64 research outputs found
Transparent Indium Tin Oxide Microelectrode Arrays for Measuring Beating Cardiomyocytes
This thesis study was made, to develop the microfabrication process for transparent microelectrode arrays (MEAs) using indium tin oxide (ITO). This was done in order to measure bioelectrical data from cardiomyocytes (CMs), without owing any obscurities due to electrodes, as it happens in the conventional MEAs. The study was carried out in three tier (parts) fashion, wherein the 1st tier was dedicated in development of transparent ITO films. The 2nd tier involved with, the transparent ITO films that were developed in the 1st tier, to be patterned into microstructures present in the MEAs. The 3rd and the final tier dealt with two important tasks. The first including, optimizations needed in the previous two tiers, in order to come up with a viable microfabrication process to develop transparent ITO MEAs. The second task of the 3rd tier covered all the necessary testing required to ensure for the best possible quality of measurements of the bioelectric signals. The study showed that the ITO layers developed had very good transparencies of more than 90% transmissions possible, with sheet resistances in the range of 13-46 Ω/sq. The results from cell experiments showed that the MEAs not only measured electrical signals of cardiomyocytes aggregates but also owed no obscurities via microscopes, in the process. The electrode impedance measurements showed that the electrodes were comparable with commercially available ITO MEAs with mean values of 1200 kΩ. The measurements of noise levels were measured in reference to a commercial titanium nitride (TiN) MEA and the noise levels were comparable. Data from other literature studies was compared to ITO electrodes from this study to theirs, it was discovered that noise levels from this study were much better than their ITO electrodes and even certain gold (Au) electrodes.
The process for ITO layer deposition was done using electron beam physical vapour deposition (EB-PVD), and later the annealing was made at temperatures from 300-500 °C. The MEA microfabrication of the ITO layers was done, by dry etching the ITO layers using reactive ion etching (RIE) device through argon. The insulation layer of silicon nitride was deposited using plasma enhanced chemical vapour deposition (PECVD) process by the personnel at the Optoelectronic Research Centre (ORC) of Tampere University of Technology. The insulation layer was also patterned using dry etching, by the same device. The beating cardiomyocyte and noise measurements were done at BioMediTech
Non-invasive assessment of esophageal varices
The assessment of non-invasive parameters for the prediction of large esophageal varices among patients with liver cirrhosisis is of utmost importance. In this study, non-invasive parameters for prediction of large esophageal varices were retrospectively evaluated. The presence of esophageal varices grade III and IV was classified as large esophageal varices positive while no varices or grade I and II were classified as large esophageal varices negative. There were 473 (90.09%) patients with ascites [mild 38 (8.03%), moderate 257 (54.33%) and severe 178 (37.63%)]. Frequency of esophageal varices was found to be higher (n=415, 79.04%). Whereas, large esophageal varices were found in 251 (47.81%) patients. The sensitivity, specificity, positive predicted value, negative predicted value and test accuracy of thrombocytopenia in predicting large esophageal varices were found to be 88.05%, 59.85%, 66.77%, 84.54% and 73.33% respectively. A significant association for large esophageal varices was observed for low platelet counts (AOR : 0.98, 95% CI : 0.97-0.99), high bilirubin level (AOR : 1.22, 95% CI : 1.07-1.39), ascites (AOR : 1.98, CI : 1.02-3.85) and Child score A (AOR : 0.26, 95% CI : 0.09-0.75) and Child Score B (AOR : 0.42, 95% CI : 0.28-0.61). In conclusion, low platelet count, high bilirubin level and ascites are found to be non-invasive predictive factor for large esophageal varices
Infections in patients with multiple myeloma treated with conventional chemotherapy: A single-center, 10-year experience in Pakistan
