Using machine learning to improve the diagnostic accuracy of the modified Duke/ESC 2015 criteria in patients with suspected prosthetic valve endocarditis - a proof of concept study.

INTRODUCTION: Prosthetic valve endocarditis (PVE) is a serious complication of prosthetic valve implantation, with an estimated yearly incidence of at least 0.4-1.0%. The Duke criteria and subsequent modifications have been developed as a diagnostic framework for infective endocarditis (IE) in clinical studies. However, their sensitivity and specificity are limited, especially for PVE. Furthermore, their most recent versions (ESC2015 and ESC2023) include advanced imaging modalities, e.g., cardiac CTA and [18F]FDG PET/CT as major criteria. However, despite these significant changes, the weighing system using major and minor criteria has remained unchanged. This may have introduced bias to the diagnostic set of criteria. Here, we aimed to evaluate and improve the predictive value of the modified Duke/ESC 2015 (MDE2015) criteria by using machine learning algorithms. METHODS: In this proof-of-concept study, we used data of a well-defined retrospective multicentre cohort of 160 patients evaluated for suspected PVE. Four machine learning algorithms were compared to the prediction of the diagnosis according to the MDE2015 criteria: Lasso logistic regression, decision tree with gradient boosting (XGBoost), decision tree without gradient boosting, and a model combining predictions of these (ensemble learning). All models used the same features that also constitute the MDE2015 criteria. The final diagnosis of PVE, based on endocarditis team consensus using all available clinical information, including surgical findings whenever performed, and with at least 1 year follow up, was used as the composite gold standard. RESULTS: The diagnostic performance of the MDE2015 criteria varied depending on how the category of 'possible' PVE cases were handled. Considering these cases as positive for PVE, sensitivity and specificity were 0.96 and 0.60, respectively. Whereas treating these cases as negative, sensitivity and specificity were 0.74 and 0.98, respectively. Combining the approaches of considering possible endocarditis as positive and as negative for ROC-analysis resulted in an excellent AUC of 0.917. For the machine learning models, the sensitivity and specificity were as follows: logistic regression, 0.92 and 0.85; XGBoost, 0.90 and 0.85; decision trees, 0.88 and 0.86; and ensemble learning, 0.91 and 0.85, respectively. The resulting AUCs were, in the same order: 0.938, 0.937, 0.930, and 0.941, respectively. DISCUSSION: In this proof-of-concept study, machine learning algorithms achieved improved diagnostic performance compared to the major/minor weighing system as used in the MDE2015 criteria. Moreover, these models provide quantifiable certainty levels of the diagnosis, potentially enhancing interpretability for clinicians. Additionally, they allow for easy incorporation of new and/or refined criteria, such as the individual weight of advanced imaging modalities such as CTA or [18F]FDG PET/CT. These promising preliminary findings warrant further studies for validation, ideally in a prospective cohort encompassing the full spectrum of patients with suspected IE.

Improved [18F]FDG PET/CT Diagnostic Accuracy for Infective Endocarditis Using Conventional Cardiac Gating or Combined Cardiac and Respiratory Motion Correction (CardioFreezeTM).

Infective endocarditis (IE) is a serious and diagnostically challenging condition. [18F]FDG PET/CT is valuable for evaluating suspected IE, but it is susceptible to motion-related artefacts. This study investigated the potential benefits of cardiac motion correction for [18F]FDG PET/CT. In this prospective study, patients underwent [18F]FDG PET/CT for suspected IE, combined with a conventional cardiac gating sequence, a data-driven cardiac and respiratory gating sequence (CardioFreezeTM), or both. Scans were performed in adherence to EANM guidelines and assessors were blinded to patients' clinical contexts. Final diagnosis of IE was established based on multidisciplinary consensus after a minimum of 4 months follow-up and surgical findings, whenever performed. Seven patients participated in the study, undergoing both an ungated [18F] FDG-PET/CT and a scan with either conventional cardiac gating, CardioFreezeTM, or both. Cardiac motion correction improved the interpretability of [18F]FDG PET/CT in four out of five patients with valvular IE lesions, regardless of the method of motion correction used, which was statistically significant by Wilcoxon's signed rank test: p = 0.046. In one patient the motion-corrected sequence confirmed the diagnosis of endocarditis, which had been missed on non-gated PET. The performance of the two gating sequences was comparable. In conclusion, in this exploratory study, cardiac motion correction of [18F]FDG PET/CT improved the interpretability of [18F]FDG PET/CT. This may improve the sensitivity of PET/CT for suspected IE. Further larger comparative studies are necessary to confirm the additive value of these cardiac motion correction methods.

