Histology is an essential, yet difficult, subject to study in medicine. As artificial intelligence (AI) is rapidly evolving with ever-growing image recognition abilities, it presents a great potential to be used in the study of histology. This research aimed to assess the ability of ChatGPT 4o and Google Gemini 2.0 Flash to recognize various histological sections of different tissues and organs from images. The two AI models were presented with high-resolution histological images and prompted with tasks to identify basic tissue types, specific organs, and specific structures indicated by arrows. Scores were given for correct identifications. The test was conducted twice without any training or feedback to assess consistency. McNemar test and Kappa coefficient were used to compare the responses. Both AI models had good image recognition abilities with varying performances. Overall, Google Gemini achieved higher correct scores across both tests (75% and 77.5%, compared to 65% and 65% for ChatGPT). McNemar showed a significant difference between the two models with only fair agreement shown by kappa. No significant difference was found between the repeated tests. Performance across different tissue types varied. Muscular tissue was the easiest to identify and epithelial tissue was the most difficult. AI may have a promising role in histology. Students and histologist can use AI, especially Gemini, to identify histological sections from images. Critical judgment, however, must be utilized as AI can make mistakes.

Chronic kidney disease is estimated to affect approximately 10 to 15% of the Chinese population. Renal fibrosis is characterized by progressive extracellular matrix deposition in the kidney parenchyma with eventual tissue scarring and inevitable deterioration of renal function. Vascular rarefaction, glomerulosclerosis, interstitial inflammation, and fibrogenesis are associated with or contribute to renal fibrosis. Recent studies have revealed that glial cell-derived neurotrophic factor (GDNF) is involved in kidney morphogenesis and amelioration of renal injury. Ideal therapies targeting the pathogenesis of renal fibrosis should have the potential to inhibit glomerular and tubulointerstitial fibrosis by targeting multiple pathological events. GDNF plays a unique role in both renal development and improvement of renal fibrosis, and GDNF kidney receptors and signaling pathways can ameliorate renal apoptosis and inflammation. Our work contributes to the establishment of GDNF as an emerging therapy that can increase the effectiveness of currently used interventions to improve renal fibrosis. This literature review focuses on the important role of GDNF in renal development and its relationship with renal fibrosis.

Chronic kidney disease is estimated to affect approximately 10 to 15% of the Chinese population. Renal fibrosis is characterized by progressive extracellular matrix deposition in the kidney parenchyma with eventual tissue scarring and inevitable deterioration of renal function. Vascular rarefaction, glomerulosclerosis, interstitial inflammation, and fibrogenesis are associated with or contribute to renal fibrosis. Recent studies have revealed that glial cell-derived neurotrophic factor (GDNF) is involved in kidney morphogenesis and amelioration of renal injury. Ideal therapies targeting the pathogenesis of renal fibrosis should have the potential to inhibit glomerular and tubulointerstitial fibrosis by targeting multiple pathological events. GDNF plays a unique role in both renal development and improvement of renal fibrosis, and GDNF kidney receptors and signaling pathways can ameliorate renal apoptosis and inflammation. Our work contributes to the establishment of GDNF as an emerging therapy that can increase the effectiveness of currently used interventions to improve renal fibrosis. This literature review focuses on the important role of GDNF in renal development and its relationship with renal fibrosis.

Chronic kidney disease is estimated to affect approximately 10 to 15% of the Chinese population. Renal fibrosis is characterized by progressive extracellular matrix deposition in the kidney parenchyma with eventual tissue scarring and inevitable deterioration of renal function. Vascular rarefaction, glomerulosclerosis, interstitial inflammation, and fibrogenesis are associated with or contribute to renal fibrosis. Recent studies have revealed that glial cell-derived neurotrophic factor (GDNF) is involved in kidney morphogenesis and amelioration of renal injury. Ideal therapies targeting the pathogenesis of renal fibrosis should have the potential to inhibit glomerular and tubulointerstitial fibrosis by targeting multiple pathological events. GDNF plays a unique role in both renal development and improvement of renal fibrosis, and GDNF kidney receptors and signaling pathways can ameliorate renal apoptosis and inflammation. Our work contributes to the establishment of GDNF as an emerging therapy that can increase the effectiveness of currently used interventions to improve renal fibrosis. This literature review focuses on the important role of GDNF in renal development and its relationship with renal fibrosis.

