Diagnosing destabilization risk in global land carbon sinks.

Global net land carbon uptake or net biome production (NBP) has increased during recent decades1. Whether its temporal variability and autocorrelation have changed during this period, however, remains elusive, even though an increase in both could indicate an increased potential for a destabilized carbon sink2,3. Here, we investigate the trends and controls of net terrestrial carbon uptake and its temporal variability and autocorrelation from 1981 to 2018 using two atmospheric-inversion models, the amplitude of the seasonal cycle of atmospheric CO2 concentration derived from nine monitoring stations distributed across the Pacific Ocean and dynamic global vegetation models. We find that annual NBP and its interdecadal variability increased globally whereas temporal autocorrelation decreased. We observe a separation of regions characterized by increasingly variable NBP, associated with warm regions and increasingly variable temperatures, lower and weaker positive trends in NBP and regions where NBP became stronger and less variable. Plant species richness presented a concave-down parabolic spatial relationship with NBP and its variability at the global scale whereas nitrogen deposition generally increased NBP. Increasing temperature and its increasing variability appear as the most important drivers of declining and increasingly variable NBP. Our results show increasing variability of NBP regionally that can be mostly attributed to climate change and that may point to destabilization of the coupled carbon-climate system.

Widespread seasonal compensation effects of spring warming on northern plant productivity.

Climate change is shifting the phenological cycles of plants1, thereby altering the functioning of ecosystems, which in turn induces feedbacks to the climate system2. In northern (north of 30° N) ecosystems, warmer springs lead generally to an earlier onset of the growing season3,4 and increased ecosystem productivity early in the season5. In situ6 and regional7-9 studies also provide evidence for lagged effects of spring warmth on plant productivity during the subsequent summer and autumn. However, our current understanding of these lagged effects, including their direction (beneficial or adverse) and geographic distribution, is still very limited. Here we analyse satellite, field-based and modelled data for the period 1982-2011 and show that there are widespread and contrasting lagged productivity responses to spring warmth across northern ecosystems. On the basis of the observational data, we find that roughly 15 per cent of the total study area of about 41 million square kilometres exhibits adverse lagged effects and that roughly 5 per cent of the total study area exhibits beneficial lagged effects. By contrast, current-generation terrestrial carbon-cycle models predict much lower areal fractions of adverse lagged effects (ranging from 1 to 14 per cent) and much higher areal fractions of beneficial lagged effects (ranging from 9 to 54 per cent). We find that elevation and seasonal precipitation patterns largely dictate the geographic pattern and direction of the lagged effects. Inadequate consideration in current models of the effects of the seasonal build-up of water stress on seasonal vegetation growth may therefore be able to explain the differences that we found between our observation-constrained estimates and the model-constrained estimates of lagged effects associated with spring warming. Overall, our results suggest that for many northern ecosystems the benefits of warmer springs on growing-season ecosystem productivity are effectively compensated for by the accumulation of seasonal water deficits, despite the fact that northern ecosystems are thought to be largely temperature- and radiation-limited10.

Multi-criteria decision making to validate performance of RBC-based formulae to screen [Formula: see text]-thalassemia trait in heterogeneous haemoglobinopathies.

