Diabetic kidney disease （DKD） is one of the more common chronic kidney diseases，and its causes are complex. DKD is very easy to progress to end-stage renal disease，and the current therapeutic effect still needs to be improved. As an important excretive organ of the human body， the kidney has physiological functions such as discharging metabolic waste， regulating fluid balance， and maintaining the stability of the body's internal environment. These highly complex biochemical processes all depend on the energy support provided by mitochondria. Mitochondrial dysfunction is a key factor causing kidney injury， and the imbalance of mitochondrial homeostasis is an important link leading to mitochondrial dysfunction. The occurrence and development of DKD are often accompanied by the imbalance of mitochondrial homeostasis in renal cells. Mitochondrial autophagy， as a means of regulating mitochondrial homeostasis， is very important for the prevention and treatment of DKD. The PTEN-induced putative kinase 1 （PINK1）/Parkin pathway is one of the most classical pathways to regulate mitochondrial autophagy. Recent studies have found that some drugs can regulate the PINK1/Parkin signaling pathway to target mitochondrial homeostasis and exert renoprotective effects. In particular， traditional Chinese medicine has a significant effect on early and middle stage DKD by regulating PINK1/Parkin pathway-mediated mitochondrial autophagy. This article discussed the mechanism of PINK1/Parkin pathway in mitochondrial autophagy and DKD and reviewed the effect of PINK1/Parkin pathway-mediated mitochondrial autophagy on DKD. At the same time， it explored the therapeutic effect of traditional Chinese and western medicine on DKD mediated by PINK1/Parkin-mediated mitochondrial autophagy， aiming to broaden the ideas of traditional Chinese and western medicine for the prevention and treatment of DKD from the perspective of PINK1/Parkin regulating mitochondrial autophagy.

Diabetic kidney disease （DKD） is one of the more common chronic kidney diseases，and its causes are complex. DKD is very easy to progress to end-stage renal disease，and the current therapeutic effect still needs to be improved. As an important excretive organ of the human body， the kidney has physiological functions such as discharging metabolic waste， regulating fluid balance， and maintaining the stability of the body's internal environment. These highly complex biochemical processes all depend on the energy support provided by mitochondria. Mitochondrial dysfunction is a key factor causing kidney injury， and the imbalance of mitochondrial homeostasis is an important link leading to mitochondrial dysfunction. The occurrence and development of DKD are often accompanied by the imbalance of mitochondrial homeostasis in renal cells. Mitochondrial autophagy， as a means of regulating mitochondrial homeostasis， is very important for the prevention and treatment of DKD. The PTEN-induced putative kinase 1 （PINK1）/Parkin pathway is one of the most classical pathways to regulate mitochondrial autophagy. Recent studies have found that some drugs can regulate the PINK1/Parkin signaling pathway to target mitochondrial homeostasis and exert renoprotective effects. In particular， traditional Chinese medicine has a significant effect on early and middle stage DKD by regulating PINK1/Parkin pathway-mediated mitochondrial autophagy. This article discussed the mechanism of PINK1/Parkin pathway in mitochondrial autophagy and DKD and reviewed the effect of PINK1/Parkin pathway-mediated mitochondrial autophagy on DKD. At the same time， it explored the therapeutic effect of traditional Chinese and western medicine on DKD mediated by PINK1/Parkin-mediated mitochondrial autophagy， aiming to broaden the ideas of traditional Chinese and western medicine for the prevention and treatment of DKD from the perspective of PINK1/Parkin regulating mitochondrial autophagy.

Objective To describe the significance of the pretreatment inflammatory indicators in predicting the prognosis of patients with esophageal squamous cell carcinoma (ESCC) after undergoing radical radiotherapy. Methods The data of 246 ESCC patients who underwent radical radiotherapy were retrospectively collected. Receiver operating characteristic (ROC) curves were drawn to determine the optimal cutoff values for platelet-lymphocyte ratio (PLR), neutrophil-lymphocyte ratio (NLR), and systemic immune-inflammation index (SII). The Kaplan-Meier method was used for survival analysis. We conducted univariate and multivariate analyses by using the Cox proportional risk regression model. Software R (version 4.2.0) was used to create the nomogram of prognostic factors. Results The results of the ROC curve analysis showed that the optimal cutoff values of PLR, NLR, and SII were 146.06, 2.67, and 493.97, respectively. The overall response rates were 77.6% and 64.5% in the low and high NLR groups, respectively (P<0.05). The results of the Kaplan-Meier survival analysis revealed that the prognosis of patients in the low PLR, NLR, and SII group was better than that of patients in the high PLR, NLR, and SII group (all P<0.05). The results of the multivariate Cox regression analysis showed that gender, treatment modalities, T stage, and NLR were independent factors affecting the overall survival (OS). In addition, T stage and NLR were independent factors affecting the progression-free survival (PFS) (all P<0.05). The nomogram models of OS and PFS prediction were established based on multivariate analysis. The C-index values were 0.703 and 0.668. The calibration curves showed excellent consistency between the predicted and observed OS and PFS. Conclusion The pretreatment values of PLR, NLR, and SII are correlated with the prognosis of patients with ESCC who underwent radical radiotherapy. Moreover, NLR is an independent factor affecting the OS and PFS of ESCC patients. The NLR-based nomogram model has a good predictive ability.