Chronic kidney disease is estimated to affect approximately 10 to 15% of the Chinese population. Renal fibrosis is characterized by progressive extracellular matrix deposition in the kidney parenchyma with eventual tissue scarring and inevitable deterioration of renal function. Vascular rarefaction, glomerulosclerosis, interstitial inflammation, and fibrogenesis are associated with or contribute to renal fibrosis. Recent studies have revealed that glial cell-derived neurotrophic factor (GDNF) is involved in kidney morphogenesis and amelioration of renal injury. Ideal therapies targeting the pathogenesis of renal fibrosis should have the potential to inhibit glomerular and tubulointerstitial fibrosis by targeting multiple pathological events. GDNF plays a unique role in both renal development and improvement of renal fibrosis, and GDNF kidney receptors and signaling pathways can ameliorate renal apoptosis and inflammation. Our work contributes to the establishment of GDNF as an emerging therapy that can increase the effectiveness of currently used interventions to improve renal fibrosis. This literature review focuses on the important role of GDNF in renal development and its relationship with renal fibrosis.

Chronic kidney disease is estimated to affect approximately 10 to 15% of the Chinese population. Renal fibrosis is characterized by progressive extracellular matrix deposition in the kidney parenchyma with eventual tissue scarring and inevitable deterioration of renal function. Vascular rarefaction, glomerulosclerosis, interstitial inflammation, and fibrogenesis are associated with or contribute to renal fibrosis. Recent studies have revealed that glial cell-derived neurotrophic factor (GDNF) is involved in kidney morphogenesis and amelioration of renal injury. Ideal therapies targeting the pathogenesis of renal fibrosis should have the potential to inhibit glomerular and tubulointerstitial fibrosis by targeting multiple pathological events. GDNF plays a unique role in both renal development and improvement of renal fibrosis, and GDNF kidney receptors and signaling pathways can ameliorate renal apoptosis and inflammation. Our work contributes to the establishment of GDNF as an emerging therapy that can increase the effectiveness of currently used interventions to improve renal fibrosis. This literature review focuses on the important role of GDNF in renal development and its relationship with renal fibrosis.

In the unrelenting race to strive to dominate type 2 diabetes mellitus(T2DM)care better,this review paper sets out on a significant discovery trip across recent advancements in treatment and the blooming era of artificial intelligence(AI)utilities.Given the considerable global burden of T2DM,innovative therapeutic approaches to improve patient outcomes remain a public health priority.This review first provides an in-depth analysis of the current state of therapy,from novel pharmacotherapy to lifestyle interventions and new treatment methods.At the same time,the rapidly increasing role of AI in diabetes care is woven into the story,mainly targeting how insulin therapy can be modified and personalized through algorithms and predictive modelling.It leaves a deep review of their pre-existing synergies,which helps understand how collaborative opportunities will unlock the future of T2DM care.This critical role is shown by integrating recent therapeutic advances and AI with overall showcasing better screening,diagnosis,and therapeutics decision-making to outcome prediction in T2DM.The review emphasizes how AI applications in insulin therapy have transformative potential in diabetes care.These person-centred approaches to T2DM management,which are more effective and personalized than some traditional strategies,only work because of the often-hidden synergies between AI algorithms in areas such as diagnostic criteria,predictive methods,and familiar classification tools for subgroups with relevant aspects/predictors on prognosis or treatment responsiveness.