BACKGROUND: India has the most significant number of children with thalassemia major worldwide, and about 10,000-15,000 children with the disease are born yearly. Scaling up e-health initiatives in rural areas using a cost-effective digital tool to provide healthcare access for all sections of people remains a challenge for government or semi-governmental institutions and agencies. METHODS: We compared the performance of a recently developed formula SCS[Formula: see text] and its web application SUSOKA with 42 discrimination formulae presently available in the literature. 6,388 samples were collected from the Postgraduate Institute of Medical Education and Research, Chandigarh, in North-Western India. Performances of the formulae were evaluated by eight different measures: sensitivity, specificity, Youden's Index, AUC-ROC, accuracy, positive predictive value, negative predictive value, and false omission rate. Three multi-criteria decision-making (MCDM) methods, TOPSIS, COPRAS, and SECA, were implemented to rank formulae by ensuring a trade-off among the eight measures. RESULTS: MCDM methods revealed that the Shine & Lal and SCS[Formula: see text] were the best-performing formulae. Further, a modification of the SCS[Formula: see text] formula was proposed, and validation was conducted with a data set containing 939 samples collected from Nil Ratan Sircar (NRS) Medical College and Hospital, Kolkata, in Eastern India. Our two-step approach emphasized the necessity of a molecular diagnosis for a lower number of the population. SCS[Formula: see text] along with the condition MCV[Formula: see text] 80 fl was recommended for a higher heterogeneous population set. It was found that SCS[Formula: see text] can classify all BTT samples with 100% sensitivity when MCV[Formula: see text] 80 fl. CONCLUSIONS: We addressed the issue of how to integrate the higher-ranked formulae in mass screening to ensure higher performance through the MCDM approach. In real-life practice, it is sufficient for a screening algorithm to flag a particular sample as requiring or not requiring further specific confirmatory testing. Implementing discriminate functions in routine screening programs allows early identification; consequently, the cost will decrease, and the turnaround time in everyday workflows will also increase. Our proposed two-step procedure expedites such a process. It is concluded that for mass screening of BTT in a heterogeneous set of data, SCS[Formula: see text] and its web application SUSOKA can provide 100% sensitivity when MCV[Formula: see text] 80 fl.

Global patterns of drought recovery.

Drought, a recurring phenomenon with major impacts on both human and natural systems, is the most widespread climatic extreme that negatively affects the land carbon sink. Although twentieth-century trends in drought regimes are ambiguous, across many regions more frequent and severe droughts are expected in the twenty-first century. Recovery time-how long an ecosystem requires to revert to its pre-drought functional state-is a critical metric of drought impact. Yet the factors influencing drought recovery and its spatiotemporal patterns at the global scale are largely unknown. Here we analyse three independent datasets of gross primary productivity and show that, across diverse ecosystems, drought recovery times are strongly associated with climate and carbon cycle dynamics, with biodiversity and CO2 fertilization as secondary factors. Our analysis also provides two key insights into the spatiotemporal patterns of drought recovery time: first, that recovery is longest in the tropics and high northern latitudes (both vulnerable areas of Earth's climate system) and second, that drought impacts (assessed using the area of ecosystems actively recovering and time to recovery) have increased over the twentieth century. If droughts become more frequent, as expected, the time between droughts may become shorter than drought recovery time, leading to permanently damaged ecosystems and widespread degradation of the land carbon sink.

Compensatory water effects link yearly global land CO2 sink changes to temperature.

Large interannual variations in the measured growth rate of atmospheric carbon dioxide (CO2) originate primarily from fluctuations in carbon uptake by land ecosystems. It remains uncertain, however, to what extent temperature and water availability control the carbon balance of land ecosystems across spatial and temporal scales. Here we use empirical models based on eddy covariance data and process-based models to investigate the effect of changes in temperature and water availability on gross primary productivity (GPP), terrestrial ecosystem respiration (TER) and net ecosystem exchange (NEE) at local and global scales. We find that water availability is the dominant driver of the local interannual variability in GPP and TER. To a lesser extent this is true also for NEE at the local scale, but when integrated globally, temporal NEE variability is mostly driven by temperature fluctuations. We suggest that this apparent paradox can be explained by two compensatory water effects. Temporal water-driven GPP and TER variations compensate locally, dampening water-driven NEE variability. Spatial water availability anomalies also compensate, leaving a dominant temperature signal in the year-to-year fluctuations of the land carbon sink. These findings help to reconcile seemingly contradictory reports regarding the importance of temperature and water in controlling the interannual variability of the terrestrial carbon balance. Our study indicates that spatial climate covariation drives the global carbon cycle response.

Quality by design-steered development and validation of analytical and bioanalytical methods for raloxifene: Application of Monte Carlo simulations and variance inflation factor.