Genomic-regions associated with cold stress tolerance in Asia-adapted tropical maize germplasm.

Maize is gaining impetus in non-traditional and non-conventional seasons such as off-season, primarily due to higher demand and economic returns. Maize varieties directed for growing in the winter season of South Asia must have cold resilience as an important trait due to the low prevailing temperatures and frequent cold snaps observed during this season in most parts of the lowland tropics of Asia. The current study involved screening of a panel of advanced tropically adapted maize lines to cold stress during vegetative and flowering stage under field conditions. A suite of significant genomic loci (28) associated with grain yield along and agronomic traits such as flowering (15) and plant height (6) under cold stress environments. The haplotype regression revealed 6 significant haplotype blocks for grain yield under cold stress across the test environments. Haplotype blocks particularly on chromosomes 5 (bin5.07), 6 (bin6.02), and 9 (9.03) co-located to regions/bins that have been identified to contain candidate genes involved in membrane transport system that would provide essential tolerance to the plant. The regions on chromosome 1 (bin1.04), 2 (bin 2.07), 3 (bin 3.05-3.06), 5 (bin5.03), 8 (bin8.05-8.06) also harboured significant SNPs for the other agronomic traits. In addition, the study also looked at the plausibility of identifying tropically adapted maize lines from the working germplasm with cold resilience across growth stages and identified four lines that could be used as breeding starts in the tropical maize breeding pipelines.

Scientific advisory on nocturnal hypoglycemia in insulin-treated patients with diabetes: Recommendations from Indian experts.

INTRODUCTION: Insulin is one of the commonly prescribed glucose lowering agents in diabetes. Hypoglycemia is the most common complication, and severe hypoglycemia is the most serious complication of insulin therapy. Almost half of all severe hypoglycemia episodes (HEs) occur at night. However, patients are often unaware of their nocturnal hypoglycaemia (NH) risk. Additionally, both healthcare professionals and patients find it difficult to manage NH. The purpose of this expert group meeting is to improve NH awareness and provide guidance for the physicians to recognize and manage NH. METHOD: The panel of experts in an e-board deliberated extensively upon the available literature and guidelines on hypoglycemia and NH discussed the consensus on definition, detection, reporting, monitoring, treatment, and optimization of therapy in NH. RESULT: & Conclusion: Though there are many guidelines on the management of HEs in patients with diabetes, very few touch the topic of NH. This scientific advisory on management of NH in insulin treated patients with diabetes is formulated to address this gap in understanding regarding management of NH. The experts provide recommendations for the nocturnal window, defining NH based on blood glucose values, recognition, prevention and management of NH.

18F-FDG PET/CT in Infective Endocarditis: Indications and Approaches for Standardization.