Objective: To investigate the distribution characteristics of CD36 antigen in healthy individuals in Xinjiang, China and analyze the molecular mechanisms underlying CD36 deficiency. Methods: Flow cytometry was used to assess CD36 antigen expression on platelets from 881 healthy individuals who underwent physical examinations between June and August 2023. Differences in CD36 antigen distribution among ethnic groups were compared, and genotyping and third-generation sequencing were conducted on samples with CD36 deficiency. Results: Among the 881 samples, 4 cases (0.5%) of CD36 type Ⅱ deficiency were identified. The deficiency frequency was 0.7% (3/430) in Han individuals and 0.3% (1/363) in Uygur individuals, with no statistically significant difference between the two groups (P>0.05). No mutations were detected in the coding regions of the deficient samples. Two samples exhibited a (TG)11 in intron 3. Among the 12 linked mutation sites, g. 55589 G>A was mutated to g. 55589G Del, while g. 55593 A del did not occur; however, g. 55591A>T was observed nearby. Additionally, 52742insGAAAA was present in 100% of the (TG)11 haplotypes, potentially representing a novel linked mutation. Conclusion: This study indicates that the positive frequency of CD36 antigen in Xinjiang is relatively high, suggesting a low risk of alloimmune diseases in clinical practice. The (TG)11 in intron 3 is not universally present in all CD36 type Ⅱ deficiency cases, and the number of linked mutation sites extends beyond the previously reported 12.

Purpose: Rare diseases occur in <50 per 100000 people and require lifelong management. However, essential epidemiological data on such diseases are lacking, and a consecutive monitoring system across time and regions remains to be established. Standardized digital phenotypes are required to leverage an international data network for research on rare endocrine diseases. We developed digital phenotypes for rare endocrine diseases using the observational medical outcome partnership common data model. Materials and Methods: Digital phenotypes of three rare endocrine diseases (medullary thyroid cancer, hypoparathyroidism, pheochromocytoma/paraganglioma) were validated across three databases that use different vocabularies: Severance Hospital’s electronic health record from South Korea; IQVIA’s United Kingdom (UK) database for general practitioners; and IQVIA’s United States (US) hospital database for general hospitals. We estimated the performance of different digital phenotyping methods based on International Classification of Diseases (ICD)-10 in the UK and the US or systematized nomenclature of medicine clinical terms (SNOMED CT) in Korea. Results: The positive predictive value of digital phenotyping was higher using SNOMED CT-based phenotyping than ICD-10-based phenotyping for all three diseases in Korea (e.g., pheochromocytoma/paraganglioma: ICD-10, 58%–62%; SNOMED CT, 89%). Estimated incidence rates by digital phenotyping were as follows: medullary thyroid cancer, 0.34–2.07 (Korea), 0.13–0.30 (US); hypoparathyroidism, 0.40–1.20 (Korea), 0.59–1.01 (US), 0.00–1.78 (UK); and pheochromocytoma/paraganglioma, 0.95–1.67 (Korea), 0.35–0.77 (US), 0.00–0.49 (UK). Conclusion Our findings demonstrate the feasibility of developing digital phenotyping of rare endocrine diseases and highlight the importance of implementing SNOMED CT in routine clinical practice to provide granularity for research.