Introduction: Multiple myeloma (MM) is a common hematologic malignancy with variable degrees of immunodeficiency. Disease- and treatment-related compromise of the immune system predisposes patients to infections, which are a major cause of morbidity and mortality.Objective: We aimed to establish the incidence and main characteristics of infections in MM patients treated at our center over a 10-year period.Method and results: Of the 412 patients retrospectively analyzed, 154 (37.4%) were documented to have at least one episode of infection and were included in this study. A total of 244 infectious episodes were documented. The most common site of infection was the lung, followed by the genitourinary system. The most common infections were bacterial, followed by viral. Escherichia coli were the most common organism. In 160 (65.5%) episodes, the organism was not isolated. Thalidomide with dexamethasone was the most common treatment regimen, followed by melphalan with dexamethasone. Infection was the main cause of death in 26 (6.3%) out of all 412 patients.Conclusion: Infections are a notable cause of morbidity and mortality in the clinical course of MM patients. By considering patient and disease characteristics, a risk-adapted selection of the MM treatment should be employed, with special attention toward patient age and disease-associated organ dysfunction. Patient education, access to healthcare and physician vigilance are also essential. Vaccination and antimicrobial prophylaxis may be considered prior to or during therapy
Potential of Indigenous Plants for Skin Healing and Care
The outer protective layer of body is skin which not only guards it from external fluctuations and effects but also performs its thermoregulation. Its functioning may get affected due to several factors like dermal wounds, injuries, aging and many other disorders. These dermal ailments can be cured with the help of indigenous flora to get economical pharamcognosal benefits with no side effects which is a serious concern of synthetic drugs now days. Furthermore, research efforts are necessary for their proper dose optimization and administration to achieve low cost and side effects free pharamcognosal skin cure and care gains
Optimizing Industrial Processes in Beverages and Aerospace Sector: A Case Study Analysis
This study examines industrial process optimization approaches using case studies, literature reviews, and original research. It explores techniques such as linear programming, simulation modelling, Lean, Six Sigma, and advanced machine learning algorithms. Case studies exemplify the application of these methods in beverages and aerospace sectors, the study employs specific strategies and data collection methods, providing insights into the applicability, strengths, and limitations of various methodologies. Results highlight both quantitative and qualitative outcomes, offering valuable insights for practitioners and decision-makers
Exogenous γ-aminobutyric acid (GABA) mitigated salinity-induced impairments in mungbean plants by regulating their nitrogen metabolism and antioxidant potential
BackgroundIncreasing soil salinization has a detrimental effect on agricultural productivity.Therefore, strategies are needed to induce salinity-tolerance in crop species for sustainable foodproduction. γ-aminobutyric acid (GABA) plays a key role in regulating plant salinity stresstolerance. However, it remains largely unknown how mungbean plants (Vigna radiata L.) respondto exogenous GABA under salinity stress.MethodsThus, we evaluated the effect of exogenous GABA (1.5 mM) on the growth and physiobiochemicalresponse mechanism of mungbean plants to saline stress (0-, 50-, and 100 mM [NaCland Na2SO4, at a 1:1 molar ratio]).ResultsIncreased saline stress adversely affected mungbean plants' growth and metabolism. Forinstance, leaf-stem-root biomass (34- and 56%, 31- and 53%, and 27- and 56% under 50- and 100mM, respectively]) and chlorophyll concentrations declined. The carotenoid level increased (10%)at 50 mM and remained unaffected at 100 mM. Hydrogen peroxide (H2O2), malondialdehyde(MDA), osmolytes (soluble sugars, soluble proteins, proline), total phenolic content, andenzymatic activities of superoxide dismutase (SOD), ascorbate peroxidase (APX), peroxidase(POD), glutathione reductase (GTR), and polyphenol oxidation (PPO) were significantlyincreased. In leaves, salinity caused a significant increase in Na+ concentration but a decrease inK+ concentration, resulting in a low K+/Na+ concentration (51- and 71% under 50- and 100- mMstress). Additionally, nitrogen concentration and the activities of nitrate reductase (NR) andglutamine synthetase (GS) decreased significantly. The reduction in glutamate synthase (GOGAT)activity was only significant (65%) at 100 mM stress. Exogenous GABA decreased Na+, H2O2,and MDA concentrations but enhanced photosynthetic pigments, K+ and K+/Na+ ratio, Nmetabolism, osmolytes, and enzymatic antioxidant activities, thus reducing salinity-associatedstress damages, resulting in improved growth and biomass.ConclusionExogenous GABA may have improved the salinity tolerance of mungbean plants by maintaining their morpho-physiological responses and reducing the accumulation of harmfulsubstances under salinity. Future molecular studies can contribute to a better understanding of themolecular mechanisms by which GABA regulates mungbean salinity tolerance