PURPOSE OF REVIEW: Additional imaging modalities, such as FDG-PET/CT, have been included into the workup for patients with suspected infective endocarditis, according to major international guidelines published in 2015. The purpose of this review is to give an overview of FDG-PET/CT indications and standardized approaches in the setting of suspected infective endocarditis. RECENT FINDINGS: There are two main indications for performing FDG-PET/CT in patients with suspected infective endocarditis: (i) detecting intracardiac infections and (ii) detection of (clinically silent) disseminated infectious disease. The diagnostic performance of FDG-PET/CT for intracardiac lesions depends on the presence of native valves, prosthetic valves, or implanted cardiac devices, with a sensitivity that is poor for native valve endocarditis and cardiac device-related lead infections, but much better for prosthetic valve endocarditis and cardiac device-related pocket infections. Specificity is high for all these indications. The detection of disseminated disease may also help establish the diagnosis and/or impact patient management. Based on current evidence, FDG-PET/CT should be considered for detection of disseminated disease in suspected endocarditis. Absence of intracardiac lesions on FDG-PET/CT cannot rule out native valve endocarditis, but positive findings strongly support the diagnosis. For prosthetic valve endocarditis, standard use of FDG-PET/CT is recommended because of its high sensitivity and specificity. For implanted cardiac devices, FDG-PET/CT is also recommended, but should be evaluated with careful attention to clinical context, because its sensitivity is high for pocket infections, but low for lead infections. In patients with prosthetic valves with or without additional aortic prosthesis, combination with CTA should be considered. Optimal timing of FDG-PET/CT is important, both during clinical workup and technically (i.e., post tracer injection). In addition, procedural standardization is key and encompasses patient preparation, scan acquisition, reconstruction, subsequent analysis, and clinical interpretation. The recommendations discussed here will hopefully contribute to improved standardization and enhanced performance of FDG-PET/CT in the clinical management of patients with suspected infective endocarditis.

Genome-wide association mapping in maize: status and prospects.

Genome-wide association study (GWAS) provides a robust and potent tool to retrieve complex phenotypic traits back to their underlying genetics. Maize is an excellent crop for performing GWAS due to diverse genetic variability, rapid decay of linkage disequilibrium, availability of distinct sub-populations and abundant SNP information. The application of GWAS in maize has resulted in successful identification of thousands of genomic regions associated with many abiotic and biotic stresses. Many agronomic and quality traits of maize are severely affected by such stresses and, significantly affecting its growth and productivity. To improve productivity of maize crop in countries like India which contribute only 2% to the world's total production in 2019-2020, it is essential to understand genetic complexity of underlying traits. Various DNA markers and trait associations have been revealed using conventional linkage mapping methods. However, it has achieved limited success in improving polygenic complex traits due to lower resolution of trait mapping. The present review explores the prospects of GWAS in improving yield, quality and stress tolerance in maize besides, strengths and challenges of using GWAS for molecular breeding and genomic selection. The information gathered will facilitate elucidation of genetic mechanisms of complex traits and improve efficiency of marker-assisted selection in maize breeding. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s13205-021-02799-4.

Cropland trees need to be included for accurate model simulations of land-atmosphere heat fluxes, temperature, boundary layer height, and ozone.

Trees significantly impact land-atmosphere feedbacks through evapotranspiration, photosynthesis and isoprene emissions. These processes influence the local microclimate, air quality and can mitigate temperature extremes and sequester carbon dioxide. Despite such importance, currently only 5 out of 15 atmospheric chemistry climate models even partially account for the presence of cropland trees. We first show that the tree cover over intensely farmed regions in Asia, Australia and South America is significantly underestimated (e.g. only 1-3% tree cover over north-India) in the Model of Emissions of Gases and Aerosol from Nature (MEGAN) and absent in Noah land-surface module of the Weather Research and Forecasting (WRF-Chem) Model. By including the actual tree cover (~10%) over the north-west Indo Gangetic Plain in the Noah land-surface module of the WRF-Chem and the MEGAN module, during the rice growing monsoon season in August, we find that the latent heat flux alone increases by 100%-300% while sensible heat flux reduces by 50%-100%, leading to a reduction in daytime boundary layer height by 200-400 m. This greatly improves agreement between the modelled and measured temperature, boundary layer height and surface ozone, which were earlier overestimated and isoprene and its oxidation products which were earlier underestimated. Mitigating peak daytime temperatures and ozone improves rice production by 10 to 20%. Our findings from north west Indo-Gangetic Plain establish that such plantations mitigate heat stress, and have beneficial effects on crop yields while also sequestering carbon. Expanding agroforestry practices to 50% of the cropland area could result in up to 40% yield gain regionally. Implementing such strategies globally could increase crop production and sequester 0.3-30 GtC per year, and therefore future climate mitigation and food security efforts should consider stakeholder participation for increased cropland agroforestry in view of its beneficial effects.

