OBJECTIVE: Impairment of spermatogenesis has been identified as an inevitable side effect of cancer treatment. Although estrogen treatment stimulates spermatogenic recovery from the impaired spermatogenesis by suppressing the intra-testicular testosterone (ITT) level, side effects of estrogen are still major impediments to its clinical application in humans. Soybeans are rich in genistein, which is a phytoestrogen that binds to estrogen receptors and has an estrogenic effect. We investigated the effects of genistein administration on ITT levels, testis weight, and recovery of spermatogenesis in rats treated with a chemotherapeutic agent, busulfan. METHODS: Busulfan was administered intraperitoneally to rats, and then a GnRH agonist was injected subcutaneously into the back, or genistein was administered orally. RESULTS: The weight of the testes was significantly reduced by the treatment with busulfan. The testis weight was partially restored after busulfan treatment by additional treatment with either the GnRH agonist or genistein. Busulfan also induced atrophy of a high percentage of the seminiferous tubules, but this percentage was decreased by additional treatment with either the GnRH agonist or genistein. Treatment with genistein was effective at suppressing and maintaining ITT levels comparable to that in the GnRH agonist group. CONCLUSION: Genistein effectively suppressed ITT levels and stimulated the recovery of spermatogenesis in rats treated with a chemotherapeutic drug. This suggests that genistein may be a substitute for estrogens, for helping humans to recover fertility after cancer therapy without the risk of side effects.
Animals ; Atrophy ; Busulfan ; Estrogens ; Fertility ; Genistein ; Gonadotropin-Releasing Hormone ; Humans ; Phytoestrogens ; Rats ; Receptors, Estrogen ; Seminiferous Tubules ; Soybeans ; Spermatogenesis ; Testis ; Testosterone

Background: Gestational diabetes mellitus (GDM) affects women with diverse pathological phenotypes, but little is known about the effects of this variation on perinatal outcomes. We explored the metabolic phenotypes of GDM and their impact on adverse pregnancy outcomes. Methods: Women diagnosed with gestational glucose intolerance or GDM were categorized into subgroups according to their prepregnancy body mass index (BMI) and the median values of the gestational Matsuda and Stumvoll indices. Logistic regression analysis was employed to assess the odds of adverse pregnancy outcomes, such as large-for-gestational age (LGA), small-for-gestational age, preterm birth, low Apgar score, and cesarean section. Results: A total of 309 women were included, with a median age of 31 years and a median BMI of 22.3 kg/m2. Women with a higher pre-pregnancy BMI had a higher risk of LGA newborns (adjusted odds ratio [aOR] for pre-pregnancy BMI ≥25 kg/m2 compared to 20–23 kg/m2, 4.26; 95% confidence interval [CI], 1.99 to 9.12; P<0.001; P for trend=0.001), but the risk of other adverse pregnancy outcomes did not differ according to pre-pregnancy BMI. Women with insulin resistance had a higher risk of LGA (aOR, 1.88; 95% CI, 1.02 to 3.47; P=0.043) and cesarean section (aOR, 2.12; 95% CI, 1.29 to 3.50; P=0.003) than women in the insulin-sensitive group. In contrast, defective β-cell function did not affect adverse pregnancy outcomes. Conclusion Different metabolic phenotypes of GDM were associated with heterogeneous pregnancy outcomes. Women with obesity and those with insulin resistance are at greater risk of adverse outcomes and might need strict glycemic management during pregnancy.

Background: Gestational diabetes mellitus (GDM) affects women with diverse pathological phenotypes, but little is known about the effects of this variation on perinatal outcomes. We explored the metabolic phenotypes of GDM and their impact on adverse pregnancy outcomes. Methods: Women diagnosed with gestational glucose intolerance or GDM were categorized into subgroups according to their prepregnancy body mass index (BMI) and the median values of the gestational Matsuda and Stumvoll indices. Logistic regression analysis was employed to assess the odds of adverse pregnancy outcomes, such as large-for-gestational age (LGA), small-for-gestational age, preterm birth, low Apgar score, and cesarean section. Results: A total of 309 women were included, with a median age of 31 years and a median BMI of 22.3 kg/m2. Women with a higher pre-pregnancy BMI had a higher risk of LGA newborns (adjusted odds ratio [aOR] for pre-pregnancy BMI ≥25 kg/m2 compared to 20–23 kg/m2, 4.26; 95% confidence interval [CI], 1.99 to 9.12; P<0.001; P for trend=0.001), but the risk of other adverse pregnancy outcomes did not differ according to pre-pregnancy BMI. Women with insulin resistance had a higher risk of LGA (aOR, 1.88; 95% CI, 1.02 to 3.47; P=0.043) and cesarean section (aOR, 2.12; 95% CI, 1.29 to 3.50; P=0.003) than women in the insulin-sensitive group. In contrast, defective β-cell function did not affect adverse pregnancy outcomes. Conclusion Different metabolic phenotypes of GDM were associated with heterogeneous pregnancy outcomes. Women with obesity and those with insulin resistance are at greater risk of adverse outcomes and might need strict glycemic management during pregnancy.

