Vegetation Composition in Hugumbirda-Gratkhassu National Forest Priority Area, South Tigray

The floristic composition and structure of the vegetation of Hugumbirda-Grat-Khassu forest, South Tigray, Northern Ethiopia is described and related to environmental factors. To analyze the vegetation and environmental data seventy-four relevè ( 20m x 20m) were used. For each species the cover/abundance value was estimated. Height and diameter at breast height (DBH) of all woody individuals taller than 2 m and thicker than 2 cm were measured. Importance Value Index was calculated for 24 tree/shrub species and the result helped to identify the five dominant tree/shrub species and to show the overall forest situation. The species and relevès were classified with the two-way indicator species analysis program TWINSPAN. We recorded 102 species belonging to 83 genera and 50 families. Five community types are described: Allophylus macrobotrys-Ficus sur, Nuxia congesta-Podocarpus falcatus, Acacia abyssinica-Olea europaea, Myrica salicifolia-Erica arborea-Maesa lanceolata and Acacia etbaica- Dichrostachys cinerea-Acacia tortilis type. Of these, community type 2 has high species richness while community type 3 is poor in species richness. The general arrangement of all species was found to show high density at lower height and DBH classes. Based on the cumulative results of Importance Value Index, Juniperus procera, Olea europaea subsp. cuspidata, Nuxia congesta, Cassipourea mallosana and Olinia rochetiana were identified to be the most dominant tree species of the forest and they contributed 71.43% of the basal area. Analysis of community-environment relationships didn’t show significant differences except for altitude and slope. Key words: Community, DBH, Floristic composition, Forest structure, Releve, Vegetation classification

Interplay of Mre11 Nuclease with Dna2 plus Sgs1 in Rad51-Dependent Recombinational Repair

The Mre11/Rad50/Xrs2 complex initiates IR repair by binding to the end of a double-strand break, resulting in 5′ to 3′ exonuclease degradation creating a single-stranded 3′ overhang competent for strand invasion into the unbroken chromosome. The nuclease(s) involved are not well understood. Mre11 encodes a nuclease, but it has 3′ to 5′, rather than 5′ to 3′ activity. Furthermore, mutations that inactivate only the nuclease activity of Mre11 but not its other repair functions, mre11-D56N and mre11-H125N, are resistant to IR. This suggests that another nuclease can catalyze 5′ to 3′ degradation. One candidate nuclease that has not been tested to date because it is encoded by an essential gene is the Dna2 helicase/nuclease. We recently reported the ability to suppress the lethality of a dna2Δ with a pif1Δ. The dna2Δ pif1Δ mutant is IR-resistant. We have determined that dna2Δ pif1Δ mre11-D56N and dna2Δ pif1Δ mre11-H125N strains are equally as sensitive to IR as mre11Δ strains, suggesting that in the absence of Dna2, Mre11 nuclease carries out repair. The dna2Δ pif1Δ mre11-D56N triple mutant is complemented by plasmids expressing Mre11, Dna2 or dna2K1080E, a mutant with defective helicase and functional nuclease, demonstrating that the nuclease of Dna2 compensates for the absence of Mre11 nuclease in IR repair, presumably in 5′ to 3′ degradation at DSB ends. We further show that sgs1Δ mre11-H125N, but not sgs1Δ, is very sensitive to IR, implicating the Sgs1 helicase in the Dna2-mediated pathway

MARVEL Analysis of the Measured High-resolution Rovibronic Spectra of 48 Ti 16 O

Accurate, experimental rovibronic energy levels, with associated labels and uncertainties, are reported for 11 low-lying electronic states of the diatomic ${}^{48}{\mathrm{Ti}}^{16}{\rm{O}}$ molecule, determined using the Marvel (Measured Active Rotational-Vibrational Energy Levels) algorithm. All levels are based on lines corresponding to critically reviewed and validated high-resolution experimental spectra taken from 24 literature sources. The transition data are in the 2–22,160 cm−1 region. Out of the 49,679 measured transitions, 43,885 are triplet–triplet, 5710 are singlet–singlet, and 84 are triplet–singlet transitions. A careful analysis of the resulting experimental spectroscopic network (SN) allows 48,590 transitions to be validated. The transitions determine 93 vibrational band origins of ${}^{48}{\mathrm{Ti}}^{16}{\rm{O}}$, including 71 triplet and 22 singlet ones. There are 276 (73) triplet–triplet (singlet–singlet) band-heads derived from Marvel experimental energies, 123(38) of which have never been assigned in low- or high-resolution experiments. The highest J value, where J stands for the total angular momentum, for which an energy level is validated is 163. The number of experimentally derived triplet and singlet ${}^{48}{\mathrm{Ti}}^{16}{\rm{O}}$ rovibrational energy levels is 8682 and 1882, respectively. The lists of validated lines and levels for ${}^{48}{\mathrm{Ti}}^{16}{\rm{O}}$ are deposited in the supporting information to this paper

