Current Issue : October - December Volume : 2014 Issue Number : 4 Articles : 7 Articles
Background: Hypervariable region 1 (HVR1) contained within envelope protein 2 (E2) gene is the most variable\npart of HCV genome and its translation product is a major target for the host immune response. Variability within\nHVR1 may facilitate evasion of the immune response and could affect treatment outcome. The aim of the study\nwas to analyze the impact of HVR1 heterogeneity employing sensitive ultra-deep sequencing, on the outcome of\nPEG-IFN-? (pegylated interferon ?) and ribavirin treatment.\nMethods: HVR1 sequences were amplified from pretreatment serum samples of 25 patients infected with genotype\n1b HCV (12 responders and 13 non-responders) and were subjected to pyrosequencing (GS Junior, 454/Roche).\nReads were corrected for sequencing error using ShoRAH software, while population reconstruction was done using\nthree different minimal variant frequency cut-offs of 1%, 2% and 5%. Statistical analysis was done using Mannââ?¬â??Whitney\nand Fisherââ?¬â?¢s exact tests.\nResults: Complexity, Shannon entropy, nucleotide diversity per site, genetic distance and the number of genetic\nsubstitutions were not significantly different between responders and non-responders, when analyzing viral\npopulations at any of the three frequencies (?1%, ?2% and ?5%). When clonal sample was used to determine\npyrosequencing error, 4% of reads were found to be incorrect and the most abundant variant was present at a\nfrequency of 1.48%. Use of ShoRAH reduced the sequencing error to 1%, with the most abundant erroneous\nvariant present at frequency of 0.5%.\nConclusions: While deep sequencing revealed complex genetic heterogeneity of HVR1 in chronic hepatitis C patients,\nthere was no correlation between treatment outcome and any of the analyzed quasispecies parameters....
Background: Rapid diagnostic tests play a pivotal role in the early diagnosis of malaria where microscopy or\npolymerase chain reaction are not immediately available.\nCase presentation: We report the case of a 39 year old traveler to Canada who presented with fever, headache,\nand abdominal pain after visiting friends and relatives in India. While in India, the individual was not ill and had no\nsigns or symptoms of malaria. Laboratory testing upon his return to Canada identified a false positive malaria rapid\ndiagnostic (BinaxNOW�® malaria) result for P. falciparum with coincident Salmonella Typhi bacteraemia without\nrheumatoid or autoimmune factors. Rapid diagnostic test false positivity for malaria coincided with the presence or\nabsence of Salmonella Typhi in the blood.\nConclusions: Clinicians should be aware that Salmonella Typhi infection may result in a false positive malaria rapid\ndiagnostic test. The mechanism of this cross-reactivity is not clear....
Background: It is important to understand the specific HPV genotype distribution in screen-detected lesions. HPV\nGenotype is helpful for separating HPV-positive women at greater risk of cancer from those who can regress\nspontaneously and for preventing cervical cancer at early stage. The aim of this study was to investigate the\nhigh-risk HPV genotype distribution among cervical cytology abnormality in Pearl River Delta Region, Southern China\nMethods: 5585 HPV-infected women were screened from 77069 women in Pearl River Delta Region. Information was\nobtained from 3226 screened subjects through questionnaires and personal interviews. Exfoliated cervical cells were\ncollected by doctors for HPV test with MassARRAY (Sequenom, Sandiego, CA) technique based on the matrix-assisted\nlaser desorption/ionization time-of flight (MALDI-TOF) mass spectrometry (MS). The ThinPrep cytology test was performed\nto screen for cervical cancer. Unconditional logistic was used to determine the most common HPV carcinogenic types.\nResults: Of the 3226 HPV-positive samples tested, 1744 (54.1%) with normal cervical cytology, 1482 (45.9%) with abnormal\ncytology. The five most common HPV types in this study were HPV16 (20.2%), HPV52 (17.1%), HPV58 (13.2%), HPV18\n(9.5%), HPV6 (7.6%). Overall, HPV16 (OR = 10.5, 95% CI: 3.7 ~ 29.6), HPV33 (OR = 9.1, 95% CI: 2.8 ~ 29.2), HPV58 (OR = 6.3,\n95% CI: 2.1 ~ 18.6), HPV31 (OR = 4.5, 95% CI: 1.3 ~ 15.5), multiple genotype infection (OR = 3.0, 95% CI: 1.7 ~ 14.7), especially\nHPV16 and HPV33, increased the risk of cytology abnormalities.\nConclusions: HPV16, HPV31, HPV33, HPV58, and multiple HPV genotype infection increased the risk of cytology\nabnormalities in Pearl River Delta Region and might be useful for the screening, preventing, treating, and monitoring of\npre-cancer lesions in southern China....