Discovery and systematic characterization of risk variants and genes for coronary artery disease in over a million participants
The discovery of genetic loci associated with complex diseases has outpaced the elucidation of mechanisms of disease pathogenesis. Here we conducted a genome-wide association study (GWAS) for coronary artery disease (CAD) comprising 181,522 cases among 1,165,690 participants of predominantly European ancestry. We detected 241 associations, including 30 new loci. Cross-ancestry meta-analysis with a Japanese GWAS yielded 38 additional new loci. We prioritized likely causal variants using functionally informed fine-mapping, yielding 42 associations with less than five variants in the 95% credible set. Similarity-based clustering suggested roles for early developmental processes, cell cycle signaling and vascular cell migration and proliferation in the pathogenesis of CAD. We prioritized 220 candidate causal genes, combining eight complementary approaches, including 123 supported by three or more approaches. Using CRISPR-Cas9, we experimentally validated the effect of an enhancer in MYO9B, which appears to mediate CAD risk by regulating vascular cell motility. Our analysis identifies and systematically characterizes >250 risk loci for CAD to inform experimental interrogation of putative causal mechanisms for CAD. 2022, The Author(s).T. Kessler is supported by the Corona-Foundation (Junior Research Group Translational Cardiovascular Genomics) and the German Research Foundation (DFG) as part of the Sonderforschungsbereich SFB 1123 (B02). T.J. was supported by a Medical Research Council DTP studentship (MR/S502443/1). J.D. is a British Heart Foundation Professor, European Research Council Senior Investigator, and National Institute for Health and Care Research (NIHR) Senior Investigator. J.C.H. acknowledges personal funding from the British Heart Foundation (FS/14/55/30806) and is a member of the Oxford BHF Centre of Research Excellence (RE/13/1/30181). R.C. has received funding from the British Heart Foundation and British Heart Foundation Centre of Research Excellence. O.G. has received funding from the British Heart Foundation (BHF) (FS/14/66/3129). P.S.d.V. was supported by American Heart Association grant number 18CDA34110116 and National Heart, Lung, and Blood Institute grant R01HL146860. The Atherosclerosis Risk in Communities study has been funded in whole or in part with Federal funds from the National Heart, Lung and Blood Institute, National Institutes of Health, Department of Health and Human Services (contract HHSN268201700001I, HHSN268201700002I, HHSN268201700003I, HHSN268201700004I and HHSN268201700005I), R01HL087641, R01HL059367 and R01HL086694; National Human Genome Research Institute contract U01HG004402; and National Institutes of Health contract HHSN268200625226C. We thank the staff and participants of the ARIC study for their important contributions. Infrastructure was partly supported by grant UL1RR025005, a component of the National Institutes of Health and NIH Roadmap for Medical Research. The Trøndelag Health Study (The HUNT Study) is a collaboration between HUNT Research Centre (Faculty of Medicine and Health Sciences, NTNU, Norwegian University of Science and Technology), Trøndelag County Council, Central Norway Regional Health Authority and the Norwegian Institute of Public Health. The K.G. Jebsen Center for Genetic Epidemiology is financed by Stiftelsen Kristian Gerhard Jebsen; Faculty of Medicine and Health Sciences, NTNU, Norwegian University of Science and Technology; and Central Norway Regional Health Authority. Whole genome sequencing for the HUNT study was funded by HL109946. The GerMIFs gratefully acknowledge the support of the Bavarian State Ministry of Health and Care, furthermore founded this work within its framework of DigiMed Bayern (grant DMB-1805-0001), the German Federal Ministry of Education and Research (BMBF) within the framework of ERA-NET on Cardiovascular Disease (Druggable-MI-genes, 