Contraceptive discontinuation among women of reproductive age in Papua New Guinea.

BACKGROUND: Papua New Guinea has one of the lowest contraceptive prevalence rates among women of reproductive age in the Western Pacific Region and this makes contraceptive discontinuation in this country a critical public health issue worth studying. This study sought to assess the factors associated with contraceptive discontinuation among women of reproductive age in Papua New Guinea. METHODS: The data used for the analysis were obtained from the Papua New Guinea Demographic and Health Survey which was conducted in 2016-2018. The outcome variable for this study was contraceptive discontinuation among women of reproductive age. Crude odds ratios and adjusted odds ratios with 95% confidence intervals were estimated using binary logistic regression. RESULTS: About 33.26% of the women discontinued injectables, 19.15% discontinued pills and 3.77% discontinued other contraception methods. Women aged 20-24 [aOR = 2.12, CI = [= [1.04,4.31] through to those aged 30-34 [aOR = 1.98, CI = 1.03,3.79] had higher odds to discontinue contraceptive usage compared to those aged 45-49. Women with no information on choice of contraception [aOR = 2.85, CI = 2.31,3.51], those with two or more births in the last five years [aOR = 2.35, CI = 1.65,3.35] and those living in the Highland region [aOR = 1.71, CI = 1.28,2.29] were more likely to discontinue contraceptive usage compared with those with information on contraceptive choices, those with no births and those living in the Island region respectively. However, women in the rural areas [aOR = 0.78, CI = 0.61,0.99], women using LARC [aOR = 0.10, CI = 0.06,0.15], injectables [aOR = 0.43, CI = 0.30,0.63] and other modern contraception methods including condom [aOR = 0.22, CI = 0.15,0.34] were less likely to discontinue contraceptive usage. CONCLUSION: A nationwide mass education on the benefits of contraception is recommended for the Papua New Guinea National Department of Health to tackle the key findings of this study which were high contraceptive discontinuation prevalence with lack of information on choice, disproportionately high contraceptive discontinuation rate in the Highland Region and the desire to give birth to more than two children as some factors associated with contraceptive discontinuation in Papua New Guinea

Validation of nonlinear PCA

Linear principal component analysis (PCA) can be extended to a nonlinear PCA by using artificial neural networks. But the benefit of curved components requires a careful control of the model complexity. Moreover, standard techniques for model selection, including cross-validation and more generally the use of an independent test set, fail when applied to nonlinear PCA because of its inherent unsupervised characteristics. This paper presents a new approach for validating the complexity of nonlinear PCA models by using the error in missing data estimation as a criterion for model selection. It is motivated by the idea that only the model of optimal complexity is able to predict missing values with the highest accuracy. While standard test set validation usually favours over-fitted nonlinear PCA models, the proposed model validation approach correctly selects the optimal model complexity.Comment: 12 pages, 5 figure

Your space or mine? : Mapping self in time

Peer reviewedPublisher PD

A loop of cancer-stroma-cancer interaction promotes peritoneal metastasis of ovarian cancer via TNFα-TGFα-EGFR.

