Uptake of three doses of HPV vaccine by primary school girls in Eldoret, Kenya : a prospective cohort study in a malaria endemic setting

Background: All women are potentially at risk of developing cervical cancer at some point in their life, yet it is avoidable cause of death among women in Sub- Saharan Africa with a world incidence of 530,000 every year. It is the 4th commonest cancer affecting women worldwide with over 260,000 deaths reported in 2012. Low resource settings account for over 75% of the global cervical cancer burden. Uptake of HPV vaccination is limited in the developing world. WHO recommended that 2 doses of HPV vaccine could be given to young girls, based on studies in developed countries. However in Africa high rates of infections like malaria and worms can affect immune responses to vaccines, therefore three doses may still be necessary. The aim of this study was to identify barriers and facilitators associated with uptake of HPV vaccine. Methods: A cross-sectional survey was conducted at Eldoret, Kenya involving 3000 girls aged 9 to 14 years from 40 schools. Parents/guardians gave consent through a questionnaire. Results: Of all 3083 the school girls 93.8% had received childhood vaccines and 63.8% had a second HPV dose, and 39. 1% had a third dose. Administration of second dose and HPV knowledge were both strong predictors of completion of the third dose. Distance to the hospital was a statistically significant risk factor for non-completion (P: 0.01). Conclusions: Distance to vaccination centers requires a more innovative vaccine-delivery strategy and education of parents/guardians on cervical screening to increase attainment of the HPV vaccination

Human papilloma virus correlates of high grade cervical dysplasia in HIV-infected women in Mombasa, Kenya: a cross-sectional analysis

Background: Women living with HIV are at increased risk to be co-infected with HPV, persistent high-risk (HR) human papillomavirus (HPV) infection and increased HR HPV viral load, which make them more at risk for cervical cancer. Despite their inherent vulnerability, there is a scarcity of data on potential high risk (pHR) and HR HPV genotypes in HIV- infected women with cervical dysplasia and HPV-type specific viral load in this population in Sub Saharan Africa. The aim of this analysis of HIV-infected women was to explore the virological correlates of high-grade cervical dysplasia (CIN 2+) in HIV-infected women, thereby profiling HPV genotypes. Method: This analysis assesses baseline data obtained from a cohort study of 74 HIV-infected women with abnormal cytology attending a Comprehensive Care Centre for patients with HIV infection in Mombasa, Kenya. Quantitative real-time PCR was used for HPV typing and viral load. Results: CIN 2 was observed in 16% (12/74) of women, CIN 3 in 23% (17/74), and, invasive cervical carcinoma (ICC) in 1% (1/74) of women. In women with CIN 3+, HPV 16 (44%), HPV 56 (33%), HPV 33 and 53 (HPV 53 (28%) were the most prevalent genotypes. HPV 53 was observed as a stand-alone HPV in one woman with ICC. A multivariate logistic regression adjusting for age, CD4 count and HPV co-infections suggested the presence of HPV 31 as a predictor of CIN 2+ (adjusted odds ratio [aOR]:4.9; p = 0.05; 95% (Confidence Interval) [CI]:1.03-22.5). Women with CIN2+ had a significantly higher viral log mean of HPV 16, (11.2 copies/ 10,000 cells; 95% CI: 9.0-13.4) than with CIN 1. Conclusion: The high prevalence of HPV 53 in CIN 3 and as a stand-alone genotype in the patient with invasive cervical cancer warrants that its clinical significance be further revisited among HIV-infected women. HPV 31, along with elevated means of HPV 16 viral load were predictors of CIN 2 + 

Associations between highly active antiretroviral therapy and the presence of HPV, premalignant and malignant cervical lesions in sub-Saharan Africa, a systematic review : current evidence and directions for future research

Objectives: In sub-Saharan Africa, substantial international funding along with evidence-based clinical practice have resulted in an unparalleled scale-up of access to antiretroviral treatment at a higher CD4 count. The role and timing of highly active antiretroviral therapy (HAART) in mediating cervical disease remains unclear. The aim of this article is to systematically review all evidence pertaining to Africa and identify research gaps regarding the epidemiological association between HAART use and the presence of premalignant/malignant cervical lesions. Method: Five databases were searched until January 2017 to retrieve relevant literature from sub-Saharan Africa. Publications were included if they addressed prevalence, incidence or clearance of human papillomavirus (HPV) infection in women undergoing HAART as well as cytological or histological neoplastic abnormalities. Results: 22 studies were included, of which seven were prospective studies. Women receiving HAART are less likely to develop squamous intraepithelial lesions (SILs). There is evidence that duration of HAART along with the CD4 count may reduce the prevalence of high-risk HPV (HR-HPV), suggesting that without HAART, severe immunosuppression increases the risk of becoming or remaining infected with HR-HPV. Furthermore, according to existent literature, the CD4 count, rather than HAART coverage or its duration, plays a central role in the prevalence of cervical intraepithelial neoplasia (CIN) 2 and CIN 3. Conclusion: Our findings suggest a positive impact of HAART duration, in conjunction and interaction with CD4 count, on reducing the prevalence of HR-HPV. The greatest treatment effect might be seen among women starting at the lowest CD4 count, which may have a more instrumental role in cervical oncogenesis than either HAART use or the treatment duration on the prevalence of CIN 2 and CIN 3. There is still insufficient evidence to show a clear association between HAART coverage and the incidence of invasive cervical cancer. Enhanced surveillance on the impact of HAART treatment is crucial