A sensitive, rapid, reproducible, and economical HPLC method is reported for the quantification of raloxifene hydrochloride employing Quality by Design (QbD) principles. Factor screening studies, employing Taguchi design, indicated buffer volume percentage and isocratic flow rate as the critical method parameters (CMPs), which significantly influence the chosen critical analytical attributes, that is, tailing factor and theoretical plate number. Method conditions were subsequently optimized using face-centered cubic design with magnitude of variance inflation factor for assessing multicollinearity among CMPs. Method operable design region (MODR) was earmarked and liquid chromatographic separation optimized using 0.05 M citrate buffer, acetonitrile, and methanol (57:40:3 v/v/v) as ggmobile phase at 0.9 mL min-1 flow rate, λmax of 280 nm, and column temperature of 40°C. Validation of the developed analytical method was accomplished as per International Council on Harmonization (ICH) guidelines confirming high levels of linearity, precision, accuracy, robustness, and sensitivity. Application of Monte Carlo simulations enabled the attainment of best plausible chromatographic resolution and corroboration of the demarcated MODR. Establishment and validation of the bioanalytical method using rat plasma samples, along with forced degradation and stability studies, corroborated the aptness of developed HPLC methods for drug quantification in the biological fluids, as well as in bulk and marketed dosage forms.

Greening drylands despite warming consistent with carbon dioxide fertilization effect.

The rising atmospheric CO2 concentration leads to a CO2 fertilization effect on plants-that is, increased photosynthetic uptake of CO2 by leaves and enhanced water-use efficiency (WUE). Yet, the resulting net impact of CO2 fertilization on plant growth and soil moisture (SM) savings at large scale is poorly understood. Drylands provide a natural experimental setting to detect the CO2 fertilization effect on plant growth since foliage amount, plant water-use and photosynthesis are all tightly coupled in water-limited ecosystems. A long-term change in the response of leaf area index (LAI, a measure of foliage amount) to changes in SM is likely to stem from changing water demand of primary productivity in water-limited ecosystems and is a proxy for changes in WUE. Using 34-year satellite observations of LAI and SM over tropical and subtropical drylands, we identify that a 1% increment in SM leads to 0.15% (±0.008, 95% confidence interval) and 0.51% (±0.01, 95% confidence interval) increments in LAI during 1982-1998 and 1999-2015, respectively. The increasing response of LAI to SM has contributed 7.2% (±3.0%, 95% confidence interval) to total dryland greening during 1999-2015 compared to 1982-1998. The increasing response of LAI to SM is consistent with the CO2 fertilization effect on WUE in water-limited ecosystems, indicating that a given amount of SM has sustained greater amounts of photosynthetic foliage over time. The LAI responses to changes in SM from seven dynamic global vegetation models are not always consistent with observations, highlighting the need for improved process knowledge of terrestrial ecosystem responses to rising atmospheric CO2 concentration.

Causes of slowing-down seasonal CO2 amplitude at Mauna Loa.

Changing amplitude of the seasonal cycle of atmospheric CO2 (SCA) in the northern hemisphere is an emerging carbon cycle property. Mauna Loa (MLO) station (20°N, 156°W), which has the longest continuous northern hemisphere CO2 record, shows an increasing SCA before the 1980s (p < .01), followed by no significant change thereafter. We analyzed the potential driving factors of SCA slowing-down, with an ensemble of dynamic global vegetation models (DGVMs) coupled with an atmospheric transport model. We found that slowing-down of SCA at MLO is primarily explained by response of net biome productivity (NBP) to climate change, and by changes in atmospheric circulations. Through NBP, climate change increases SCA at MLO before the 1980s and decreases it afterwards. The effect of climate change on the slowing-down of SCA at MLO is mainly exerted by intensified drought stress acting to offset the acceleration driven by CO2 fertilization. This challenges the view that CO2 fertilization is the dominant cause of emergent SCA trends at northern sites south of 40°N. The contribution of agricultural intensification on the deceleration of SCA at MLO was elusive according to land-atmosphere CO2 flux estimated by DGVMs and atmospheric inversions. Our results also show the necessity to adequately account for changing circulation patterns in understanding carbon cycle dynamics observed from atmospheric observations and in using these observations to benchmark DGVMs.

State of the science in reconciling top-down and bottom-up approaches for terrestrial CO2 budget.