The value of 18F-FDG PET/CT for the diagnosis of device-related infections in patients with a left ventricular assist device: a systematic review and meta-analysis.

BACKGROUND: Left ventricular assist devices (LVADs) are increasingly used for the treatment of advanced heart failure. LVADs improve quality of life and decrease mortality, but the driveline carries substantial risk for major infections. These device-related LVAD and driveline infections are difficult to diagnose with conventional imaging. We reviewed and analysed the current literature on the additive value of 18F-fluorodeoxyglucose positron emission tomography combined with computed tomography (FDG-PET/CT) imaging for the diagnosis of LVAD-related infections." MATERIALS/METHODS: We performed a systematic literature review using several databases from their inception until the 31st of December, 2019. Studies investigating the diagnostic performance of FDG-PET/CT in patients with suspected LVAD infection were retrieved. After a bias risk assessment using QUADAS-2, a study-aggregate meta-analysis was performed on a per examination-based analysis. RESULTS: A total of 10 studies were included in the systematic review, eight of which were also eligible for study-aggregate meta-analysis. For the meta-analysis, a total of 256 FDG-PET/CT scans, examining pump/pocket and/or driveline infection, were acquired in 230 patients. Pooled sensitivity of FDG-PET/CT was 0.95 (95% confidence interval (CI) 0.89-0.97) and pooled specificity was 0.91 (95% CI 0.54-0.99) for the diagnosis of device-related infection. For pump/pocket infection, sensitivity and specificity of FDG-PET/CT were 0.97 (95%CI 0.69-1.00) and 0.93 (95%CI 0.64-0.99), respectively. For driveline infection, sensitivity and specificity were 0.96 (95%CI 0.88-0.99) and 0.99 (95%CI 0.13-1.00) respectively. Significant heterogeneity existed across studies for specificity, mostly caused by differences in scan procedures. Predefined criteria for suspicion of LVAD and/or driveline infection were lacking in all included studies. CONCLUSIONS: FDG-PET/CT is a valuable tool for assessment of device-related infection in LVAD patients, with high sensitivity and high, albeit variable, specificity. Standardization of FDG-PET/CT procedures and criteria for suspected device-related LVAD infections are needed for consistent reporting of FDG-PET/CT scans.

[Hydroxychloroquine and chloroquine for COVID-19: no evidence of effectiveness]. / Hydroxychloroquine en chloroquine bij COVID-19.

On 3 March 2020, the document 'Drug treatment options for patients with COVID-19 (infections with SARS-CoV-2)' was published on the website of the Dutch Working Party on Antibiotic Policy (StichtingWerkgroepAntibioticabeleid, SWAB). Based on a 7-step analysis of the literature, hydroxychloroquine (HCQ) and chloroquine (CQ) were initially included in the SWAB document as possible drug treatments for hospitalised adult COVID-19 patients. However, recent weeks have seen the publication of the results of various studies into the effectiveness of treatment with HCQ and CQ in patients with COVID-19. On the basis of these results, we conclude that there is insufficient evidence to consider HCQ and CQ as meaningful treatment options in patients with COVID-19. Clinically relevant QTc prolongation occurs in at least 1 in 10 COVID-19 patients treated with HCQ or HQ.

Machine learning in infection management using routine electronic health records: tools, techniques, and reporting of future technologies.

