Andrographis paniculata transcriptome provides molecular insights into tissue-specific accumulation of medicinal diterpenes

A summary of SSRs identified in leaf and root transcriptomes. (DOCX 11 kb

Novel Classification Approach for Thyroid Detection: Feature Enhanced AdaBoost Optimization with Max Voting

The need for enhanced methods in disease prediction is a significant challenge in the medical field. Current predictive models often face challenges such as limited accuracy, insufficient adaptability to diverse datasets, and inefficiencies in feature selection and model training. These limitations can hinder early diagnosis and effective management of thyroid conditions, which are vital for patient outcomes. The study introduces an innovative method for enhancing thyroid disease prediction using a machine learning study employs algorithms such as support vector machine (SVM), Naive Bayes (NB), K-nearest neighbor (KNN), logistic regression (LR), and stochastic gradient descent (SGD) in conjunction with filter, wrapper, and embedded feature selection methods across three distinct models. The study uses two thyroid datasets, one from Dew Medicare Ternity Hospital, Nagpur, and the other from the UCI thyroid repository, revealing the potential of the novel ‘FeatureBoostThyro’ approach for improving thyroid risk prediction across diverse datasets. The proposed method achieved accuracies of 98.10%, 97.47%, and 95.58% for the three models using the UCI dataset, and 97.42%, 98.71%, and 97.83% for the DMTH dataset. The novelty of this approach lies in its integrated pipeline that ensures the selection of the best features, systematic model training, and rigorous evaluation. This results in a robust, accurate, and reliable model that outperforms traditional approaches, making it a significant advancement in the field of disease prediction. The enhanced performance metrics, especially accuracy, highlight the potential of this method in clinical settings for early and accurate thyroid disease detection

Genotype independent regeneration and agrobacterium-mediated genetic transformation of sweet potato (Ipomoea batatas L.)

Development of an efficient genotype independent regeneration and genetic transformation system in sweet potato continues to be of great interest. Agrobacterium‐mediated genetic transformation protocol was established in two different cultivars of sweet potato using Agrobacterium strain EHA105 harbouring binary plasmid pBI121 containing GUS and nptII genes. The internodal stem segments from 30‐day‐old micropropogated plants were used as explant with different combinations of media and hormones. MS and LS media with various concentrations of growth regulators proved to be non‐responsive and the infecundity was severe with the addition of cytokinins. Nonetheless, MS with 2,4‐D and TDZ gave a good percentage of callusing but with low differentiation. In different concentrations of NAA, significant amount of callusing was observed but percentage of rooting remained low in both the genotypes. Gamborg’s B5 supplemented with NAA proved to be the most suitable media and hormone combination, which yielded shoot formation after 8 ‐ 10 weeks with a regenera‐ tion efficiency of 40 ‐ 70%. Stable integration of transgene was confirmed by PCR analysis. Furthermore, qRT‐PCR analysis was performed to assess the transcript accumulation in addition to the GUS enzymatic assay in the transgenic lines

Development of transgenic cucumber mosaic virus (CMV) resistant gerbera plants expressing CMV coat protein gene

121-130Gerbera (Gerbera jamesonii L.) has its immense importance to the floriculture industry worldwide. The gerbera flower production has been hampered by various viruses, among them cucumber mosaic virus (CMV) has shown considerable damage.As natural resistance to CMV is absent in gerbera, here, we have made an attempt to develop transgenic gerbera plants expressing coat protein (CP) gene of CMV via Agrobacterium mediated transformation of base petiole explants for genetic resistance to CMV infection. Among the 44 putative transgenic gerbera plant acclimatized, 39 were found positive for integration of CP gene by polymerase chain reaction and southern hybridization assay using their specific primer and probe respectively. Northern hybridization assay using CP gene specific probe confirmed the transcription of transgene in all 39 transgenic plants. These plants showed translation of CP during DAS-ELISA when tested with antiserum specific to CP of CMV. These 39 plants when challenged by mechanical inoculations with CMV gerbera isolate showed virus resistance in 53% (21 out of 39) plants, virus tolerance (delayed mild symptom) in 33% (13/39) plants, while rest 12.8% (5/39) plants showed severe disease symptoms. The CP mediated resistance of CMV in transgenic gerbera is being reported for the first time from India

