A disease predictive model based on epidemiological factors for the management of bacterial leaf blight of rice / Um modelo preditivo de doenças baseado em fatores epidemiológicos para o manejo da queima bacteriana das folhas do arroz

Rice is a widely consumed staple food for a large part of the world's human population. Approximately 90% of the world's rice is grown in Asian continent and constitutes a staple food for 2.7 billion people worldwide. Bacterial leaf blight (BLB) caused by Xanthomonas oryzae pv. oryzae is one of the devastating diseases of rice. A field experiment was conducted during the year 2016 and 2017 to investigate the influence of different meteorological parameters on BLB development as well as the computation of a predictive model to forecast the disease well ahead of its appearance in the field. The seasonal dataset of disease incidence and environmental factors was used to assess five rice varieties/ cultivars (Basmati-2000, KSK-434, KSK-133, Super Basmati, and IRRI-9). The accumulated effect of two year environmental data; maximum and minimum temperature, relative humidity, wind speed, and rainfall, was studied and correlated with disease incidence. Average temperature (maximum & minimum) showed a negative significant correlation with BLB disease and all other variables; relative humidity, rainfall, and wind speed had a positive correlation with BLB disease development on individual varieties. Stepwise regression analysis was performed to indicate potentially useful predictor variables and to rule out incompetent parameters. Environmental data from the growing seasons of July to October 2016 and 2017 revealed that, with the exception of the lowest temperature, all environmental factors contributed to disease development throughout the cropping season. A disease prediction multiple regression model was developed based on two-year data (Y = 214.3-3.691 Max T-0.508 Min T + 0.767 RH + 2.521 RF + 5.740 WS), which explained 95% variability. This disease prediction model will not only help farmers in early detection and timely management of bacterial leaf blight disease of rice but may also help reduce input costs and improve product quality and quantity. The model will be both farmer and environmentally friendly.

O arroz é um alimento básico amplamente consumido por grande parte da população humana mundial. Aproximadamente 90% do arroz do mundo é cultivado no continente asiático e constitui um alimento básico para 2,7 bilhões de pessoas em todo o mundo. O crestamento bacteriano das folhas (BLB) causado por Xanthomonas oryzae pv. oryzae é uma das doenças devastadoras do arroz. Um experimento de campo foi realizado durante os anos de 2016 e 2017 para investigar a influência de diferentes parâmetros meteorológicos no desenvolvimento do BLB, bem como o cálculo de um modelo preditivo para prever a doença bem antes de seu aparecimento em campo. O conjunto de dados sazonais de incidência de doenças e fatores ambientais foi usado para avaliar cinco variedades/cultivares de arroz (Basmati-2000, KSK-434, KSK-133, Super Basmati e IRRI-9). O efeito acumulado de dados ambientais de dois anos; temperatura máxima e mínima, umidade relativa do ar, velocidade do vento e precipitação pluviométrica foram estudados e correlacionados com a incidência da doença. A temperatura média (máxima e mínima) apresentou correlação significativa negativa com a doença BLB e todas as outras variáveis; umidade relativa, precipitação e velocidade do vento tiveram uma correlação positiva com o desenvolvimento da doença BLB em variedades individuais. A análise de regressão stepwise foi realizada para indicar variáveis preditoras potencialmente úteis e para descartar parâmetros incompetentes. Os dados ambientais das safras de julho a outubro de 2016 e 2017 revelaram que, com exceção da temperatura mais baixa, todos os fatores ambientais contribuíram para o desenvolvimento da doença ao longo da safra. Um modelo de regressão múltipla de previsão de doença foi desenvolvido com base em dados de dois anos (Y = 214,3-3,691 Max T-0,508 Min T + 0,767 RH + 2,521 RF + 5,740 WS), que explicou 95% de variabilidade. Este modelo de previsão de doenças não só ajudará os agricultores na detecção precoce e gestão atempada da doença bacteriana das folhas do arroz, mas também pode ajudar a reduzir os custos de insumos e melhorar a qualidade e a quantidade do produto. O modelo será agricultor e ambientalmente amigável.

