generative pre-trained transformer (ChatGPT) are reaching a level of maturity that will soon impact clinical medicine as a whole and improve the delivery of individualized, compassionate, and scalable healthcare. It is unlikely that AI will replace physicians in the near future. The human aspects of care, including empathy, compassion, critical thinking, and complex decision-making, are invaluable in providing holistic patient care beyond diagnosis and treatment decisions. The GPT-4 has many limitations and cannot replace direct contact between an experienced physician and a patient for even the most seemingly simple consultations, not to mention the ethical and legal aspects of responsibility for diagnosis. Over the past few years, artificial intelligence (AI) has significantly improved healthcare. Once the stuff of science fiction, AI is now widely used, even in our daily lives — often without us thinking about it. All healthcare professionals — especially executives and medical doctors — need to understand the capabilities of advanced AI tools and other breakthrough innovations. This understanding will allow them to recognize opportunities and threats emerging technologies can bring to their organizations. We hope to contribute to a meaningful public discussion about the role of this new type of AI and how our approach to healthcare and medicine can best evolve with the rapid development of this technology. Since medicine learns by example, only a few possible uses of AI in medicine are provided, which merely outline the system’s capabilities. Among the examples, it is worth highlighting the roles of AI in medical notes, education, preventive programs, consultation, triage and intervention. It is believed by the authors that large language models such as chat generative pre-trained transformer (ChatGPT) are reaching a level of maturity that will soon impact clinical medicine as a whole and improve the delivery of individualized, compassionate, and scalable healthcare. It is unlikely that AI will replace physicians in the near future. The human aspects of care, including empathy, compassion, critical thinking, and complex decision-making, are invaluable in providing holistic patient care beyond diagnosis and treatment decisions. The GPT-4 has many limitations and cannot replace direct contact between an experienced physician and a patient for even the most seemingly simple consultations, not to mention the ethical and legal aspects of responsibility for diagnosis.

Impaired thermogenesis can promote obesity. Therefore, the aim of this study was to investigate whether the expression of thermogenesis-related genes is altered in adipose tissues of obese individuals and whether excessive methylation of their promoters is involved in this phenomenon. The expression of genes encoding β adrenergic receptors (ADRBs), thyroid hormone receptors (THRs), 5’-iodothyronine deiodinases (DIOs), and uncoupling proteins (UCPs) was measured by real-time PCR in visceral and in subcutaneous adipose tissues of 58 obese (BMI >40 kg/m2) and 50 slim (BMI 20-24.9 kg/m2) individuals. The methylation status of these genes was studied by the methylation-sensitive digestion/real-time PCR method. The expression of ADRB2, ADRB3, THRA, THRB, DIO2, UCP2 was significantly lower in the adipose tissues of obese patients than in tissues of normal-weight individuals (P < 0.00001). In the obese, the expression of ADRB2, ADRB3, DIO2 was lower in visceral adipose tissue than in subcutaneous adipose tissue (P = 0.008, P = 0.002, P = 0.001, respectively). However, the mean methylation of CpG islands of these genes was similar in tissues with their high and low expression, and there was no correlation between the level of expression and the level of methylation. Decreased expression of thermogenesis-related genes in adipose tissues of obese patients might result in the reduced reactivity to both hormonal and adrenergic stimuli and therefore in a lower potential to activate thermogenesis.

Overweight and obesity are becoming a worldwide health problem associated with numerous co-morbidities. National costs of obesity and pelvic flor disorders have been rising since the 1950s across the world. Obesity is thought to have a very ...

