An in vitro model of human hematopoiesis identifies a regulatory role for the aryl hydrocarbon receptor.

In vitro models to study simultaneous development of different human immune cells and hematopoietic lineages are lacking. We identified and characterized, using single-cell methods, an in vitro stromal cell-free culture system of human hematopoietic stem and progenitor cell (HSPC) differentiation that allows concurrent development of multiple immune cell lineages. The aryl hydrocarbon receptor (AHR) is a ligand-activated transcription factor influencing many biological processes in diverse cell types. Using this in vitro model, we found that AHR activation by the highly specific AHR ligand, 2,3,7,8-tetrachlorodibenzo-p-dioxin, drives differentiation of human umbilical cord blood-derived CD34+ HSPCs toward monocytes and granulocytes with a significant decrease in lymphoid and megakaryocyte lineage specification that may lead to reduced immune competence. To our knowledge, we also discovered for the first time, using single-cell modalities, that AHR activation decreased the expression of BCL11A and IRF8 in progenitor cells, which are critical genes involved in hematopoietic lineage specification processes at both transcriptomic and protein levels. Our in vitro model of hematopoiesis, coupled with single-cell tools, therefore allows for a better understanding of the role played by AHR in modulating hematopoietic differentiation.

Evaluation of the anti-inflammatory effects of selected cannabinoids and terpenes from Cannabis Sativa employing human primary leukocytes.

Cannabis is well established as possessing immune modulating activity. The objective of this study was to evaluate the anti-inflammatory properties of selected cannabis-derived terpenes and cannabinoids. Based on their activity in cannabis-chemovar studies, α-pinene, trans-nerolidol, D-limonene, linalool and phytol were the selected terpenes evaluated. The cannabinoid compounds evaluated included cannabidivarin, cannabidiol, cannabinol, cannabichromene, cannabigerol and delta-9-tetrahydrocannabinol. Human PBMC were pretreated with each compound, individually, at concentrations extending from 0.001 to 10 µM and then stimulated with CpG (plasmacytoid dendritic cell), LPS (monocytes), or anti-CD3/CD28 (T cells). Proliferation, activation marker expression, cytokine production and phagocytosis, were quantified. Of the 21 responses assayed for each compound, cannabinoids showed the greatest immune modulating activity compared to their vehicle control. Delta-9-tetrahydrocannabinol possessed the greatest activity affecting 11 immune parameters followed by cannabidivarin, cannabigerol, cannabichromene, cannabinol and cannabidiol. α-Pinene showed the greatest immune modulating activity from the selected group of terpenes, followed by linalool, phytol, trans-nerolidol. Limonene had no effect on any of the parameters tested. Overall, these studies suggest that selected cannabis-derived terpenes displayed minimal immunological activity, while cannabinoids exhibited a broader range of activity. Compounds possessing anti-inflammatory effects may be useful in decreasing inflammation associated with a range of disorders, including neurodegenerative disorders.

Statistical modeling for analyzing grain yield of durum wheat under rainfed conditions in Azad Jammu Kashmir, Pakistan / Modelagem estatística para analisar o rendimento de grãos de trigo durum sob condições de chuva em Azad Jammu Kashmir, Paquistão

One of the most important traits that plant breeders aim to improve is grain yield which is a highly quantitative trait controlled by various agro-morphological traits. Twelve morphological traits such as Germination Percentage, Days to Spike Emergence, Plant Height, Spike Length, Awn Length, Tillers/Plant, Leaf Angle, Seeds/Spike, Plant Thickness, 1000-Grain Weight, Harvest Index and Days to Maturity have been considered as independent factors. Correlation ,regression, and principal component analysis (PCA) are used to identify the different durum wheat traits, which significantly contribute to the yield. The necessary assumptions required for applying regression modeling have been tested and all the assumptions are satisfied by the observed data. The outliers are detected in the observations of fixed traits and Grain Yield. Some observations are detected as outliers but the outlying observations did not show any influence on the regression fit. For selecting a parsimonious regression model for durum wheat, best subset regression, and stepwise regression techniques have been applied. The best subset regression analysis revealed that Germination Percentage, Tillers/Plant, and Seeds/Spike have a marked increasing effect whereas Plant thickness has a negative effect on durum wheat yield. While stepwise regression analysis identified that the traits, Germination Percentage, Tillers/Plant, and Seeds/Spike significantly contribute to increasing the durum wheat yield. The simple correlation coefficient specified the significant positive correlation of Grain Yield with Germination Percentage, Number of Tillers/Plant, Seeds/Spike, and Harvest Index. These results of correlation analysis directed the importance of morphological characters and their significant positive impact on Grain Yield. [...].