01KL1802), within the scheme of target validation (BlockCAD, 16GW0198K), within the framework of the e:Med research and funding concept (AbCD-Net, 01ZX1706C), the British Heart Foundation (BHF)/German Centre of Cardiovascular Research (DZHK)-collaboration (VIAgenomics) and the German Research Foundation (DFG) as part of the Sonderforschungsbereich SFB 1123 (B02), the Sonderforschungsbereich SFB TRR 267 (B05), and EXC2167 (PMI). This work was supported by the British Heart Foundation (BHF) under grant RG/14/5/30893 (P.D.) and forms part of the research themes contributing to the translational research portfolios of the Barts Biomedical Research Centre funded by the UK National Institute for Health Research (NIHR). I.S. is supported by a Precision Health Scholars Award from the University of Michigan Medical School. This work was supported by the European Commission (HEALTH-F2–2013-601456) and the TriPartite Immunometabolism Consortium (TrIC)-NovoNordisk Foundation (NNF15CC0018486), VIAgenomics (SP/19/2/344612), the British Heart Foundation, a Wellcome Trust core award (203141/Z/16/Z to M.F. and H.W.) and the NIHR Oxford Biomedical Research Centre. M.F. and H.W. are members of the Oxford BHF Centre of Research Excellence (RE/13/1/30181). The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health. C.P.N. and T.R.W. received funding from the British Heart Foundation (SP/16/4/32697). C.J.W. is funded by NIH grant R35-HL135824. B.N.W. is supported by the National Science Foundation Graduate Research Program (DGE, 1256260). This research was supported by BHF (SP/13/2/30111) and conducted using the UK Biobank Resource (application 9922). O.M. was funded by the Swedish Heart and Lung Foundation, the Swedish Research Council, the European Research Council ERC-AdG-2019-885003 and Lund University Infrastructure grant ‘Malmö population-based cohorts’ (STYR 2019/2046). T.R.W. is funded by the British Heart Foundation. I.K., S. Koyama, and K. Ito are funded by the Japan Agency for Medical Research and Development, AMED, under grants JP16ek0109070h0003, JP18kk0205008h0003, JP18kk0205001s0703, JP20km0405209 and JP20ek0109487. The Biobank Japan is supported by AMED under grant JP20km0605001. J.L.M.B. acknowledges research support from NIH R01HL125863, American Heart Association (A14SFRN20840000), the Swedish Research Council (2018-02529) and Heart Lung Foundation (20170265) and the Foundation Leducq (PlaqueOmics: New Roles of Smooth Muscle and Other Matrix Producing Cells in Atherosclerotic Plaque Stability and Rupture, 18CVD02. A.V.K. has been funded by grant 1K08HG010155 from the National Human Genome Research Institute. K.G.A. has received support from the American Heart Association Institute for Precision Cardiovascular Medicine (17IFUNP3384001), a KL2/Catalyst Medical Research Investigator Training (CMeRIT) award from the Harvard Catalyst (KL2 TR002542) and the NIH (1K08HL153937). A.S.B. has been supported by funding from the National Health and Medical Research Council (NHMRC) of Australia (APP2002375). D.S.A. has received support from a training grant from the NIH (T32HL007604). N.P.B., M.C.C., J.F. and D.-K.J. have been funded by the National Institute of Diabetes and Digestive and Kidney Diseases (2UM1DK105554). EPIC-CVD was funded by the European Research Council (268834) and the European Commission Framework Programme 7 (HEALTH-F2-2012-279233). The coordinating center was supported by core funding from the UK Medical Research Council (G0800270; MR/L003120/1), British Heart Foundation (SP/09/002, RG/13/13/30194, RG/18/13/33946) and NIHR Cambridge Biomedical Research Centre (BRC-1215-20014). The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care. This work was supported by Health Data Research UK, which is funded by the UK Medical Research Council, Engineering and Physical Sciences Research Council, Economic and Social Research Council, Department of Health and Social Care (England), Chief Scientist Office of the Scottish Government Health and Social Care Directorates, Health and Social Care Research and Development Division (Welsh Government), Public Health Agency (Northern Ireland), British Heart Foundation and Wellcome. Support for title page creation and format was provided by AuthorArranger, a tool developed at the National Cancer Institute.Scopu
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Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021
BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation
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