Summary Background In November, 2015, an epidemic of microcephaly was reported in Brazil, which was later attributed to congenital Zika virus infection. 7830 suspected cases had been reported to the ...Brazilian Ministry of Health by June 4, 2016, but little is known about their characteristics. We aimed to describe these newborn babies in terms of clinical findings, anthropometry, and survival. Methods We reviewed all 1501 liveborn infants for whom investigation by medical teams at State level had been completed as of Feb 27, 2016, and classified suspected cases into five categories based on neuroimaging and laboratory results for Zika virus and other relevant infections. Definite cases had laboratory evidence of Zika virus infection; highly probable cases presented specific neuroimaging findings, and negative laboratory results for other congenital infections; moderately probable cases had specific imaging findings but other infections could not be ruled out; somewhat probable cases had imaging findings, but these were not reported in detail by the local teams; all other newborn babies were classified as discarded cases. Head circumference by gestational age was assessed with InterGrowth standards. First week mortality and history of rash were provided by the State medical teams. Findings Between Nov 19, 2015, and Feb 27, 2015, investigations were completed for 1501 suspected cases reported to the Brazilian Ministry of Health, of whom 899 were discarded. Of the remainder 602 cases, 76 were definite, 54 highly probable, 181 moderately probable, and 291 somewhat probable of congenital Zika virus syndrome. Clinical, anthropometric, and survival differences were small among the four groups. Compared with these four groups, the 899 discarded cases had larger head circumferences (mean Z scores −1·54 vs −3·13, difference 1·58 95% CI 1·45–1·72); lower first-week mortality (14 per 1000 vs 51 per 1000; rate ratio 0·28 95% CI 0·14–0·56); and were less likely to have a history of rash during pregnancy (20·7% vs 61·4%, ratio 0·34 95% CI 0·27–0·42). Rashes in the third trimester of pregnancy were associated with brain abnormalities despite normal sized heads. One in five definite or probable cases presented head circumferences in the normal range (above −2 SD below the median of the InterGrowth standard) and for one third of definite and probable cases there was no history of a rash during pregnancy. The peak of the epidemic occurred in late November, 2015. Interpretation Zika virus congenital syndrome is a new teratogenic disease. Because many definite or probable cases present normal head circumference values and their mothers do not report having a rash, screening criteria must be revised in order to detect all affected newborn babies. Funding Brazilian Ministry of Health, Pan American Health Organization, and Wellcome Trust.
Summary
We evaluate 38 elderly women who had received long-term denosumab treatment after stopping the drug. Taking into account the gain during treatment and the loss after stopping treatment, they ...lost 35.5% of the total gain in the spine, 44.6% of the total gain in the femoral neck, and 103.3% in the total hip.
Introduction
Denosumab (DMAb) is a soluble inhibitor of the receptor activator of nuclear factor-kappaB ligand (RANKL) and, therefore, does not incorporate into the bone matrix. Consistently, DMAb discontinuation is associated with reversal of the effects attained with treatment.
Purpose
The aim of this study is to assess changes in BMD after a year of discontinuation of DMAb in a group of postmenopausal women treated with DMAb for 7 or 10 years. Secondly, is to evaluate the occurrence of fragility fractures.
Methods
Women who had participated in the FREEDOM study and its extension were invited to participate in this follow-up study. BMD at LS and hip and spine X-rays were obtained. Results were compared to the last value obtained while in treatment to assess changes after discontinuation.
Results
Thirty-eight women, mean age: 81 ± 3.4 years completed study procedures; none had received bisphosphonates after stopping DMAb. Mean gap time between DMAb last dose and the follow-up visit was 17 months (range 16–20 months). Bone mineral density (BMD) decreased significantly in all regions: − 8.1% in LS, − 6% in FN, and − 8.4% in TH. Five (5/38, 13.15%) patients had a fragility fracture, one suffered a wrist fracture, and four experienced vertebral fractures. Three patients suffered one vertebral fracture and one of them had two vertebral fractures. Laboratory results showed the following mean values: CTX = 996 ± 307 pg/ml (normal values 550 ± 226 pg/ml); osteocalcin = 55.2 ± 18.6 ng/ml (normal value 42 ng/ml); and 25 OH vitamin
D
= 23.7 ± 6.9 ng/ml.
Conclusion
Our results describe the rapid bone loss occurring after cessation of denosumab treatment. Further studies are needed to assess if patients have a higher risk of fracture after stopping DMAb and if so, which patients have the highest risk, and assess the role of transitioning to bisphosphonates in the long term.