Background: Gestational diabetes mellitus (GDM) affects women with diverse pathological phenotypes, but little is known about the effects of this variation on perinatal outcomes. We explored the metabolic phenotypes of GDM and their impact on adverse pregnancy outcomes. Methods: Women diagnosed with gestational glucose intolerance or GDM were categorized into subgroups according to their prepregnancy body mass index (BMI) and the median values of the gestational Matsuda and Stumvoll indices. Logistic regression analysis was employed to assess the odds of adverse pregnancy outcomes, such as large-for-gestational age (LGA), small-for-gestational age, preterm birth, low Apgar score, and cesarean section. Results: A total of 309 women were included, with a median age of 31 years and a median BMI of 22.3 kg/m2. Women with a higher pre-pregnancy BMI had a higher risk of LGA newborns (adjusted odds ratio [aOR] for pre-pregnancy BMI ≥25 kg/m2 compared to 20–23 kg/m2, 4.26; 95% confidence interval [CI], 1.99 to 9.12; P<0.001; P for trend=0.001), but the risk of other adverse pregnancy outcomes did not differ according to pre-pregnancy BMI. Women with insulin resistance had a higher risk of LGA (aOR, 1.88; 95% CI, 1.02 to 3.47; P=0.043) and cesarean section (aOR, 2.12; 95% CI, 1.29 to 3.50; P=0.003) than women in the insulin-sensitive group. In contrast, defective β-cell function did not affect adverse pregnancy outcomes. Conclusion Different metabolic phenotypes of GDM were associated with heterogeneous pregnancy outcomes. Women with obesity and those with insulin resistance are at greater risk of adverse outcomes and might need strict glycemic management during pregnancy.

Background: Gestational diabetes mellitus (GDM) affects women with diverse pathological phenotypes, but little is known about the effects of this variation on perinatal outcomes. We explored the metabolic phenotypes of GDM and their impact on adverse pregnancy outcomes. Methods: Women diagnosed with gestational glucose intolerance or GDM were categorized into subgroups according to their prepregnancy body mass index (BMI) and the median values of the gestational Matsuda and Stumvoll indices. Logistic regression analysis was employed to assess the odds of adverse pregnancy outcomes, such as large-for-gestational age (LGA), small-for-gestational age, preterm birth, low Apgar score, and cesarean section. Results: A total of 309 women were included, with a median age of 31 years and a median BMI of 22.3 kg/m2. Women with a higher pre-pregnancy BMI had a higher risk of LGA newborns (adjusted odds ratio [aOR] for pre-pregnancy BMI ≥25 kg/m2 compared to 20–23 kg/m2, 4.26; 95% confidence interval [CI], 1.99 to 9.12; P<0.001; P for trend=0.001), but the risk of other adverse pregnancy outcomes did not differ according to pre-pregnancy BMI. Women with insulin resistance had a higher risk of LGA (aOR, 1.88; 95% CI, 1.02 to 3.47; P=0.043) and cesarean section (aOR, 2.12; 95% CI, 1.29 to 3.50; P=0.003) than women in the insulin-sensitive group. In contrast, defective β-cell function did not affect adverse pregnancy outcomes. Conclusion Different metabolic phenotypes of GDM were associated with heterogeneous pregnancy outcomes. Women with obesity and those with insulin resistance are at greater risk of adverse outcomes and might need strict glycemic management during pregnancy.

