Thelazia callipaeda (Spirurida, Thelaziidae), a parasitic eye worm causing thelaziasis has been reported in humans and dogs in Korea. However, its occurrence in other potential reservoir hosts, including wild animals, remains unclear. In the present study, we described the 2 cases of thelaziasis from both of feral and captive wild animal in Korea. In August and November 2017, 2 cases of the parasitic infections were found in the third eyelid of rescued leopard cat Prionailurus bengalensis and reared raccoon dog Nyctereutes procyonoides at the Chungnam Wild Animal Rescue Center. A total of 20 and 24 worms were detected from the left and right eyes of leopard cat, respectively. In the left eye of the raccoon dog, 5 worms were recognized. Male worms were 969–11,860 μm long (10,600 μm on average) and 300–320 μm width (315 μm on average). Female worms were 13,430–15,330 (14,480) μm long and 320–370 (344) μm wide in size. They commonly had a characteristic scalariform buccal cavity and short esophagus. The vulva openings were located at the anterior of esophago-intestinal junction in females. The thelaziasis is reported in 2 species of wildlife, P. bengalensis and N. procyonoides, for the first time in Korea.

Objectives: Developing large language models (LLMs) in biomedicine requires access to high-quality training and alignment tuning datasets. However, publicly available Korean medical preference datasets are scarce, hindering the advancement of Korean medical LLMs. This study constructs and evaluates the efficacy of the Korean Medical Preference Dataset (KoMeP), an alignment tuning dataset constructed with an automated pipeline, minimizing the high costs of human annotation. Methods: KoMeP was generated using the DAHL score, an automated hallucination evaluation metric. Five LLMs (Dolly-v2-3B, MPT-7B, GPT-4o, Qwen-2-7B, Llama-3-8B) produced responses to 8,573 biomedical examination questions, from which 5,551 preference pairs were extracted. Each pair consisted of a “chosen” response and a “rejected” response, as determined by their DAHL scores. The dataset was evaluated when trained through two different alignment tuning methods, direct preference optimization (DPO) and odds ratio preference optimization (ORPO) respectively across five different models. The KorMedMCQA benchmark was employed to assess the effectiveness of alignment tuning. Results: Models trained with DPO consistently improved KorMedMCQA performance; notably, Llama-3.1-8B showed a 43.96% increase. In contrast, ORPO training produced inconsistent results. Additionally, English-to-Korean transfer learning proved effective, particularly for English-centric models like Gemma-2, whereas Korean-to-English transfer learning achieved limited success. Instruction tuning with KoMeP yielded mixed outcomes, which suggests challenges in dataset formatting. Conclusions KoMeP is the first publicly available Korean medical preference dataset and significantly improves alignment tuning performance in LLMs. The DPO method outperforms ORPO in alignment tuning. Future work should focus on expanding KoMeP, developing a Korean-native dataset, and refining alignment tuning methods to produce safer and more reliable Korean medical LLMs.

Thelazia callipaeda (Spirurida, Thelaziidae), a parasitic eye worm causing thelaziasis has been reported in humans and dogs in Korea. However, its occurrence in other potential reservoir hosts, including wild animals, remains unclear. In the present study, we described the 2 cases of thelaziasis from both of feral and captive wild animal in Korea. In August and November 2017, 2 cases of the parasitic infections were found in the third eyelid of rescued leopard cat Prionailurus bengalensis and reared raccoon dog Nyctereutes procyonoides at the Chungnam Wild Animal Rescue Center. A total of 20 and 24 worms were detected from the left and right eyes of leopard cat, respectively. In the left eye of the raccoon dog, 5 worms were recognized. Male worms were 969–11,860 μm long (10,600 μm on average) and 300–320 μm width (315 μm on average). Female worms were 13,430–15,330 (14,480) μm long and 320–370 (344) μm wide in size. They commonly had a characteristic scalariform buccal cavity and short esophagus. The vulva openings were located at the anterior of esophago-intestinal junction in females. The thelaziasis is reported in 2 species of wildlife, P. bengalensis and N. procyonoides, for the first time in Korea.