BACKGROUND: Machine learning (ML) is increasingly being used in many areas of health care. Its use in infection management is catching up as identified in a recent review in this journal. We present here a complementary review to this work. OBJECTIVES: To support clinicians and researchers in navigating through the methodological aspects of ML approaches in the field of infection management. SOURCES: A Medline search was performed with the keywords artificial intelligence, machine learning, infection∗, and infectious disease∗ for the years 2014-2019. Studies using routinely available electronic hospital record data from an inpatient setting with a focus on bacterial and fungal infections were included. CONTENT: Fifty-two studies were included and divided into six groups based on their focus. These studies covered detection/prediction of sepsis (n = 19), hospital-acquired infections (n = 11), surgical site infections and other postoperative infections (n = 11), microbiological test results (n = 4), infections in general (n = 2), musculoskeletal infections (n = 2), and other topics (urinary tract infections, deep fungal infections, antimicrobial prescriptions; n = 1 each). In total, 35 different ML techniques were used. Logistic regression was applied in 18 studies followed by random forest, support vector machines, and artificial neural networks in 18, 12, and seven studies, respectively. Overall, the studies were very heterogeneous in their approach and their reporting. Detailed information on data handling and software code was often missing. Validation on new datasets and/or in other institutions was rarely done. Clinical studies on the impact of ML in infection management were lacking. IMPLICATIONS: Promising approaches for ML use in infectious diseases were identified. But building trust in these new technologies will require improved reporting. Explainability and interpretability of the models used were rarely addressed and should be further explored. Independent model validation and clinical studies evaluating the added value of ML approaches are needed.

Volatile organic compound measurements point to fog-induced biomass burning feedback to air quality in the megacity of Delhi.

We report the first ambient measurements of thirteen VOCs for investigations of emissions and air quality during fog and non-fog wintertime conditions at a tower site (28.57° N, 77.11° E, 220 m amsl) in the megacity of Delhi. Measurements of acetonitrile (biomass burning (BB) tracer), isoprene (biogenic emission tracer in daytime), toluene (a traffic exhaust tracer) and benzene (emitted from BB and traffic), together with soluble and reactive oxygenated VOCs such as methanol, acetone and acetaldehyde were performed during the winters of 2015-16 and 2016-17, using proton transfer reaction mass spectrometry. Remarkably, ambient VOC composition changes during fog were not governed by solubility. Acetaldehyde, toluene, sum of C8-aromatics (e.g. xylenes), sum of C9-aromatics (e.g. trimethyl benzenes) decreased by ≥30% (>95% confidence interval), whereas acetonitrile and benzene showed significant increases by 20% (>70% confidence interval), even after accounting for boundary layer dilution. During fog, the lower temperatures appeared to induce an emissions feedback from enhanced open BB within Delhi for warming, releasing both gaseous and aerosol pollutants with consequences for fog chemistry, sustenance and intensity. The potential feedback is important to consider for improving current emission parametrizations in models used for predicting air quality and fog in such atmospheric environments.

Nutritional composition, mineral content, antioxidant activity and quantitative estimation of water soluble vitamins and phenolics by RP-HPLC in some lesser used wild edible plants.

The present study aimed to investigate the nutritional properties and antioxidant activities of six underutilized wild edible plants viz. Ipomoea aquatica, Achyranthes aspera, Aasystasia ganjetica, Enhydra fluctuans, Oldenlandia corymbosa and Amaranthus viridis that are commonly consumed as food in the India The antioxidant properties of the plants were evaluated by using 1,1-diphenyl-2-picryl hydrazyl (DPPH) radical scavenging activity, ABTS radical scavenging ability, reducing power capacity, metal chelating activity, lipid peroxidation assay, estimation of total phenolic content and flavonoids content in different solvent extraction system like benzene, chloroform, methanol and 70% aqueous (aq.) ethanol. The quantitation of phenolic acids and flavonoids and water soluble vitamins in these plants were carried out by HPLC using Acclaim C 18 column (5 µm particle size, 250 × 4.6 mm), Dionex Ultimate 3000 liquid chromatograph and detection was carried out in photo diode array (PDA) detector. The results of investigation showed that these plants are rich sources of protein, carbohydrate minerals and vitamins, especially the B group of vitamins that can contribute immensely to nutrition, food security, and health and therapeutic benefits. The different levels of antioxidant activities were found in the solvent systems used. The HPLC analysis also showed the presence of phenolic acids and flavonoids in various amounts in these plants which could be utilized as natural antioxidant.

Liraglutide and Dulaglutide therapy in addition to SGLT-2 inhibitor and metformin treatment in Indian type 2 diabetics: a real world retrospective observational study.

