Mapping lung cancer epithelial-mesenchymal transition states and trajectories with single-cell resolution.

Elucidating the spectrum of epithelial-mesenchymal transition (EMT) and mesenchymal-epithelial transition (MET) states in clinical samples promises insights on cancer progression and drug resistance. Using mass cytometry time-course analysis, we resolve lung cancer EMT states through TGFβ-treatment and identify, through TGFβ-withdrawal, a distinct MET state. We demonstrate significant differences between EMT and MET trajectories using a computational tool (TRACER) for reconstructing trajectories between cell states. In addition, we construct a lung cancer reference map of EMT and MET states referred to as the EMT-MET PHENOtypic STAte MaP (PHENOSTAMP). Using a neural net algorithm, we project clinical samples onto the EMT-MET PHENOSTAMP to characterize their phenotypic profile with single-cell resolution in terms of our in vitro EMT-MET analysis. In summary, we provide a framework to phenotypically characterize clinical samples in the context of in vitro EMT-MET findings which could help assess clinical relevance of EMT in cancer in future studies

Field efficacy of aqueous extracts of Artemisia annua, Commelina benghalensis and Euphorbia hirta on rice growth, yield and brown spot disease incidence

Importance of the work: Brown leaf spot disease is one of the major causes of yield losses in rice production in Cameroon. Objectives: To evaluate the bioactivity of aqueous extracts of three Cameroonian medicinal plants on rice growth, yield and brown spot disease incidence. Materials & Methods: Plant extracts were tested at two doses (1 kg/15 L and 2 kg/15 L sprayed), while water and Mancozeb were used as negative and positive controls, respectively, in a split plot design made up of two factors (variety and plant extract). The varieties were NERICA 8, NERICA L56, Long grain red rice and Toukbem. Results: NERICAs 8 and L56 (exotic) and, Toukbem (local) varieties had the highest number of leaves and tillers while Toukbem had the highest plants and leaf area at 9 wk after transplanting. The numbers of leaves (31.3) and tillers (9.7) were significantly (p < 0.05) higher in plants treated with Euphorbia hirta extract at 67 g/L compared to Artemesia annua and Commelina benghalensis extracts. Brown spot severity was lower with E. hirta at 134 g/L (30%) and not significantly different to Mancozeb (23.6%). The NERICA L56 × E. hirta interaction at 134 g/L had the highest yield (5.8 t/ha) compared to the NERICA L56 × Mancozeb (6.1 t/ha) interaction. Chemical analysis of the E. hirta aqueous extract showed the presence of known bioactive compounds. Main finding: Field application of aqueous extract of E. hirta at 134 g/L could be used as a bioagent for rice brown spot management. The formulation of a natural product with this extract is necessary for large-scale field applications

Short-Term Dry Season Forage Monitoring in Rangelands and Savannas of West Africa

Dry season plant biomass is critical for livestock production and hence livelihoods in rangeland communities. We have developed a cloud-based application that employs remote sensing data to provide weekly spatially explicit information on plant vegetation cover in West Africa during the dry season (typically October-June). In this paper, we discuss the data analysis steps and results that drive the application. Linear spectral mixture analysis is used to derive endmember samples of basic landcover primitives (active/green vegetation, non-active vegetation, and bare soil) from very high-resolution imagery that spans the spatiotemporal spectrum from wet/peak-green to dry/dormant conditions in Senegal. These samples are used to train and evaluate ensemble tree models for predicting proportional cover of the same land cover primitives at 500m scale, using MODIS derived NDVI, shortwave infra-red bands 3 and 2 (SWIR3 and SWIR2), and total 15-day antecedent precipitation as predictors. Our trained models can predict the fractional cover of green vegetation, non-green vegetation and bare soil across space and time with cross-validation root-mean square errors of 12%, 15% and 9% respectively. With a weekly cadence and low latency (~2-3 weeks), the tool can also provide timely information to support local decision making in the management of critical rangeland resources

Process evaluation of a kindergarten-based intervention for obesity prevention in early childhood: the Toybox study Malaysia