Towards On-Device AI and Blockchain for 6G enabled Agricultural Supply-chain Management

6G envisions artificial intelligence (AI) powered solutions for enhancing the quality-of-service (QoS) in the network and to ensure optimal utilization of resources. In this work, we propose an architecture based on the combination of unmanned aerial vehicles (UAVs), AI and blockchain for agricultural supply-chain management with the purpose of ensuring traceability, transparency, tracking inventories and contracts. We propose a solution to facilitate on-device AI by generating a roadmap of models with various resource-accuracy trade-offs. A fully convolutional neural network (FCN) model is used for biomass estimation through images captured by the UAV. Instead of a single compressed FCN model for deployment on UAV, we motivate the idea of iterative pruning to provide multiple task-specific models with various complexities and accuracy. To alleviate the impact of flight failure in a 6G enabled dynamic UAV network, the proposed model selection strategy will assist UAVs to update the model based on the runtime resource requirements.Comment: 8 pages, 5 figures, 1 table. Accepted to IEEE Internet of Things Magazin

Challenges to support edge-as-a-service

A new era in telecommunications is emerging. Virtualized networking functions and resources will offer network operators a way to shift the balance of expenditure from capital to operational, opening up networks to new and innovative services. This article introduces the concept of edge as a service (EaaS), a means of harnessing the flexibility of virtualized network functions and resources to enable network operators to break the tightly coupled relationship they have with their infrastructure and enable more effective ways of generating revenue. To achieve this vision, we envisage a virtualized service access interface that can be used to programmatically alter access network functions and resources available to service providers in an elastic fashion. EaaS has many technically and economically difficult challenges that must be addressed before it can become a reality; the main challenges are summarized in this article

Energy-aware AI-driven Framework for Edge Computing-based IoT Applications

The significant growth in the number of Internetof- things (IoT) devices has given impetus to the idea of edge computing for several applications. In addition, energy harvestable or wireless-powered wearable devices are envisioned to empower the edge intelligence in IoT applications. However, the intermittent energy supply and network connectivity of such devices in scenarios including remote areas and hard-to-reach regions such as in-body applications can limit the performance of edge computing-based IoT applications. Hence, deploying stateof-the-art convolutional neural networks (CNNs) on such energy constrained devices is not feasible due to their computational cost. Existing model compression methods such as network pruning and quantization can reduce complexity, but these methods only work for fixed computational or energy requirements, which is not the case for edge devices with an intermittent energy source. In this work, we propose a pruning scheme based on deep reinforcement learning (DRL), which can compress the CNN model adaptively according to the energy dictated by the energy management policy and accuracy requirements for IoT applications. The proposed energy policy uses predictions of energy to be harvested and dictates the amount of energy that can be used by the edge device for deep learning inference. We compare the performance of our proposed approach with existing state-of-the-art CNNs and datasets using different filter-ranking criteria and pruning ratios.We observe that by using DRL driven pruning, the convolutional layers that consume relatively higher energy are pruned more as compared to their counterparts. Thereby, our approach outperforms existing approaches by reducing energy consumption and maintaining accuracy

Epidemiology of HPV Genotypes among HIV Positive Women in Kenya: A Systematic Review and Meta-Analysis

