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Background: Developing a simple quantitative tool for mastitis diagnosis is essential. The Ion-Selective Electrode for sodium has been reported to reliably measure sodium concentrations in human milk. Research Aim: To determine whether an Ion-Selective Electrode measurement of sodium:potassium ratios could serve as a diagnostic tool for mastitis and, if so, to determine the diagnostic cut-off value. Methods: A total of 107 milk samples, including 55 from milk bank donors and 52 from participants with mastitis, were studied. The sodium:potassium ratios were determined in 33 samples (without mastitis n = 15; with mastitis n = 18) by the Ion-Selective Electrode and ion chromatography. The remaining 74 samples (donor milk n = 40; participants with mastitis n = 34) were analyzed by Ion-Selective Electrode only. Values were averaged over three measurements for each method. Results: The median postpartum months of donors and participants with mastitis were 2 and 3 months, respectively. The mean ( SD) sodium:potassium ratios without and with mastitis were 0.5 (0.1) and 1.7 (1.2), respectively. A positive correlation existed between sodium:potassium ratios obtained from the two methods ( r = 0.98). Area under the curve values were 0.951 (95% CI [0.904, 0.986]) for the Ion-Selective Electrode ( N = 107) and 0.978 (95% CI [0.926, 1.000]) for the ion chromatography ( n = 33) methods. The optimal cut-off value for the Ion-Selective Electrode method was 0.60, with 86.5% sensitivity and 92.7% specificity. Conclusions: The Ion-Selective Electrode was sufficiently accurate for the diagnosis of mastitis. Cohort studies are needed to explore the relationship between sodium:potassium ratios and clinical outcomes.

Objective BRCA1 and BRCA2 mutation carriers are recommended to undergo risk-reducing salpingo-oophorectomy (RRSO) by age 40 and 45, respectively. However, the carriers have a different way of thinking about their life plan. We aimed to investigate the distribution of age at diagnosis of ovarian cancer (OC) patients to examine the optimal timing of RRSO in the carriers. Methods We examined a correlation between age at diagnosis of OC and common mutation types in 3,517 probands that received BRCA genetic testing. Among them, germline BRCA1 mutation (g BRCA1 m), germline BRCA2 mutation (g BRCA2 m) and germline BRCA wild-type (g BRCA wt) were found in 185, 42 and 241 OC patients, respectively. Results The average age at diagnosis of OC in g BRCA1 m and g BRCA2 m was 51.3 and 58.3 years, respectively, and the difference from g BRCA wt (53.8 years) was significant. The g BRCA2 m carriers did not develop OC under the age of 40. The average age was 50.1 years for L63X and 52.8 years for Q934X in BRCA1 , and 55.1 years for R2318X and 61.1 years for STOP1861 in BRCA2 . The age at diagnosis in L63X or R2318X carriers was relatively younger than other BRCA1 or BRCA2 carriers, however their differences were not significant. With L63X and R2318X carriers, 89.4% (42/47) and 100% (7/7) of women were able to prevent the development of OC, respectively, when RRSO was performed at age 40. Conclusion There appears to be no difference in the age at diagnosis of OC depending on the type of BRCA common mutation. Further analysis would be needed.

Developmental dysplasia of the hip (DDH) is a cluster of hip development disorders and one of the most common hip diseases in infants. Hip radiography is a convenient diagnostic tool for DDH, but its diagnostic accuracy is dependent on the interpreter’s level of experience. The aim of this study was to develop a deep learning model for detecting DDH. Patients younger than 12 months who underwent hip radiography between June 2009 and November 2021 were selected. Using their radiography images, transfer learning was performed to develop a deep learning model using the “You Only Look Once” v5 (YOLOv5) and single shot multi-box detector (SSD). A total of 305 anteroposterior hip radiography images (205 normal and 100 DDH hip images) were collected. Of these, 30 normal and 17 DDH hip images were used as the test dataset. The sensitivity and the specificity of our best YOLOv5 model (YOLOv5l) were 0.94 (95% confidence interval [CI] 0.73–1.00) and 0.96 (95% CI 0.89–0.99), respectively. This model also outperformed the SSD model. This is the first study to establish a model for detecting DDH using YOLOv5. Our deep learning model provides good diagnostic performance for DDH. We believe our model is a useful diagnostic assistant tool.

Background Risk-reducing mastectomy is one option for women with hereditary breast and ovarian cancer to reduce the risk of breast cancer. Patients and methods We analyzed data of the Japanese Organization of Hereditary Breast and Ovarian Cancer on women who were diagnosed as hereditary breast and ovarian cancer by BRCA germline genetic testing between 2010 and 2019 to reveal the rate and likelihood of risk-reducing mastectomy. Results There were 412 women with BRCA1, 271 with BRCA2 and 4 with both female pathogenic variants. Ninety (13.1%) received risk-reducing mastectomy. The rates of risk-reducing mastectomy were statistically significantly higher in women with BRCA1 pathogenic variants than BRCA2, in women who had breast cancer than those who did not, in women with a breast cancer family history than in those without, in mothers than in those without children, in women who were receiving surveillance with MRI than those who were not and in women who received risk-reducing salpingo-oophorectomy than in those who did not on univariate analyses. The ages when they received the genetic testing were statistically significantly younger in the women receiving risk-reducing mastectomy than those who did not receive it. The women with BRCA1 pathogenic variants, personal history of breast cancer, mothers, those receiving MRI surveillance and younger women were independently significantly more likely to receive risk-reducing mastectomy based on multivariate analysis. Conclusions The rate of risk-reducing mastectomy was not high in Japan; however, risk-reducing surgery was approved by the Japanese National Medical Insurance for hereditary breast and ovarian cancer patients with breast and/or ovarian cancer in 2020, so this rate will increase.