OBJECTIVE: To measure Irish opinion on a range of assisted human reproduction (AHR) treatments. METHODS: A nationally representative sample of Irish adults (n=1,003) were anonymously sampled by telephone survey. RESULTS: Most participants (77%) agreed that any fertility services offered internationally should also be available in Ireland, although only a small minority of the general Irish population had personal familiarity with AHR or infertility. This sample finds substantial agreement (63%) that the Government of Ireland should introduce legislation covering AHR. The range of support for gamete donation in Ireland ranged from 53% to 83%, depending on how donor privacy and disclosure policies are presented. For example, donation where the donor agrees to be contacted by the child born following donation, and anonymous donation where donor privacy is completely protected by law were supported by 68% and 66%, respectively. The least popular (53%) donor gamete treatment type appeared to be donation where the donor consents to be involved in the future life of any child born as a result of donor fertility treatment. Respondents in social class ABC1 (58%), age 18 to 24 (62%), age 25 to 34 (60%), or without children (61%) were more likely to favour this donor treatment policy in our sample. CONCLUSION: This is the first nationwide assessment of Irish public opinion on the advanced reproductive technologies since 2005. Access to a wide range of AHR treatment was supported by all subgroups studied. Public opinion concerning specific types of AHR treatment varied, yet general support for the need for national AHR legislation was reported by 63% of this national sample. Contemporary views on AHR remain largely consistent with the Commission for Assisted Human Reproduction recommendations from 2005, although further research is needed to clarify exactly how popular opinion on these issues has changed. It appears that legislation allowing for the full range of donation options (and not mandating disclosure of donor identity at a stipulated age) would better align with current Irish public opinion.
Adult ; Anonyms and Pseudonyms ; Child ; Surveys and Questionnaires ; Disclosure ; Fertility ; Fertilization in Vitro ; Humans* ; Infertility ; Ireland ; Jurisprudence ; Privacy ; Public Opinion* ; Public Policy ; Recognition (Psychology) ; Reproduction* ; Reproductive Techniques ; Social Class ; Telephone ; Tissue Donors

OBJECTIVE: During IVF, non-transferred embryos are usually selected for cryopreservation on the basis of morphological criteria. This investigation evaluated an application for array comparative genomic hybridization (aCGH) in assessment of surplus embryos prior to cryopreservation. METHODS: First-time IVF patients undergoing elective single embryo transfer and having at least one extra non-transferred embryo suitable for cryopreservation were offered enrollment in the study. Patients were randomized into two groups: Patients in group A (n=55) had embryos assessed first by morphology and then by aCGH, performed on cells obtained from trophectoderm biopsy on post-fertilization day 5. Only euploid embryos were designated for cryopreservation. Patients in group B (n=48) had embryos assessed by morphology alone, with only good morphology embryos considered suitable for cryopreservation. RESULTS: Among biopsied embryos in group A (n=425), euploidy was confirmed in 226 (53.1%). After fresh single embryo transfer, 64 (28.3%) surplus euploid embryos were cryopreserved for 51 patients (92.7%). In group B, 389 good morphology blastocysts were identified and a single top quality blastocyst was selected for fresh transfer. All group B patients (48/48) had at least one blastocyst remaining for cryopreservation. A total of 157 (40.4%) blastocysts were frozen in this group, a significantly larger proportion than was cryopreserved in group A (p=0.017, by chi-squared analysis). CONCLUSION: While aCGH and subsequent frozen embryo transfer are currently used to screen embryos, this is the first investigation to quantify the impact of aCGH specifically on embryo cryopreservation. Incorporation of aCGH screening significantly reduced the total number of cryopreserved blastocysts compared to when suitability for freezing was determined by morphology only. IVF patients should be counseled that the benefits of aCGH screening will likely come at the cost of sharply limiting the number of surplus embryos available for cryopreservation.
Biopsy ; Blastocyst ; Comparative Genomic Hybridization ; Cryopreservation ; Embryo Transfer ; Embryonic Structures ; Fertilization in Vitro ; Freezing ; Humans ; Mass Screening ; Preimplantation Diagnosis ; Single Embryo Transfer