Background: Identifying risk factors for postpartum type 2 diabetes in women with gestational diabetes mellitus (GDM) is crucial for effective interventions. We examined whether changes in insulin sensitivity after delivery affects the risk of type 2 diabetes in women with GDM. Methods: This prospective cohort study included 347 women with GDM or gestational impaired glucose tolerance, who attended the follow-up visits at 2 months postpartum and annually thereafter. Changes in insulin sensitivity were calculated using the Matsuda index at GDM diagnosis and at 2 months postpartum (ΔMatsuda index). After excluding women with pregestational diabetes or those followed up only once, we analyzed the risk of postpartum type 2 diabetes based on the ΔMatsuda index tertiles. Results: The incidence of type 2 diabetes at the two-month postpartum visit decreased with increasing ΔMatsuda index tertiles (16.4%, 9.5%, and 1.8%, P=0.001). During a 4.1-year follow-up, 26 out of 230 women who attended more than two follow-up visits (11.3%) developed type 2 diabetes. Compared to the lowest tertile, subjects in the highest ΔMatsuda index tertile showed a significantly reduced risk of type 2 diabetes (hazard ratio, 0.33; 95% confidence interval, 0.12 to 0.93; P=0.036) after adjusting for confounders. Conclusion Improvement in insulin sensitivity after delivery is associated with a reduced risk of postpartum type 2 diabetes in women with GDM. Postpartum changes in insulin sensitivity could be a useful prediction for future type 2 diabetes development in women with GDM.

Purpose: This study aimed to investigate the oncologic outcomes and prognostic factors of salvage treatments in patients with recurrent oropharyngeal squamous cell carcinoma (OPSCC) after radiotherapy (RT)-based treatment. Materials and Methods: A cancer registry was used to retrieve the records of 337 patients treated with definitive RT or concurrent chemoradiotherapy (CRT) from 2008 to 2018 at a single institution. The poor-responder group (PRG) was defined as patients with residual or recurrent disease after primary treatment, and the oncologic outcomes for each salvage treatment method were analyzed. In addition, prognostic indicators of recurrence-free survival (RFS) and overall survival (OS) were identified in patients who underwent salvage treatment. Results: After initial (C)RT, the PRG comprised 71 of the 337 patients (21.1%): 18 patients had residual disease, and 53 had recurrence after primary treatment (mean time to recurrence 19.5 months). Of these, 63 patients received salvage treatment (surgery 57.2%, re-(C)RT 23.8%, and chemotherapy 19.0%), and the salvage success rate was 47.6% at the last follow-up. The overall 2-year OS for salvage treatments was 56.4% (60.8% for the salvage surgery group and 46.2% for the salvage re-(C)RT). Salvage surgery patients with negative resection margins had better oncologic outcomes than those with close/positive resection margins. Using multivariate analyses, locoregional recurrence and residual disease after primary surgery were associated with poor outcome after salvage treatment. In Kaplan-Meier analyses, p16 status was significantly associated with OS in the initial treatment setting but not in the salvage setting. Conclusion In recurrent OPSCC after RT-based treatment, successful salvage was achieved in 56.4% patients who had undergone salvage surgery and radiation treatment. Salvage treatment methods should be selected carefully, given recurrence site as a prognostic factor for RFS.

Background: We explored the utility of a small multi-gene DNA panel for assessing molecular profiles of thyroid nodules and influencing clinical decisions by comparing outcomes between tested and untested nodules. Methods: Between April 2022 and May 2023, we prospectively performed fine-needle aspiration (FNA) with gene testing via DNA panel of 11 genes (BRAF, RAS [NRAS, HRAS, KRAS], EZH1, DICER1, EIF1AX, PTEN, TP53, PIK3CA, TERT promoter) in 278 consecutive nodules (panel group). Propensity score-matching (1:1) was performed with 475 nodules that consecutively underwent FNA without gene testing between January 2021 and December 2021 (control group). Results: In the panel group, positive call rate for mutations was 41.7% (BRAF 16.2%, RAS 12.6%, others 11.5%, double mutation 1.4%) for all nodules, and 40.0% (BRAF 4.3%, RAS 19.1%, others 15.7%, double mutation 0.9%) for indeterminate nodules. Benign call rate was 69.8% for all nodules, and 75.7% for indeterminate nodules. In four nodules, additional TP53 (in addition to BRAF or EZH1) or PIK3CA (in addition to BRAF or TERT) mutations were co-detected. Sensitivity, specificity, positive predictive value, and negative predictive value were 80.0%, 53.3%, 88.1%, 38.1% for all nodules, and 78.6%, 45.5%, 64.7%, 62.5% for indeterminate nodules, respectively. Panel group exhibited lower surgical resection rates than the control group for all nodules (27.0% vs. 52.5%, P<0.001), and indeterminate nodules (23.5% vs. 68.2%, P<0.001). Malignancy risk was significantly different between the panel and control groups (81.5% vs. 63.9%, P=0.008) for all nodules. Conclusion Our panel aids in managing thyroid nodules by providing information on malignancy risk based on mutations, potentially reducing unnecessary surgery in benign nodules or patients with less aggressive malignancies.