BackgroundToybox is a kindergarten-based intervention program that targets sedentary behavior, snacking and drinking habits, as well as promoting physical activity in an effort to improve healthy energy balance-related behaviors among children attending kindergartens in Malaysia. The pilot of this program was conducted as a randomized controlled trial (RCT) involving 837 children from 22 intervention kindergartens and 26 control kindergartens respectively. This paper outlines the process evaluation of this intervention.MethodsWe assessed five process indicators: recruitment, retention, dosage, fidelity, and satisfaction for the Toybox program. Data collection was conducted via teachers’ monthly logbooks, post-intervention feedback through questionnaires, and focus group discussions (FGD) with teachers, parents, and children. Data were analyzed using quantitative and qualitative data analysis methods.ResultsA total of 1072 children were invited. Out of the 1001 children whose parents consented to join, only 837 completed the program (Retention rate: 88.4%). As high as 91% of the 44 teachers and their assistants engaged positively in one or more of the process evaluation data collection methods. In terms of dosage and fidelity, 76% of parents had received newsletters, tip cards, and posters at the appropriate times. All teachers and their assistants felt satisfied with the intervention program. However, they also mentioned some barriers to its implementation, including the lack of suitable indoor environments to conduct activities and the need to make kangaroo stories more interesting to captivate the children’s attention. As for parents, 88% of them were satisfied with the family-based activities and enjoyed them. They also felt that the materials provided were easy to understand and managed to improve their knowledge. Lastly, the children showed positive behaviors in consuming more water, fruits, and vegetables.ConclusionsThe Toybox program was deemed acceptable and feasible to implement by the parents and teachers. However, several factors need to be improved before it can be expanded and embedded as a routine practice across Malaysia

Molecular markers for artemisinin and partner drug resistance in natural Plasmodium falciparum populations following increased insecticide treated net coverage along the slope of mount Cameroon: cross-sectional study.

BACKGROUND: Drug resistance is one of the greatest challenges of malaria control programmes, with the monitoring of parasite resistance to artemisinins or to Artemisinin Combination Therapy (ACT) partner drugs critical to elimination efforts. Markers of resistance to a wide panel of antimalarials were assessed in natural parasite populations from southwestern Cameroon. METHODS: Individuals with asymptomatic parasitaemia or uncomplicated malaria were enrolled through cross-sectional surveys from May 2013 to March 2014 along the slope of mount Cameroon. Plasmodium falciparum malaria parasitaemic blood, screened by light microscopy, was depleted of leucocytes using CF11 cellulose columns and the parasite genotype ascertained by sequencing on the Illumina HiSeq platform. RESULTS: A total of 259 participants were enrolled in this study from three different altitudes. While some alleles associated with drug resistance in pfdhfr, pfmdr1 and pfcrt were highly prevalent, less than 3% of all samples carried mutations in the pfkelch13 gene, none of which were amongst those associated with slow artemisinin parasite clearance rates in Southeast Asia. The most prevalent haplotypes were triple mutants Pfdhfr I 51 R 59 N 108 I 164(99%), pfcrt- C72V73 I 74 E 75 T 76 (47.3%), and single mutants PfdhpsS436 G 437K540A581A613(69%) and Pfmdr1 N86 F 184D1246 (53.2%). CONCLUSIONS: The predominance of the Pf pfcrt CVIET and Pf dhfr IRN triple mutant parasites and absence of pfkelch13 resistance alleles suggest that the amodiaquine and pyrimethamine components of AS-AQ and SP may no longer be effective in their role while chloroquine resistance still persists in southwestern Cameroon

Testing for differential abundance in mass cytometry data.

When comparing biological conditions using mass cytometry data, a key challenge is to identify cellular populations that change in abundance. Here, we present a computational strategy for detecting 'differentially abundant' populations by assigning cells to hyperspheres, testing for significant differences between conditions and controlling the spatial false discovery rate. Our method (http://bioconductor.org/packages/cydar) outperforms other approaches in simulations and finds novel patterns of differential abundance in real data.This work was supported by Cancer Research UK (core funding to J.C.M., award no. A17197), the University of Cambridge and Hutchison Whampoa Limited. J.C.M. was also supported by core funding from EMBL

Deterministic Effects Propagation Networks for reconstructing protein signaling networks from multiple interventions

<p>Abstract</p> <p>Background</p> <p>Modern gene perturbation techniques, like RNA interference (RNAi), enable us to study effects of targeted interventions in cells efficiently. In combination with mRNA or protein expression data this allows to gain insights into the behavior of complex biological systems.</p> <p>Results</p> <p>In this paper, we propose Deterministic Effects Propagation Networks (DEPNs) as a special Bayesian Network approach to reverse engineer signaling networks from a combination of protein expression and perturbation data. DEPNs allow to reconstruct protein networks based on combinatorial intervention effects, which are monitored via changes of the protein expression or activation over one or a few time points. Our implementation of DEPNs allows for latent network nodes (i.e. proteins without measurements) and has a built in mechanism to impute missing data. The robustness of our approach was tested on simulated data. We applied DEPNs to reconstruct the <it>ERBB </it>signaling network in <it>de novo </it>trastuzumab resistant human breast cancer cells, where protein expression was monitored on Reverse Phase Protein Arrays (RPPAs) after knockdown of network proteins using RNAi.</p> <p>Conclusion</p> <p>DEPNs offer a robust, efficient and simple approach to infer protein signaling networks from multiple interventions. The method as well as the data have been made part of the latest version of the R package "nem" available as a supplement to this paper and via the Bioconductor repository.</p

