Reduced ovulation rate in adolescent girls born small for gestational age

FSH and insulin are key hormones involved in spontaneous ovulation. Adolescent girls born small for gestational age (SGA) are at risk for FSH and insulin resistance. We have assessed whether ovulation rate is reduced in SGA girls. Ovulatory function was assessed by weekly filter paper progesterone measurements, obtained by finger-stick auto-sampling for 3 consecutive months in matched populations of asymptomatic, nonobese girls (mean age, 15.5 yr; > or =3 yr postmenarche) who were either born with an appropriate weight for gestational age (AGA; n = 24; mean birthweight, 3.3 kg) or born small for gestational age (SGA; n = 25; mean birthweight, 2.3 kg). The prevalence of anovulation was higher among SGA than AGA girls (40% vs. 4%; P = 0.002). Moreover, in the relatively small fraction of ovulating SGA girls, the ovulation rate was lower than in AGA adolescents (average number of ovulations during the study, 1.4 vs. 1.9; P < 0.01). In conclusion, the endocrine correlates of prenatal growth restraint are herewith extended to include oligo-ovulation and anovulation in adolescence. It remains to be verified whether this SGA-related phenomenon persists into the reproductive age range. If it does, then fetal growth restraint may prove to be one of the enigmatic components underpinning hitherto unexplained female subfertility.     

CD34+-enriched-CD19+-depleted autologous peripheral blood stem cell transplantation for chronic lymphoproliferative disorders: high purging efficiency but increased risk of severe infections

OBJECTIVE: The main objective of this work was to decrease the incidence of relapse after autologous stem cell transplantation with a "double purging" procedure. METHODS: We used a "positive" (CD34) and "negative" (CD19) double selection method to improve the efficacy of "single purging" of hematopoietic harvests in poor-prognosis lymphoproliferative disorders. All patients included in the study had a positive molecular marker of their disease. Minimal residual disease (MRD) was studied by flow cytometry and PCR techniques during the purging procedure and after transplantation. RESULTS: Twenty-six patients fulfilled entry criteria. Median age of patients was 50 years (range: 33-66); 17 were male and 9 female. Thirteen (50%) of the patients mobilized an adequate number of CD34+ cells (>or=3 x 10(6)/kg) to proceed with the double-selection protocol. Twelve of the 13 harvests became PCR negative after purging. Ten patients were grafted with the selected products and all but one engrafted without delay. After a median follow-up of 30 months, 2 of 10 patients suffered a molecular relapse at 7 and 19 months respectively. The earlier relapse was observed in the patient who received a MRD+ product. Only one patient experienced a clinical relapse. Three patients died due to obliterans bronchiolitis, pneumococcal sepsis, and septic shock of unknown origin, respectively, and three others presented life-threatening infections. CONCLUSION: Therefore, CD34+/CD19+ positive/negative selection is an effective purging approach in patients with chronic lymphoproliferative disorders. This favorable effect is, however, counterbalanced by the high frequency of life-threatening infections.     

The case-fatality rate of meningococcal disease in Catalonia, 1990-1997

The objective was to analyse the case-fatality rate (CFR) of meningococcal disease (MD) in Catalonia, Spain. A retrospective study was carried out. Clinical histories of cases of MD reported for the period 1990-1997 in Catalonia were reviewed. For all cases, the variables gender, age, clinical type, y of presentation, province, phenotype and death by meningococcal disease were collected. The association between death and the other variables was studied by bivariate and unconditional logistic regression analysis. In the 2343 cases studied there were 146 deaths (6.2%) due to meningococcal disease. The CFR was higher in females (OR: 1.5, 95%CI: 1.1-2.1), in the 20 to 49 y (OR: 2.4, 95%CI: 1.2-4.9) and > or = 50 y (OR: 5.3, 95%CI: 2.8-10.1) age groups, in cases with septicaemia (OR: 2.4, 95%CI: 1.6-3.5), in the cases produced by serogroup A (OR: 4.7, 95%CI: 1.0-23.4) and in cases occurring during 1993 (OR: 2.1, 95%CI: 1.1-4.1) or in the province of Lleida (OR: 2.9, 95%CI: 1.2-7.2). In the multivariate analysis, death was associated with the 20-49 y age group (OR: 3.9, 95%CI: 1.8-8.4), the > or = 50 y age group (OR: 7.3, 95%CI: 3.6-14.7), septicaemia (OR: 3.1; 95%CI: 2.0-4.7) and residing in the province of Lleida (OR: 3.2; 95%CI: 1.2-8.5). The CFR of meningococcal disease in Catalonia was not associated with the emergent phenotype C:2b:P1.2,5 strain, which caused an outbreak in other regions of Spain.     

