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1.
Hum Reprod ; 30(6): 1437-46, 2015 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-25801499

RESUMO

STUDY QUESTION: What is the effect of different alkylating agents used without pelvic radiation to treat childhood cancer in girls on the ovarian reserve in survivors? SUMMARY ANSWER: Ovarian reserve seems to be particularly reduced in survivors who received procarbazine (in most cases for Hodgkin lymphoma) or high-dose chemotherapy; procarbazine but not cyclophosphamide dose is associated with diminished ovarian reserve. WHAT IS KNOWN ALREADY: A few studies have demonstrated diminished ovarian reserve in survivors after various combination therapies, but the individual role of each treatment is difficult to assess. STUDY DESIGN: Prospective cross-sectional study, involving 105 survivors and 20 controls. PARTICIPANTS/MATERIALS, SETTING, METHODS: One hundred and five survivors aged 17-40 years and 20 controls investigated on Days 2-5 of a menstrual cycle or Day 7 of an oral contraceptive pill-free interval. MAIN OUTCOME MEASURES: ovarian surface area (OS), total number of antral follicles (AFC), serum levels of follicle-stimulating hormone (FSH), luteinizing hormone (LH), estradiol and anti-Müllerian hormone (AMH). MAIN RESULTS AND THE ROLE OF CHANCE: Survivors had a lower OS than controls: 3.5 versus 4.4 cm(2) per ovary (P = 0.0004), and lower AMH levels: 10.7 versus 22 pmol/l (P = 0.003). Ovarian markers (OS, AMH, AFC) were worse in patients who received high-dose compared with conventional-dose alkylating agents (P = 0.01 for OS, P = 0.002 for AMH, P < 0.0001 for AFC). Hodgkin lymphoma survivors seemed to have a greater reduction in ovarian reserve than survivors of leukaemia (P = 0.04 for AMH, P = 0.01 for AFC), sarcoma (P = 0.04 for AMH, P = 0.04 for AFC) and other lymphomas (P = 0.04 for AFC). A multiple linear regression analysis showed that procarbazine but not cyclophosphamide nor ifosfamide dose was associated with reduced OS (P = 0.0003), AFC (P = 0.0007), AMH (P < 0.0001) and higher FSH levels (P < 0.0001). LIMITATIONS, REASONS FOR CAUTION: The small percentage of participating survivors (28%) from the total cohort does not allow conclusion on fertility issues because of possible response bias. The association between procarbazine and HL makes it impossible to dissociate their individual impacts on ovarian reserve. The number of controls is small, but ovarian volume and AMH levels in survivors were compared with published normal values and results were unchanged. WIDER IMPLICATIONS OF THE FINDINGS: Early detection and follow-up of compromised ovarian function after cancer therapy should help physicians to counsel young survivors about their fertility window. However, longitudinal follow-up is required to determine the rate of progression from low ovarian reserve to premature ovarian failure. STUDY FUNDING/COMPETING INTERESTS: La Ligue contre le Cancer (grant no., PRAYN7497). The authors have no competing interests to disclose.


Assuntos
Antineoplásicos Alquilantes/efeitos adversos , Doença de Hodgkin/tratamento farmacológico , Reserva Ovariana/efeitos dos fármacos , Procarbazina/efeitos adversos , Adolescente , Adulto , Hormônio Antimülleriano/sangue , Antineoplásicos Alquilantes/uso terapêutico , Estudos Transversais , Estradiol/sangue , Feminino , Hormônio Foliculoestimulante/sangue , Humanos , Modelos Lineares , Hormônio Luteinizante/sangue , Ovário/diagnóstico por imagem , Ovário/efeitos dos fármacos , Procarbazina/uso terapêutico , Estudos Prospectivos , Sobreviventes , Ultrassonografia
2.
Nucleic Acid Ther ; 34(2): 90-99, 2024 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-38215303

RESUMO

RNA interference (RNAi)-based therapeutics hold the potential for dominant genetic disorders, enabling sequence-specific inhibition of pathogenic gene products. We aimed to direct RNAi for the selective suppression of the heterozygous GNAO1 c.607 G > A variant causing GNAO1 encephalopathy. By screening short interfering RNA (siRNA), we showed that GNAO1 c.607G>A is a druggable target for RNAi. The si1488 candidate achieved at least twofold allelic discrimination and downregulated mutant protein to 35%. We created vectorized RNAi by incorporating the si1488 sequence into the short hairpin RNA (shRNA) in the adeno-associated virus (AAV) vector. The shRNA stem and loop were modified to improve the transcription, processing, and guide strand selection. All tested shRNA constructs demonstrated selectivity toward mutant GNAO1, while tweaking hairpin structure only marginally affected the silencing efficiency. The selectivity of shRNA-mediated silencing was confirmed in the context of AAV vector transduction. To conclude, RNAi effectors ranging from siRNA to AAV-RNAi achieve suppression of the pathogenic GNAO1 c.607G>A and discriminate alleles by the single-nucleotide substitution. For gene therapy development, it is crucial to demonstrate the benefit of these RNAi effectors in patient-specific neurons and animal models of the GNAO1 encephalopathy.


Assuntos
Encefalopatias , Terapia Genética , Animais , Humanos , Interferência de RNA , RNA Interferente Pequeno/farmacologia , Alelos , Encefalopatias/genética , Vetores Genéticos/genética , Subunidades alfa Gi-Go de Proteínas de Ligação ao GTP/genética
3.
AI Ethics ; 2(4): 713-725, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-35043105

RESUMO

The paper suggests that AI ethics should pay attention to morally relevant systemic effects of AI use. It draws the attention of ethicists and practitioners to systemic risks that have been neglected so far in professional AI-related codes of conduct, industrial standards and ethical discussions more generally. The paper uses the financial industry as an example to ask: how can AI-enhanced systemic risks be ethically accounted for? Which specific issues does AI use raise for ethics that takes systemic effects into account? The paper (1) relates the literature about AI ethics to the ethics of systemic risks to clarify the moral relevance of AI use with respect to the imposition of systemic risks, (2) proposes a theoretical framework based on the ethics of complexity and (3) applies this framework to discuss implications for AI ethics concerned with AI-enhanced systemic risks.

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