ToyBox Malaysia Panduan Umum Guru

Konsep ToyBox Study diadaptasi daripada program ENERGY, program intervensi Cretan Health and Nutrition, manakala teks dan bahan diadaptasi daripada TigerKids. Bahan berkaitan Pinggan Sihat Malaysia digunapakai dengan izin daripada Bahagian Pemakanan, Kementerian Kesihatan Malaysia

Placental Plasmodium falciparum malaria infection: Operational accuracy of HRP2 rapid diagnostic tests in a malaria endemic setting

<p>Abstract</p> <p>Background</p> <p>Malaria has a negative effect on the outcome of pregnancy. Pregnant women are at high risk of severe malaria and severe haemolytic anaemia, which contribute 60-70% of foetal and perinatal losses. Peripheral blood smear microscopy under-estimates sequestered placental infections, therefore malaria rapid diagnostic tests (RDTs) detecting histidine rich protein-2 antigen (HRP-2) in peripheral blood are a potential alternative.</p> <p>Methods</p> <p>HRP-2 RDTs accuracy in detecting malaria in pregnancy (MIP >28 weeks gestation) and placental <it>Plasmodium falciparum </it>malaria (after childbirth) were conducted using Giemsa microscopy and placental histopathology respectively as the reference standard. The study was conducted in Mbale Hospital, using the midwives to perform and interpret the RDT results. Discordant results samples were spot checked using PCR techniques.</p> <p>Results</p> <p>Among 433 febrile women tested, RDTs had a sensitivity of 96.8% (95% CI 92-98.8), specificity of 73.5% (95% CI 67.8-78.6), a positive predictive value (PPV) of 68.0% (95% CI 61.4-73.9), and negative predictive value (NPV) of 97.5% (95% CI 94.0-99.0) in detecting peripheral <it>P. falciparum </it>malaria during pregnancy. At delivery, in non-symptomatic women, RDTs had a 80.9% sensitivity (95% CI 57.4-93.7) and a 87.5% specificity (95%CI 80.9-92.1), PPV of 47.2% (95% CI 30.7-64.2) and NPV of 97.1% (95% CI 92.2-99.1) in detecting placental <it>P. falciparum </it>infections among 173 samples. At delivery, 41% of peripheral infections were detected by microscopy without concurrent placental infection. The combination of RDTs and microscopy improved the sensitivity to 90.5% and the specificity to 98.4% for detecting placental malaria infection (McNemar's <it>X </it>²> 3.84). RDTs were not superior to microscopy in detecting placental infection (McNemar's <it>X </it>²< 3.84). Presence of malaria in pregnancy and active placental malaria infection were 38% and 12% respectively. Placental infections were associated with poor pregnancy outcome [pre-term, still birth and low birth weight] (aOR = 37.9) and late pregnancy malaria infection (aOR = 20.9). Mosquito net use (aOR 2.1) and increasing parity (aOR 2.7) were associated with lower risk for malaria in pregnancy.</p> <p>Conclusion</p> <p>Use of HRP-2 RDTs to detect malaria in pregnancy in symptomatic women was accurate when performed by midwives. A combination of RDTs and microscopy provided the best means of detecting placental malaria. RDTs were not superior to microscopy in detecting placental infection. With a high sensitivity and specificity, RDTs could be a useful tool for assessing malaria in pregnancy, with further (cost-) effectiveness studies.</p

Data-analysis strategies for image-based cell profiling

Image-based cell profiling is a high-throughput strategy for the quantification of phenotypic differences among a variety of cell populations. It paves the way to studying biological systems on a large scale by using chemical and genetic perturbations. The general workflow for this technology involves image acquisition with high-throughput microscopy systems and subsequent image processing and analysis. Here, we introduce the steps required to create high-quality image-based (i.e., morphological) profiles from a collection of microscopy images. We recommend techniques that have proven useful in each stage of the data analysis process, on the basis of the experience of 20 laboratories worldwide that are refining their image-based cell-profiling methodologies in pursuit of biological discovery. The recommended techniques cover alternatives that may suit various biological goals, experimental designs, and laboratories' preferences.Peer reviewe