Peritoneum is the most common site for ovarian cancer metastasis. Here we investigate how cancer epigenetics regulates reciprocal tumor-stromal interactions in peritoneal metastasis of ovarian cancer. Firstly, we find that omental stromal fibroblasts enhance colony formation of metastatic ovarian cancer cells, and de novo expression of transforming growth factor-alpha (TGF-α) is induced in stromal fibroblasts co-cultured with ovarian cancer cells. We also observed an over-expression of tumor necrosis factor-alpha (TNF-α) in ovarian cancer cells, which is regulated by promoter DNA hypomethylation as well as chromatin remodeling. Interestingly, this ovarian cancer-derived TNF-α induces TGF-α transcription in stromal fibroblasts through nuclear factor-κB (NF-κB). We further show that TGF-α secreted by stromal fibroblasts in turn promotes peritoneal metastasis of ovarian cancer through epidermal growth factor receptor (EGFR) signaling. Finally, we identify a TNFα-TGFα-EGFR interacting loop between tumor and stromal compartments of human omental metastases. Our results therefore demonstrate cancer epigenetics induces a loop of cancer-stroma-cancer interaction in omental microenvironment that promotes peritoneal metastasis of ovarian cancer cells via TNFα-TGFα-EGFR

Examining the validity and utility of two secondary sources of food environment data against street audits in England

Background: Secondary data containing the locations of food outlets is increasingly used in nutrition and obesity research and policy. However, evidence evaluating these data is limited. This study validates two sources of secondary food environment data: Ordnance Survey Points of Interest data (POI) and food hygiene data from the Food Standards Agency (FSA), against street audits in England and appraises the utility of these data. Methods: Audits were conducted across 52 Lower Super Output Areas in England. All streets within each Lower Super Output Area were covered to identify the name and street address of all food outlets therein. Audit-identified outlets were matched to outlets in the POI and FSA data to identify true positives (TP: outlets in both the audits and the POI/FSA data), false positives (FP: outlets in the POI/FSA data only) and false negatives (FN: outlets in the audits only). Agreement was assessed using positive predictive values (PPV: TP/(TP+FP)) and sensitivities (TP/(TP+FN)). Variations in sensitivities and PPVs across environment and outlet types were assessed using multi-level logistic regression. Proprietary classifications within the POI data were additionally used to classify outlets, and agreement between audit-derived and POI-derived classifications was assessed. Results: Street audits identified 1172 outlets, compared to 1100 and 1082 for POI and FSA respectively. PPVs were statistically significantly higher for FSA (0.91, CI: 0.89-0.93) than for POI (0.86, CI: 0.84-0.88). However, sensitivity values were not different between the two datasets. Sensitivity and PPVs varied across outlet types for both datasets. Without accounting for this, POI had statistically significantly better PPVs in rural and affluent areas. After accounting for variability across outlet types, FSA had statistically significantly better sensitivity in rural areas and worse sensitivity in rural middle affluence areas (relative to deprived). Audit-derived and POI-derived classifications exhibited substantial agreement (p < 0.001; Kappa = 0.66, CI: 0.63 - 0.70). Conclusions: POI and FSA data have good agreement with street audits; although both datasets had geographic biases which may need to be accounted for in analyses. Use of POI proprietary classifications is an accurate method for classifying outlets, providing time savings compared to manual classification of outlets

Paclitaxel induces immunogenic cell death in ovarian cancer via TLR4/IKK2/SNARE-dependent exocytosis

Emerging evidence shows that the efficacy of chemotherapeutic drugs are reliant on their capability to induce immunogenic cell death (ICD), thus transforming dying tumor cells into antitumor vaccines. We wanted to uncover potential therapeutic strategies that target ovarian cancer by having a better understanding of the standard-of-care chemotherapy treatment. Here, we showed in ovarian cancer that paclitaxel induced ICD-associated DAMPs (i.e. damage-associated molecular patterns, such as CALR exposure, ATP secretion and HMGB1 release) in vitro and elicited significant antitumor responses in tumor vaccination assays in vivo. Paclitaxel-induced TLR4 signaling was essential to the release of DAMPs, which lead to the activation of NF-κB-mediated CCL2 transcription and IKK2-mediated SNARE-dependent vesicle exocytosis, thus exposing CALR on the cell surface. Paclitaxel induced ER stress, which triggered PERK activation and eIF2α phosphorylation independent of TLR4. Paclitaxel chemotherapy induced T cell infiltration in ovarian tumors of the responsive patients; CALR expression in primary ovarian tumors also correlated with patients' survival and patient response to chemotherapy. These findings suggest that the effectiveness of paclitaxel relied upon the activation of antitumor immunity through ICD via TLR4 and highlighted the importance of CALR expression in cancer cells as an indicator of response to paclitaxel chemotherapy in ovarian cancer