Spaces of Chernobyl: Emptiness and fullness, absence and presence

"Spaces of Chernobyl: Emptiness and Fullness, Absence and Presence" is a research project situated at the intersection of two discourses: the historically specific and the architectural. Underpinning and weaving its way through the report is a dialectic of spatial fullness and emptiness, of presence and absence, a theoretical framework that facilitates the development of a novel and layered perspective on the spaces and architectures of Chernobyl. Methodologically, these spaces are investigated through multi media representations available to an outside, Western European audience, including maps, photographic imagery, websites, written accounts and sound recordings. Representations are acknowledged as a valuable source of (mediated) knowledge and experience, and the report elucidates as much, if not more, about the representations themselves than the actual spaces they represent. In Section I, radiation, an immaterial danger that fills space but exists beyond our sensory capabilities, is discussed in terms of how it was geographically mapped after Chernobyl to make it (phenomenally and conceptually) present. Section 2 is an exploration of emptied architectures, spaces of former habitation evacuated of their inhabitants: the focus is on representations of the permanently abandoned city of Pripyat, mythologized as a dystopic space. Section 3 describes the phenomena of the empty space's new, resilient inhabitants: the reclaiming of space by nature the contaminated space reveals itself to be ecologically full. In Section 4, the Sarcophagus, the concrete and steel container that houses the ruined nuclear reactor, is discussed as a significant presence in the landscape, in terms of human activity and as a symbolic reminder of the Chernobyl disaster. In conclusion, general ramifications for architectural history and further questions are proposed, situating the research within wider debates on wasteland spaces, phenomenology and ocularcentnsm

Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks for 195 countries and territories, 1990–2017 : a systematic analysis for the Global Burden of Disease Study 2017