Background: and Purpose Infarcts in acute ischemic stroke (AIS) patients may continue to grow even after reperfusion, due to mechanisms such as microvascular obstruction and reperfusion injury. We investigated whether and how much infarcts grow in AIS patients after near-complete (expanded Thrombolysis in Cerebral Infarction [eTICI] 2c/3) reperfusion following endovascular treatment (EVT), and to assess the association of post-reperfusion infarct growth with clinical outcomes. Methods: Data are from a single-center retrospective observational cohort study that included AIS patients undergoing EVT with near-complete reperfusion who received diffusion-weighted magnetic resonance imaging (MRI) within 2 hours post-EVT and 24 hours after EVT. Association of infarct growth between 2 and 24 hours post-EVT and 24-hour National Institutes of Health Stroke Scale (NIHSS) as well as 90-day modified Rankin Scale score was assessed using multivariable logistic regression. Results: Ninety-four of 155 (60.6%) patients achieved eTICI 2c/3 and were included in the analysis. Eighty of these 94 (85.1%) patients showed infarct growth between 2 and 24 hours post-reperfusion. Infarct growth ≥5 mL was seen in 39/94 (41.5%) patients, and infarct growth ≥10 mL was seen in 20/94 (21.3%) patients. Median infarct growth between 2 and 24 hours post-reperfusion was 4.5 mL (interquartile range: 0.4–9.2 mL). Post-reperfusion infarct growth was associated with the 24-hour NIHSS in multivariable analysis (odds ratio: 1.16 [95% confidence interval 1.09–1.24], P<0.01). Conclusion Infarcts continue to grow after EVT, even if near-complete reperfusion is achieved. Investigating the underlying mechanisms may inform future therapeutic approaches for mitigating the process and help improve patient outcome.

Objective: To develop a machine learning (ML) pipeline based on radiomics to predict Coronavirus Disease 2019 (COVID-19) severity and the future deterioration to critical illness using CT and clinical variables. Materials and Methods: Clinical data were collected from 981 patients from a multi-institutional international cohort with real-time polymerase chain reaction-confirmed COVID-19. Radiomics features were extracted from chest CT of the patients. The data of the cohort were randomly divided into training, validation, and test sets using a 7:1:2 ratio. A ML pipeline consisting of a model to predict severity and time-to-event model to predict progression to critical illness were trained on radiomics features and clinical variables. The receiver operating characteristic area under the curve (ROC-AUC), concordance index (C-index), and time-dependent ROC-AUC were calculated to determine model performance, which was compared with consensus CT severity scores obtained by visual interpretation by radiologists. Results: Among 981 patients with confirmed COVID-19, 274 patients developed critical illness. Radiomics features and clinical variables resulted in the best performance for the prediction of disease severity with a highest test ROC-AUC of 0.76 compared with 0.70 (0.76 vs. 0.70, p = 0.023) for visual CT severity score and clinical variables. The progression prediction model achieved a test C-index of 0.868 when it was based on the combination of CT radiomics and clinical variables compared with 0.767 when based on CT radiomics features alone (p < 0.001), 0.847 when based on clinical variables alone (p = 0.110), and 0.860 when based on the combination of visual CT severity scores and clinical variables (p = 0.549). Furthermore, the model based on the combination of CT radiomics and clinical variables achieved time-dependent ROC-AUCs of 0.897, 0.933, and 0.927 for the prediction of progression risks at 3, 5 and 7 days, respectively. Conclusion CT radiomics features combined with clinical variables were predictive of COVID-19 severity and progression to critical illness with fairly high accuracy.

Objective: To develop a machine learning (ML) pipeline based on radiomics to predict Coronavirus Disease 2019 (COVID-19) severity and the future deterioration to critical illness using CT and clinical variables. Materials and Methods: Clinical data were collected from 981 patients from a multi-institutional international cohort with real-time polymerase chain reaction-confirmed COVID-19. Radiomics features were extracted from chest CT of the patients. The data of the cohort were randomly divided into training, validation, and test sets using a 7:1:2 ratio. A ML pipeline consisting of a model to predict severity and time-to-event model to predict progression to critical illness were trained on radiomics features and clinical variables. The receiver operating characteristic area under the curve (ROC-AUC), concordance index (C-index), and time-dependent ROC-AUC were calculated to determine model performance, which was compared with consensus CT severity scores obtained by visual interpretation by radiologists. Results: Among 981 patients with confirmed COVID-19, 274 patients developed critical illness. Radiomics features and clinical variables resulted in the best performance for the prediction of disease severity with a highest test ROC-AUC of 0.76 compared with 0.70 (0.76 vs. 0.70, p = 0.023) for visual CT severity score and clinical variables. The progression prediction model achieved a test C-index of 0.868 when it was based on the combination of CT radiomics and clinical variables compared with 0.767 when based on CT radiomics features alone (p < 0.001), 0.847 when based on clinical variables alone (p = 0.110), and 0.860 when based on the combination of visual CT severity scores and clinical variables (p = 0.549). Furthermore, the model based on the combination of CT radiomics and clinical variables achieved time-dependent ROC-AUCs of 0.897, 0.933, and 0.927 for the prediction of progression risks at 3, 5 and 7 days, respectively. Conclusion CT radiomics features combined with clinical variables were predictive of COVID-19 severity and progression to critical illness with fairly high accuracy.