A disease predictive model based on epidemiological factors for the management of bacterial leaf blight of rice

Abstract Rice is a widely consumed staple food for a large part of the worlds human population. Approximately 90% of the worlds rice is grown in Asian continent and constitutes a staple food for 2.7 billion people worldwide. Bacterial leaf blight (BLB) caused by Xanthomonas oryzae pv. oryzae is one of the devastating diseases of rice. A field experiment was conducted during the year 2016 and 2017 to investigate the influence of different meteorological parameters on BLB development as well as the computation of a predictive model to forecast the disease well ahead of its appearance in the field. The seasonal dataset of disease incidence and environmental factors was used to assess five rice varieties/ cultivars (Basmati-2000, KSK-434, KSK-133, Super Basmati, and IRRI-9). The accumulated effect of two year environmental data; maximum and minimum temperature, relative humidity, wind speed, and rainfall, was studied and correlated with disease incidence. Average temperature (maximum & minimum) showed a negative significant correlation with BLB disease and all other variables; relative humidity, rainfall, and wind speed had a positive correlation with BLB disease development on individual varieties. Stepwise regression analysis was performed to indicate potentially useful predictor variables and to rule out incompetent parameters. Environmental data from the growing seasons of July to October 2016 and 2017 revealed that, with the exception of the lowest temperature, all environmental factors contributed to disease development throughout the cropping season. A disease prediction multiple regression model was developed based on two-year data (Y = 214.3-3.691 Max T-0.508 Min T + 0.767 RH + 2.521 RF + 5.740 WS), which explained 95% variability. This disease prediction model will not only help farmers in early detection and timely management of bacterial leaf blight disease of rice but may also help reduce input costs and improve product quality and quantity. The model will be both farmer and environmentally friendly.

Resumo O arroz é um alimento básico amplamente consumido por grande parte da população humana mundial. Aproximadamente 90% do arroz do mundo é cultivado no continente asiático e constitui um alimento básico para 2,7 bilhões de pessoas em todo o mundo. O crestamento bacteriano das folhas (BLB) causado por Xanthomonas oryzae pv. oryzae é uma das doenças devastadoras do arroz. Um experimento de campo foi realizado durante os anos de 2016 e 2017 para investigar a influência de diferentes parâmetros meteorológicos no desenvolvimento do BLB, bem como o cálculo de um modelo preditivo para prever a doença bem antes de seu aparecimento em campo. O conjunto de dados sazonais de incidência de doenças e fatores ambientais foi usado para avaliar cinco variedades/cultivares de arroz (Basmati-2000, KSK-434, KSK-133, Super Basmati e IRRI-9). O efeito acumulado de dados ambientais de dois anos; temperatura máxima e mínima, umidade relativa do ar, velocidade do vento e precipitação pluviométrica foram estudados e correlacionados com a incidência da doença. A temperatura média (máxima e mínima) apresentou correlação significativa negativa com a doença BLB e todas as outras variáveis; umidade relativa, precipitação e velocidade do vento tiveram uma correlação positiva com o desenvolvimento da doença BLB em variedades individuais. A análise de regressão stepwise foi realizada para indicar variáveis preditoras potencialmente úteis e para descartar parâmetros incompetentes. Os dados ambientais das safras de julho a outubro de 2016 e 2017 revelaram que, com exceção da temperatura mais baixa, todos os fatores ambientais contribuíram para o desenvolvimento da doença ao longo da safra. Um modelo de regressão múltipla de previsão de doença foi desenvolvido com base em dados de dois anos (Y = 214,3-3,691 Max T-0,508 Min T + 0,767 RH + 2,521 RF + 5,740 WS), que explicou 95% de variabilidade. Este modelo de previsão de doenças não só ajudará os agricultores na detecção precoce e gestão atempada da doença bacteriana das folhas do arroz, mas também pode ajudar a reduzir os custos de insumos e melhorar a qualidade e a quantidade do produto. O modelo será agricultor e ambientalmente amigável.

In vivo analysis the effect of antibiotic growth promoters (AGPs), Oxytetracycline di-hydrate and Tylosin phosphate on the intestinal microflora in broiler chicken.