Background: The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 comparative risk assessment (CRA) is a comprehensive approach to risk factor quantification that offers a useful tool for synthesising evidence on risks and risk outcome associations. With each annual GBD study, we update the GBD CRA to incorporate improved methods, new risks and risk outcome pairs, and new data on risk exposure levels and risk outcome associations. Methods: We used the CRA framework developed for previous iterations of GBD to estimate levels and trends in exposure, attributable deaths, and attributable disability-adjusted life-years (DALYs), by age group, sex, year, and location for 84 behavioural, environmental and occupational, and metabolic risks or groups of risks from 1990 to 2017. This study included 476 risk outcome pairs that met the GBD study criteria for convincing or probable evidence of causation. We extracted relative risk and exposure estimates from 46 749 randomised controlled trials, cohort studies, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. Using the counterfactual scenario of theoretical minimum risk exposure level (TMREL), we estimated the portion of deaths and DALYs that could be attributed to a given risk. We explored the relationship between development and risk exposure by modelling the relationship between the Socio-demographic Index (SDI) and risk-weighted exposure prevalence and estimated expected levels of exposure and risk-attributable burden by SDI. Finally, we explored temporal changes in risk-attributable DALYs by decomposing those changes into six main component drivers of change as follows: (1) population growth; (2) changes in population age structures; (3) changes in exposure to environmental and occupational risks; (4) changes in exposure to behavioural risks; (5) changes in exposure to metabolic risks; and (6) changes due to all other factors, approximated as the risk-deleted death and DALY rates, where the risk-deleted rate is the rate that would be observed had we reduced the exposure levels to the TMREL for all risk factors included in GBD 2017. Findings: In 2017,34.1 million (95% uncertainty interval [UI] 33.3-35.0) deaths and 121 billion (144-1.28) DALYs were attributable to GBD risk factors. Globally, 61.0% (59.6-62.4) of deaths and 48.3% (46.3-50.2) of DALYs were attributed to the GBD 2017 risk factors. When ranked by risk-attributable DALYs, high systolic blood pressure (SBP) was the leading risk factor, accounting for 10.4 million (9.39-11.5) deaths and 218 million (198-237) DALYs, followed by smoking (7.10 million [6.83-7.37] deaths and 182 million [173-193] DALYs), high fasting plasma glucose (6.53 million [5.23-8.23] deaths and 171 million [144-201] DALYs), high body-mass index (BMI; 4.72 million [2.99-6.70] deaths and 148 million [98.6-202] DALYs), and short gestation for birthweight (1.43 million [1.36-1.51] deaths and 139 million [131-147] DALYs). In total, risk-attributable DALYs declined by 4.9% (3.3-6.5) between 2007 and 2017. In the absence of demographic changes (ie, population growth and ageing), changes in risk exposure and risk-deleted DALYs would have led to a 23.5% decline in DALYs during that period. Conversely, in the absence of changes in risk exposure and risk-deleted DALYs, demographic changes would have led to an 18.6% increase in DALYs during that period. The ratios of observed risk exposure levels to exposure levels expected based on SDI (O/E ratios) increased globally for unsafe drinking water and household air pollution between 1990 and 2017. This result suggests that development is occurring more rapidly than are changes in the underlying risk structure in a population. Conversely, nearly universal declines in O/E ratios for smoking and alcohol use indicate that, for a given SDI, exposure to these risks is declining. In 2017, the leading Level 4 risk factor for age-standardised DALY rates was high SBP in four super-regions: central Europe, eastern Europe, and central Asia; north Africa and Middle East; south Asia; and southeast Asia, east Asia, and Oceania. The leading risk factor in the high-income super-region was smoking, in Latin America and Caribbean was high BMI, and in sub-Saharan Africa was unsafe sex. O/E ratios for unsafe sex in sub-Saharan Africa were notably high, and those for alcohol use in north Africa and the Middle East were notably low. Interpretation: By quantifying levels and trends in exposures to risk factors and the resulting disease burden, this assessment offers insight into where past policy and programme efforts might have been successful and highlights current priorities for public health action. Decreases in behavioural, environmental, and occupational risks have largely offset the effects of population growth and ageing, in relation to trends in absolute burden. Conversely, the combination of increasing metabolic risks and population ageing will probably continue to drive the increasing trends in non-communicable diseases at the global level, which presents both a public health challenge and opportunity. We see considerable spatiotemporal heterogeneity in levels of risk exposure and risk-attributable burden. Although levels of development underlie some of this heterogeneity, O/E ratios show risks for which countries are overperforming or underperforming relative to their level of development. As such, these ratios provide a benchmarking tool to help to focus local decision making. Our findings reinforce the importance of both risk exposure monitoring and epidemiological research to assess causal connections between risks and health outcomes, and they highlight the usefulness of the GBD study in synthesising data to draw comprehensive and robust conclusions that help to inform good policy and strategic health planning

Ageratum enation virus Infection Induces Programmed Cell Death and Alters Metabolite Biosynthesis in Papaver somniferum

A previously unknown disease which causes severe vein thickening and inward leaf curl was observed in a number of opium poppy (Papaver somniferum L.) plants. The sequence analysis of full-length viral genome and associated betasatellite reveals the occurrence of Ageratum enation virus (AEV) and Ageratum leaf curl betasatellite (ALCB), respectively. Co-infiltration of cloned agroinfectious DNAs of AEV and ALCB induces the leaf curl and vein thickening symptoms as were observed naturally. Infectivity assay confirmed this complex as the cause of disease and also satisfied the Koch’s postulates. Comprehensive microscopic analysis of infiltrated plants reveals severe structural anomalies in leaf and stem tissues represented by unorganized cell architecture and vascular bundles. Moreover, the characteristic blebs and membranous vesicles formed due to the virus-induced disintegration of the plasma membrane and intracellular organelles were also present. An accelerated nuclear DNA fragmentation was observed by Comet assay and confirmed by TUNEL and Hoechst dye staining assays suggesting virus-induced programmed cell death. Virus-infection altered the biosynthesis of several important metabolites. The biosynthesis potential of morphine, thebaine, codeine, and papaverine alkaloids reduced significantly in infected plants except for noscapine whose biosynthesis was comparatively enhanced. The expression analysis of corresponding alkaloid pathway genes by real time-PCR corroborated well with the results of HPLC analysis for alkaloid perturbations. The changes in the metabolite and alkaloid contents affect the commercial value of the poppy plants