Thelazia callipaeda (Spirurida, Thelaziidae), a parasitic eye worm causing thelaziasis has been reported in humans and dogs in Korea. However, its occurrence in other potential reservoir hosts, including wild animals, remains unclear. In the present study, we described the 2 cases of thelaziasis from both of feral and captive wild animal in Korea. In August and November 2017, 2 cases of the parasitic infections were found in the third eyelid of rescued leopard cat Prionailurus bengalensis and reared raccoon dog Nyctereutes procyonoides at the Chungnam Wild Animal Rescue Center. A total of 20 and 24 worms were detected from the left and right eyes of leopard cat, respectively. In the left eye of the raccoon dog, 5 worms were recognized. Male worms were 969–11,860 μm long (10,600 μm on average) and 300–320 μm width (315 μm on average). Female worms were 13,430–15,330 (14,480) μm long and 320–370 (344) μm wide in size. They commonly had a characteristic scalariform buccal cavity and short esophagus. The vulva openings were located at the anterior of esophago-intestinal junction in females. The thelaziasis is reported in 2 species of wildlife, P. bengalensis and N. procyonoides, for the first time in Korea.

Objectives: Developing large language models (LLMs) in biomedicine requires access to high-quality training and alignment tuning datasets. However, publicly available Korean medical preference datasets are scarce, hindering the advancement of Korean medical LLMs. This study constructs and evaluates the efficacy of the Korean Medical Preference Dataset (KoMeP), an alignment tuning dataset constructed with an automated pipeline, minimizing the high costs of human annotation. Methods: KoMeP was generated using the DAHL score, an automated hallucination evaluation metric. Five LLMs (Dolly-v2-3B, MPT-7B, GPT-4o, Qwen-2-7B, Llama-3-8B) produced responses to 8,573 biomedical examination questions, from which 5,551 preference pairs were extracted. Each pair consisted of a “chosen” response and a “rejected” response, as determined by their DAHL scores. The dataset was evaluated when trained through two different alignment tuning methods, direct preference optimization (DPO) and odds ratio preference optimization (ORPO) respectively across five different models. The KorMedMCQA benchmark was employed to assess the effectiveness of alignment tuning. Results: Models trained with DPO consistently improved KorMedMCQA performance; notably, Llama-3.1-8B showed a 43.96% increase. In contrast, ORPO training produced inconsistent results. Additionally, English-to-Korean transfer learning proved effective, particularly for English-centric models like Gemma-2, whereas Korean-to-English transfer learning achieved limited success. Instruction tuning with KoMeP yielded mixed outcomes, which suggests challenges in dataset formatting. Conclusions KoMeP is the first publicly available Korean medical preference dataset and significantly improves alignment tuning performance in LLMs. The DPO method outperforms ORPO in alignment tuning. Future work should focus on expanding KoMeP, developing a Korean-native dataset, and refining alignment tuning methods to produce safer and more reliable Korean medical LLMs.

Thelazia callipaeda (Spirurida, Thelaziidae), a parasitic eye worm causing thelaziasis has been reported in humans and dogs in Korea. However, its occurrence in other potential reservoir hosts, including wild animals, remains unclear. In the present study, we described the 2 cases of thelaziasis from both of feral and captive wild animal in Korea. In August and November 2017, 2 cases of the parasitic infections were found in the third eyelid of rescued leopard cat Prionailurus bengalensis and reared raccoon dog Nyctereutes procyonoides at the Chungnam Wild Animal Rescue Center. A total of 20 and 24 worms were detected from the left and right eyes of leopard cat, respectively. In the left eye of the raccoon dog, 5 worms were recognized. Male worms were 969–11,860 μm long (10,600 μm on average) and 300–320 μm width (315 μm on average). Female worms were 13,430–15,330 (14,480) μm long and 320–370 (344) μm wide in size. They commonly had a characteristic scalariform buccal cavity and short esophagus. The vulva openings were located at the anterior of esophago-intestinal junction in females. The thelaziasis is reported in 2 species of wildlife, P. bengalensis and N. procyonoides, for the first time in Korea.