Uma das características mais importantes que os produtores de plantas visam melhorar é o rendimento de grãos, que é uma particularidade altamente quantitativa e controlada por várias características agromorfológicas. Foram considerados 12 traços morfológicos como fatores independentes, como Porcentagem de Germinação, Dias para Emergência da Espiga, Altura da Planta, Comprimento da Espiga, Comprimento da Aresta, Perfilhos /Planta, Ângulo da Folha, Sementes /Espiga, Espessura da Planta, Peso de 1000 Grãos, Índice de Colheita e Dias até a Maturidade. A correlação, regressão e análise de componentes principais (em inglês Principal Component Analysis (PCA)) são usadas para identificar as diferentes características do trigo duro, que contribuem significativamente para o rendimento. As suposições necessárias exigidas para a aplicação da modelagem de regressão foram testadas e todas as suposições são adequadas de acordo com os dados observados. Os outliers são detectados nas observações de características fixas e rendimento de grãos. Algumas observações são detectadas como outliers, mas as observações outliers não mostraram qualquer influência no ajuste da regressão. Para selecionar um modelo de regressão parcimonioso para o trigo duro, foram aplicadas tanto a melhor regressão de subconjunto quanto as técnicas de regressão stepwise. A melhor análise de regressão de subconjunto revelou que a porcentagem de germinação, perfilhos /planta e sementes /espiga tem um efeito de aumento acentuado, enquanto a espessura da planta tem um efeito negativo sobre o rendimento do trigo duro. Enquanto a análise de regressão passo a passo identificou que as características, porcentagem de germinação, perfilhos/planta e sementes /espiga contribuem significativamente para aumentar a produtividade do trigo duro. O coeficiente de correlação simples especificou a correlação positiva significativa do [...].

Statistical modeling for analyzing grain yield of durum wheat under rainfed conditions in Azad Jammu Kashmir, Pakistan

Abstract One of the most important traits that plant breeders aim to improve is grain yield which is a highly quantitative trait controlled by various agro-morphological traits. Twelve morphological traits such as Germination Percentage, Days to Spike Emergence, Plant Height, Spike Length, Awn Length, Tillers/Plant, Leaf Angle, Seeds/Spike, Plant Thickness, 1000-Grain Weight, Harvest Index and Days to Maturity have been considered as independent factors. Correlation, regression, and principal component analysis (PCA) are used to identify the different durum wheat traits, which significantly contribute to the yield. The necessary assumptions required for applying regression modeling have been tested and all the assumptions are satisfied by the observed data. The outliers are detected in the observations of fixed traits and Grain Yield. Some observations are detected as outliers but the outlying observations did not show any influence on the regression fit. For selecting a parsimonious regression model for durum wheat, best subset regression, and stepwise regression techniques have been applied. The best subset regression analysis revealed that Germination Percentage, Tillers/Plant, and Seeds/Spike have a marked increasing effect whereas Plant thickness has a negative effect on durum wheat yield. While stepwise regression analysis identified that the traits, Germination Percentage, Tillers/Plant, and Seeds/Spike significantly contribute to increasing the durum wheat yield. The simple correlation coefficient specified the significant positive correlation of Grain Yield with Germination Percentage, Number of Tillers/Plant, Seeds/Spike, and Harvest Index. These results of correlation analysis directed the importance of morphological characters and their significant positive impact on Grain Yield. The results of PCA showed that most variation (70%) among data set can be explained by the first five components. It also identified that Seeds/Spike; 1000-Grain Weight and Harvest Index have a higher influence in contributing to the durum wheat yield. Based on the results it is recommended that these important parameters might be considered and focused in future durum wheat breeding programs to develop high yield varieties.