In the unrelenting race to strive to dominate type 2 diabetes mellitus (T2DM) care better, this review paper sets out on a significant discovery trip across recent advancements in treatment and the blooming era of artificial intelligence (AI) utilities. Given the considerable global burden of T2DM, innovative therapeutic approaches to improve patient outcomes remain a public health priority. This review first provides an in-depth analysis of the current state of therapy, from novel pharmacotherapy to lifestyle interventions and new treatment methods. At the same time, the rapidly increasing role of AI in diabetes care is woven into the story, mainly targeting how insulin therapy can be modified and personalized through algorithms and predictive modelling. It leaves a deep review of their pre-existing synergies, which helps understand how collaborative opportunities will unlock the future of T2DM care. This critical role is shown by integrating recent therapeutic advances and AI with overall showcasing better screening, diagnosis, and therapeutics decision-making to outcome prediction in T2DM. The review emphasizes how AI applications in insulin therapy have transformative potential in diabetes care. These person-centred approaches to T2DM management, which are more effective and personalized than some traditional strategies, only work because of the often-hidden synergies between AI algorithms in areas such as diagnostic criteria, predictive methods, and familiar classification tools for subgroups with relevant aspects/predictors on prognosis or treatment responsiveness.

Background/Aims: Roxadustat, an oral medication for treating renal anemia, is a hypoxia-inducible factor prolyl hydroxylase inhibitor used for regulating iron metabolism and promoting erythropoiesis. To investigate the efficacy and safety of roxadustat in patients undergoing peritoneal dialysis (PD) with erythropoietin hyporesponsiveness. Methods: Single-center, retrospective study, 81 PD patients (with erythropoietin hyporesponsiveness) were divided into the roxadustat group (n = 61) and erythropoiesis-stimulating agents (ESAs) group (n = 20). Hemoglobin (Hb), total cholesterol, intact parathyroid hormone (iPTH), brain natriuretic peptide (BNP), related indicators of cardiac function and high-sensitivity C-reactive protein (hs-CRP) were collected. Additionally, adverse events were also recorded. The follow-up period was 16 weeks. Results: The two groups exhibited similar baseline demographic and clinical characteristics. At baseline, the roxadustat group had a mean Hb level of 89.8 ± 18.9 g/L, while the ESAs group had a mean Hb level of 95.2 ± 16.0 g/L. By week 16, the Hb levels had increased to 118 ± 19.8 g/L (p < 0.05) in the roxadustat group and 101 ± 19.3 g/L (p > 0.05) in the ESAs group. The efficacy of roxadustat in improving anemia was not influenced by baseline levels of hs-CRP and iPTH. Cholesterol was decreased in the roxadustat group without statin use. An increase in left ventricular ejection fraction and stabilization of BNP were observed in the roxadustat group. Conclusions For PD patients with erythropoietin hyporesponsiveness, roxadustat can significantly improve renal anemia. The efficacy of roxadustat in improving renal anemia was not affected by baseline levels of hs-CRP0 and iPTH.

The incidence of chronic kidney disease (CKD) is increasing worldwide and the current prevalence rate is 13.4%. There are > 120 million CKD patients in China and this number is expected to increase. One of the main abnormalities in patients with CKD and kidney impairment is decreased synthesis of erythropoietin (EPO), which causes anemia and affects iron metabolism. The probability of developing is higher in anemia patients with CKD than in the general population, and the incidence increases as kidney function decreases. Deficient EPO production by the kidney is the most important cause of renal anemia. Notably, anemia in patients with CKD has multiple causes, such as bleeding caused by platelet dysfunction, iron deficiency due to digestive and absorption disorders of the gastrointestinal tract, and shorter red blood cell life. Anemia is also a leading cause of hospitalization in patients with CKD. A new oral medication to treat renal anemia, the hypoxia-inducible factor prolyl hydroxylase inhibitor called roxadustat (FG-4592), regulates iron metabolism and promotes erythropoiesis. This drug has a therapeutic effect on patients with CKD. Roxadustat showed advantages over EPO in clinical experiments. This review summarizes the mechanisms of action, clinical applications, effectiveness, and safety of roxadustat.