Background: Immunocompromised patients with severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection often have prolonged viral shedding, and some are clinically suspected of reinfection with different SARSCoV-2 variants. However, data on this issue are limited. This study investigated the SARS-CoV-2 variants in serially collected respiratory samples from immunocompromised patients with prolonged viral shedding for over 12 weeks or relapsed viral shedding after at least 2 weeks of viral clearance. Materials and Methods: From February 2022 to September 2023, we prospectively enrolled immunocompromised patients with coronavirus disease 2019 who had hematologic malignancies or had undergone transplantation and were admitted to a tertiary hospital. Weekly saliva or nasopharyngeal swabs were collected from enrolled patients for at least 12 weeks after diagnosis. Genomic RNA polymerase chain reaction (PCR) was performed on samples, and those testing positive underwent viral culture to isolate the live virus. Spike gene full sequencing via Sanger sequencing and real-time reverse transcription-PCR for detecting mutation genes were conducted to identify SARSCoV-2 variants. Results: Among 116 enrolled patients, 20 with prolonged or relapsed viral shedding were screened to identify the variants. Of these 20 patients, 7 (35%) exhibited evidence of re-infection; one of 8 patients with prolonged viral shedding and 6 of 12 with relapsed viral shedding were reinfected with SARS-CoV-2. Conclusion Our data suggest that approximately one-third of immunocompromised patients with persistent or relapsed viral shedding had reinfection with different variants of SARS-CoV-2.

Background: Immunocompromised patients with severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection often have prolonged viral shedding, and some are clinically suspected of reinfection with different SARSCoV-2 variants. However, data on this issue are limited. This study investigated the SARS-CoV-2 variants in serially collected respiratory samples from immunocompromised patients with prolonged viral shedding for over 12 weeks or relapsed viral shedding after at least 2 weeks of viral clearance. Materials and Methods: From February 2022 to September 2023, we prospectively enrolled immunocompromised patients with coronavirus disease 2019 who had hematologic malignancies or had undergone transplantation and were admitted to a tertiary hospital. Weekly saliva or nasopharyngeal swabs were collected from enrolled patients for at least 12 weeks after diagnosis. Genomic RNA polymerase chain reaction (PCR) was performed on samples, and those testing positive underwent viral culture to isolate the live virus. Spike gene full sequencing via Sanger sequencing and real-time reverse transcription-PCR for detecting mutation genes were conducted to identify SARSCoV-2 variants. Results: Among 116 enrolled patients, 20 with prolonged or relapsed viral shedding were screened to identify the variants. Of these 20 patients, 7 (35%) exhibited evidence of re-infection; one of 8 patients with prolonged viral shedding and 6 of 12 with relapsed viral shedding were reinfected with SARS-CoV-2. Conclusion Our data suggest that approximately one-third of immunocompromised patients with persistent or relapsed viral shedding had reinfection with different variants of SARS-CoV-2.

Background: Immunocompromised patients with severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection often have prolonged viral shedding, and some are clinically suspected of reinfection with different SARSCoV-2 variants. However, data on this issue are limited. This study investigated the SARS-CoV-2 variants in serially collected respiratory samples from immunocompromised patients with prolonged viral shedding for over 12 weeks or relapsed viral shedding after at least 2 weeks of viral clearance. Materials and Methods: From February 2022 to September 2023, we prospectively enrolled immunocompromised patients with coronavirus disease 2019 who had hematologic malignancies or had undergone transplantation and were admitted to a tertiary hospital. Weekly saliva or nasopharyngeal swabs were collected from enrolled patients for at least 12 weeks after diagnosis. Genomic RNA polymerase chain reaction (PCR) was performed on samples, and those testing positive underwent viral culture to isolate the live virus. Spike gene full sequencing via Sanger sequencing and real-time reverse transcription-PCR for detecting mutation genes were conducted to identify SARSCoV-2 variants. Results: Among 116 enrolled patients, 20 with prolonged or relapsed viral shedding were screened to identify the variants. Of these 20 patients, 7 (35%) exhibited evidence of re-infection; one of 8 patients with prolonged viral shedding and 6 of 12 with relapsed viral shedding were reinfected with SARS-CoV-2. Conclusion Our data suggest that approximately one-third of immunocompromised patients with persistent or relapsed viral shedding had reinfection with different variants of SARS-CoV-2.