Resumo Uma das características mais importantes que os produtores de plantas visam melhorar é o rendimento de grãos, que é uma particularidade altamente quantitativa e controlada por várias características agromorfológicas. Foram considerados 12 traços morfológicos como fatores independentes, como Porcentagem de Germinação, Dias para Emergência da Espiga, Altura da Planta, Comprimento da Espiga, Comprimento da Aresta, Perfilhos /Planta, Ângulo da Folha, Sementes /Espiga, Espessura da Planta, Peso de 1000 Grãos, Índice de Colheita e Dias até a Maturidade,. A correlação, regressão e análise de componentes principais (em inglês Principal Component Analysis (PCA)) são usadas para identificar as diferentes características do trigo duro, que contribuem significativamente para o rendimento. As suposições necessárias exigidas para a aplicação da modelagem de regressão foram testadas e todas as suposições são adequadas de acordo com os dados observados. Os outliers são detectados nas observações de características fixas e rendimento de grãos. Algumas observações são detectadas como outliers, mas as observações outliers não mostraram qualquer influência no ajuste da regressão. Para selecionar um modelo de regressão parcimonioso para o trigo duro, foram aplicadas tanto a melhor regressão de subconjunto quanto as técnicas de regressão stepwise. A melhor análise de regressão de subconjunto revelou que a porcentagem de germinação, perfilhos /planta e sementes /espiga tem um efeito de aumento acentuado, enquanto a espessura da planta tem um efeito negativo sobre o rendimento do trigo duro. Enquanto a análise de regressão passo a passo identificou que as características, porcentagem de germinação, perfilhos/planta e sementes /espiga contribuem significativamente para aumentar a produtividade do trigo duro. O coeficiente de correlação simples especificou a correlação positiva significativa do rendimento de grãos com a porcentagem de germinação, número de perfilhos/planta, sementes / espiga e índice de colheita. Esses resultados da análise de correlação direcionaram a importância dos caracteres morfológicos e seu impacto positivo e significativo no rendimento de grãos. Os resultados da PCA mostraram que a maior parte da variação (70%) entre o conjunto de dados pôde ser explicada pelos cinco primeiros componentes. Também identificou que Sementes / Espiga, Peso de 1000 Grãos e Índice de Colheita têm uma maior influência na contribuição para o rendimento do trigo duro. Com base nos resultados, recomenda-se que esses importantes parâmetros possam ser considerados e focados em futuros programas de melhoramento de trigo duro para desenvolver variedades de alto rendimento.

Statistical modeling for analyzing grain yield of durum wheat under rainfed conditions in Azad Jammu Kashmir, Pakistan / Modelagem estatística para analisar o rendimento de grãos de trigo durum sob condições de chuva em Azad Jammu Kashmir, Paquistão

One of the most important traits that plant breeders aim to improve is grain yield which is a highly quantitative trait controlled by various agro-morphological traits. Twelve morphological traits such as Germination Percentage, Days to Spike Emergence, Plant Height, Spike Length, Awn Length, Tillers/Plant, Leaf Angle, Seeds/Spike, Plant Thickness, 1000-Grain Weight, Harvest Index and Days to Maturity have been considered as independent factors. Correlation, regression, and principal component analysis (PCA) are used to identify the different durum wheat traits, which significantly contribute to the yield. The necessary assumptions required for applying regression modeling have been tested and all the assumptions are satisfied by the observed data. The outliers are detected in the observations of fixed traits and Grain Yield. Some observations are detected as outliers but the outlying observations did not show any influence on the regression fit. For selecting a parsimonious regression model for durum wheat, best subset regression, and stepwise regression techniques have been applied. The best subset regression analysis revealed that Germination Percentage, Tillers/Plant, and Seeds/Spike have a marked increasing effect whereas Plant thickness has a negative effect on durum wheat yield. While stepwise regression analysis identified that the traits, Germination Percentage, Tillers/Plant, and Seeds/Spike significantly contribute to increasing the durum wheat yield. The simple correlation coefficient specified the significant positive correlation of Grain Yield with Germination Percentage, Number of Tillers/Plant, Seeds/Spike, and Harvest Index. These results of correlation analysis directed the importance of morphological characters and their significant positive impact on Grain Yield. The results of PCA showed that most variation (70%) among data set can be explained by the first five components. It also identified that Seeds/Spike; 1000-Grain Weight and Harvest Index have a higher influence in contributing to the durum wheat yield. Based on the results it is recommended that these important parameters might be considered and focused in future durum wheat breeding programs to develop high yield varieties.

