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PurposeTo develop a predictive model using machine learning for levothyroxine (L-T4) dose selection in patients with differentiated thyroid cancer (DTC) after resection and radioactive iodine (RAI) therapy and to prospectively validate the accuracy of the model in two institutions.MethodsA total of 266 DTC patients who received RAI therapy after thyroidectomy and achieved target thyroid stimulating hormone (TSH) level were included in this retrospective study. Sixteen clinical and biochemical characteristics that could potentially influence the L-T4 dose were collected; Significant features correlated with L-T4 dose were selected using machine learning random forest method, and a total of eight regression models were established to assess their performance in prediction of L-T4 dose after RAI therapy; The optimal model was validated through a two-center prospective study (n=263).ResultsSix significant clinical and biochemical features were selected, including body surface area (BSA), weight, hemoglobin (HB), height, body mass index (BMI), and age. Cross-validation showed that the support vector regression (SVR) model was with the highest accuracy (53.4%) for prediction of L-T4 dose among the established eight models. In the two-center prospective validation study, a total of 263 patients were included. The TSH targeting rate based on constructed SVR model were dramatically higher than that based on empirical administration (Rate 1 (first rate): 52.09% (137/263) vs 10.53% (28/266); Rate 2 (cumulative rate): 85.55% (225/263) vs 53.38% (142/266)). Furthermore, the model significantly shortens the time (days) to achieve target TSH level (62.61 ± 58.78 vs 115.50 ± 71.40).ConclusionsThe constructed SVR model can effectively predict the L-T4 dose for postoperative DTC after RAI therapy, thus shortening the time to achieve TSH target level and improving the quality of life for DTC patients.

IntroductionThe impact of stress on reproductive function is significant. Hypothalamic paraventricular nucleus (PVN) corticotrophin-releasing hormone (CRH) plays a major role in regulating the stress response. Understanding how the hypothalamic-pituitary-adrenal (HPA) axis and the hypothalamic-pituitary-gonadal (HPG) axis interact is crucial for comprehending how stress can lead to reproductive dysfunction. However, whether stress influences reproductive function via modulating PVN CRH or HPA sequelae is not fully elucidated.MethodsIn this study, we investigated the impact of chemogenetic activation of PVN CRH neurons on reproductive function. We chronically and selectively stimulated PVN CRH neurons in female CRH-Cre mice using excitatory designer receptor exclusively activated by designer drugs (DREADDs) viral constructs, which were bilaterally injected into the PVN. The agonist compound-21 (C21) was delivered through the drinking water. We determined the effects of DREADDs activation of PVN CRH neurons on the estrous cycles, LH pulse frequency in diestrus and metestrus and LH surge in proestrus mice. The effect of long-term C21 administration on basal corticosterone secretion and the response to acute restraint stress during metestrus was also examined. Additionally, computer simulations of a mathematical model were used to determine the effects of DREADDs activation of PVN CRH neurons, simulating chronic stress, on the physiological parameters examined experimentally.ResultsAs a result, and consistent with our mathematical model predictions, the length of the estrous cycle was extended, with an increase in the time spent in estrus and metestrus, and a decrease in proestrus and diestrus. Additionally, the frequency of LH pulses during metestrus was decreased, but unaffected during diestrus. The occurrence of the preovulatory LH surge during proestrus was disrupted. The basal level of corticosterone during metestrus was not affected, but the response to acute restraint stress was diminished after long-term C21 application.DiscussionThese data suggest that PVN CRH neurons play a functional role in disrupting ovarian cyclicity and the preovulatory LH surge, and that the activity of the GnRH pulse generator remains relatively robust during diestrus but not during metestrus under chronic stress exposure in accordance with our mathematical model predictions.