Background: There is a scarcity of data on the distribution of human papillomavirus (HPV) genotypes in the HIV positive population and in invasive cervical cancer (ICC) in Kenya. This may be different from genotypes found in abnormal cytology. Yet, with the advent of preventive HPV vaccines that target HPV 16 and 18, and the nonavalent vaccine targeting 90% of all ICC cases, such HPV genotype distribution data are indispensable for predicting the impact of vaccination and HPV screening on prevention. Even with a successful vaccination program, vaccinated women will still require screening to detect those who will develop ICC from other High risk (HR) HPV genotypes not prevented by current vaccines. The aim of this review is to report on the prevalence of pHR/HR HPV types and multiple pHR/HR HPV genotypes in Kenya among HIV positive women with normal, abnormal cytology and ICC. Methods: PUBMED, EMBASE, SCOPUS, and PROQUEST were searched for articles on HPV infection up to August 2nd 2016. Search terms were HIV, HPV, Cervical Cancer, Incidence or Prevalence, and Kenya. Results: The 13 studies included yielded a total of 2116 HIV-infected women, of which 89 had ICC. The overall prevalence of pHR/HR HPV genotypes among HIV-infected women was 64% (95%CI: 50%-77%). There was a borderline significant difference in the prevalence of pHR/HR HPV genotypes between Female Sex workers (FSW) compared to non-FSW in women with both normal and abnormal cytology. Multiple pHR/HR HPV genotypes were highly prominent in both normal cytology/HSIL and ICC. The most prevalent HR HPV genotypes in women with abnormal cytology were HPV 16 with 26%, (95%CI: 23.0%-30.0%) followed by HPV 35 and 52, with 21% (95%CI: 18%-25%) and 18% (95%CI: 15%-21%), respectively. In women with ICC, the most prevalent HPV genotypes were HPV 16 (37%; 95%CI: 28%-47%) and HPV 18 (24%; 95%CI: 16%-33%). Conclusion: HPV 16/18 gains prominence as the severity of cervical disease increases, with HPV 16/18 accounting for 61% (95%CI: 50.0%-70.0%) of all ICC cases. A secondary prevention program will be necessary as this population harbors multiple pHR/HR HPV co-infections, which may not be covered by current vaccines. A triage based on FSW as an indicator may be warranted

Thickness characterization toolbox for transparent protective coatings on polymer substrates

The thickness characterization of transparent protective coatings on functional, transparent materials is often problematic. In this paper, a toolbox to determine the thicknesses of a transparent coating on functional window films is presented. The toolbox consists of a combination of secondary ion mass spectrometry and profilometry and can be transferred to other transparent polymeric materials. A coating was deposited on designed model samples, which were characterized with cross-sectional views in transmission and in scanning/transmission electron microscopy and ellipsometry. The toolbox was then used to assess the thicknesses of the protective coatings on the pilot-scale window films. This coating was synthesized using straightforward sol-gel alkoxide chemistry. The kinetics of the condensation are studied in order to obtain a precursor that allows fast drying and complete condensation after simple heat treatment. The shelf life of this precursor solution was investigated in order to verify its accordance to industrial requirements. Deposition was performed successfully at low temperatures below 100 °C, which makes deposition on polymeric foils possible. By using roll-to-roll coating, the findings of this paper are easily transferrable to industrial scale. The coating was tested for scratch resistance and adhesion. Values for the emissivity (ε) of the films were recorded to justify the use of the films obtained as infrared reflective window films. In this work, it is shown that the toolbox measures similar thicknesses to those measured by electron microscopy and can be used to set a required thickness for protective coatings

The AllWISE Motion Survey, Part 2

We use the AllWISE Data Release to continue our search for WISE-detected motions. In this paper, we publish another 27,846 motion objects, bringing the total number to 48,000 when objects found during our original AllWISE motion survey are included. We use this list, along with the lists of confirmed WISE-based motion objects from the recent papers by Luhman and by Schneider et al. and candidate motion objects from the recent paper by Gagne et al. to search for widely separated, common-proper-motion systems. We identify 1,039 such candidate systems. All 48,000 objects are further analyzed using color-color and color-mag plots to provide possible characterizations prior to spectroscopic follow-up. We present spectra of 172 of these, supplemented with new spectra of 23 comparison objects from the literature, and provide classifications and physical interpretations of interesting sources. Highlights include: (1) the identification of three G/K dwarfs that can be used as standard candles to study clumpiness and grain size in nearby molecular clouds because these objects are currently moving behind the clouds, (2) the confirmation/discovery of several M, L, and T dwarfs and one white dwarf whose spectrophotometric distance estimates place them 5-20 pc from the Sun, (3) the suggestion that the Na 'D' line be used as a diagnostic tool for interpreting and classifying metal-poor late-M and L dwarfs, (4) the recognition of a triple system including a carbon dwarf and late-M subdwarf, for which model fits of the late-M subdwarf (giving [Fe/H] ~ -1.0) provide a measured metallicity for the carbon star, and (5) a possible 24-pc-distant K5 dwarf + peculiar red L5 system with an apparent physical separation of 0.1 pc.Comment: 62 pages with 80 figures, accepted for publication in The Astrophysical Journal Supplement Series, 23 Mar 2016; second version fixes a few small typos and corrects the footnotes for Table