Covid-19 and maternal and perinatal outcomes

Background: Alveolar capillary dysplasia with or without misalignment of the pulmonary veins (ACD/MPV) is a lethal congenital lung disorder associated with a variety of heterozygous genomic alterations in the FOXF1 gene or its 60 kb enhancer. Cases without a genomic alteration in the FOXF1 locus have been described as well. The mechanisms responsible for FOXF1 haploinsufficiency and the cause of ACD/MPV in patients without a genomic FOXF1 variant are poorly understood, complicating the search for potential therapeutic targets for ACD/MPV. To investigate the contribution of aberrant DNA methylation, genome wide methylation patterns of ACD/MPV lung tissues were compared with methylation patterns of control lung tissues using the recently developed technique Methylated DNA sequencing (MeD-seq). Results: Eight ACD/MPV lung tissue samples and three control samples were sequenced and their mutual comparison resulted in identification of 319 differentially methylated regions (DMRs) genome wide, involving 115 protein coding genes. The potentially upregulated genes were significantly enriched in developmental signalling pathways, whereas potentially downregulated genes were mainly enriched in O-linked glycosylation. In patients with a large maternal deletion encompassing the 60 kb FOXF1 enhancer, DNA methylation patterns in this FOXF1 enhancer were not significantly different compared to controls. However, two hypermethylated regions were detected in the 60 kb FOXF1 enhancer of patients harbouring a FOXF1 point mutation. Lastly, a large hypermethylated region overlapping the first FOXF1 exon was found in one of the ACD/MPV patients without a known pathogenic FOXF1 variation. Conclusion: This is the first study providing genome wide methylation data on lung tissue of ACD/MPV patients. DNA methylation analyses in the FOXF1 locus excludes maternal imprinting of the 60 kb FOXF1 enhancer. Hypermethylation at the 60 kb FOXF1 enhancer might contribute to FOXF1 haploinsufficiency caused by heterozygous mutations in the FOXF1 coding region. Interestingly, DNA methylation analyses of patients without a genomic FOXF1 variant suggest that abnormal hypermethylation of exon 1 might play a role in some ACD/MPV in patients.</p

The prevalence and severity of fatigue in meningioma patients and its association with patient-, tumor-and treatment-related factors

Background: Fatigue is a commonly reported and severe symptom in primary brain tumor patients, but the exact occurrence in meningioma patients is unknown. This study aimed to determine the frequency and severity of fatigue in meningioma patients as well as associations between the level of fatigue and patient-, tumor-, and treatment-related factors. Methods: In this multicenter cross-sectional study, meningioma patients completed questionnaires on fatigue (MFI-20), sleep (PSQI), anxiety and depression (HADS), tumor-related symptoms (MDASI-BT), and cognitive functioning (MOS-CFS). Multivariable regression models were used to evaluate the independent association between fatigue and each patient-, tumor-, and treatment-related factor separately, corrected for relevant confounders. Results: Based on predetermined in-and exclusion criteria, 275 patients, on average 5.3 (SDa=a2.0) year since diagnosis, were recruited. Most patients had undergone resection (92%). Meningioma patients reported higher scores on all fatigue subscales compared to normative data and 26% were classified as fatigued. Having experienced a complication due to resection (OR 3.6, 95% CI: 1.8-7.0), having received radiotherapy (OR 2.4, 95% CI: 1.2-4.8), a higher number of comorbidities (OR 1.6, 95% CI: 1.3-1.9) and lower educational level (low level as reference; high level OR 0.3, 95% CI: 0.2-0.7) were independently associated with more fatigue. Conclusions: Fatigue is a frequent problem in meningioma patients even many years after treatment. Both patient-and treatment-related factors were determinants of fatigue, with the treatment-related factors being the most likely target for intervention in this patient population.</p

Future and potential spending on health 2015-40: Development assistance for health, and government, prepaid private, and out-of-pocket health spending in 184 countries

Background: The amount of resources, particularly prepaid resources, available for health can affect access to health care and health outcomes. Although health spending tends to increase with economic development, tremendous variation exists among health financing systems. Estimates of future spending can be beneficial for policy makers and planners, and can identify financing gaps. In this study, we estimate future gross domestic product (GDP), all-sector government spending, and health spending disaggregated by source, and we compare expected future spending to potential future spending. Methods: We extracted GDP, government spending in 184 countries from 1980-2015, and health spend data from 1995-2014. We used a series of ensemble models to estimate future GDP, all-sector government spending, development assistance for health, and government, out-of-pocket, and prepaid private health spending through 2040. We used frontier analyses to identify patterns exhibited by the countries that dedicate the most funding to health, and used these frontiers to estimate potential health spending for each low-income or middle-income country. All estimates are inflation and purchasing power adjusted. Findings: We estimated that global spending on health will increase from US$9.21 trillion in 2014 to$24.24 trillion (uncertainty interval [UI] 20.47-29.72) in 2040. We expect per capita health spending to increase fastest in upper-middle-income countries, at 5.3% (UI 4.1-6.8) per year. This growth is driven by continued growth in GDP, government spending, and government health spending. Lower-middle income countries are expected to grow at 4.2% (3.8-4.9). High-income countries are expected to grow at 2.1% (UI 1.8-2.4) and low-income countries are expected to grow at 1.8% (1.0-2.8). Despite this growth, health spending per capita in low-income countries is expected to remain low, at $154 (UI 133-181) per capita in 2030 and$195 (157-258) per capita in 2040. Increases in national health spending to reach the level of the countries who spend the most on health, relative to their level of economic development, would mean $321 (157-258) per capita was available for health in 2040 in low-income countries. Interpretation: Health spending is associated with economic development but past trends and relationships suggest that spending will remain variable, and low in some low-resource settings. Policy change could lead to increased health spending, although for the poorest countries external support might remain essential

Biowaiver monographs for immediate release solid oral dosage forms: Ciprofloxacin hydrochloride

Literature data relevant to the decision to allow a waiver of in vivo bioequivalence (BE) testing for the approval of new multisource and reformulated immediate release (IR) solid oral dosage forms containing ciprofloxacin hydrochloride as the only active pharmaceutical ingredient (API) are reviewed. Ciprofloxacin hydrochloride's solubility and permeability, its therapeutic use and index, pharmacokinetics, excipient interactions and reported BE/bioavailability (BA) problems were taken into consideration. Solubility and BA data indicate that ciprofloxacin hydrochloride is a BCS Class IV drug. Therefore, a biowaiver based approval of ciprofloxacin hydrochloride containing IR solid oral dosage forms cannot be recommended for either new multisource drug products or for major scale-up and postapproval changes (variations) to existing drug products.Fil: Olivera, Maria Eugenia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; Argentina. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Departamento de Farmacia; ArgentinaFil: Manzo, Ruben Hilario. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; Argentina. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Departamento de Farmacia; ArgentinaFil: Junginger, H. E.. Naresuan University; TailandiaFil: Midha, K. K.. University of Saskatchewan; CanadáFil: Shah, V. P.. International Pharmaceutical Federation; Países BajosFil: Stavchansky, S. University of Texas at Austin. Oden Institute for Computational Engineering and Sciences; Estados UnidosFil: Dressman, J.B.. Goethe Universitat Frankfurt; AlemaniaFil: D.M. Barends.. National Institute for Public Health and the Environment; Países Bajo