The p21(Cip1) protein, a cyclin inhibitor, regulates the levels and the intracellular localization of CDC25A in mice regenerating livers

Liver cells from p21(Cip1-/-) mice subjected to partial hepatectomy (PH) progress into DNA synthesis faster than those from wild-type mice. These cells also show a premature induction of cyclin E/cyclin-dependent kinase (CDK) 2 activity. We studied the mechanisms whereby cells lacking p21(Cip1) showed a premature induction of this activity. Whereas the levels of CDK2, cyclin E, and p27(Kip1) were similar in both wild-type and p21(Cip1-/-) mice, those of the activator CDC25A were much higher in p21(Cip1-/-) quiescent and regenerating livers than in wild-type animals. Moreover, p21(Cip1-/-) cells also showed a premature translocation of CDC25A from cytoplasm into the nucleus. The ectopic expression of p21(Cip1) into mice embryo fibroblasts from p21(Cip1-/-) mice decreased the levels of CDC25A and delayed its nuclear translocation. The levels of CDC25A messenger RNA in p21(Cip1-/-) cells were higher than in wild-type cells, suggesting that this increase might be responsible, at least in part, for the high levels of CDC25A protein in these cells. Thus, the results reported here indicate that p21(Cip1) regulates the levels and the intracellular localization of CDC25A. We also found a good correlation between CDC25A nuclear translocation and cyclin E/CDK2 activation. In conclusion, premature translocation of CDC25A to the nucleus might be involved in the advanced induction of cyclin E/CDK2 activity and DNA replication in cells from animals lacking p21(Cip1).     

The value of detecting surface and cytoplasmic antigens in acute myeloid leukaemia

The immunophenotype of leukaemia cells from 60 patients with acute myeloid leukaemia (AML) was analysed with the APAAP technique using a panel of anti-myeloid and lymphoid associated monoclonal antibodies (McAb). Cells from all cases, including three with negative cytochemical features, were labelled by at least one of the anti-myeloid McAb CD13, anti-myeloperoxidase (anti-Mpo), and/or CD14. The most sensitive marker was CD13, since it was positive in 90% of cases. In two out of three AML cases defined as M0-AML, CD13 was expressed in the cytoplasm but not on the membrane; in these three cases peroxidase (Mpo) was not detected by conventional cytochemistry, but could be demonstrated in all of them using the McAb anti-Mpo. The simultaneous expression of CD14 and CD68 McAb was often confined to the M4 and M5 FAB AML subtypes (92% cases) as compared to the others: M1, M2, M3 (18% cases). Lymphoid antigens were rarely positive (TdT+: 13%, CD7+: 15%, CD19+: 5%) and none of the AML cases were CD3+ or CD10+. By contrast, CD4 was expressed in blasts from 44% of cases and this was not restricted to AML with a monocytic component (M4, M5) but also found in other subtypes. There were no significant differences in the clinical or prognostic features according to the positivity or negativity with TdT and CD4. By contrast, expression of CD7 was associated with refractoriness to the treatment or short complete remission duration, although the number of patients is too small to draw firm conclusions. Our findings support the clinical and diagnostic relevance of immunophenotypic studies in AML.     

From the Cover: Monitoring war destruction from space using machine learning

Existing data on building destruction in conflict zones rely on eyewitness reports or manual detection, which makes it generally scarce, incomplete, and potentially biased. This lack of reliable data imposes severe limitations for media reporting, humanitarian relief efforts, human-rights monitoring, reconstruction initiatives, and academic studies of violent conflict. This article introduces an automated method of measuring destruction in high-resolution satellite images using deep-learning techniques combined with label augmentation and spatial and temporal smoothing, which exploit the underlying spatial and temporal structure of destruction. As a proof of concept, we apply this method to the Syrian civil war and reconstruct the evolution of damage in major cities across the country. Our approach allows generating destruction data with unprecedented scope, resolution, and frequency—and makes use of the ever-higher frequency at which satellite imagery becomes available.

