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.

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.

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.

AIM: To evaluate the performance of three distinct large language models(LLM), including GPT-3.5, GPT-4, and PaLM2, in responding to queries within the field of ophthalmology, and to compare their performance with three different levels of medical professionals: medical undergraduates, master of medicine, and attending physicians.METHODS: A total of 100 ophthalmic multiple-choice tests, which covered ophthalmic basic knowledge, clinical knowledge, ophthalmic examination and diagnostic methods, and treatment for ocular disease, were conducted on three different kinds of LLM and three different levels of medical professionals(9 undergraduates, 6 postgraduates and 3 attending physicians), respectively. The performance of LLM was comprehensively evaluated from the aspects of mean scores, consistency and confidence of response, and it was compared with human.RESULTS: Notably, each LLM surpassed the average performance of undergraduate medical students(GPT-4:56, GPT-3.5:42, PaLM2:47, undergraduate students:40). Specifically, performance of GPT-3.5 and PaLM2 was slightly lower than those of master's students(51), while GPT-4 exhibited a performance comparable to attending physicians(62). Furthermore, GPT-4 showed significantly higher response consistency and self-confidence compared with GPT-3.5 and PaLM2.CONCLUSION: LLM represented by GPT-4 performs well in the field of ophthalmology, and the LLM model can provide clinical decision-making and teaching aids for clinicians and medical education.

Objective To design a mobile personnel radiation protection equipment for operation in environments with high radiation such as spent fuel reprocessing plants, to achieve simultaneous protection against γ radiation, neutron radiation, and radioactive aerosol, to reduce the internal and external exposure dose of radioactive workers, and to meet the requirement of operation for two hours. Methods The core parts of the mobile personnel radiation protection equipment included a shielding chamber and a respiratory maintenance system. An automated chassis was used for the movement and lifting of the shielding chamber. MCNP software was used to simulate and calculate the protective effects of shielding chamber made of different materials and material thicknesses. Experimental verification of the shielding chamber design was conducted. Mathematical models were established to describe the variations in the content of various gases in the chamber with personnel operation time. A respiratory maintenance system, a harmful gas absorption device, and an automated mobile chassis were designed. Results The shielding chamber made of polyethylene with a thickness of 80 mm achieved an 80% neutron shielding rate. The respiratory maintenance system could support workers for 2 hours of operation inside the equipment. The mobile chassis allowed operation of the equipment with one person. Conclusion This mobile personnel radiation protection equipment can solve the problem in simultaneous protection against γ radiation, neutron radiation, and radioactive aerosol. The equipment can provide radiation protection for radioactive workers, reduce exposure dose, and reduce personnel burden. This system provides technical means for the operation and maintenance of equipment in high-radiation sites such as spent fuel reprocessing plants.

ObjectiveTo observe the effects of electroacupuncture at Zhongwan （CV12） on gastric nociceptive response induced by gastric acid stimulation and explore the underlying mechanisms associated with nuclei of the medullary viscerosensory and visceral motor neurons. MethodsTwenty SD rats were given intragastric administration of 0.5 mol/L diluted hydrochloric acid （0.5 ml/100 g） to induce gastric nociceptive response induction. Eight rats were randomly selected to record the gastric slow wave （GSW） area under the curve， and extracellular discharge frequency of neurons in the nucleus of the solitary tract （NTS） and dorsal motor nucleus of the vagus nerve （DMV） before intragastric administration and at 1， 5， 10， 15， 20， 25， 30， 35， 40， 45， 50， 55， and 60 minutes after intragastric administration. The remaining 12 rats received electroacupuncture intervention at Zhongwan within 5 to 25 minutes after intragastric administration of diluted hydrochloric acid， with a duration of one minute. The GSW area under the curve and extracellular discharge frequency of NTS and DMV neurons were compared between the 1-minute intervals before and after electroacupuncture intervention. ResultsCompared to the baseline before intragastric administration， the area under the curve of GSW significantly increased at 1， 5， 10， 15， 20， and 25 minutes after intragastric administration， and the extracellular discharge frequency of excitatory neurons in the NTS （accounting for 90%， 57/63） significantly increased at 1， 5， 10， 15， 20， 25， 30， 35， and 40 minutes， both reaching peak values at 1 minute after intragastric administration （P＜0.01 or P＜0.05）. The extracellular discharge frequency of inhibitory neurons in the DMV （accounting for 91%， 20/22） showed a non-significant increase at 1 minute after intragastric administration （P＞0.05）， but significantly decreased at other timepoints （P＜0.05）. Compared to the baseline before electroacupuncture intervention， the GSW area under the curve and the extracellular discharge frequency of excitatory neurons in the NTS significantly decreased （P＜0.05）， while the extracellular discharge frequency of inhibitory neurons in the DMV showed no significant difference （P＞0.05）. ConclusionElectroacupuncture at Zhongwan can improve gastric nociceptive response induced by gastric acid stimulation， possibly by reducing the transmission of visceral sensation and decreasing the excitability of NTS neurons in the medulla.

The application of function-preserving pancreatic surgery as a restrictive resection technique is primarily targeted towards benign or those with borderline or low-grade lesions. This approach has been shown to significantly improve both short-term and long-term quality of life outcomes for patients following surgical intervention. In comparison to conventional laparoscopic procedures, robotic surgical systems have demonstrated superior efficacy and precision when employed in pancreas surgeries, and the safety and reliability are widely recognized within the medical community. Nevertheless, there remains a dearth of research investigating the specific appli-cations of robotic-assisted function-preserving pancreatic surgery. Consequently, the authors compre-hensive review the latest progress on robot-assisted function-preserving pancreatic surgery, while highlighting of surgical scope, techniques utilized during these procedures as well as associated prognostic considerations.

Drugs and physical stimulation,including light,electricity,and magnetic fields,can be used to influence how neurons operate,among which chemogenetic and optogenetic technologies are most widely used.In recent years,magnetogenetic technology has also been developed that can acti-vate neurons in magnetic fields through magnetic sensitive actuators,leading to non-invasive and instanta-neous activation of specific brain regions.This article reviews the evolution of and problems with chemoge-netic and optogenetic techniques commonly used in brain science research.It also outlines the latest progress in magnetogenetic technologies,which are not full-fledged yet,as well as the role of transcra-nial electrical stimulation,transcranial magnetic stimulation,deep brain stimulation and transcranial ultra-sound stimulation technology in the functional regulation of brain diseases.Constant adjustment and improvement can make it possible for these technologies to be used more widely for the study of brain sciences and the treatment of brain diseases.