Objectives: Developing large language models (LLMs) in biomedicine requires access to high-quality training and alignment tuning datasets. However, publicly available Korean medical preference datasets are scarce, hindering the advancement of Korean medical LLMs. This study constructs and evaluates the efficacy of the Korean Medical Preference Dataset (KoMeP), an alignment tuning dataset constructed with an automated pipeline, minimizing the high costs of human annotation. Methods: KoMeP was generated using the DAHL score, an automated hallucination evaluation metric. Five LLMs (Dolly-v2-3B, MPT-7B, GPT-4o, Qwen-2-7B, Llama-3-8B) produced responses to 8,573 biomedical examination questions, from which 5,551 preference pairs were extracted. Each pair consisted of a “chosen” response and a “rejected” response, as determined by their DAHL scores. The dataset was evaluated when trained through two different alignment tuning methods, direct preference optimization (DPO) and odds ratio preference optimization (ORPO) respectively across five different models. The KorMedMCQA benchmark was employed to assess the effectiveness of alignment tuning. Results: Models trained with DPO consistently improved KorMedMCQA performance; notably, Llama-3.1-8B showed a 43.96% increase. In contrast, ORPO training produced inconsistent results. Additionally, English-to-Korean transfer learning proved effective, particularly for English-centric models like Gemma-2, whereas Korean-to-English transfer learning achieved limited success. Instruction tuning with KoMeP yielded mixed outcomes, which suggests challenges in dataset formatting. Conclusions KoMeP is the first publicly available Korean medical preference dataset and significantly improves alignment tuning performance in LLMs. The DPO method outperforms ORPO in alignment tuning. Future work should focus on expanding KoMeP, developing a Korean-native dataset, and refining alignment tuning methods to produce safer and more reliable Korean medical LLMs.

Thelazia callipaeda (Spirurida, Thelaziidae), a parasitic eye worm causing thelaziasis has been reported in humans and dogs in Korea. However, its occurrence in other potential reservoir hosts, including wild animals, remains unclear. In the present study, we described the 2 cases of thelaziasis from both of feral and captive wild animal in Korea. In August and November 2017, 2 cases of the parasitic infections were found in the third eyelid of rescued leopard cat Prionailurus bengalensis and reared raccoon dog Nyctereutes procyonoides at the Chungnam Wild Animal Rescue Center. A total of 20 and 24 worms were detected from the left and right eyes of leopard cat, respectively. In the left eye of the raccoon dog, 5 worms were recognized. Male worms were 969–11,860 μm long (10,600 μm on average) and 300–320 μm width (315 μm on average). Female worms were 13,430–15,330 (14,480) μm long and 320–370 (344) μm wide in size. They commonly had a characteristic scalariform buccal cavity and short esophagus. The vulva openings were located at the anterior of esophago-intestinal junction in females. The thelaziasis is reported in 2 species of wildlife, P. bengalensis and N. procyonoides, for the first time in Korea.

Background: With the ultimate goal of developing chatbot content to address consumer inquiries about pressure injuries (PIs), this study analyzed consumer perceptions of PI using big data. Methods: This study collected text data, with PI as the central word, from three search engines (Naver, Daum, Google) from January 2019 through December 2022, using Textom version 4.5. The words were refined through text mining, keyword analysis, and TF-IDF (term frequency-inverse document frequency) analysis. N-gram analysis and centrality visualization were conducted using Ucinet 6.0. The keywords and frequencies were clustered based on the frequency of words used in CONCOR (convergence of iteration correlation) analysis. Results: Consumers for PI showed a high perception of common sites for PI, concept of PI, healthcare facility for PI, PI products, PI care, PI-related life, and PI-related disease. Conclusion Development of chatbot content customized to consumers’ needs, based on seven clusters associated with consumers’ perception of PI obtained through extensive data analysis with PI as the central word, is expected to make a significant contribution to improving consumers’ understanding of PI and enhancing the quality of PI management.

This review comprehensively examines the diverse spectrum of gastric cancers, focusing on unusual or uncommon histology that presents significant diagnostic and therapeutic challenges. While the predominant form, tubular adenocarcinoma, is well-characterized, this review focuses on lesser-known variants, including papillary adenocarcinoma, micropapillary carcinoma, adenosquamous carcinoma, squamous cell carcinoma (SCC), hepatoid adenocarcinoma, gastric choriocarcinoma, gastric carcinoma with lymphoid stroma, carcinosarcoma, gastroblastoma, parietal cell carcinoma, oncocytic adenocarcinoma, Paneth cell carcinoma, gastric adenocarcinoma of the fundic gland type, undifferentiated carcinoma, and extremely well-differentiated adenocarcinoma. Although these diseases have different nomenclatures characterized by distinct histopathological features, these phenotypes often overlap, making it difficult to draw clear boundaries. Furthermore, the number of cases was limited, and the unique histopathological nature and potential pathogenic mechanisms were not well defined. This review highlights the importance of understanding these rare variants for accurate diagnosis, effective treatment planning, and improving patient outcomes. This review emphasizes the need for ongoing research and case studies to enhance our knowledge of these uncommon forms of gastric cancer, which will ultimately contribute to more effective treatments and better prognostic assessments. This review aimed to broaden the pathological narrative by acknowledging and addressing the intricacies of all cancer types, regardless of their rarity, to advance patient care and improve prognosis.