Robust estimates of CO2 budget, CO2 exchanged between the atmosphere and terrestrial biosphere, are necessary to better understand the role of the terrestrial biosphere in mitigating anthropogenic CO2 emissions. Over the past decade, this field of research has advanced through understanding of the differences and similarities of two fundamentally different approaches: "top-down" atmospheric inversions and "bottom-up" biosphere models. Since the first studies were undertaken, these approaches have shown an increasing level of agreement, but disagreements in some regions still persist, in part because they do not estimate the same quantity of atmosphere-biosphere CO2 exchange. Here, we conducted a thorough comparison of CO2 budgets at multiple scales and from multiple methods to assess the current state of the science in estimating CO2 budgets. Our set of atmospheric inversions and biosphere models, which were adjusted for a consistent flux definition, showed a high level of agreement for global and hemispheric CO2 budgets in the 2000s. Regionally, improved agreement in CO2 budgets was notable for North America and Southeast Asia. However, large gaps between the two methods remained in East Asia and South America. In other regions, Europe, boreal Asia, Africa, South Asia, and Oceania, it was difficult to determine whether those regions act as a net sink or source because of the large spread in estimates from atmospheric inversions. These results highlight two research directions to improve the robustness of CO2 budgets: (a) to increase representation of processes in biosphere models that could contribute to fill the budget gaps, such as forest regrowth and forest degradation; and (b) to reduce sink-source compensation between regions (dipoles) in atmospheric inversion so that their estimates become more comparable. Advancements on both research areas will increase the level of agreement between the top-down and bottom-up approaches and yield more robust knowledge of regional CO2 budgets.

Global vegetation biomass production efficiency constrained by models and observations.

Plants use only a fraction of their photosynthetically derived carbon for biomass production (BP). The biomass production efficiency (BPE), defined as the ratio of BP to photosynthesis, and its variation across and within vegetation types is poorly understood, which hinders our capacity to accurately estimate carbon turnover times and carbon sinks. Here, we present a new global estimation of BPE obtained by combining field measurements from 113 sites with 14 carbon cycle models. Our best estimate of global BPE is 0.41 ± 0.05, excluding cropland. The largest BPE is found in boreal forests (0.48 ± 0.06) and the lowest in tropical forests (0.40 ± 0.04). Carbon cycle models overestimate BPE, although models with carbon-nitrogen interactions tend to be more realistic. Using observation-based estimates of global photosynthesis, we quantify the global BP of non-cropland ecosystems of 41 ± 6 Pg C/year. This flux is less than net primary production as it does not contain carbon allocated to symbionts, used for exudates or volatile carbon compound emissions to the atmosphere. Our study reveals a positive bias of 24 ± 11% in the model-estimated BP (10 of 14 models). When correcting models for this bias while leaving modeled carbon turnover times unchanged, we found that the global ecosystem carbon storage change during the last century is decreased by 67% (or 58 Pg C).

Climate-Driven Variability and Trends in Plant Productivity Over Recent Decades Based on Three Global Products.

Variability in climate exerts a strong influence on vegetation productivity (gross primary productivity; GPP), and therefore has a large impact on the land carbon sink. However, no direct observations of global GPP exist, and estimates rely on models that are constrained by observations at various spatial and temporal scales. Here, we assess the consistency in GPP from global products which extend for more than three decades; two observation-based approaches, the upscaling of FLUXNET site observations (FLUXCOM) and a remote sensing derived light use efficiency model (RS-LUE), and from a suite of terrestrial biosphere models (TRENDYv6). At local scales, we find high correlations in annual GPP among the products, with exceptions in tropical and high northern latitudes. On longer time scales, the products agree on the direction of trends over 58% of the land, with large increases across northern latitudes driven by warming trends. Further, tropical regions exhibit the largest interannual variability in GPP, with both rainforests and savannas contributing substantially. Variability in savanna GPP is likely predominantly driven by water availability, although temperature could play a role via soil moisture-atmosphere feedbacks. There is, however, no consensus on the magnitude and driver of variability of tropical forests, which suggest uncertainties in process representations and underlying observations remain. These results emphasize the need for more direct long-term observations of GPP along with an extension of in situ networks in underrepresented regions (e.g., tropical forests). Such capabilities would support efforts to better validate relevant processes in models, to more accurately estimate GPP.

Stimuli Responsive In Situ Gelling Systems Loaded with PLGA Nanoparticles of Moxifloxacin Hydrochloride for Effective Treatment of Periodontitis.

