BackgroundThe seroprevalence and risk factors of bovine brucellosis were studied at animal and herd level using a combination of culture, serological and molecular methods. The study was conducted in 253 randomly selected cattle herds of the Potohar plateau, Pakistan from which a total of 2709 serum (1462 cattle and 1247 buffaloes) and 2330 milk (1168 cattle and 1162 buffaloes) samples were collected. Data on risk factors associated with seroprevalence of brucellosis were collected through interviews using questionnaires. Univariable and multivariable random effects logistic regression models were used for identifying important risk factors at animal and herd levels.ResultsOne hundred and seventy (6.3%) samples and 47 (18.6%) herds were seropositive for brucellosis by Rose Bengal Plate test. Variations in seroprevalence were observed across the different sampling sites. At animal level, sex, species and stock replacement were found to be potential risk factors for brucellosis. At herd level, herd size (≥9 animals) and insemination method used were important risk factors. The presence of Brucella DNA was confirmed with a real-time polymerase chain reaction assay (qRT-PCR) in 52.4% out of 170 serological positive samples. In total, 156 (6.7%) milk samples were positive by milk ring test. B. abortus biovar 1 was cultured from 5 positive milk samples.ConclusionThis study shows that the seroprevalence of bovine brucellosis is high in some regions in Pakistan. Prevalence was associated with herd size, abortion history, insemination methods used, age, sex and stock replacement methods. The infected animal may act as source of infection for other animals and for humans. The development of control strategies for bovine brucellosis through implementation of continuous surveillance and education programs in Pakistan is warranted.Electronic supplementary materialThe online version of this article (doi:10.1186/s13104-017-2394-2) contains supplementary material, which is available to authorized users.

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Additional energy demand is needed to accomplish the mega-projects of the Belt & Road Initiative (BRI). As energy consumption is one of the prime determinants of environmental degradation, the present study investigates the impact of energy inequalities on environmental degradation along with financial development. The entropy approach is applied to quantify the three energy consumption inequalities; average, between, and total energy consumption inequality respectively. The energy consumption inequality of BRI economies follows an uprising temporal trend. The estimates reveal that East Asia and South Asia have the highest and lowest energy consumption inequality among the BRI regions. Within regions, it is found that Central Asia has the lowest, and East Asia has the highest energy inequality among the BRI regions, respectively. Based on bootstrapping, the generalized least square (GLS) is applied to quantify the impact of energy consumption inequalities on environmental degradation along financial development. The energy inequalities have a statistically positive impact on environmental degradation in BRI regions, East Asia, Central Asia, the Middle East and North African region (MENA), and Southeast Asia respectively. In contrast, South Asian economies are sustaining environmental quality despite the energy consumption inequalities. Financial development also has a significantly major impact on environmental degradation in BRI, and its regions except for Central Asia, and MENA.

Although glioblastomas are common, there remains a need to elucidate the underlying mechanisms behind their initiation and progression and identify molecular pathways for improving treatment. In this study, sixteen fresh-frozen glioblastoma samples and seven samples of healthy brain tissues were analyzed with miRNA and whole transcriptome microarray chips. Candidate miRNAs and mRNAs were selected to validate expression in fifty patient samples in total with the criteria of abundance, relevance and prediction scores. miRNA and target mRNA relationships were assessed by inhibiting selected miRNAs in glioblastoma cells. Functional tests have been conducted in order to see the effects of miRNAs on invasion, migration and apoptosis of GBM cells. Analyses were carried out to determine correlations between selected molecules and clinicopathological features. 1332 genes and 319 miRNAs were found to be dysregulated by the microarrays. The results were combined and analyzed with Transcriptome Analysis Console 3 software and the DAVID online database. Primary differential pathways included Ras, HIF-1, MAPK signaling and cell adhesion. OncomiR candidates 21-5p, 92b-3p, 182-5p and 339-5p for glioblastoma negatively correlated with notable mRNA targets both in tissues and in in vitro experiments. miR-21-5p and miR-339-5p significantly affected migration, invasion and apoptosis of GBM cells in vitro. Significant correlations with overall survival, tumor volume, recurrence and age at diagnosis were discovered. In this article we present valuable integrated microarray analysis of glioblastoma samples regarding miRNA and gene-expression levels. Notable biomarkers and miRNA-mRNA interactions have been identified, some of which correlated with clinicopathological features in our cohort.

