A Continuum Model for Metabolic Gas Exchange in Pear Fruit

Exchange of O2 and CO2 of plants with their environment is essential for metabolic processes such as photosynthesis and respiration. In some fruits such as pears, which are typically stored under a controlled atmosphere with reduced O2 and increased CO2 levels to extend their commercial storage life, anoxia may occur, eventually leading to physiological disorders. In this manuscript we have developed a mathematical model to predict the internal gas concentrations, including permeation, diffusion, and respiration and fermentation kinetics. Pear fruit has been selected as a case study. The model has been used to perform in silico experiments to evaluate the effect of, for example, fruit size or ambient gas concentration on internal O2 and CO2 levels. The model incorporates the actual shape of the fruit and was solved using fluid dynamics software. Environmental conditions such as temperature and gas composition have a large effect on the internal distribution of oxygen and carbon dioxide in fruit. Also, the fruit size has a considerable effect on local metabolic gas concentrations; hence, depending on the size, local anaerobic conditions may result, which eventually may lead to physiological disorders. The model developed in this manuscript is to our knowledge the most comprehensive model to date to simulate gas exchange in plant tissue. It can be used to evaluate the effect of environmental stresses on fruit via in silico experiments and may lead to commercial applications involving long-term storage of fruit under controlled atmospheres

Using a reaction‐diffusion model to estimate day respiration and reassimilation of (photo)respiredCO2in leaves

peer-reviewedMethods using gas exchange measurements to estimate respiration in the light (day respiration Rd) make implicit assumptions about reassimilation of (photo)respired CO2; however, this reassimilation depends on the positions of mitochondria. We used a reaction-diffusion model without making these assumptions to analyse datasets on gas exchange, chlorophyll fluorescence and anatomy for tomato leaves. We investigated how Rd values obtained by the Kok and the Yin methods are affected by these assumptions and how those by the Laisk method are affected by the positions of mitochondria. The Kok method always underestimated Rd. Estimates of Rd by the Yin method and by the reaction-diffusion model agreed only for nonphotorespiratory conditions. Both the Yin and Kok methods ignore reassimilation of (photo)respired CO2, and thus underestimated Rd for photorespiratory conditions, but this was less so in the Yin than in the Kok method. Estimates by the Laisk method were affected by assumed positions of mitochondria. It did not work if mitochondria were in the cytosol between the plasmamembrane and the chloroplast envelope. However, mitochondria were found to be most likely between the tonoplast and chloroplasts. Our reaction-diffusion model effectively estimates Rd, enlightens the dependence of Rd estimates on reassimilation and clarifies (dis)advantages of existing methods.KU Leuve

Features of trastuzumab-related cardiac dysfunction: deformation analysis outside left ventricular global longitudinal strain

BackgroundCancer therapy-related cardiac dysfunction due to trastuzumab has been well-known for many years, and echocardiographic surveillance is recommended every 3 months in patients undergoing trastuzumab treatment, irrespective of the baseline cardiotoxicity risk. However, the potential harm and cost of overscreening in low- and moderate-risk patients have become great concerns.ObjectivesThis study aimed to identify the incidence of early cancer therapy-related cardiac dysfunction (CTRCD) and the behaviours of left and right heart deformations during trastuzumab chemotherapy in low- and moderate-risk patients.MethodsWe prospectively enrolled 110 anthracycline-naïve women with breast cancer and cardiovascular risk factors who were scheduled to receive trastuzumab. The left ventricular ejection fraction (LVEF), left ventricular global longitudinal strain (LV-GLS), and right ventricular and left atrial longitudinal strains were evaluated using echocardiography at baseline, before every subsequent cycle and 3 weeks after the final dose of trastuzumab. The baseline risk of CTRCD was graded according to the risk score proposed by the Heart Failure Association (HFA) Cardio-Oncology Working Group and the International Cardio-Oncology Society (ICOS). CTRCD and its severity were defined according to the current European Society of Cardiology (ESC) guidelines.ResultsTwelve (10.9%) patients had asymptomatic CTRCD. All CTRCD occurred sporadically during the first 9 months of the active trastuzumab regimen in both low- and moderate-risk patients. While CTRCD was graded as moderate severity in 41.7% of patients and heart failure therapy was initiated promptly, no irreversible cardiotoxicity or trastuzumab interruption was recorded at the end of follow-up. Among the left and right heart deformation indices, only LV-GLS decreased significantly in the CTRCD group during the trastuzumab regimen.ConclusionsCTRCD is prevalent in patients with non-high-risk breast cancer undergoing trastuzumab chemotherapy. Low- and moderate-risk patients show distinct responses to trastuzumab. The LV-GLS is the only deformation index sensitive to early trastuzumab-related cardiac dysfunction

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

Insights into adsorptive interactions between antibiotic molecules and rutile-TiO2 (110) surface

Intermolecular interactions between antibiotic molecules, ampicillin (AP), amoxicillin (AX) and tetracycline (TC), and rutile-TiO2 (110) surface (r-TiO2) were thoroughly investigated using density functional theory calculations in solid state. The popular rutile-TiO2 is considered as a material for treatment of antibiotic molecules present in waste water. Calculated results revealed that in these adsorbate-adsorbent systems, significant contributions of Ti··O electrostatic interactions and important addition of O/N-H···O hydrogen bonds occur in stabilization of configurations of the most favored structures. Existence and role of adsorptive interactions are clarified by the atom-in-molecule theory, density of states and electron density transfer analyses. Adsorption of antibiotic molecules onto the r-TiO2 surface is characterized as chemisorption processes. Furthermore, the most stable configurations tend to be formed preferably in horizontal arrangement of molecules onto the material surface. The adhesive capacity of these AP, AX and TC antibiotic molecules on r-TiO2 surface is large and quantitatively evaluated

Using a reaction-diffusion model to estimate day respiration and reassimilation of (photo)respired CO2 in leaves

Methods using gas exchange measurements to estimate respiration in the light (day respiration R d ) make implicit assumptions about reassimilation of (photo)respired CO2 ; however, this reassimilation depends on the positions of mitochondria. We used a reaction-diffusion model without making these assumptions to analyse datasets on gas exchange, chlorophyll fluorescence and anatomy for tomato leaves. We investigated how R d values obtained by the Kok and the Yin methods are affected by these assumptions and how those by the Laisk method are affected by the positions of mitochondria. The Kok method always underestimated R d . Estimates of R d by the Yin method and by the reaction-diffusion model agreed only for nonphotorespiratory conditions. Both the Yin and Kok methods ignore reassimilation of (photo)respired CO2 , and thus underestimated R d for photorespiratory conditions, but this was less so in the Yin than in the Kok method. Estimates by the Laisk method were affected by assumed positions of mitochondria. It did not work if mitochondria were in the cytosol between the plasmamembrane and the chloroplast envelope. However, mitochondria were found to be most likely between the tonoplast and chloroplasts. Our reaction-diffusion model effectively estimates R d , enlightens the dependence of R d estimates on reassimilation and clarifies (dis)advantages of existing methods.status: publishe

Values of parameters and variable input for the model.

<p>Values of parameters and variable input for the model.</p