The objectives of the present research work were systematic development of novel in situ gel formulation containing nanoparticles for localised delivery of moxifloxacin against bacterial periodontitis. PLGA nanoparticles were prepared and optimised in a systematic manner. Factor screening was performed with the help of half-factorial design to identify the influential factors, while response surface optimisation of the nanoparticles was conducted using central composite design. The optimum nanoparticle formulation was chosen on the basis of lower particle size, higher drug entrapment and controlled drug release characteristics up to 1 week time period, while the optimum in situ gel was selected on the basis of faster gelling and higher viscosity and gel strength properties for improved retention in the periodontium. In vivo histopathological studies and in vivo gamma scintigraphy studies revealed the extended release, superior efficacy and enhanced retention of nanoparticle-loaded in situ gelling system. Results obtained from in vivo histopathological studies after 1 week treatment with in situ gel formulation containing nanoparticles of moxifloxacin were found to be better than with 3 weeks treatment of marketed gel formulation. Overall, the studies ratify successful development of an effective site-specific drug delivery system with enhanced biopharmaceutical attributes for the periodontitis treatment.

Quantifying the biophysical and socioeconomic drivers of changes in forest and agricultural land in South and Southeast Asia.

South and Southeast Asia (SSEA) has been a hotspot for land use and land cover change (LULCC) in the past few decades. The identification and quantification of the drivers of LULCC are crucial for improving our understanding of LULCC trends. So far, the biophysical and socioeconomic drivers of forest change have not been quantified at the regional scale, particularly for SSEA. In this study, we quantify the biophysical and socioeconomic drivers of forest change on a country-by-country basis in SSEA using an integrated quantitative methodology, which systematically accounts for previously published driver information and regional datasets. We synthesize more than 200 publications to identify the drivers of the forest change at different spatial scales in SSEA. Subsequently, we collect spatially explicit proxy data to represent the identified drivers. We quantify the dynamics of forest and agricultural land from 1992 to 2015 using the Climate Change Initiative (CCI) land cover data developed by the European Space Agency (ESA). A geographically weighted regression method is employed to quantify the spatially heterogeneous drivers of forest change. Our results show that socioeconomic drivers are more important than biophysical drivers for the conversion of forest to agricultural land in South Asia and maritime Southeast Asia. In contrast, biophysical drivers are more important than socioeconomic drivers for the conversion of agricultural land to forest in maritime Southeast Asia and less important in South Asia. Both biophysical and socioeconomic drivers contribute approximately equally to both changes in the mainland Southeast Asia region. By quantifying the dynamics of forest and agricultural land and the spatially explicit drivers of their changes in SSEA, this study provides a solid foundation for LULCC modeling and projection.

Development of a validated liquid chromatographic method for quantification of sorafenib tosylate in the presence of stress-induced degradation products and in biological matrix employing analytical quality by design approach.

The current research work envisages an analytical quality by design-enabled development of a simple, rapid, sensitive, specific, robust and cost-effective stability-indicating reversed-phase high-performance liquid chromatographic method for determining stress-induced forced-degradation products of sorafenib tosylate (SFN). An Ishikawa fishbone diagram was constructed to embark upon analytical target profile and critical analytical attributes, i.e. peak area, theoretical plates, retention time and peak tailing. Factor screening using Taguchi orthogonal arrays and quality risk assessment studies carried out using failure mode effect analysis aided the selection of critical method parameters, i.e. mobile phase ratio and flow rate potentially affecting the chosen critical analytical attributes. Systematic optimization using response surface methodology of the chosen critical method parameters was carried out employing a two-factor-three-level-13-run, face-centered cubic design. A method operable design region was earmarked providing optimum method performance using numerical and graphical optimization. The optimum method employed a mobile phase composition consisting of acetonitrile and water (containing orthophosphoric acid, pH 4.1) at 65:35 v/v at a flow rate of 0.8 mL/min with UV detection at 265 nm using a C18 column. Response surface methodology validation studies confirmed good efficiency and sensitivity of the developed method for analysis of SFN in mobile phase as well as in human plasma matrix. The forced degradation studies were conducted under different recommended stress conditions as per ICH Q1A (R2). Mass spectroscopy studies showed that SFN degrades in strongly acidic, alkaline and oxidative hydrolytic conditions at elevated temperature, while the drug was per se found to be photostable. Oxidative hydrolysis using 30% H2 O2 showed maximum degradation with products at retention times of 3.35, 3.65, 4.20 and 5.67 min. The absence of any significant change in the retention time of SFN and degradation products, formed under different stress conditions, ratified selectivity and specificity of the systematically developed method.

Novel pathomorphologic classification of capsulo-articular lesions of the pubic symphysis in athletes to predict treatment and outcome.

INTRODUCTION: Radiographic abnormalities of the symphysis as well as the formation of accessory clefts, indicating injury at the rectus-adductor aponeurosis, reportedly relate to longstanding groin pain in athletes. However, yet, no systematic classification for clinical and scientific purposes exists. We aimed to (1) create a radiographic classification based on symphysography; (2) test intra- and interobserver reliability; (3) characterise clinical significance of the morphologic patterns by evaluating success of injection therapy. PATIENTS AND METHODS: We retrospectively reviewed symphysography, AP radiographs, and MRI of the pelvis from 70 consecutive competitive athletes, with chronic groin pain. Symphysographs were evaluated for intra- and interobserver variance using cohen's kappa statistics. Morphologic studies of the different contrast distribution patterns and their clinical and radiological correlation with symptom relief were investigated. All patients were followed up to evaluate immediate and long-term response to the initial therapeutic injection with steroid. RESULTS: Four reproducible symphysographic patterns were identified: type 0, no changes; type 1, symphyseal disk degeneration; types 2a with unilateral clefts, bilateral clefts (2b), suprapubic clefts (2c); and type 3, with expanded or multidirectional clefts. Analysis revealed excellent intra (0.94)-and interobserver (0.90) reliability. Our findings showed that 78.6% of our patients had significant short-term improvement enabling early resumption of physiotherapy, only in types 1 and 2 (p = 0.001), while type 0 and 3 did not respond. At follow-up, only 21.8% had permanent pain relief. Regarding the detection of pathologic clefts with symphysography, sensitivity (88%) and specifity (77%) were superior to that of MRI. CONCLUSIONS: A reproducible symphysography-based classification of distinct morphologic patterns is proposed. It serves as a predictive tool for response to injection therapy in a select group of pathologic lesions. Complete recovery after injection can only be expected in a lesser percentage, as this might indicate surgical treatment for long-term non-responders.

Challenging terrestrial biosphere models with data from the long-term multifactor Prairie Heating and CO2 Enrichment experiment.

Multifactor experiments are often advocated as important for advancing terrestrial biosphere models (TBMs), yet to date, such models have only been tested against single-factor experiments. We applied 10 TBMs to the multifactor Prairie Heating and CO2 Enrichment (PHACE) experiment in Wyoming, USA. Our goals were to investigate how multifactor experiments can be used to constrain models and to identify a road map for model improvement. We found models performed poorly in ambient conditions; there was a wide spread in simulated above-ground net primary productivity (range: 31-390 g C m-2  yr-1 ). Comparison with data highlighted model failures particularly with respect to carbon allocation, phenology, and the impact of water stress on phenology. Performance against the observations from single-factors treatments was also relatively poor. In addition, similar responses were predicted for different reasons across models: there were large differences among models in sensitivity to water stress and, among the N cycle models, N availability during the experiment. Models were also unable to capture observed treatment effects on phenology: they overestimated the effect of warming on leaf onset and did not allow CO2 -induced water savings to extend the growing season length. Observed interactive (CO2  × warming) treatment effects were subtle and contingent on water stress, phenology, and species composition. As the models did not correctly represent these processes under ambient and single-factor conditions, little extra information was gained by comparing model predictions against interactive responses. We outline a series of key areas in which this and future experiments could be used to improve model predictions of grassland responses to global change.

Assessing uncertainties in land cover projections.

