Mhc-DRB genes in primates appear to possess a complex and highly divergent microsatellite, DRB-STR. A panel of 154 pedigreed olive baboons (Papio anubis) was examined for their DRB content by DRB-STR analysis of genomic DNA. Using the same methodology on DNA of feces samples, DRB variability of a silvery gibbon population (Hylobates moloch) (N = 24), an endangered species, could successfully be studied. In both species, length determination of the DRB-STR resulted in the definition of unique genotyping patterns that appeared to be specific for a certain chromosome. Moreover, the different STR lengths were shown to segregate with the allelic variation of the respective gene. The results obtained expand data gained previously on DRB-STR typing in macaques, great apes, and humans and strengthen the conclusion that this protocol is applicable in molecular ecology, conservation biology, and colony management, especially of endangered primate species.Gene products of the major histocompatibility complex (MHC) of human and non-human primates play a crucial role in adaptive immunity, and most of the relevant genes not only show a high degree of variability (polymorphism) but also copy number variation (CNV) is observed. Due to this diversity, MHC proteins influence the capability of individuals to cope with various pathogens. MHC and/or MHC-linked gene products such as odorant receptor genes are thought to influence mate choice and reproductive success. Therefore, MHC typing of wild and captive primate populations is considered to be useful in conservation biology, which is, however, often hampered by the need of invasive and time-consuming methods. All intact The online version of this article (doi:10.1007/s00251-016-0968-0) contains supplementary material, which is available to authorized users. DRB gene encoding the beta chain of the class II DR molecule. Therefore, DRB typing has often been used as an indication for MHC diversity in various species and for diverse purposes, as e.g., the importance of the MHC for mate choice  class I and II molecules are cell-surface glycoproteins, which play a central role in immune-related processes as in control or susceptibility to infectious diseases, in transplantation research, and in reproduction immunology by presenting peptides to CD8 and/or CD4 T lymphocytes. The MHC genes/loci encoding these molecules are structured in gene families, the hallmark of which is the allelic and copy number variation (CNV) of most of their genes. Balancing selection exerted mainly by pathogen pressure is believed to represent one of the major forces driving MHC polymorphism and diversity  encoding one or several beta chains. In humans, for example, five DR region configurations have been defined. Each configuration is composed of a DRA gene in conjunction with a unique combination of DRB genes/lineages, which are usually inherited together as a so-called haplotype. A lineage is defined as group of alleles  within a given gene that cluster together in the phylogenetic tree and are thus supposed to have the same evolutionary origin. The high degree of human DRB variability is mainly due to its polymorphic (variable) DRB1 gene. Chimpanzees, as representatives of the great apes and the closest relatives of humans, show a higher number of region configurations, only three of which displaying allelic variation. This allelic variation is, however, not unique to the DRB1 gene as polymorphism is present within all genes. In contrast, Old World monkeys (OWM) as macaques show a far higher number of region configurations with a very low degree of allelic variation. This peculiar situation of CNV in OWM is the reason, why DRB typing in these animals is hampered by the need of invasive DNA/RNA isolation procedures from blood samples as well as subsequent laborious and expensive techniques such as cloning/Sanger sequencing or next-generation sequencing. However, in close proximity to the highly variable DRB exon 2 is a complex microsatellite located in intron 2. This so-called DRB-STR (D6S2878) is present in all primate DRB genes analyzed so far with an intact exon 2–intron 2 boundary , although the olive baboon serves as model species in renal . Fortunately, primers that had been developed for the amplification of the human DRB-STR could be successfully used for the amplification of Hymo- as well as Paan-DRB. For the latter, primers used for the amplification of the DRB-STR in macaques could additionally be employed. In such a way, a large cohort of olive baboons, which had been partially pedigreed beforehand, has been defined for their DRB content. Although it has been widely reported that both DNA yield and quality derived from fecal samples is lower than that extracted from blood or tissue , were housed at the large animal facility of the INSERM unit 1064 . Blood sampling was performed under anesthesia in accordance with the institutional ethical guidelines. The 154 animals analyzed in this study were partly pedigreed and descended from 34 sires and 105 dames. In most cases, the sires were known but often two males could possibly have sired the offspring.Twenty-four silvery gibbon individuals reside at Port Lympne and Howletts, UK, zoological institutions, of which the pedigree was partly known. Fecal samples were allocated to specific individuals either by direct observation, and two fecal samples per individual were collected immediately or by hand feeding foodstuffs containing maize that could then be identified on subsequent days. Samples were immediately frozen upon collection.DNA was extracted from fresh EDTA or citrate blood samples using a conventional phenol/chloroform method. Briefly, white blood cells (WBC) were harvested after the lysis of red blood cells and removing the plasma by spinning down the WBCs. WBC pellets were then lysed using a 0.2% SDS and 100 μg/ml proteinase K solution and incubated overnight at 55 °C. An equal volume of phenol was then added to the lysate, and the incubation tubes were intensively mixed and then centrifuged. The upper aqueous layer was harvested and an equal volume of phenol and then of chloroform were added. Tubes were again intensively mixed, centrifuged, and the upper aqueous layer was harvested. Finally, an equal volume of chloroform was added, tubes were mixed, centrifuged, and the upper aqueous layer was harvested again. DNA were precipitated at −20 °C with two