A STUDY OF STOOL SAMPLE FROM HIV POSITIVE AND HIV NEGATIVE AT ANDHRA PRADESH.

 Objective: The objective of this study is to investigate the variations, if any, in the types of intestinal parasites in HIV-positive and HIV-negative individuals.Methods: For their HIV status in our laboratory by enzyme-linked immunoasorbant assay and TRIDOT, sample stool, macroscopic and microscopic examination, formal-ether concentration technique f, saline wet mount, iodine wet mount, modified acid-fast stain. Results: For the purpose of statistical analysis, the enteric parasites are divided into the coccidian group (Cryptosporidium+Isospora belli) and conventional enteric parasites (Entamoeba histolytica, Giardia intestinalis, and Ascaris lumbricoides), and enteric parasitic infection is more common in HIV-positive patients with diarrhea than HIV-positive patient without diarrhea or HIV-negative individuals.Conclusion: The study period of 1 year and 8 months revealed that it is difficult to locate/identify a HIV-positive person in a place like Kadapa on account of confidentiality/lack of awareness among the population. Detection of intestinal parasites is 17.3% in HIV-positive patients and 12% in HIV-negative individuals

A STUDY OF URINE FROM HIV-POSITIVE AND HIV-NEGATIVE INDIVIDUALS AT ANDHRA PRADESH

Objective: The aim of this study is to investigate the variations, if any, in urinary bacterial pathogens in HIV-positive and HIV-negative individuals.Methods: Urine sample, macroscopic and microscopic examination for identification of bacteria use by method of Standard loop method, using identification methods, Grams-staining, Biochemical tests.Results: Out of 75 HIV-positive males, 52 males were married, 23 males were unmarried; risk factors are sexually 28, occupationally majority were labor, 31, age group more in 19-25 age, only 9 HIV-positive patients presented with symptoms of urinary tract infection, Escherichia coli was the most frequently occurring bacterial isolate from positive urine culture followed by Klebsiella spp.Conclusion: The study period of 1 year and 8 months revealed that it is difficult to locate/identify an HIV-positive person in a place like Kadapa on account of confidentiality/lack of awareness among the population. Having identified the HIV-positive cases, collection of urine samples from the patients also needed counseling and intervention by the respective clinicians, especially when patients were not having any symptoms. Out of 50 HIV-negative individuals, only 1 (2%) urine sample is showing significant bacteriuria

PREVALENCE OF FUNGAL IN OPPORTUNISTIC INFECTION HIV TYPE-1 IN SUBURBAN, KADAPA

Objective: Isolate fungal element causing in opportunistic infection of human immunodeficiency virus and correlated with CD4 cell counts.Methods: Different samples are used and media: Sabouraud dextrose agar, using mycological methods such as potassium hydroxide, lactophenol cotton blue mount, India ink preparation, and Gram-staining.Results: Both bacterial and fungal isolates were obtained from 8 cases. Pneumococci and Candida spp. were observed in 3 cases followed by Staphylococcus aureus and Aspergillus in 2 cases, Klebsiella pneumoniae and Geotrichum spp., Pneumococci and Penicillium spp., and Acinetobacter baumannii, and Cryptococcus spp. from 1 case each. Only fungal isolates were obtained from 6 cases of sputum samples. Candida spp. (50%) were predominant fungal isolate followed by Aspergillus spp. (33.33%) and Cryptococcus spp. (16.66%). Cryptococcus spp. was the predominant fungal isolate (66.6%) followed by Candida pseudotropicalis (Kefyr) in 16.66% (1/6) and Acinetobacter spp. was isolated from 16.66 % (1/6).Conclusion: Respiratory infections were the predominant manifestations comprising chronic bronchitis, pneumonia, chronic obstructive pulmonary disease, and chronic cough. 66 individuals were with respiratory symptoms, of them 28 individuals had CD4 count 50-200/mm3, 22 had CD4 <50/mm3

Environmental Response and Genomic Regions Correlated with Rice Root Growth and Yield under Drought in the OryzaSNP Panel across Multiple Study Systems