Background: Protease inhibitor monotherapy is associated with more frequent episodes of viral rebounds above\n50 copies/mL than triple therapy. Objective: To evaluate if, compared to triple-drug therapy, protease inhibitor\nmonotherapy is associated with increased levels of inflammatory/procoagulant markers and more frequent plasma\nresidual viremia detection.\nMethods: In this cross-sectional study, we included patients treated for ? 1 year with darunavir/ritonavir or lopinavir/\nritonavir as monotherapy (n = 72) or with two nucleos(t)ides (n = 74). All samples were tested for CRP, IL-6, fibrinogen\nand D-dimer. Residual viremia was determined using an ultrasensitive qualitative nested-PCR of the HIV pol gene with\na limit of detection of 1 copy of HIV-RNA.\nResults: We found no differences in levels of inflammatory/procoagulant markers or in the proportion of patients with\nplasma residual viremia detection by treatment group.\nConclusion: The long-term treatment with protease inhibitor monotherapy in the setting of routine clinical practice is\nnot associated with a higher prevalence of plasma residual viremia or more elevated inflammatory/procoagulant\nmarkers levels than triple drug therapy....
Background: The impact of socio-demographic factors and baseline health on the mortality burden of seasonal\nand pandemic influenza remains debated. Here we analyzed the spatial-temporal mortality patterns of the 1918\ninfluenza pandemic in Spain, one of the countries of Europe that experienced the highest mortality burden.\nMethods: We analyzed monthly death rates from respiratory diseases and all-causes across 49 provinces of Spain,\nincluding the Canary and Balearic Islands, during the period January-1915 to June-1919. We estimated the\ninfluenza-related excess death rates and risk of death relative to baseline mortality by pandemic wave and province.\nWe then explored the association between pandemic excess mortality rates and health and socio-demographic\nfactors, which included population size and age structure, population density, infant mortality rates, baseline death\nrates, and urbanization.\nResults: Our analysis revealed high geographic heterogeneity in pandemic mortality impact. We identified 3\npandemic waves of varying timing and intensity covering the period from Jan-1918 to Jun-1919, with the highest\npandemic-related excess mortality rates occurring during the months of October-November 1918 across all Spanish\nprovinces. Cumulative excess mortality rates followed a southââ?¬â??north gradient after controlling for demographic factors,\nwith the North experiencing highest excess mortality rates. A model that included latitude, population density,\nand the proportion of children living in provinces explained about 40% of the geographic variability in cumulative\nexcess death rates during 1918ââ?¬â??19, but different factors explained mortality variation in each wave.\nConclusions: A substantial fraction of the variability in excess mortality rates across Spanish provinces remained\nunexplained, which suggests that other unidentified factors such as comorbidities, climate and background\nimmunity may have affected the 1918ââ?¬â??19 pandemic mortality rates. Further archeo-epidemiological research should\nconcentrate on identifying settings with combined availability of local historical mortality records and information\non the prevalence of underlying risk factors, or patient-level clinical data, to further clarify the drivers of 1918\npandemic influenza mortality....