Building destruction during war is a specific form of violence that is particularly harmful to civilians, commonly used to displace populations, and therefore warrants special attention. Yet, data from war-ridden areas are typically scarce, often incomplete, and highly contested, when available. The lack of such data from conflict zones severely limits media reporting, humanitarian relief efforts, human-rights monitoring, and reconstruction initiatives, as well as the study of violent conflict in academic research. A novel solution to this problem is to use remote sensing to identify destruction in satellite images (1–3). This approach is gaining momentum as high-resolution imagery is becoming readily available at ever-higher frequency, yielding weekly, or even daily, images. At the same time, recent methodological advances related to deep learning have provided sophisticated tools to extract data from these images (4–7).While seminal research has demonstrated the use of automated classifiers for destruction detection, practical applications have so far been hampered by severe problems with labeling, domain transfer, and class imbalance in real-world imagery from urban war zones. As a consequence, international organizations such as the United Nations, the World Bank, and Amnesty International use remote sensing with manual human classification to produce damage-assessment case studies (8–10). On the other hand, providers of conflict data for research purposes still rely heavily on news and eyewitness reports, which leads to large data-publishing lags and potential biases (11–17). An automated building-damage classifier for use with satellite imagery, which has a low rate of false positives in unbalanced samples and allows tracking on-the-ground destruction in close to real-time, would therefore be extremely valuable for the international community and academic researchers alike.In this article, we present a way of combining computer-vision techniques and publicly available high-resolution satellite images to produce building-destruction estimates that are of practical use to both practitioners and researchers. The standard architectures for this task are convolutional neural networks (CNNs),^* as they have achieved unprecedented success in large-scale visual image classification with error rates beating humans (18, 19). We train a CNN to spot destruction features from heavy weaponry attacks (i.e., artillery and bombing) in satellite images, such as the rubble from collapsed buildings or the presence of bomb craters.We make three relevant methodological contributions. First, we introduce a label-augmentation method for expanding destruction class labels by making reasonable assumptions about the data-generating process using contextual information. Second, we introduce a two-stage classification process to control for spatial and temporal noise where the results from the CNN are processed through a random-forest model that relies on spatial and temporal leads and lags to improve classification performance. Third, we apply our trained computer-vision model to repeated satellite images of the entire populated areas of major Syrian cities, including parks and highways, and produce longitudinal estimates of building destruction over the course of the recent civil war.We demonstrate that our method yields high performance in out-of-sample tests and validate its ability for destruction monitoring using a separate database of heavy weaponry attacks. Our results highlight the importance of repeated satellite imagery in combination with temporal filtering to improve monitoring performance. As a result, our approach can be applied to any populated area, provided that repeated, high-resolution (i.e., submeter) satellite imagery is available.     

Disease expression and molecular genotype in congenital adrenal hyperplasia due to 21-hydroxylase deficiency.

Genotyping for 10 mutations in the CYP21 gene was performed in 88 families with congenital adrenal hyperplasia due to 21-hydroxylase deficiency. Southern blot analysis was used to detect CYP21 deletions or large gene conversions, and allele-specific hybridizations were performed with DNA amplified by the polymerase chain reaction to detect smaller mutations. Mutations were detected on 95% of chromosomes examined. The most common mutations were an A----G change in the second intron affecting pre-mRNA splicing (26%), large deletions (21%), Ile-172----Asn (16%), and Val-281----Leu (11%). Patients were classified into three mutation groups based on degree of predicted enzymatic compromise. Mutation groups were correlated with clinical diagnosis and specific measures of in vivo 21-hydroxylase activity, such as 17-hydroxyprogesterone, aldosterone, and sodium balance. Mutation group A (no enzymatic activity) consisted principally of salt-wasting (severely affected) patients, group B (2% activity) of simple virilizing patients, and group C (10-20% activity) of nonclassic (mildly affected) patients, but each group contained patients with phenotypes either more or less severe than predicted. These data suggest that most but not all of the phenotypic variability in 21-hydroxylase deficiency results from allelic variation in CYP21. Accurate prenatal diagnosis should be possible in most cases using the described strategy.     

Isoxaben Soil Biodegradation in Pear Tree Orchard After Repeated High Dose Application

During the past nine years, each of the plots of a pear tree orchard were treated annually with the same herbicide treatment. The following herbicide treatments were compared, each being made by application of a mixture of two or three herbicides: 1a, no herbicide at all, weeds being hoed (control 1a); 2, diuron + paraquat 3 + 1 kg/ha; 3, simazine + paraquat 2 + 1 kg/ha; 4, isoxaben + diuron + paraquat 0.5 + 1.6 + 1 kg/ha; and 5, isoxaben + simazine + paraquat 0.5 + 1.25 + 1 kg/ha. In March 1996, one year after the final orchard herbicide treatment, isoxaben could not be detected in the soils of any field plots; isoxaben was incorporated at 0.74 mg/kg in the loamy soils sampled separately in each of the field plots, and the soils were incubated in the laboratory. Isoxaben soil half-lives were 92 days in the soils treated previously with herbicide treatments 1a, 2, or 3 and 42 days in the soils treated with herbicide treatments 4 and 5. The repeated isoxaben treatments applied in the past thus enhanced the isoxaben soil biodegradation; diuron, simazine, and paraquat had no influence on this rate enhancement. On the other hand, herbicide treatments 4 and 5 were applied in the orchard in April 1996 on the corresponding plots treated in this manner for the last nine years. Isoxaben + paraquat 0.5 + 1 kg/ha was applied simultaneously on other plots (control 1b) not treated in the past with isoxaben. During the growth season in the orchard, the isoxaben soil half-lives in the control plots 1b was 101 days, and 41 days in the plots where herbicide treatments 4 or 5 were applied. Received: 25 March 1997/Accepted: 15 July 1997