Vincenzo De Leo

Bio: Vincenzo De Leo is an academic researcher from University of Siena. The author has contributed to research in topics: Polycystic ovary & Insulin resistance. The author has an hindex of 33, co-authored 140 publications receiving 5001 citations. Previous affiliations of Vincenzo De Leo include University of Catania & University of Bari.

Wisdom of crowds for robust gene network inference

Abstract: Reconstructing gene regulatory networks from high-throughput data is a long-standing challenge. Through the Dialogue on Reverse Engineering Assessment and Methods (DREAM) project, we performed a comprehensive blind assessment of over 30 network inference methods on Escherichia coli, Staphylococcus aureus, Saccharomyces cerevisiae and in silico microarray data. We characterize the performance, data requirements and inherent biases of different inference approaches, and we provide guidelines for algorithm application and development. We observed that no single inference method performs optimally across all data sets. In contrast, integration of predictions from multiple inference methods shows robust and high performance across diverse data sets. We thereby constructed high-confidence networks for E. coli and S. aureus, each comprising ∼1,700 transcriptional interactions at a precision of ∼50%. We experimentally tested 53 previously unobserved regulatory interactions in E. coli, of which 23 (43%) were supported. Our results establish community-based methods as a powerful and robust tool for the inference of transcriptional gene regulatory networks.

Insulin-lowering agents in the management of polycystic ovary syndrome.

Abstract: Polycystic ovary syndrome (PCOS) is a medical condition that has brought multiple specialists together. Gynecologists, endocrinologists, cardiologists, pediatricians, and dermatologists are all concerned with PCOS patients and share research data and design clinical trials to learn more about the syndrome. Insulin resistance is a common feature of PCOS and is more marked in obese women, suggesting that PCOS and obesity have a synergistic effect on the magnitude of the insulin disorder. Hyperinsulinemia associated with insulin resistance has been causally linked to all features of the syndrome, such as hyperandrogenism, reproductive disorders, acne, hirsutism, and metabolic disturbances. Women with PCOS should be evaluated for cardiovascular risk factors, such as lipid profile and blood pressure. Modification of diet and lifestyle should be suggested to those who are obese. Several insulin-lowering agents have been tested in the management of PCOS. In particular, metformin is the only drug currently in widespread clinical use for treatment of PCOS. In a high percentage of patients, treatment with metformin is followed by regularization of menstrual cycle, reduction in hyperandrogenism and in cardiovascular risk factors, and improvement in response to therapies for induction of ovulation.

Insulin-dependent diabetes in men is associated with hypothalamo-pituitary derangement and with impairment in semen quality

Abstract: BACKGROUND: The objective of the study was to investigate the hypothalamo-pituitary–testicular axis and sperm structure at the transmission electron microscope (TEM) level in men affected by insulin-dependent diabetes. METHODS: Twenty-two diabetic men and 24 controls were recruited. GnRH (100 µg) was administered and FSHand LH-induced secretion was evaluated. Semen samples were collected and sperm concentration and motility were determined using a Makler chamber. Ejaculated sperm were fixed and observed with a TEM. RESULTS: The response of gonadotrophins to GnRH was significantly lower in diabetics than in control men. Sperm motility was also significantly lower. At the electron microscope level, sperm from diabetics exhibited a higher percentage of immaturity- and apoptosis-related defects than sperm from controls. CONCLUSIONS: The reduced response of gonadotrophins to GnRH in diabetic men may indicate a decreased acute releasable pool of pituitary gonadotrophins. The results of TEM examination showed that sperm from men with diabetes presented severe structural defects in comparison with sperm from controls. It is possible that the reproductive impairment recognized in men with diabetes could be the result of interference by the disease on the hypothalamo-pituitary–testicular axis at multiple levels, as indicated by the reduced gonadotrophin response to appropriate stimuli and by the abnormal ultrastructure of ejaculated sperm. The defective spermatogenesis may be the consequence of a direct testicular effect of the disease.

Hormonal effects of flutamide in young women with polycystic ovary syndrome

Abstract: Anovulation in women with polycystic ovary syndrome (PCOS) is the direct effect of high local androgen concentrations on the ovary. Antiandrogens are substances that prevent androgens from expressing their activity on target tissues. Flutamide is a nonsteroid antiandrogen that has been found effective in hirsute patients, although its mechanism of action is unclear. Eight girls, ranging in age from 16–19 yr, with moderate to severe hirsutism and menstrual irregularities were enrolled in this study. The basal hormonal pattern showed anovulatory cycles; increased concentrations of LH, androstenedione, and testosterone; and increased LH/FSH ratio. A baseline ultrasound scan revealed polycystic ovaries in all patients. All were given 250 mg flutamide twice a day for 6 months. LH, FSH, androstenedione, testosterone, estradiol, and progesterone were evaluated before treatment, every 4 days during the third month of treatment, and on day 24 of the sixth month of treatment. Hirsutism improved, androgen levels dro...

Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study

Abstract: Summary Background Since December, 2019, Wuhan, China, has experienced an outbreak of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Epidemiological and clinical characteristics of patients with COVID-19 have been reported but risk factors for mortality and a detailed clinical course of illness, including viral shedding, have not been well described. Methods In this retrospective, multicentre cohort study, we included all adult inpatients (≥18 years old) with laboratory-confirmed COVID-19 from Jinyintan Hospital and Wuhan Pulmonary Hospital (Wuhan, China) who had been discharged or had died by Jan 31, 2020. Demographic, clinical, treatment, and laboratory data, including serial samples for viral RNA detection, were extracted from electronic medical records and compared between survivors and non-survivors. We used univariable and multivariable logistic regression methods to explore the risk factors associated with in-hospital death. Findings 191 patients (135 from Jinyintan Hospital and 56 from Wuhan Pulmonary Hospital) were included in this study, of whom 137 were discharged and 54 died in hospital. 91 (48%) patients had a comorbidity, with hypertension being the most common (58 [30%] patients), followed by diabetes (36 [19%] patients) and coronary heart disease (15 [8%] patients). Multivariable regression showed increasing odds of in-hospital death associated with older age (odds ratio 1·10, 95% CI 1·03–1·17, per year increase; p=0·0043), higher Sequential Organ Failure Assessment (SOFA) score (5·65, 2·61–12·23; p Interpretation The potential risk factors of older age, high SOFA score, and d-dimer greater than 1 μg/mL could help clinicians to identify patients with poor prognosis at an early stage. Prolonged viral shedding provides the rationale for a strategy of isolation of infected patients and optimal antiviral interventions in the future. Funding Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences; National Science Grant for Distinguished Young Scholars; National Key Research and Development Program of China; The Beijing Science and Technology Project; and Major Projects of National Science and Technology on New Drug Creation and Development.

SCENIC: single-cell regulatory network inference and clustering.

Abstract: We present SCENIC, a computational method for simultaneous gene regulatory network reconstruction and cell-state identification from single-cell RNA-seq data (http://scenicaertslaborg) On a compendium of single-cell data from tumors and brain, we demonstrate that cis-regulatory analysis can be exploited to guide the identification of transcription factors and cell states SCENIC provides critical biological insights into the mechanisms driving cellular heterogeneity