Background. Brain death is associated with hemodynamic disturbances in systemic circulation and metabolic storm, and, thus, free radical-mediated injury to donor tissues was hypothesized. An assessment of oxidative stress in the donor and its effect on posttransplant kidney graft function comprised the scope of the study. Methods. A prospective study was performed in 27 donors and 50 kidney transplant recipients. Sera from 27 brain-dead organ donors and preservation media were tested for malondialdehyde (MDA) and for total antioxidant status (TAS). Kidneys were preserved in University of Wisconsin-gluconate solution with machine perfusion. Mean ischemia time was 36.7±8 hours. Organs were transplanted to recipients on the Polish National Waiting List and posttransplant kidney function was monitored periodically. Posttransplant delayed graft function (DF) was diagnosed when a patient required at least one dialysis within first week after transplantation. Acute rejection was diagnosed clinically and confirmed with fine-needle biopsy if necessary. Results. Thirty-two recipients had immediate graft function (IF), and 18 suffered from DF. MDA level in preservation solution at the end of machine perfusion was significantly higher in the DF group (52.6±31 vs. 25.3±19 μmol/L) whereas donor TAS activity was lower (1.14±0.2 vs. 0.97±0.3 mmol/mL). Patients who suffered from acute rejection received kidneys from donors with significantly higher serum MDA (66±73 μmol/ml vs. 23±49 for patients without rejection). Serum creatinine 12 to 48 months after transplantation correlated to donor- and preservation-solution MDA (P <0.006). Conclusions. Free-radical mediated injury occurring in the donor and during preservation is strictly correlated with immediate and long-term kidney function. It may also cause grafts to be prone to acute rejection.

Machine perfusion (MP) has been used as the kidney preservation method in our center for over 10 years. The first, small (n = 74) prospective, single-blinded randomized study comparing MP and Cold Storage (CS) showed that the incidence of delayed graft function was higher after CS. There have been no reports in the literature on the effect of storage modality on long-term function of renal allografts. This paper presents an analysis of long-term results of renal transplantation in 415 patients operated on between 1994 and 1999. Of those, 227 kidneys were MP-stored prior to KTx. The control group consisted of 188 CS kidney transplants. Kidneys were not randomized to MP or to CS. Donor demographics, medical and biochemical data, cold ischemia time, HLA match and recipient data were collected. Standard triple-drug immunosuppression was administered to both groups. Mortality, graft survival and incidence of return to hemodialysis treatment were analyzed. Despite longer cold ischemia time and poorer donor hemodynamics in MP group, 5-year Kaplan-Meier graft survival was better in MP-stored than in CS-stored kidneys (68.2% vs. 54.2%, p = 0.02). In this nonrandomized analysis, kidney storage by MP improved graft survival and reduced the number of patients who returned to dialysis.

Background: We are currently experiencing a third digital revolution driven by artificial intelligence (AI), and the emergence of new chat generative pre-trained transformer (ChatGPT) represents a significant technological advancement with profound implications for global society, especially in the field of education. Methods: The aim of this study was to see how well ChatGPT performed on medical school exams and to highlight how it might change medical education and practice. Recently, OpenAI’s ChatGPT (OpenAI, San Francisco; GPT-4 May 24 Version) was put to the test against a significant Polish medical specialization licensing exam (PES), and the results are in. The version of ChatGPT-4 used in this study was the most up-to-date model at the time of publication (GPT-4). ChatGPT answered questions from June 28, 2023, to June 30, 2023. Results: ChatGPT demonstrates notable advancements in natural language processing models on the tasks of medical question answering. In June 2023, the performance of ChatGPT was assessed based on its ability to answer a set of 120 questions, where it achieved a correct response rate of 67.1%, accurately responding to 80 questions. Conclusions: ChatGPT may be used as an assistance tool in medical education. While ChatGPT can serve as a valuable tool in medical education, it cannot fully replace human expertise and knowledge due to its inherent limitations. Background: We are currently experiencing a third digital revolution driven by artificial intelligence (AI), and the emergence of new chat generative pre-trained transformer (ChatGPT) represents a significant technological advancement with profound implications for global society, especially in the field of education. Methods: The aim of this study was to see how well ChatGPT performed on medical school exams and to highlight how it might change medical education and practice. Recently, OpenAI’s ChatGPT (OpenAI, San Francisco; GPT-4 May 24 Version) was put to the test against a significant Polish medical specialization licensing exam (PES), and the results are in. The version of ChatGPT-4 used in this study was the most up-to-date model at the time of publication (GPT-4). ChatGPT answered questions from June 28, 2023, to June 30, 2023. Results: ChatGPT demonstrates notable advancements in natural language processing models on the tasks of medical question answering. In June 2023, the performance of ChatGPT was assessed based on its ability to answer a set of 120 questions, where it achieved a correct response rate of 67.1%, accurately responding to 80 questions. Conclusions: ChatGPT may be used as an assistance tool in medical education. While ChatGPT can serve as a valuable tool in medical education, it cannot fully replace human expertise and knowledge due to its inherent limitations.