Understanding uncertainties in land cover projections is critical to investigating land-based climate mitigation policies, assessing the potential of climate adaptation strategies and quantifying the impacts of land cover change on the climate system. Here, we identify and quantify uncertainties in global and European land cover projections over a diverse range of model types and scenarios, extending the analysis beyond the agro-economic models included in previous comparisons. The results from 75 simulations over 18 models are analysed and show a large range in land cover area projections, with the highest variability occurring in future cropland areas. We demonstrate systematic differences in land cover areas associated with the characteristics of the modelling approach, which is at least as great as the differences attributed to the scenario variations. The results lead us to conclude that a higher degree of uncertainty exists in land use projections than currently included in climate or earth system projections. To account for land use uncertainty, it is recommended to use a diverse set of models and approaches when assessing the potential impacts of land cover change on future climate. Additionally, further work is needed to better understand the assumptions driving land use model results and reveal the causes of uncertainty in more depth, to help reduce model uncertainty and improve the projections of land cover.

Time-Gated Detection of Cystathionine γ-Lyase Activity and Inhibition with a Selective, Luminogenic Hydrogen Sulfide Sensor.

Herein, we report the design, synthesis, and characterization of a lanthanideIII complex-based probe for the time-gated luminescence detection of hydrogen sulfide (H2 S) in aqueous media. The probe's unique sensing mechanism relies on the selective reduction of azide to amine by sulfide, followed by intramolecular cyclization to form a quinolinone. The quinolinone is a sensitizer that absorbs near-UV light and transfers excitation energy to coordinated TbIII or EuIII ions to trigger a strong "turn-on" luminescence response with ms-scale lifetimes characteristic of lanthanide complexes. Using this probe, we developed a robust, high throughput screening (HTS) assay for detecting H2 S generated by cystathionine γ-lyase (CSE), one of the main producers of H2 S in mammalian cells. In a 240-compound screen to identify potential CSE inhibitors, the EuIII analogue of the sensor showed a low false-positive rate and high Z'-factor (>0.7).

Dynamics and determinants of land change in India: integrating satellite data with village socioeconomics.

We examine the dynamics and spatial determinants of land change in India by integrating decadal land cover maps (1985-1995-2005) from a wall-to-wall analysis of Landsat images with spatiotemporal socioeconomic database for ~630,000 villages in India. We reinforce our results through collective evidence from synthesis of 102 case studies that incorporate field knowledge of the causes of land change in India. We focus on cropland-fallow land conversions, and forest area changes (excludes non-forest tree categories including commercial plantations). We show that cropland to fallow conversions are prominently associated with lack of irrigation and capital, male agricultural labor shortage, and fragmentation of land holdings. We find gross forest loss is substantial and increased from ~23,810 km2 (1985-1995) to ~25,770 km2 (1995-2005). The gross forest gain also increased from ~6000 km2 (1985-1995) to ~7440 km2 (1995-2005). Overall, India experienced a net decline in forest by ~18,000 km2 (gross loss-gross gain) consistently during both decades. We show that the major source of forest loss was cropland expansion in areas of low cropland productivity (due to soil degradation and lack of irrigation), followed by industrial development and mining/quarrying activities, and excessive economic dependence of villages on forest resources.

Influence of Television Advertising on Behavior of Children across Socioeconomic Backgrounds.

INTRODUCTION: This research analyzed the influence of television on the behavior of children belonging to urban and rural socioeconomic backgrounds of Bhopal city and its vicinity. MATERIALS AND METHODS: About 400 parents with children between 1 and 18 years of age were subjected to a self-designed questionnaire, which sought information regarding the television viewing habits of children. Differences in responses were noted between the subjects of urban and rural areas. Obtained data were subjected to statistical analysis using Pearson's chi-square test to determine the level of significance. RESULTS: The urban class showed a dominating pattern in the positive aspects of television viewing, such as significantly better awareness of oral health, more emphasis shown toward oral care adverts, and a higher knowledge of the cause of dental caries. However, the urban class also possessed a poor attitude; the appearance of a dentist on television did not remind them about oral needs, products with gifts pleased their children to a greater extent, they had more demanding children, parents fulfilled their children's demand more, and they relied on the self for selection of toothpaste. Overall, in all aspects, the rural class lacked significantly. CONCLUSION: Television exerts a positive as well as negative influence on children's behavior among urban and rural communities, with the influence being more obvious in the urban class. CLINICAL SIGNIFICANCE: The results of this study can be utilized in bringing about better and effective advertising oriented toward attaining optimum oral health of children; overall general health through adverts that discourage obesogenic diet and promote a diet rich in protein and fiber can also be focused on.