Background/Aims: Metabolic dysfunction-associated steatohepatitis (MASH) is a significant risk factor for gallstone formation, but mechanisms underlying MASH-related gallstone formation remain unclear. Golgi membrane protein 1 (GOLM1) participates in hepatic cholesterol metabolism and is upregulated in MASH. Here, we aimed to explore the role of GOLM1 in MASH-related gallstone formation. Methods: The UK Biobank cohort was used for etiological analysis. GOLM1 knockout (GOLM1-/-) and wild-type (WT) mice were fed with a high-fat diet (HFD). Livers were excised for histology and immunohistochemistry analysis. Gallbladders were collected to calculate incidence of cholesterol gallstones (CGSs). Biles were collected for biliary lipid analysis. HepG2 cells were used to explore underlying mechanisms. Human liver samples were used for clinical validation. Results: MASH patients had a greater risk of cholelithiasis. All HFD-fed mice developed MASH, and the incidence of gallstones was 16.7% and 75.0% in GOLM1-/- and WT mice, respectively. GOLM1-/- decreased biliary cholesterol concentration and output. In vivo and in vitro assays confirmed that GOLM1 facilitated cholesterol efflux through upregulating ATP binding cassette transporter subfamily G member 5 (ABCG5). Mechanistically, GOLM1 translocated into nucleus to promote osteopontin (OPN) transcription, thus stimulating ABCG5-mediated cholesterol efflux. Moreover, GOLM1 was upregulated by interleukin-1β (IL-1β) in a dose-dependent manner. Finally, we confirmed that IL-1β, GOLM1, OPN, and ABCG5 were enhanced in livers of MASH patients with CGSs. Conclusions In MASH livers, upregulation of GOLM1 by IL-1β increases ABCG5-mediated cholesterol efflux in an OPN-dependent manner, promoting CGS formation. GOLM1 has the potential to be a molecular hub interconnecting MASH and CGSs.

Purpose: Rare diseases occur in <50 per 100000 people and require lifelong management. However, essential epidemiological data on such diseases are lacking, and a consecutive monitoring system across time and regions remains to be established. Standardized digital phenotypes are required to leverage an international data network for research on rare endocrine diseases. We developed digital phenotypes for rare endocrine diseases using the observational medical outcome partnership common data model. Materials and Methods: Digital phenotypes of three rare endocrine diseases (medullary thyroid cancer, hypoparathyroidism, pheochromocytoma/paraganglioma) were validated across three databases that use different vocabularies: Severance Hospital’s electronic health record from South Korea; IQVIA’s United Kingdom (UK) database for general practitioners; and IQVIA’s United States (US) hospital database for general hospitals. We estimated the performance of different digital phenotyping methods based on International Classification of Diseases (ICD)-10 in the UK and the US or systematized nomenclature of medicine clinical terms (SNOMED CT) in Korea. Results: The positive predictive value of digital phenotyping was higher using SNOMED CT-based phenotyping than ICD-10-based phenotyping for all three diseases in Korea (e.g., pheochromocytoma/paraganglioma: ICD-10, 58%–62%; SNOMED CT, 89%). Estimated incidence rates by digital phenotyping were as follows: medullary thyroid cancer, 0.34–2.07 (Korea), 0.13–0.30 (US); hypoparathyroidism, 0.40–1.20 (Korea), 0.59–1.01 (US), 0.00–1.78 (UK); and pheochromocytoma/paraganglioma, 0.95–1.67 (Korea), 0.35–0.77 (US), 0.00–0.49 (UK). Conclusion Our findings demonstrate the feasibility of developing digital phenotyping of rare endocrine diseases and highlight the importance of implementing SNOMED CT in routine clinical practice to provide granularity for research.

Purpose: Rare diseases occur in <50 per 100000 people and require lifelong management. However, essential epidemiological data on such diseases are lacking, and a consecutive monitoring system across time and regions remains to be established. Standardized digital phenotypes are required to leverage an international data network for research on rare endocrine diseases. We developed digital phenotypes for rare endocrine diseases using the observational medical outcome partnership common data model. Materials and Methods: Digital phenotypes of three rare endocrine diseases (medullary thyroid cancer, hypoparathyroidism, pheochromocytoma/paraganglioma) were validated across three databases that use different vocabularies: Severance Hospital’s electronic health record from South Korea; IQVIA’s United Kingdom (UK) database for general practitioners; and IQVIA’s United States (US) hospital database for general hospitals. We estimated the performance of different digital phenotyping methods based on International Classification of Diseases (ICD)-10 in the UK and the US or systematized nomenclature of medicine clinical terms (SNOMED CT) in Korea. Results: The positive predictive value of digital phenotyping was higher using SNOMED CT-based phenotyping than ICD-10-based phenotyping for all three diseases in Korea (e.g., pheochromocytoma/paraganglioma: ICD-10, 58%–62%; SNOMED CT, 89%). Estimated incidence rates by digital phenotyping were as follows: medullary thyroid cancer, 0.34–2.07 (Korea), 0.13–0.30 (US); hypoparathyroidism, 0.40–1.20 (Korea), 0.59–1.01 (US), 0.00–1.78 (UK); and pheochromocytoma/paraganglioma, 0.95–1.67 (Korea), 0.35–0.77 (US), 0.00–0.49 (UK). Conclusion Our findings demonstrate the feasibility of developing digital phenotyping of rare endocrine diseases and highlight the importance of implementing SNOMED CT in routine clinical practice to provide granularity for research.