The study was aimed to analyse the effects of antibiotic growth promoters (AGPs), Oxytetracycline di-hydrate and Tylosin phosphate on the intestinal microflora in broiler chicken. The AGPs were provided in different concentrations solely or in combinations for 42 days of rearing. Faecal samples were collected from the intestine (duodenum, jejunum and caeca) of broiler chicken on 14th, 28th and 42nd days of trial. Samples were cultured on different selective medium and bacterial identification was performed by different biochemical and molecular diagnostic tools. Results showed a significant effect of AGPs on the growth of pathogenic microorganisms such as Escherichia coli and Clostridium perfringens in the intestine. Interestingly, an impaired growth was observed for both bacterium showing a significant effect (P<0.05) of AGPs on E. coli and C. perfringens on day 14th, 28th, and 42nd. This effect was observed solely and in combination while using AGPs. Data further showed that the effect was more prominent in combination and with an increase concentration of AGPs. Remarkably, no impairment was seen on the growth of L. reuteri at different sites of intestine and duration (14th, 28th, and 42nd days). The results showed that the use of AGPs in diet has no harmful effect on beneficial bacteria, however, an impaired growth was seen on the harmful bacteria. It is suggested that a combination of AGPs (OXY-1.0+TP-0.5) is economical and have no harmful effect on the broiler chicken. The use of AGPs in a recommended dose and for a specific period of time are safe to use in poultry both as growth promoter and for the prevention of diseases.

A disease predictive model based on epidemiological factors for the management of bacterial leaf blight of rice.

Rice is a widely consumed staple food for a large part of the world's human population. Approximately 90% of the world's rice is grown in Asian continent and constitutes a staple food for 2.7 billion people worldwide. Bacterial leaf blight (BLB) caused by Xanthomonas oryzae pv. oryzae is one of the devastating diseases of rice. A field experiment was conducted during the year 2016 and 2017 to investigate the influence of different meteorological parameters on BLB development as well as the computation of a predictive model to forecast the disease well ahead of its appearance in the field. The seasonal dataset of disease incidence and environmental factors was used to assess five rice varieties/ cultivars (Basmati-2000, KSK-434, KSK-133, Super Basmati, and IRRI-9). The accumulated effect of two year environmental data; maximum and minimum temperature, relative humidity, wind speed, and rainfall, was studied and correlated with disease incidence. Average temperature (maximum & minimum) showed a negative significant correlation with BLB disease and all other variables; relative humidity, rainfall, and wind speed had a positive correlation with BLB disease development on individual varieties. Stepwise regression analysis was performed to indicate potentially useful predictor variables and to rule out incompetent parameters. Environmental data from the growing seasons of July to October 2016 and 2017 revealed that, with the exception of the lowest temperature, all environmental factors contributed to disease development throughout the cropping season. A disease prediction multiple regression model was developed based on two-year data (Y = 214.3-3.691 Max T-0.508 Min T + 0.767 RH + 2.521 RF + 5.740 WS), which explained 95% variability. This disease prediction model will not only help farmers in early detection and timely management of bacterial leaf blight disease of rice but may also help reduce input costs and improve product quality and quantity. The model will be both farmer and environmentally friendly.

Differential effects of experimental hyperthyroidism on declined immunity of broiler chicken.

Thyroid hormones (THs) are involved in the development of lymphoid organs and regulation of immune function in birds. However, their role as an immune-modulator in the hyperthyroid state is still debatable. To explore the interrelationship of thyroxine (T4 ) and the immune system, chicks were divided into three groups. Group I was comprised of control birds, who received the basal diet while group II and III were given diets supplemented with 5 µg and 10 µg thyroxine/kg feed, respectively, from 15 to 28 days of age. Cell-mediated immune response was evaluated through in vitro abdominal macrophage phagocytosis assay, macrophage nitric oxide (NO) production, heterophil-to-lymphocyte (H:L) ratio and delayed-type hypersensitivity response against phytohemagglutinin (PHA). Humoural immune response was assessed through serum IgG and IgM antibody production against sheep red blood cells (SRBCs) and antibody production against infectious bronchitis virus (IBV). Sampling was carried out at 7, 14 and 21 days of treatment. Results have shown higher levels (p < .001) of circulating T4 in both treatment groups compared to the control group. There was a lower (p < .05) macrophage engulfment percentage, an increase in H:L ratio (p < .001) in treated birds, while their NO production remained higher (p < .05) in thyroxine supplemented groups after bacterial lipopolysaccharide stimulation. The humoural immune response revealed a significant decline (p < .001) in IgG, IgM antibody production against SRBCs but IBV circulating antibodies increased with age. In conclusion, hyperthyroidism has a strong co-relation with decreased immune performance of birds.

