Effect of Dietary Aluminum Sulfate on Calcium and Phosphorus Metabolism of Broiler Chicks

The effect of dietary aluminum sulfate on Ca and P metabolism was studied using 1-day-oldmale broiler chicks. In Experiment 1, practical diets providing .90% Ca plus .45% available P (Pav), .90% Ca plus .78% Pav, 1.80% Ca plus .45% Pav, or 1.80% Ca plus .90% Pav were fed with 0 or .392% Al as aluminum sulfate for 21 days. The control diet (.90% Caplus .45% Pav) without added A1 was fed to all chicks during Days 22 to 49. In general, Al significantly (Pi), tibia breaking strength, tibia weight, percentage of tibia ash, and plasma Zn, measured at Day 21. Elevating Pav increased BW gain, feed intake, gain:feed ratio, tibia weight and plasma Zn, and decreased plasma total Ca in the presence of .392% Al plus 1.80% Ca. Plasma Pi, tibia breaking strength, and percentage of tibia ash were increased by raising dietary Pav in the presence of .392% Al with either level of Ca. Negative effects of dietary Al on feed intake and BW persisted through Day 49. In Experiment 2, a control diet (.90% Ca, .45% Pav) was fed for ad libitum access either alone or supplemented with .2% Al as aluminum sulfate or with an equivalent amount of sulfate provided by potassium sulfate. The control diet was also pair-fed to chicks given .2% Al. Dietary Al significantly depressed weight gain, feed intake, gain:feed ratio, and plasma Pi. No effects were noted due to adding potassium sulfate to the diet. Pair-feeding the control diet decreased weight gain, feed intake, and tibia weight, but not plasma Pi. These results indicate that the toxic effect of aluminum sulfate is due to the aluminum and not the sulfate ions. The influence of aluminum on growth is mainly due to depressed feed intake, while the altered Ca and P metabolism results from a direct effect of Al per se

Relationship of Dietary Aluminum, Phosphorus, and Calcium to Phosphorus and Calcium Metabolism and Growth Performance of Broiler Chicks

Dietary treatments providing three levels of added Al (0, .196, or .392%) as aluminum sulfate and of available phosphorus (Pav) (.45, .68, or .78%) in a factorial arrangement were administered to day-old chicks in Experiment 1. Plasma inorganic phosphorus (Pi) was significantly (P \u3c .05) elevated by increasing Pav and was decreased by Al. Body weight gain, feed intake, and the gain:feed ratio at Day 21 were significantly decreased by increased concentrations of Al, but were unaffected by the Pav concentrations. Decreases of 39 and 73% in weight gain and of 34 and 66% in feed intake resulted from feeding .196 and .392% AL respectively. In Experiment 2, day-old chicks were fed diets supplemented with 0 or .392% Al in combination with .9% Ca plus .45% Pav, .9% Ca plus .78% Pav, 1.8% Ca plus .45% Pav, or 1.8% Caplus .9% Pav. After 21 days, the supplemental A1 resulted in: 1) significantly poorer growth performance; 2) decreased plasma Pi, total Ca, Zn, and Mg; and 3) decreased tibia weight and breaking strength. Elevating Pav improved growth performance, plasma Pi, and tibia weight and strength, and decreased plasma total Ca. Increasing dietary Ca significantly decreased plasma Pi and increased plasma total Ca without affecting other parameters. Increasing Pav alleviated the negative effect of Al on plasma Pi without correcting the negative effect of Al on growth performance

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease