Sonographic Association Between Fatty Liver and Gall Baldder Stone

Background: Fatty liver (chronic liver disease) was most frequently found associated with gall stones. It arises due to accumulation of lipid in hepatocytes mainly triglyceride. Due to high existence of obesity in the population, the risk of fatty liver and gall stones also increases. In Pakistan the prevalence of fatty liver was 15-20 %. Fatty liver and gall stones could easily be observed on ultrasound. Objective: To evaluate the sonographic association between fatty liver and gall bladder Stone. Study Design: Descriptive Study was conducted Settings: Sanabil health services. Lahore Period: Four months Material & Methods: In our study patients presents with epigastric pain high cholesterol level and previous history of gall stones.While patient with the history of cholecystectomy were excluded. All the data had been composed from Sanabil Health Services Lahore. After informed consent, data was composed through ultrasound machine GE LOGIQ P7 with convex probe (frequency 2.5- 5MHZ) Results: According to results total volume of patient was 220. Now we were comparing between cholelithiasis and grading of fatty liver. Total no of GRADE 1 fatty liver patients were 63 out of 220 in which 13 patients were showing absence of GS while 50 patients showed GS. Total no of GRADE II fatty liver patients were 89 out of 220 in which 36 patients were showing absence of GS while 53 patients showed GS. Total no of GRADE III fatty liver patients were 68 out of 250 in which 20 patients were showing absence of GS while 48 patients showed GS. Total no of 69 out of 220 patients showed absence of GS while 151 patients out of 220 showed with GS. Conclusion: We concluded that the patients who had high cholesterol level, gall stones are associated with fatty liver disease. Moreover fatty liver disease was more common in females than males. Keywords: Nonalcoholic fatty liver, chronic liver disease, Gallbladder, Gall stones, Ultrasound and cholecystokinin. DOI: 10.7176/JHMN/91-09 Publication date:July 31st 202

Phytohormones as Growth Regulators During Abiotic Stress Tolerance in Plants

Phytohormones (PHs) play crucial role in regulation of various physiological and biochemical processes that govern plant growth and yield under optimal and stress conditions. The interaction of these PHs is crucial for plant survival under stressful environments as they trigger signaling pathways. Hormonal cross regulation initiate a cascade of reactions which finely tune the physiological processes in plant architecture that help plant to grow under suboptimal growth conditions. Recently, various studies have highlighted the role of PHs such as abscisic acid, salicylic acid, ethylene, and jasmonates in the plant responses toward environmental stresses. The involvement of cytokinins, gibberellins, auxin, and relatively novel PHs such as strigolactones and brassinosteroids in plant growth and development has been documented under normal and stress conditions. The recent identification of the first plant melatonin receptor opened the door to this regulatory molecule being considered a new plant hormone. However, polyamines, which are not considered PHs, have been included in this chapter. Various microbes produce and secrete hormones which helped the plants in nutrient uptake such as N, P, and Fe. Exogenous use of such microbes help plants in correcting nutrient deficiency under abiotic stresses. This chapter focused on the recent developments in the knowledge related to PHs and their involvement in abiotic stresses of anticipation, signaling, cross-talk, and activation of response mechanisms. In view of role of hormones and capability of microbes in producing hormones, we propose the use of hormones and microbes as potential strategy for crop stress management.Fil: EL Sabagh, Ayman. Scientific And Technological Research Council Of Turkey; TurquíaFil: Islam, Mohammad Sohidul. Kafrelsheikh University; EgiptoFil: Hossain, Akbar. Hajee Mohammad Danesh And Technology University; BangladeshFil: Iqbal, Muhammad Aamir. University Of Poonch; PakistánFil: Mubeen, Mohammad. Comsats University Islamabad; PakistánFil: Waleed, Mirza. Comsats University Islamabad; PakistánFil: Reginato, Mariana Andrea. Universidad Nacional de Río Cuarto. Facultad de Ciencias Exactas Fisicoquímicas y Naturales. Instituto de Investigaciones Agrobiotecnológicas. - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigaciones Agrobiotecnológicas; ArgentinaFil: Battaglia, Martin. Cornell University; Estados UnidosFil: Ahmed, Sharif. International Rice Research Institute; FilipinasFil: Rehman, Abdul. The Islamia University Of Bahawalpur; PakistánFil: Arif, Muhammad. The University Of Agriculture; PakistánFil: Athar, Habib-Ur-Rehman. Bahauddin Zakariya University; PakistánFil: Ratnasekera, Disna. University Of Ruhuna; Sri LankaFil: Danish, Subhan. Bahauddin Zakariya University; PakistánFil: Raza, Ali. Sichuan Agricultural University; ChinaFil: Rajendran, Karthika. Vellore Institute Of Technology; IndiaFil: Mushtaq, Muntazir. Icar-national Bureau Of Plant Genetic Resources; IndiaFil: Skalicky, Milan. Czech University Of Life Sciences Prague; República ChecaFil: Brestic, Marian. Czech University Of Life Sciences Prague; República ChecaFil: Soufan, Walid. King Saud University; Arabia SauditaFil: Fahad, Shah. University Of Haripur; PakistánFil: Pandey, Saurabh. Guru Nanak Dev University; IndiaFil: Abdelhamid, Magdi T.. National Research Centre Dokki; Egipt