Funding: This research was funded by the Generation Challenge Program (GCP) project G3008.06, “Targeting Drought-Avoidance Root Traits to Enhance Rice Productivity under Water-Limited Environments". The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Peer reviewedPublisher PD

Environmental Response and Genomic Regions Correlated with Rice Root Growth and Yield under Drought in the OryzaSNP Panel across Multiple Study Systems

The rapid progress in rice genotyping must be matched by advances in phenotyping. A better understanding of genetic variation in rice for drought response, root traits, and practical methods for studying them are needed. In this study, the OryzaSNP set (20 diverse genotypes that have been genotyped for SNP markers) was phenotyped in a range of field and container studies to study the diversity of rice root growth and response to drought. Of the root traits measured across more than 20 root experiments, root dry weight showed the most stable genotypic performance across studies. The environment (E) component had the strongest effect on yield and root traits. We identified genomic regions correlated with root dry weight, percent deep roots, maximum root depth, and grain yield based on a correlation analysis with the phenotypes and aus, indica, or japonica introgression regions using the SNP data. Two genomic regions were identified as hot spots in which root traits and grain yield were co-located; on chromosome 1 (39.7–40.7 Mb) and on chromosome 8 (20.3–21.9 Mb). Across experiments, the soil type/ growth medium showed more correlations with plant growth than the container dimensions. Although the correlations among studies and genetic co-location of root traits from a range of study systems points to their potential utility to represent responses in field studies, the best correlations were observed when the two setups had some similar properties. Due to the co-location of the identified genomic regions (from introgression block analysis) with QTL for a number of previously reported root and drought traits, these regions are good candidates for detailed characterization to contribute to understanding rice improvement for response to drought. This study also highlights the utility of characterizing a small set of 20 genotypes for root growth, drought response, and related genomic regions

The OryzaSNP germplasm set was phenotyped with a range of root-screening techniques.

<p>A) rhizotron (Ab09CR: Univ Aberdeen), B) penetration of nonwoven fabric (Ab09CNWNW: Univ Aberdeen), C) monoliths from line source sprinkler (Na10 and Na11; Nagoya Univ), D) soil-filled cylinders (Ba10C; Barwale Foundation, and CS09C; Charles Sturt Univ), E) hydroponics (Ab09CH: Univ Aberdeen), F) monoliths in the field (IR08FL and IR09dFL; IRRI), G) lysimeters (IR08C; IRRI, IC09C; ICRISAT), and (H) in the field by excavation (TN10F, TN11F; Tamil Nadu Agric. Univ).</p

Biplots for A) grain yield, B) root dry weight, C) maximum root depth, and D) % deep roots.

<p>Data previously reported by Henry et al (2011), Gowda et al (2012), and Shrestha et al (2013) were used to calculate some of the results shown in this figure.</p

A genomic region on chromosome 8 (20.3–21.9 Mb) was identified as a hot spot in which percent deep roots and yield aligned.

<p>Colors indicate each experiment from which the phenotypic data and introgression regions were correlated. Experiments from which introgression regions fell within the hot spot are identified in the legend.</p

AMMI (mean polish) and location standardized model analysis of GxE interactions across all experiments from which yield, root dry weight (RDW), maximum root depth (MRL), and percent deep roots (%DR) were measured.

<p>AMMI (mean polish) and location standardized model analysis of GxE interactions across all experiments from which yield, root dry weight (RDW), maximum root depth (MRL), and percent deep roots (%DR) were measured.</p

Previously reported root-related QTLs within the regions of chromosomes 1 and 8 where the highest number of traits aligned in this study.

<p>Gramene QTL ID: the Gramene database accession code; List hits: the number of 100kb blocks in the current introgression bin that intersect the Gramene QTL; List total: the total number of 100kb blocks in current QTL bin; Population hits: the total number of genome-wide 100kb introgression blocks for the current Gramene QTL category (out of a total of 3680 100kb introgression blocks for all Gramene QTLs; P value: probability based on a one-tailed Fisher's Exact Test; Reference: the publication in which the QTL was reported.</p><p>Previously reported root-related QTLs within the regions of chromosomes 1 and 8 where the highest number of traits aligned in this study.</p