ObjectiveThis study aimed to explore the relationship between the plasma metabolites of adolescent obesity and hypertension and whether metabolite alterations had a mediating effort between adolescent obesity and hypertension.MethodsWe applied untargeted ultra-performance liquid chromatography–mass spectrometry (UPLC-MS) to detect the plasma metabolomic profiles of 105 adolescents. All participants were selected randomly based on a previous cross-sectional study. An orthogonal partial least squares- discriminant analysis (OPLS-DA), followed by univariate statistics and enrichment analysis, was used to identify differential metabolites. Using logistic regression for variable selection, an obesity-related metabolite score (OMS, OMS=∑k=1nβnmetabolite n) was constructed from the metabolites identified, and hypertension risk was estimated.ResultsIn our study, based on P< 0.05, variable importance in projection (VIP) > 1.0, and impact value > 0.1, we identified a total of 12 differential metabolites. Significantly altered metabolic pathways were the sphingolipid metabolism, purine metabolism, pyrimidine metabolism, phospholipid metabolism, steroid hormone biosynthesis, tryptophan, tyrosine, and phenylalanine biosynthesis. The logistic regression selection resulted in a four-metabolite score (thymidine, sphingomyelin (SM) d40:1, 4-hydroxyestradiol, and L-lysinamide), which was positively associated with hypertension risk (odds ratio: 7.79; 95% confidence interval: 2.13, 28.47; for the quintile 4 compared with quartile 1 of OMS) after multivariable adjustment.ConclusionsThe OMS constructed from four differential metabolites was used to predict the risk of hypertension in adolescents. These findings could provide sensitive biomarkers for the early recognition of hypertension in adolescents with obesity.

BackgroundThe association between serum cystatin C levels and obesity has not been fully explored in adolescents. This study aimed to explore the association between serum cystatin C levels and obesity in adolescents of different sexes.MethodsWe conducted a cross-sectional study including 481 adolescents aged 14−17 years. Cystatin C level was measured by immunoassay. Health examinations data, biochemical parameters, and questionnaire information were collected. The restricted cubic spline model analyzed the association between cystatin C levels and obesity in boys and girls.ResultsBoys exhibited significantly higher cystatin C levels than girls, with a mean level of 0.97 ± 0.10 mg/L in boys and 0.86 ± 0.09 mg/L in girls (P < 0.001). The restricted cubic spline model suggested that low or high cystatin C levels were associated with an increased risk of obesity in boys, whereas only higher cystatin C levels were associated with an increased risk of obesity in girls.ConclusionsA U-shaped correlation was observed between serum cystatin C levels and the risk of obesity in boys. However, in girls, the risk of obesity showed a trend of initially increase and then decrease with increasing cystatin C levels. Longitudinal studies should be conducted to further investigate the diagnostic potential of cystatin C in the progression of early obesity in adolescents of different sexes.

Traditionally, the anteroventral periventricular (AVPV) nucleus has been the brain area associated with luteinizing hormone (LH) surge secretion in rodents. However, the role of the other population of hypothalamic kisspeptin neurons, in the arcuate nucleus (ARC), has been less well characterized with respect to surge generation. Previous experiments have demonstrated ARC kisspeptin knockdown reduced the amplitude of LH surges, indicating that they have a role in surge amplification. The present study used an optogenetic approach to selectively stimulate ARC kisspeptin neurons and examine the effect on LH surges in mice with different hormonal administrations. LH level was monitored from 13:00 to 21:00 h, at 30-minute intervals. Intact Kiss-Cre female mice showed increased LH secretion during the stimulation period in addition to displaying a spontaneous LH surge around the time of lights off. In ovariectomized Kiss-Cre mice, optogenetic stimulation was followed by a surge-like secretion of LH immediately after the stimulation period. Ovariectomized Kiss-Cre mice with a low dose of 17β-estradiol (OVX+E) replacement displayed a surge-like increase in LH release during period of optic stimulation. No LH response to the optic stimulation was observed in OVX+E mice on the day of estradiol benzoate (EB) treatment (day 1). However, after administration of progesterone (day 2), all OVX+E+EB+P mice exhibited an LH surge during optic stimulation. A spontaneous LH surge also occurred in these mice at the expected time. Taken together, these results help to affirm the fact that ARC kisspeptin may have a novel amplificatory role in LH surge production, which is dependent on the gonadal steroid milieu.