Users and Internet service providers (ISPs) are constantly affected by denial-of-service (DoS) attacks. This cyber threat continues to grow even with the development of new protection technologies. ...Developing mechanisms to detect this threat is a current challenge in network security. This article presents a machine learning- (ML-) based DoS detection system. The proposed approach makes inferences based on signatures previously extracted from samples of network traffic. The experiments were performed using four modern benchmark datasets. The results show an online detection rate (DR) of attacks above 96%, with high precision (PREC) and low false alarm rate (FAR) using a sampling rate (SR) of 20% of network traffic.
Most of the research efforts involving the bovine gastrointestinal microbiota have focused on cattle's forestomach, particularly the rumen, so information concerning the bovine fecal microbiota is ...more scarce, especially in young beef cattle. The present study was performed to evaluate the ruminal and fecal microbiotas of beef calves as they reached the end of their nursing phase. A total of 18 Angus cow/calf pairs were selected and assigned to one of two treatment groups for the last 92 days of the calves' nursing period, as follows: 1) calves were supplemented with concentrate in a creep feeding system; or 2) control group with no supplementation of calves. After 92 days, ruminal and fecal samples were individually obtained from calves in both groups, and their microbiotas were evaluated using 16S rRNA gene sequencing. Ruminal samples were predominated by Prevotella (18 to 23% of the total bacterial abundance), regardless if calves received supplementation or not; however, in the feces, Prevotella was only the seventh most abundant genus (0.6 to 2.1% of total bacterial abundance). Both the rumen (P = 0.01) and the feces (P = 0.05) of calves that received supplementation had greater abundance of Firmicutes. In addition, calves that were supplemented had lower abundance of Fibrobacteres (P = 0.03) in their rumens. Regardless if the calves were supplemented or not, Faith's Phylogenetic Diversity index (P ≤ 0.007) and total concentration of short chain fatty acids (P < 0.001) were both greater in the rumen than in the feces of calves. In summary, the ruminal and fecal microbiotas of weanling beef calves were considerably distinct. Additionally, supplementation with creep feed caused some significant changes in the composition of the gastrointestinal microbiota of the calves, especially in the rumen, where supplementation caused an increase in Firmicutes and a decrease in abundance of Fibrobacteres.
By enabling multiple non-orthogonal transmissions, power domain non-orthogonal multiple access (PD-NOMA) potentially increases a system's spectral efficiency. This technique can become an alternative ...for future generations of wireless communication networks. The efficiency of this method fundamentally depends on two previous processing steps: an appropriate grouping of users (transmission candidates) as a function of the channel gains and the choice of power levels that will be used to transmit each signal. Thus far, the solutions presented in the literature to address the problems of user clustering and power allocation do not consider the dynamics of communication systems, i.e., the temporal variation in the number of users and the channel conditions. In order to consider these dynamic characteristics in the clustering of users in NOMA systems, this work proposes a new clustering technique based on a modification of the DenStream evolutionary algorithm, chosen for its evolutionary capacity, noise robustness and online processing. We evaluated the performance of the proposed clustering technique considering, for simplicity, the use of an already widely known power allocation strategy called improved fractional strategy power allocation (IFSPA). The results show that the proposed clustering technique can follow the system dynamics, clustering all users and favoring the uniformity of the transmission rate between the clusters. Compared to orthogonal multiple access (OMA) systems, the proposed model's gain was approximately 10%, obtained on a challenging communication scenario for NOMA systems since the channel model adopted does not favor a large difference in the channel gains between users.
Microscopy is integral to medical research, facilitating the exploration of various biological questions, notably cell quantification. However, this process's time-consuming and error-prone nature, ...attributed to human intervention or automated methods usually applied to fluorescent images, presents challenges. In response, machine learning algorithms have been integrated into microscopy, automating tasks and constructing predictive models from vast datasets. These models adeptly learn representations for object detection, image segmentation, and target classification. An advantageous strategy involves utilizing unstained images, preserving cell integrity and enabling morphology-based classification-something hindered when fluorescent markers are used. The aim is to introduce a model proficient in classifying distinct cell lineages in digital contrast microscopy images. Additionally, the goal is to create a predictive model identifying lineage and determining optimal quantification of cell numbers. Employing a CNN machine learning algorithm, a classification model predicting cellular lineage achieved a remarkable accuracy of 93%, with ROC curve results nearing 1.0, showcasing robust performance. However, some lineages, namely SH-SY5Y (78%), HUH7_mayv (85%), and A549 (88%), exhibited slightly lower accuracies. These outcomes not only underscore the model's quality but also emphasize CNNs' potential in addressing the inherent complexities of microscopic images.
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