BackgroundOur previous studies have shown that Tongxinluo (TXL), a compound Chinese medicine, can decrease myocardial ischemia-reperfusion injury, protect capillary endothelium function, and lessen cardiac ventricle reconstitution in animal models. The aim of this study was to illuminate whether TXL can improve hypercholesterolemia-impaired heart function by protecting artery endothelial function and increasing microvascular density (MVD) in heart. Furthermore, we will explore the underlying molecular mechanism of TXL cardiovascular protection.

MethodsAfter intragastric administration of TXL (0.1 ml/10 g body weight) to C57BL/6J wild-type mice (n = 8) and ApoE-/- mice (n = 8), total cholesterol, high-density lipoprotein-cholesterol, very-low-density lipoprotein (VLDL)-cholesterol, triglyceride, and blood glucose levels in serum were measured. The parameters of heart rate (HR), left ventricular diastolic end diameter, and left ventricular systolic end diameter were harvested by ultrasonic cardiogram. The left ventricular ejection fraction, stroke volume, cardiac output, and left ventricular fractional shortening were calculated. Meanwhile, aorta peak systolic flow velocity (PSV), end diastolic flow velocity, and mean flow velocity (MFV) were measured. The pulsatility index (PI) and resistant index were calculated in order to evaluate the vascular elasticity and resistance. The endothelium-dependent vasodilatation was evaluated by relaxation of aortic rings in response to acetylcholine. Western blotting and real-time quantitative reverse transcription polymerase chain reaction were performed for protein and gene analyses of vascular endothelial growth factor (VEGF). Immunohistochemical detection was performed for myocardial CD34 expression. Data in this study were compared by one-way analysis of variance between groups. A value of P < 0.05 was considered statistically significant.

ResultsAlthough there was no significant decrease of cholesterol level (F = 2.300, P = 0.240), TXL inhibited the level of triglyceride and VLDL (F = 9.209, P = 0.024 and F = 9.786, P = 0.020, respectively) in ApoE-/- mice. TXL improved heart function of ApoE-/- mice owing to the elevations of LVEF, SV, CO, and LVFS (all P < 0.05). TXL enhanced aortic PSV and MFV (F = 10.774, P = 0.024 and F = 11.354, P = 0.020, respectively) and reduced PI of ApoE-/- mice (1.41 ± 0.17 vs. 1.60 ± 0.17; P = 0.037). After incubation with 10 μmol/L acetylcholine, the ApoE-/- mice treated with TXL aortic segment relaxed by 44% ± 3%, significantly higher than control group mice (F = 9.280, P = 0.040). TXL also restrain the angiogenesis of ApoE-/- mice aorta (F = 21.223, P = 0.010). Compared with C57BL/6J mice, the MVD was decreased in heart tissue of untreated ApoE-/- mice (54.0 ± 3.0/mmvs. 75.0 ± 2.0/mm; F = 16.054, P = 0.010). However, TXL could significantly enhance MVD (65.0 ± 5.0/mmvs. 54.0 ± 3.0/mm; F = 11.929, P = 0.020) in treated ApoE-/- mice. In addition, TXL obviously increased the expression of VEGF protein determined by Western blot (F = 20.247, P = 0.004).

ConclusionsTXL obviously improves the ApoE-/- mouse heart function from different pathways, including reduces blood fat to lessen atherosclerosis; enhances aortic impulsivity, blood supply capacity, and vessel elasticity; improves endothelium-dependent vasodilatation; restraines angiogenesis of aorta-contained plaque; and enhances MVD of heart. The molecular mechanism of MVD enhancement maybe relate with increased VEGF expression.