Mapping of variations in child stunting, wasting and underweight within the states of India: the Global Burden of Disease Study 2000–2017

Background To inform actions at the district level under the National Nutrition Mission (NNM), we assessed the prevalence trends of child growth failure (CGF) indicators for all districts in India and inequality between districts within the states. Methods We assessed the trends of CGF indicators (stunting, wasting and underweight) from 2000 to 2017 across the districts of India, aggregated from 5 × 5 km grid estimates, using all accessible data from various surveys with subnational geographical information. The states were categorised into three groups using their Socio-demographic Index (SDI) levels calculated as part of the Global Burden of Disease Study based on per capita income, mean education and fertility rate in women younger than 25 years. Inequality between districts within the states was assessed using coefficient of variation (CV). We projected the prevalence of CGF indicators for the districts up to 2030 based on the trends from 2000 to 2017 to compare with the NNM 2022 targets for stunting and underweight, and the WHO/UNICEF 2030 targets for stunting and wasting. We assessed Pearson correlation coefficient between two major national surveys for district-level estimates of CGF indicators in the states. Findings The prevalence of stunting ranged 3.8-fold from 16.4% (95% UI 15.2–17.8) to 62.8% (95% UI 61.5–64.0) among the 723 districts of India in 2017, wasting ranged 5.4-fold from 5.5% (95% UI 5.1–6.1) to 30.0% (95% UI 28.2–31.8), and underweight ranged 4.6-fold from 11.0% (95% UI 10.5–11.9) to 51.0% (95% UI 49.9–52.1). 36.1% of the districts in India had stunting prevalence 40% or more, with 67.0% districts in the low SDI states group and only 1.1% districts in the high SDI states with this level of stunting. The prevalence of stunting declined significantly from 2010 to 2017 in 98.5% of the districts with a maximum decline of 41.2% (95% UI 40.3–42.5), wasting in 61.3% with a maximum decline of 44.0% (95% UI 42.3–46.7), and underweight in 95.0% with a maximum decline of 53.9% (95% UI 52.8–55.4). The CV varied 7.4-fold for stunting, 12.2-fold for wasting, and 8.6-fold for underweight between the states in 2017; the CV increased for stunting in 28 out of 31 states, for wasting in 16 states, and for underweight in 20 states from 2000 to 2017. In order to reach the NNM 2022 targets for stunting and underweight individually, 82.6% and 98.5% of the districts in India would need a rate of improvement higher than they had up to 2017, respectively. To achieve the WHO/UNICEF 2030 target for wasting, all districts in India would need a rate of improvement higher than they had up to 2017. The correlation between the two national surveys for district-level estimates was poor, with Pearson correlation coefficient of 0.7 only in Odisha and four small north-eastern states out of the 27 states covered by these surveys. Interpretation CGF indicators have improved in India, but there are substantial variations between the districts in their magnitude and rate of decline, and the inequality between districts has increased in a large proportion of the states. The poor correlation between the national surveys for CGF estimates highlights the need to standardise collection of anthropometric data in India. The district-level trends in this report provide a useful reference for targeting the efforts under NNM to reduce CGF across India and meet the Indian and global targets. Keywords Child growth failureDistrict-levelGeospatial mappingInequalityNational Nutrition MissionPrevalenceStuntingTime trendsUnder-fiveUndernutritionUnderweightWastingWHO/UNICEF target

Mapping development and health effects of cooking with solid fuels in low-income and middle-income countries, 2000–18: a geospatial modelling study