BACKGROUND: Therapy for Type 2 diabetes (T2D) has been transformed by the introduction of newer agents like Glucagon like Peptide Receptor Agonists (GLP-1RA) and Sodium-glucose linked transporter inhibitors (SGLT2i). However with co-initiation of SGLT2i and GLP-1RA in the DURATION 8 trial an improvement in HbA1c was noted but the beneficial effect was not equal to the sum of its parts. In view of this we proceeded to test the hypothesis that sequential addition of GLP-1RA therapy to metformin and SGLT-2i may be more beneficial. METHODS: A retrospective real world observational case note study conducted in two diabetes care centres in India analyzed the first 60 consecutive T2D patients who could afford this therapy and had not achieved their glycaemic target (HbA1c < 7%)on metformin and SGLT2i. All these patients were additionally treated with either Dulaglutide or Liraglutide and followed up for 13 weeks. RESULTS: Across the entire 13-week study period, both liraglutide and dulaglutide proved to be an excellent add on to metformin and SGLT-2 inhibitor. There was significant reduction in HbA1c and body weight. Liraglutide had an additional significant impact on systolic blood pressure reduction in contrast to the dulaglutide arm. Comparatively, liraglutide and dulaglutide achieved similar metabolic control. However, a larger proportion of patients achieved HbA1c below 7.0% in the liraglutide arm (63.3%) compared to the dulaglutide arm (30%) and this difference was statistically significant. CONCLUSION: In this retrospective study in Indian type 2 diabetic patients poorly controlled with metformin and SGLT-2 inhibitor we found a meaningful impact of adding a GLP-1 RA on all metabolic parameters. There were additional advantages seen with liraglutide as far achieving target HbA1c of less than 7% and also on the quantum of weight loss and systolic blood pressure reduction.

Diagnosis of bloodstream infections from positive blood cultures and directly from blood samples: recent developments in molecular approaches.

BACKGROUND: Bloodstream infections are a major cause of death with increasing incidence and severity. Blood cultures are still the reference standard for microbiological diagnosis, but are rather slow. Molecular methods can be used as add-on complementary assays. They can be useful to speed up microbial identification and to predict antimicrobial susceptibility, applied to direct blood samples or positive blood cultures. AIM: To review recent developments in molecular-based diagnostic platforms used for the identification of bloodstream infections, with a focus on assays performed directly on blood samples and positive blood cultures. SOURCES: Peer reviewed articles, conference abstracts, and manufacturers' websites. CONTENT: We give an update on recent developments of molecular methods in diagnosing BSIs. We first describe the currently available molecular methods to be used for positive blood cultures including: a) in situ hybridization-based methods; b) DNA-microarray-based hybridization technology; c) nucleic acid amplification-based methods; and d) combined methods. Subsequently, molecular methods applied directly to whole blood samples are discussed, including the use of nucleic acid amplification-based methods, T2 magnetic resonance-based methods, and metagenomics for diagnosing BSIs. IMPLICATIONS: Advances in molecular-based methods complementary to conventional blood culture diagnostics and antimicrobial stewardship programmes may optimize infection management by allowing rapid identification of pathogens and relevant antimicrobial resistance genes. Rapid diagnosis of the causing microorganism and relevant resistance determinants is important for early administration and modification of appropriate antimicrobial therapy. Ultimately, this may lead to improved quality and cost-effectiveness of health care, as well as reduced antimicrobial resistance selection.

Biopsy-proven hypersensitivity pneumonitis caused by a fluorocarbon waterproofing spray.

BACKGROUND: We present the case of a 35-year-old male who developed a chronic hypersensitivity pneumonitis (HP) following inhalational exposure to a fluorocarbon waterproofing aerosol spray, caused by his work for an upholstery and soft furnishings retailer. This is the first case report from inhalational fluorocarbon exposure with histological evidence of chronic HP. This is then discussed in the context of previous reports of interstitial lung disease and lung injury, caused by similar occupational and non-occupational exposures.

Assessment of structural, morphological, magnetic and gas sensing properties of CoFe(2)O(4) thin films.