Maize Adaptability to Heat Stress under Changing Climate

The rapidly increasing human population is an alarming issue and would need more food production under changing climate. Abiotic stresses like heat stress and temperature fluctuation are becoming key issues to be addressed for boosting crop production. Maize growth and productivity are sensitive to temperature fluctuations. Grain yield losses in maize from heat stress are expected to increase owing to higher temperatures during the growing season. This situation demands the development of maize hybrids tolerant to heat and drought stresses without compromising grain yield under stress conditions. The chapter aimed to assess the updates on the influence of high-temperature stress (HTS) on the physio-biochemical processes in plants and to draw an association between yield components and heat stress on maize. Moreover, exogenous applications of protectants, antioxidants, and signaling molecules induce HTS tolerance in maize plants and could help the plants cope with HTS by scavenging reactive oxygen species, upregulation of antioxidant enzymes, and protection of cellular membranes by the accrual of compatible osmolytes. It is expected that a better thought of the physiological basis of HTS tolerance in maize plants will help to develop HTS maize cultivars. Developing HTS-tolerant maize varieties may ensure crops production sustainability along with promoting food and feed security under changing climate

The global burden of cancer attributable to risk factors, 2010-19 : a systematic analysis for the Global Burden of Disease Study 2019

Background Understanding the magnitude of cancer burden attributable to potentially modifiable risk factors is crucial for development of effective prevention and mitigation strategies. We analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 to inform cancer control planning efforts globally. Methods The GBD 2019 comparative risk assessment framework was used to estimate cancer burden attributable to behavioural, environmental and occupational, and metabolic risk factors. A total of 82 risk-outcome pairs were included on the basis of the World Cancer Research Fund criteria. Estimated cancer deaths and disability-adjusted life-years (DALYs) in 2019 and change in these measures between 2010 and 2019 are presented. Findings Globally, in 2019, the risk factors included in this analysis accounted for 4.45 million (95% uncertainty interval 4.01-4.94) deaths and 105 million (95.0-116) DALYs for both sexes combined, representing 44.4% (41.3-48.4) of all cancer deaths and 42.0% (39.1-45.6) of all DALYs. There were 2.88 million (2.60-3.18) risk-attributable cancer deaths in males (50.6% [47.8-54.1] of all male cancer deaths) and 1.58 million (1.36-1.84) risk-attributable cancer deaths in females (36.3% [32.5-41.3] of all female cancer deaths). The leading risk factors at the most detailed level globally for risk-attributable cancer deaths and DALYs in 2019 for both sexes combined were smoking, followed by alcohol use and high BMI. Risk-attributable cancer burden varied by world region and Socio-demographic Index (SDI), with smoking, unsafe sex, and alcohol use being the three leading risk factors for risk-attributable cancer DALYs in low SDI locations in 2019, whereas DALYs in high SDI locations mirrored the top three global risk factor rankings. From 2010 to 2019, global risk-attributable cancer deaths increased by 20.4% (12.6-28.4) and DALYs by 16.8% (8.8-25.0), with the greatest percentage increase in metabolic risks (34.7% [27.9-42.8] and 33.3% [25.8-42.0]). Interpretation The leading risk factors contributing to global cancer burden in 2019 were behavioural, whereas metabolic risk factors saw the largest increases between 2010 and 2019. Reducing exposure to these modifiable risk factors would decrease cancer mortality and DALY rates worldwide, and policies should be tailored appropriately to local cancer risk factor burden. Copyright (C) 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.Peer reviewe

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