Background: In healthcare facilities, conventional surveillance techniques using rule-based guidelines may result in\nunder- or over-reporting of methicillin-resistant Staphylococcus aureus (MRSA) outbreaks, as these guidelines are\ngenerally unvalidated. The objectives of this study were to investigate the utility of the temporal scan statistic for\ndetecting MRSA clusters, validate clusters using molecular techniques and hospital records, and determine significant\ndifferences in the rate of MRSA cases using regression models.\nMethods: Patients admitted to a community hospital between August 2006 and February 2011, and identified with\nMRSA > 48 hours following hospital admission, were included in this study. Between March 2010 and February 2011,\nMRSA specimens were obtained for spa typing. MRSA clusters were investigated using a retrospective temporal\nscan statistic. Tests were conducted on a monthly scale and significant clusters were compared to MRSA outbreaks\nidentified by hospital personnel. Associations between the rate of MRSA cases and the variables year, month, and\nseason were investigated using a negative binomial regression model.\nResults: During the study period, 735 MRSA cases were identified and 167 MRSA isolates were spa typed. Nine\ndifferent spa types were identified with spa type 2/t002 (88.6%) the most prevalent. The temporal scan statistic\nidentified significant MRSA clusters at the hospital (n = 2), service (n = 16), and ward (n = 10) levels (P ? 0.05). Seven\nclusters were concordant with nine MRSA outbreaks identified by hospital staff. For the remaining clusters, seven\nevents may have been equivalent to true outbreaks and six clusters demonstrated possible transmission events.\nThe regression analysis indicated years 2009ââ?¬â??2011, compared to 2006, and months March and April, compared to\nJanuary, were associated with an increase in the rate of MRSA cases (P ? 0.05).\nConclusions: The application of the temporal scan statistic identified several MRSA clusters that were not\ndetected by hospital personnel. The identification of specific years and months with increased MRSA rates may\nbe attributable to several hospital level factors including the presence of other pathogens. Within hospitals, the\nincorporation of the temporal scan statistic to standard surveillance techniques is a valuable tool for healthcare\nworkers to evaluate surveillance strategies and aid in the identification of MRSA clusters....
Background: Human papillomavirus (HPV) is the necessary cause of cervical cancer. Published data on the\nepidemiology of HPV in women with invasive cervical cancer (ICC) in New Zealand (NZ) are limited. This\ncross-sectional study investigated the distribution of high-risk and low-risk HPV types in cervical specimens collected\nfrom women throughout NZ who had been diagnosed with ICC between 2004 and 2010.\nMethods: Women aged ?18 years, with ICC International Federation of Gynecology and Obstetrics stage Ib or\ngreater were identified from the five tertiary public hospitals in NZ regularly treating women with ICC. Women\nwere enrolled in the study only after obtaining informed consent. Stored, formalin fixed, paraffin-embedded cervical\nspecimens were retrieved and histopathologically reviewed to confirm the diagnosis of ICC. Cervical specimens\nwere tested for HPV using polymerase chain reaction-short fragment10; HPV DNA was detected using DNA enzyme\nimmunoassay and typed by reverse hybridization line probe assay.\nResults: 242 women were enrolled and ICC was histologically confirmed in 227 samples. HPV infection was\ndetected in 88.5% (n = 201; 95% CI: 83.7ââ?¬â??92.4) of women with ICC; high-risk HPV types were detected in 87.2% of\nwomen. The most commonly detected HPV types were HPV-16 (51.1%) and HPV-18 (20.7%), followed by HPV-31\n(4.0%), HPV-45 and HPV-52 (3.1% each). Overall, HPV distribution was highest (94.3%) in women aged 30ââ?¬â??39 years at\ndiagnosis and a higher distribution of HPV-16 (68.8%) was observed in women younger than 30 years. The overall\ndistribution of HPV types between Maori and non-Maori women were similar. HPV-positive women with ICC stage II\nor greater were less likely to be infected with HPV-16/18 (P = 0.002) or HPV-18 (P = 0.029) compared with the other\nhigh-risk types. Single type infection and multiple infections were detected in 93.5% and 5.5% of women, respectively.\nConclusions: HPV-16, HPV-18, HPV-31, HPV-45 and HPV-52 were the most commonly detected high-risk HPV types.\nFindings from the study fill an important data gap on HPV type distribution from NZ which will help facilitate better\nunderstanding of the epidemiology of HPV in NZ women....
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