Polycrystalline CoFe2O4 thin films are deposited onto the quartz substrates by spray pyrolysis technique. Rietveld refinement analysis confirmed the films are polycrystalline in nature with spinel cubic crystal structure. Rietveld refinement analysis was employed to estimate the cation distribution in spinel lattice sites. Surface micrographs shows the granular morphology with average grain size decreases with increase in solution concentration. The presence of two characteristic absorption bands around 579 and 391cm-1 in the FTIR study confirms the formation of single phase CoFe2O4. Vibrating sample magnetometer measurement confirmed the predominant ferrimagnetic nature of thin films which confirms the maximum saturation magnetization with moderate coercivity was useful for making effective gas sensor. The gas response towards different operating temperatures, gas concentrations and solution concentrations was systematically studied. The films show the maximum gas response 70% at 0.1M solution concentration at 150°C operating temperature. The films are well selective towards NO2 as compared with other test gases with good reproducibility.

Arsenic load in rice ecosystem and its mitigation through deficit irrigation.

Rice the staple food is a notable intake source of arsenic to the rural population of eastern India through food-chain. A field survey was carried out to study the variation of arsenic load in different parts of rice genotype Shatabdi (most popular genotype of the region) exposed to varying level of arsenic present in the irrigation water and soil. As irrigation is the primary source of arsenic contamination, a study was conducted to assess arsenic load in rice ecosystem under deficit irrigation practices like intermittent ponding (IP), saturation (SAT) and aerobic (AER) imposed during stress allowable stage (16-40 days after transplanting) of the crop (genotype Shatabdi). Present survey showed that arsenic content in water and soil influenced the arsenic load of rice grain. Variation in arsenic among different water and soil samples influenced grain arsenic load to the maximum extent followed by straw. Deviation in root arsenic load due to variation in water and soil arsenic content was lowest. Arsenic concentration of grain is strongly related to the arsenic content of both irrigation water and soil. However, water has 10% higher impact on grain arsenic load over soil. Translocation of arsenic from root to shoot decreased with the increase in arsenic content of water. Imposition of saturated and aerobic environment reduced both yield and grain arsenic load. In contrast under IP a marked decrease in grain arsenic content recorded with insignificant reduction in yield. Deficit irrigation resulted in significant reduction (17.6-25%) in arsenic content of polished rice and the values were lower than that of the toxic level (<0.2 mg kg-1). In contrast the decrease in yield was to the tune of 0.9% under IP regime over CP.

An epidemiological profile of chronic obstructive pulmonary disease: A community-based study in Delhi.

BACKGROUND: Different definitions used for chronic obstructive pulmonary disease (COPD) preclude getting reliable prevalence estimates. Study objective was to find the prevalence of COPD as per standard Global Initiative for Chronic Obstructive Lung Disease definition, risk factors associated, and treatment seeking in adults >30 years. METHODOLOGY: Community-based cross-sectional study was conducted in Delhi, among 1200 adults, selected by systematic random sampling. Pretested questionnaire was used to interview all subjects and screen for symptoms of COPD. Postbronchodilator spirometry was done to confirm COPD. STATISTICAL ANALYSIS: Adjusted odds ratio (aOR) was calculated by multivariable analysis to examine the association of risk factors with COPD. Receiver operating characteristic (ROC) curve was developed to assess predictability. RESULTS: The prevalence of COPD was 10.1% (95% confidence interval [CI] 8.5, 11.9%). Tobacco smoking was the strongest risk factor associated (aOR 9.48; 95% CI 4.22, 14.13) followed by environmental tobacco smoke (ETS), occupational exposure, age, and biomass fuel. Each pack-year of smoking increased 15% risk of COPD. Ex-smokers had 63% lesser risk compared to current smokers. Clinical allergy seems to preclude COPD (aOR 0.06; 95% CI 0.02, 0.37). ROC analysis showed 94.38% of the COPD variability can be assessed by this model (sensitivity 57.4%; positive predictive value 93.3%). Only 48% patients were on treatment. Treatment continuation was impeded by its cost. CONCLUSION: COPD prevalence in the region of Delhi, India, is high, and our case-finding population study identified a high rate of patients who were not on any treatment. Our study adds to creating awareness on the importance of smoking cessation, early diagnosis of COPD, and the need for regular treatment.