Aims: Molecular heterogeneity of breast cancer results in variation in morphology, metastatic potential and response to therapy. We previously showed that breast cancer cell line sub-groups obtained by a clustering approach using highly variable genes overlapped almost completely with sub-groups generated by a drug cytotoxicity-profile based approach. Two distinct cell populations thus identified were CSC(cancer stem cell)-like and non-CSC-like. In this study we asked whether an mRNA based gene signature identifying these two cell types would explain variation in stemness, EMT, drug sensitivity, and prognosis in silico and in vitro. Main methods: In silico analyses were performed using publicly available cell line and patient tumor datasets. In vitro analyses of phenotypic plasticity and drug responsiveness were obtained using human breast cancer cell lines. Key findings: We find a novel gene list (CNCL) that can generate both categorical and continuous variables corresponding to the stemness/EMT (epithelial to mesenchymal transition) state of tumors. We are presenting a novel robust gene signature that unites previous observations related either to EMT or stemness in breast cancer. We show in silico, that this signature perfectly predicts behavior of tumor cells tested in vitro, and can reflect tumor plasticity. We thus demonstrate for the first time, that breast cancer subtypes are sensitive to either Lapatinib or Midostaurin. The same gene list is not capable of predicting prognosis in most cohorts, except for one that includes patients receiving neo-adjuvant taxene therapy. Significance: CNCL is a robust gene list that can identify both stemness and the EMT state of cell lines and tumors. It can be used to trace tumor cells during the course of phenotypic changes they undergo, that result in altered responses to therapeutic agents. The fact that such a list cannot be used to identify prognosis in most patient cohorts suggests that presence of factors other than stemness and EMT affect mortality.

Belt and road initiative (BRI) contains the transport, construction, and energy-related projects to push the wheel of economic development of BRI's participant at the cost of ecological consequences. These sectors are highly energy-intensive and upsurge the CO 2 emission. Energy efficiency and renewable energy are considered two essential solutions to control CO 2 emissions. Energy efficiency is proficient in yielding energy and demand savings that can relocate the electricity generation from primary energy resources, that is why, nowadays, energy efficiency is considered as an energy resource worldwide. Fiscal policy is a vital policy tool regarding energy policies related to production, growth, distribution, and energy consumption. Therefore, this study investigates the relationship between energy efficiency and CO 2 emission in light of the fiscal policy index for BRI countries. The results infer that energy efficiency and fiscal policy deteriorate the CO 2 emission. On the other side, FDI and GDP will lead to an increase in CO 2 emission. This study provides useful insights for policymakers on how to take preventive and remedial measures to reduce CO 2 emissions in different sectors and demonstrated that technology in the energy sector could help to mitigate climate change through energy efficiency. Furthermore, future research can be carried out on how digitalization, energy efficiency monitoring processes, and management process can help to mitigate.

Despite the availability of various treatment protocols, response to therapy in patients with Acute Myeloid Leukemia (AML) remains largely unpredictable. Transcriptomic profiling studies have thus far revealed the presence of molecular subtypes of AML that are not accounted for by standard clinical parameters or by routinely used biomarkers. Such molecular subtypes of AML are predicted to vary in response to chemotherapy or targeted therapy. The Renin-Angiotensin System (RAS) is an important group of proteins that play a critical role in regulating blood pressure, vascular resistance and fluid/electrolyte balance. RAS pathway genes are also known to be present locally in tissues such as the bone marrow, where they play an important role in leukemic hematopoiesis. In this study, we asked if the RAS genes could be utilized to predict drug responses in patients with AML. We show that the combined in silico analysis of up to five RAS genes can reliably predict sensitivity to Doxorubicin as well as Etoposide in AML. The same genes could also predict sensitivity to Doxorubicin when tested in vitro. Additionally, gene set enrichment analysis revealed enrichment of TNF-alpha and type-I IFN response genes among sensitive, and TGF-beta and fibronectin related genes in resistant cancer cells. However, this does not seem to reflect an epithelial to mesenchymal transition per se. We also identified that RAS genes can stratify patients with AML into subtypes with distinct prognosis. Together, our results demonstrate that genes present in RAS are biomarkers for drug sensitivity and the prognostication of AML.

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