Vitamin B12 deficiency causing night sweats.

Vitamin B12 deficiency is common. It is known to cause a wide spectrum of neurological syndromes, including autonomic dysfunction. Three cases are discussed here in which drenching night sweats were thought to be caused by vitamin B12 deficiency. All three responded dramatically to vitamin B12 therapy.

Evidence of lifestyle modification in the management of hypercholesterolemia.

BACKGROUND: Coronary heart disease (CHD) is the leading cause of morbidity and mortality worldwide. The growth of ageing populations in developing countries with progressively urbanized lifestyles are major contributors. The key risk factors for CHD such as hypercholesterolemia, diabetes mellitus, and obesity are likely to increase in the future. These risk factors are modifiable through lifestyle. OBJECTIVES: To review current literature on the potential benefit of cholesterol lowering in CHD risk reduction with a particular focus on the evidence of non-pharmacological/lifestyle management of hypercholesterolemia. METHODS: Medline/PubMed systematic search was conducted using a two-tier approach limited to all recent English language papers. Primary search was conducted using key words and phrases and all abstracts were subsequently screened and relevant papers were selected. The next tier of searching was conducted by (1) reviewing the citation lists of the selected papers and (2) by using PubMed weblink for related papers. Over 3600 reports were reviewed. RESULTS: Target cholesterol levels set out in various guidelines could be achieved by lifestyle changes, including diet, weight reduction, and increased physical activity with the goal of reducing total cholesterol to <200 mg/dL and LDL-C<100 mg/dL. Various dietary constituents such as green tea, plant sterols, soy protein have important influences on total cholesterol. Medical intervention should be reserved for those patients who have not reached this goal after 3 months of non-pharmacological approach. CONCLUSION: CHD remains as a leading cause of death worldwide and hypercholesterolemia is an important cause of CHD. Non-pharmacological methods provide initial as well as long-term measures to address this issue.

The work-up for mixed hyperlipidemia: a case study.

This case demonstrates that a history, physical exam, and laboratory studies are all needed to determine if the disorder is primary, secondary, or both.

Condom use among high-risk heterosexual women with concurrent sexual partnerships, Houston, Texas, USA.

Concurrent sexual partnerships allow for enhanced transmission of sexually transmitted infections (STIs). Condom use dynamics in this context may be an important factor for transmission of HIV. We conducted a cross-sectional study to describe the frequency of concurrency among high-risk heterosexual women in Houston, Texas and determine the factors associated with condom use. A total of 553 participants were recruited using respondent-driven sampling and completed an anonymous questionnaire; 256 (49%) were identified as having a concurrent partnership. The prevalence of condom use at last sexual encounter was 26%. Women were significantly more likely to use condoms if their sexual encounter was with a casual partner and if alcohol and/or drugs were not used. The high prevalence of concurrent partnerships suggests the presence of a dense sexual network which may enable the rapid spread of STIs and HIV. The risk of transmission may be additionally increased due to the low prevalence of condom use.

Neuroendocrinology of menopause.

It was once thought that menopause is the result of exhaustion of ovarian follicles. However, it is now known that complex interplay of neurohormonal and ovarian signals heralds the onset of menopause and hypothalamus plays an important role. Increasing dysfunction of these neurohormonal and ovarian factors with aging ultimately leads to reproductive senescence. Early in the menopause transition, the initial event is a decline in circulating inhibin-B levels in the early follicular phase. In the late perimenopause, levels of estradiol (E2) and inhibin-A also fall, inhibin-B levels remain low and follicle stimulating hormone (FSH) is markedly elevated. Serum androgen levels appear to fall with age rather than having any clear-cut relationship to the menopausal transition or menopause.