Uma das características mais importantes que os produtores de plantas visam melhorar é o rendimento de grãos, que é uma particularidade altamente quantitativa e controlada por várias características agromorfológicas. Foram considerados 12 traços morfológicos como fatores independentes, como Porcentagem de Germinação, Dias para Emergência da Espiga, Altura da Planta, Comprimento da Espiga, Comprimento da Aresta, Perfilhos /Planta, Ângulo da Folha, Sementes /Espiga, Espessura da Planta, Peso de 1000 Grãos, Índice de Colheita e Dias até a Maturidade,. A correlação, regressão e análise de componentes principais (em inglês Principal Component Analysis (PCA)) são usadas para identificar as diferentes características do trigo duro, que contribuem significativamente para o rendimento. As suposições necessárias exigidas para a aplicação da modelagem de regressão foram testadas e todas as suposições são adequadas de acordo com os dados observados. Os outliers são detectados nas observações de características fixas e rendimento de grãos. Algumas observações são detectadas como outliers, mas as observações outliers não mostraram qualquer influência no ajuste da regressão. Para selecionar um modelo de regressão parcimonioso para o trigo duro, foram aplicadas tanto a melhor regressão de subconjunto quanto as técnicas de regressão stepwise. A melhor análise de regressão de subconjunto revelou que a porcentagem de germinação, perfilhos /planta e sementes /espiga tem um efeito de aumento acentuado, enquanto a espessura da planta tem um efeito negativo sobre o rendimento do trigo duro. Enquanto a análise de regressão passo a passo identificou que as características, porcentagem de germinação, perfilhos/planta e sementes /espiga contribuem significativamente para aumentar a produtividade do trigo duro. O coeficiente de correlação simples especificou a correlação positiva significativa do rendimento de grãos com a porcentagem de germinação, número de perfilhos/planta, sementes / espiga e índice de colheita. Esses resultados da análise de correlação direcionaram a importância dos caracteres morfológicos e seu impacto positivo e significativo no rendimento de grãos. Os resultados da PCA mostraram que a maior parte da variação (70%) entre o conjunto de dados pôde ser explicada pelos cinco primeiros componentes. Também identificou que Sementes / Espiga, Peso de 1000 Grãos e Índice de Colheita têm uma maior influência na contribuição para o rendimento do trigo duro. Com base nos resultados, recomenda-se que esses importantes parâmetros possam ser considerados e focados em futuros programas de melhoramento de trigo duro para desenvolver variedades de alto rendimento.

Statistical modeling for analyzing grain yield of durum wheat under rainfed conditions in Azad Jammu Kashmir, Pakistan.

One of the most important traits that plant breeders aim to improve is grain yield which is a highly quantitative trait controlled by various agro-morphological traits. Twelve morphological traits such as Germination Percentage, Days to Spike Emergence, Plant Height, Spike Length, Awn Length, Tillers/Plant, Leaf Angle, Seeds/Spike, Plant Thickness, 1000-Grain Weight, Harvest Index and Days to Maturity have been considered as independent factors. Correlation, regression, and principal component analysis (PCA) are used to identify the different durum wheat traits, which significantly contribute to the yield. The necessary assumptions required for applying regression modeling have been tested and all the assumptions are satisfied by the observed data. The outliers are detected in the observations of fixed traits and Grain Yield. Some observations are detected as outliers but the outlying observations did not show any influence on the regression fit. For selecting a parsimonious regression model for durum wheat, best subset regression, and stepwise regression techniques have been applied. The best subset regression analysis revealed that Germination Percentage, Tillers/Plant, and Seeds/Spike have a marked increasing effect whereas Plant thickness has a negative effect on durum wheat yield. While stepwise regression analysis identified that the traits, Germination Percentage, Tillers/Plant, and Seeds/Spike significantly contribute to increasing the durum wheat yield. The simple correlation coefficient specified the significant positive correlation of Grain Yield with Germination Percentage, Number of Tillers/Plant, Seeds/Spike, and Harvest Index. These results of correlation analysis directed the importance of morphological characters and their significant positive impact on Grain Yield. The results of PCA showed that most variation (70%) among data set can be explained by the first five components. It also identified that Seeds/Spike; 1000-Grain Weight and Harvest Index have a higher influence in contributing to the durum wheat yield. Based on the results it is recommended that these important parameters might be considered and focused in future durum wheat breeding programs to develop high yield varieties.

Evaluation of immunologic and intestinal effects in rats administered an E 171-containing diet, a food grade titanium dioxide (TiO2).

The toxicity of dietary E 171, a food grade titanium dioxide was evaluated. A recent study reported rats receiving E 171 in water developed inflammation and aberrant crypt foci (ACF) in the gastrointestinal tract. Here, rats received food containing E 171 (7 or 100 days). The 100-day study included feeding E 171 after dimethylhydrazine (DMH) or vehicle only pretreatment. Food consumption was similar between treatment groups with maximum total cumulative E 171 exposure being 2617 mg/kg in 7 days and 29,400 mg/kg in 100 days. No differences were observed due to E 171 in the percentage of dendritic, CD4+ T or Treg cells within Peyer's patches or the periphery, or in cytokine production in plasma, sections of jejunum, and colon in 7- or 100-day E 171 alone fed rats. Differences were observed for IL-17A in colon (400 ppm E 171 + DMH) and IL-12p70 in plasma (40 ppm E 171 + DMH). E 171 had no effect on histopathologic evaluations of small and large intestines, liver, spleen, lungs, or testes, and no effects on ACF, goblet cell numbers, or colonic gland length. Dietary E 171 administration (7- or 100-day), even at high doses, produced no effect on the immune parameters or tissue morphology.