Background: Genetic alterations play a pivotal role in multiple myeloma (MM) development and therapeutic resistance. Traditionally, the genetic profiling of MM requires invasive bone marrow (BM) procedures; however, these procedures are associated with patient discomfort and cannot fully capture the spatial and temporal heterogeneity of the disease.Therefore, we investigated the clinical implications of liquid biopsy using targeted deep sequencing. Methods: We analyzed the genetic profiles of circulating tumor DNA (ctDNA) by targeted deep sequencing from 102 patients, including those with monoclonal gammopathy of undetermined significance (MGUS, N = 7), smoldering MM (N = 6), and symptomatic MM (N = 89). Results: The number of ctDNA mutations increased with disease progression from MGUS to MM, with averages of 1.0 mutations in MGUS, 1.8 mutations in smoldering MM, and 1.9 mutations in MM, respectively. Shared mutations between BM and ctDNA were more prevalent in MM (68.9%) than in MGUS (25.0%). RAS/RAF and TP53 mutations were significantly enriched in MM ctDNA. Specific mutations were associated with clinical features in patients with MM: hypercalcemia and TET2 (P = 0.006), renal insufficiency and NRAS (P = 0.012), paramedullary myeloma and TP53(P = 0.02), and extramedullary myeloma and NRAS (P = 0.007). TET2 mutations significantly affected 2-yr progression-free survival (hazard ratio = 7.11, P = 0.003). Serial ctDNA profiling accurately predicted treatment response in patients with MM. Conclusions Our findings highlight the potential of liquid biopsy for understanding MM progression and prognosis utilizing a minimally invasive approach, paving the way for its integration into personalized treatment strategies and real-time disease monitoring.

Through the use of intraoral scanners, it is possible to obtain intraoral scan impressions and produce prostheses. This approach isalso being attempted not only in dentate patients but also in edentulous patients. However, obtaining scans of edentulous areas can be more challenging than scanning dental areas, and there may be limitations, especially in capturing the details of the mucosal tissues. On the other hand, when obtaining impressions with intraoral scanners, simultaneous recording of the occlusal relationship of the maxilla and mandible can reduce the number of patient visits and expedite the restoration process. In this case, we aimed to combine the advantages of direct intraoral scanning and indirect digital impressions obtained after traditional impression-taking by merging two types of scan files. Consequently, in patients with partially edentulous arches, we sought to provide effective in-terim prostheses through direct and indirect digital model impressions and report our findings accordingly.

Objective: The performance of large language models (LLMs) and their potential utility in obstetric and gynecological education are topics of ongoing debate. This study aimed to contribute to this discussion by examining the recent advancements in LLM technology and their transformative potential in artificial intelligence. Methods: This study assessed the performance of generative pre-trained transformer (GPT)-3.5 and -4 in understanding clinical information, as well as its potential implications for obstetric and gynecological education. Obstetrics and gynecology residents at three hospitals underwent an annual promotional examination, from which 116 of the 170 questions over 4 years (2020-2023) were analyzed, excluding 54 questions with images. The scores achieved by GPT-3.5, -4, and the 100 residents were compared. Results: The average scores across all 4 years for GPT-3.5 and -4 were 38.79 (standard deviation [SD], 5.65) and 79.31 (SD, 3.67), respectively. For groups first-year resident, second-year resident, and third-year resident, the cumulative annual average scores were 79.12 (SD, 9.00), 80.95 (SD, 5.86), and 83.60 (SD, 6.82), respectively. No statistically significant differences were observed between the scores of GPT-4.0 and those of the residents. When analyzing questions specific to obstetrics, the average scores for GPT-3.5 and -4.0 were 33.44 (SD, 10.18) and 90.22 (SD, 7.68), respectively. Conclusion GPT-4 demonstrated exceptional performance in obstetrics, different types of data interpretation, and problem solving, showcasing the potential utility of LLMs in these areas. However, acknowledging the constraints of LLMs is crucial and their utilization should augment human expertise and discernment.

Objective: The performance of large language models (LLMs) and their potential utility in obstetric and gynecological education are topics of ongoing debate. This study aimed to contribute to this discussion by examining the recent advancements in LLM technology and their transformative potential in artificial intelligence. Methods: This study assessed the performance of generative pre-trained transformer (GPT)-3.5 and -4 in understanding clinical information, as well as its potential implications for obstetric and gynecological education. Obstetrics and gynecology residents at three hospitals underwent an annual promotional examination, from which 116 of the 170 questions over 4 years (2020-2023) were analyzed, excluding 54 questions with images. The scores achieved by GPT-3.5, -4, and the 100 residents were compared. Results: The average scores across all 4 years for GPT-3.5 and -4 were 38.79 (standard deviation [SD], 5.65) and 79.31 (SD, 3.67), respectively. For groups first-year resident, second-year resident, and third-year resident, the cumulative annual average scores were 79.12 (SD, 9.00), 80.95 (SD, 5.86), and 83.60 (SD, 6.82), respectively. No statistically significant differences were observed between the scores of GPT-4.0 and those of the residents. When analyzing questions specific to obstetrics, the average scores for GPT-3.5 and -4.0 were 33.44 (SD, 10.18) and 90.22 (SD, 7.68), respectively. Conclusion GPT-4 demonstrated exceptional performance in obstetrics, different types of data interpretation, and problem solving, showcasing the potential utility of LLMs in these areas. However, acknowledging the constraints of LLMs is crucial and their utilization should augment human expertise and discernment.

Through the use of intraoral scanners, it is possible to obtain intraoral scan impressions and produce prostheses. This approach isalso being attempted not only in dentate patients but also in edentulous patients. However, obtaining scans of edentulous areas can be more challenging than scanning dental areas, and there may be limitations, especially in capturing the details of the mucosal tissues. On the other hand, when obtaining impressions with intraoral scanners, simultaneous recording of the occlusal relationship of the maxilla and mandible can reduce the number of patient visits and expedite the restoration process. In this case, we aimed to combine the advantages of direct intraoral scanning and indirect digital impressions obtained after traditional impression-taking by merging two types of scan files. Consequently, in patients with partially edentulous arches, we sought to provide effective in-terim prostheses through direct and indirect digital model impressions and report our findings accordingly.

Through the use of intraoral scanners, it is possible to obtain intraoral scan impressions and produce prostheses. This approach isalso being attempted not only in dentate patients but also in edentulous patients. However, obtaining scans of edentulous areas can be more challenging than scanning dental areas, and there may be limitations, especially in capturing the details of the mucosal tissues. On the other hand, when obtaining impressions with intraoral scanners, simultaneous recording of the occlusal relationship of the maxilla and mandible can reduce the number of patient visits and expedite the restoration process. In this case, we aimed to combine the advantages of direct intraoral scanning and indirect digital impressions obtained after traditional impression-taking by merging two types of scan files. Consequently, in patients with partially edentulous arches, we sought to provide effective in-terim prostheses through direct and indirect digital model impressions and report our findings accordingly.

Objective: The performance of large language models (LLMs) and their potential utility in obstetric and gynecological education are topics of ongoing debate. This study aimed to contribute to this discussion by examining the recent advancements in LLM technology and their transformative potential in artificial intelligence. Methods: This study assessed the performance of generative pre-trained transformer (GPT)-3.5 and -4 in understanding clinical information, as well as its potential implications for obstetric and gynecological education. Obstetrics and gynecology residents at three hospitals underwent an annual promotional examination, from which 116 of the 170 questions over 4 years (2020-2023) were analyzed, excluding 54 questions with images. The scores achieved by GPT-3.5, -4, and the 100 residents were compared. Results: The average scores across all 4 years for GPT-3.5 and -4 were 38.79 (standard deviation [SD], 5.65) and 79.31 (SD, 3.67), respectively. For groups first-year resident, second-year resident, and third-year resident, the cumulative annual average scores were 79.12 (SD, 9.00), 80.95 (SD, 5.86), and 83.60 (SD, 6.82), respectively. No statistically significant differences were observed between the scores of GPT-4.0 and those of the residents. When analyzing questions specific to obstetrics, the average scores for GPT-3.5 and -4.0 were 33.44 (SD, 10.18) and 90.22 (SD, 7.68), respectively. Conclusion GPT-4 demonstrated exceptional performance in obstetrics, different types of data interpretation, and problem solving, showcasing the potential utility of LLMs in these areas. However, acknowledging the constraints of LLMs is crucial and their utilization should augment human expertise and discernment.