Background: More than 3 billion people do not have access to clean energy and primarily use solid fuels to cook. Use of solid fuels generates household air pollution, which was associated with more than 2 million deaths in 2019. Although local patterns in cooking vary systematically, subnational trends in use of solid fuels have yet to be comprehensively analysed. We estimated the prevalence of solid-fuel use with high spatial resolution to explore subnational inequalities, assess local progress, and assess the effects on health in low-income and middle-income countries (LMICs) without universal access to clean fuels. Methods: We did a geospatial modelling study to map the prevalence of solid-fuel use for cooking at a 5 km × 5 km resolution in 98 LMICs based on 2·1 million household observations of the primary cooking fuel used from 663 population-based household surveys over the years 2000 to 2018. We use observed temporal patterns to forecast household air pollution in 2030 and to assess the probability of attaining the Sustainable Development Goal (SDG) target indicator for clean cooking. We aligned our estimates of household air pollution to geospatial estimates of ambient air pollution to establish the risk transition occurring in LMICs. Finally, we quantified the effect of residual primary solid-fuel use for cooking on child health by doing a counterfactual risk assessment to estimate the proportion of deaths from lower respiratory tract infections in children younger than 5 years that could be associated with household air pollution. Findings: Although primary reliance on solid-fuel use for cooking has declined globally, it remains widespread. 593 million people live in districts where the prevalence of solid-fuel use for cooking exceeds 95%. 66% of people in LMICs live in districts that are not on track to meet the SDG target for universal access to clean energy by 2030. Household air pollution continues to be a major contributor to particulate exposure in LMICs, and rising ambient air pollution is undermining potential gains from reductions in the prevalence of solid-fuel use for cooking in many countries. We estimated that, in 2018, 205 000 (95% uncertainty interval 147 000–257 000) children younger than 5 years died from lower respiratory tract infections that could be attributed to household air pollution. Interpretation: Efforts to accelerate the adoption of clean cooking fuels need to be substantially increased and recalibrated to account for subnational inequalities, because there are substantial opportunities to improve air quality and avert child mortality associated with household air pollution. Funding: Bill & Melinda Gates Foundation

Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990–2015: a systematic analysis for the Global Burden of Disease Study 2015

Background The Global Burden of Diseases, Injuries, and Risk Factors Study 2015 provides an up-to-date synthesis of the evidence for risk factor exposure and the attributable burden of disease. By providing national and subnational assessments spanning the past 25 years, this study can inform debates on the importance of addressing risks in context. Methods We used the comparative risk assessment framework developed for previous iterations of the Global Burden of Disease Study to estimate attributable deaths, disability-adjusted life-years (DALYs), and trends in exposure by age group, sex, year, and geography for 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks from 1990 to 2015. This study included 388 risk-outcome pairs that met World Cancer Research Fund-defi ned criteria for convincing or probable evidence. We extracted relative risk and exposure estimates from randomised controlled trials, cohorts, pooled cohorts, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. We developed a metric that allows comparisons of exposure across risk factors—the summary exposure value. Using the counterfactual scenario of theoretical minimum risk level, we estimated the portion of deaths and DALYs that could be attributed to a given risk. We decomposed trends in attributable burden into contributions from population growth, population age structure, risk exposure, and risk-deleted cause-specifi c DALY rates. We characterised risk exposure in relation to a Socio-demographic Index (SDI).Background The Global Burden of Diseases, Injuries, and Risk Factors Study 2015 provides an up-to-date synthesis of the evidence for risk factor exposure and the attributable burden of disease. By providing national and subnational assessments spanning the past 25 years, this study can inform debates on the importance of addressing risks in context. Methods We used the comparative risk assessment framework developed for previous iterations of the Global Burden of Disease Study to estimate attributable deaths, disability-adjusted life-years (DALYs), and trends in exposure by age group, sex, year, and geography for 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks from 1990 to 2015. This study included 388 risk-outcome pairs that met World Cancer Research Fund-defi ned criteria for convincing or probable evidence. We extracted relative risk and exposure estimates from randomised controlled trials, cohorts, pooled cohorts, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. We developed a metric that allows comparisons of exposure across risk factors—the summary exposure value. Using the counterfactual scenario of theoretical minimum risk level, we estimated the portion of deaths and DALYs that could be attributed to a given risk. We decomposed trends in attributable burden into contributions from population growth, population age structure, risk exposure, and risk-deleted cause-specifi c DALY rates. We characterised risk exposure in relation to a Socio-demographic Index (SDI)