Apocynin prevented inflammation and oxidative stress in carbon tetra chloride induced hepatic dysfunction in rats.

BACKGROUND: Liver fibrosis is a leading pathway to cirrhosis and a global clinical issue. Oxidative stress mediated tissue damage is one of the prime causes of hepatic dysfunction and fibrosis. Apocynin is one of many strong antioxidants. OBJECTIVE: To evaluate the effect of apocynin in the CCl4 administered hepatic dysfunction in rats. METHODS: Female Long Evans rats were administered with CCl4 orally (1mL/kg) twice a week for 2 weeks and were treated with apocynin (100mg/kg). Both plasma and liver tissues were analyzed for alanine aminotransferase (ALT), aspartate aminotransferase (AST) and alkaline phosphatase activities. Oxidative stress parameters were also measured by determining malondialdehyde (MDA), nitric oxide (NO), myeloperoxidase (MPO), advanced protein oxidation product (APOP). In addition, antioxidant enzyme activities such as superoxide dismutase (SOD) and catalase activities in plasma and liver tissues were analyzed. Moreover, inflammation and tissue fibrosis were confirmed by histological staining of liver tissue sections. RESULTS: Apocynin significantly reduced serum AST, ALT, and ALP activities in carbon tetrachloride treated rats. It also exhibited a considerable reduction of the oxidative stress markers (MDA, MPO, NO, and APOP level) which was elevated due to CCl4 administration in rats. Apocynin treatment also restored the catalase and superoxide dismutase activity in CCl4 treated rats. Histological analysis of liver sections revealed that apocynin prevented inflammatory cells infiltration and fibrosis in CCl4 administered rats. CONCLUSION: These results suggest that apocynin protects liver damage induced by CCl4 by inhibiting lipid peroxidation and stimulating the cellular antioxidant system.

Pulmonary Arteriovenous Malformation Causing Systemic Hypoxemia in Early Infancy.

Pulmonary arteriovenous malformation (AVM) is not routinely appreciated during the standard echocardiogram to assess for structural abnormalities or pulmonary hypertension. The distal pulmonary AVM is suspected only if an injection of agitated saline is performed and late entry of particles is appreciated in the left heart structures. A large or complex pulmonary AVM can result in significant right-to-left shunting and consequential systemic hypoxemia in the presence or absence of pulmonary hypertension. For direct visualization of the pulmonary AVM, computerized tomography (CT) scan is the procedure of choice. Here, we present two young infants with systemic hypoxemia who underwent standard medical management including mechanical ventilation and one patient was placed on extracorporeal membrane oxygenation (ECMO) before the diagnosis of pulmonary AVM was established. Subsequently, both patients have done well into mid-term follow-up after being treated successfully using transcatheter occlusion techniques in the cardiac catheterization laboratory during early infancy. We aim to emphasize the importance of a high index of suspicion for pulmonary AVM in infants with refractory systemic hypoxemia of unclear etiology.

Ciprofloxacin in multi-resistant infections in childhood: an audit.

Ciprofloxacin is a new orally administrable fluoroquinolones, with considerable efficacy against multiresistant organisms. Its use in the paediatric age group however, is controversial because of the risk of potential articular toxicity. We retrospectively reviewed ciprofloxacin usage over a 32 week periods (June, 1991-September, 1993) in paediatric inpatients at The Aga Khan University Hospital. Ciprofloxacin was used in 21 cases, singly in 11 (52%) and in combination with other antibiotics in a further 10 (48%). The response to therapy was adjudged as 'good' or 'fair' in 13 (62%) cases. Ciprofloxacin was the only sensitive antibiotic in 4 (19%) and resistance to it was detected in another 4 (19%) cases. Despite all efforts, adequate follow-up could only be achieved in a third of the patients. Although no toxic or side effects were detected, in view of poor follow-up and emergence of ciprofloxacin resistant strains, our experience highlights the need to regulate ciprofloxacin use in the paediatric age group.