volumes of 96% ethanol. The DNA pellets were washed using 70% ethanol and then air-dried before reconstitution in sterile water. DNA concentration were adjusted at 50 ng/μl and stored at 4 °C.Taq polymerase enzymatic reaction  following the Stool Larger Volumes protocol. This commercially available kit was chosen as it included a step that involved binding secondary compounds found in plant matter that is present in herbivorous diets, which is applicable to the silvery gibbon species. Plant secondary compounds negatively impact the PCR process by interfering with the Taq polymerase  with 0.1 μM of the forward primer, 0.1 μM of the reverse primer, 2.5 mM MgCl2, 0.2 mM of each dNTP, 1× PCR buffer II , and 100 ng DNA.Amplification of the relevant DNA segment in olive baboon and silvery gibbon was performed as described for humans and rhesus macaques using the same primer sets . STR analysis was performed with the Genemapper software 5 program (Applied Biosystems) and all samples were at least analyzed twice. For Paan-DRB alleles and 15 different Hymo-DRB alleles were sequenced from exon 2 to intron 2, including the microsatellite. Therefore, we used the same primers and PCR reaction as described for humans and rhesus macaques  and phylogenetic analyses were then performed using MEGA version 4.0.2. Pairwise distances were calculated using maximum likelihood and Kimura-2 parameter for creating a phylogram. Confidence estimates of grouping were calculated according to the bootstrap method generated from 1000 replicates and the tree was rooted with Caja-DRB*W16:01.Multiple sequence alignments of exon 2 of silvery gibbon DNA sequences are deposited to the EMBL gene bank with accessions numbers JQ666205–JQ666210, JQ666212–JQ666215, JQ666217–JQ666230, JQ666232–JQ666251, KJ701253–KJ701266, and LN867601).DRB region configurations of humans . These infrequent amplification failures of DRB alleles or STR sequences are most probably due to primer inconsistencies. Although dames and sires of the first generation were mostly not available for the analyses, it can be shown that sire PA956A has not fathered offspring K22BA, since this animal does not share one of the sire’s DRB haplotypes.A large cohort of olive baboons # 154) of mostly two generations originating from 34 sires and 105 dames have been analyzed with the DRB-STR method. As has been observed for other primates, microsatellite typing of the baboon samples with this STR resulted in the definition of various microsatellite patterns. As comparison, Fig. 54 of mosDRB typing results of the entire olive baboon panel, we have been able to define 19 different DRB region configurations/haplotypes varying in content and numbers of DRB genes present , the only baboon species of which many DRB alleles had been sequenced in the past  the same approach as for the olive baboon was followed. With the human DRB-STR primers, the DRB microsatellites could be successfully amplified of all but one silvery gibbon. As for the olive baboons, the amplification resulted in specific microsatellite patterns, which segregate in a Mendelian fashion. Subsequent sequencing of exon 2 plus the adjacent microsatellite showed that also in silvery gibbons, a certain microsatellite length is indicative for a DRB allele, and a DRB haplotype can be defined by a specific microsatellite pattern. As a result, part of the pedigree of the two founder pairs can be substantiated by the segregation of DRB haplotypes  and the composition of the DRB region configurations/haplotypes appears to show a low degree of variability. In contrast to other primate species and especially to Old World monkeys as baboons . Furthermore, the lineage DRB*W099 seems to be monomorphic and its one allele, DRB*W099:01, is present on 8 of 13 haplotypes. Remarkably, the DRB5 and DRB6 lineages, which are both old entities in primate evolution, are not observed ESM 2(PDF 32 kb)ESM 3(PDF 32 kb)Suppl. Fig. 1DRB exon 2 of humans, chimpanzees, rhesus macaques, and silvery gibbons. The alignment is sorted according the amino acids (9–13) of the peptide binding site. (PDF 27 kb)Alignment of deduced amino acids of part of Suppl. Fig. 2Nucleotide composition of the DRB-STR in intron 2 of humans, chimpanzees, and silvery gibbons (PDF 54 kb)


To describe patterns in thermal injury incidence and hospitalisations by age, gender, calendar year and socioeconomic status among 0–4 year olds in England for the period 1998–2013.708,050 children with linked primary care and hospitalisation data from the Clinical Practice Research Datalink (CPRD) and Hospital Episode Statistics (HES), respectively.Incidence rates of all thermal injuries (identified in CPRD and/or HES), hospitalised thermal injuries, and serious thermal injuries . Adjusted incidence rate ratios (IRR) and 95% confidence intervals (95%CI), estimated using Poisson regression.Incidence rates of all thermal injuries, hospitalised thermal injuries, and serious thermal injuries were 59.5 per 10,000 person-years (95%CI 58.4–60.6), 11.3 (10.8–11.8) and 2.15 (1.95–2.37), respectively. Socioeconomic gradients, between the most and least deprived quintiles, were steepest for serious thermal injuries . Incidence of all thermal injuries  and serious thermal injuries  reduced between 1998/9 and 2012/13. Incidence rates of hospitalised thermal injuries did not significantly change over time.Incidence of all thermal injuries and those hospitalised for ≥72 h reduced over time. Steep socioeconomic gradients support continued targeting of preventative interventions to those living in the most deprived areas. They are the fourth leading cause of injury-related hospitalisation among 0–4 year olds in England Quantifying the burden of thermal injuries in England is a challenge, with existing national data focusing on those undergoing hospitalisation 22.1The CPRD is a primary care research database containing the longitudinal primary care records of over 11 million patients from the UK Using the CPRD, we carried out an open cohort study, with children entering the cohort at the latest date of: their date of birth, their general practice registration date, 1st January 1998, and the date the practice met the CPRD data quality standards. Each child contributed data to the study until their end of follow-up date, which was the earliest of: 31st December 2013, the child's fifth birthday, the date medical data were last collected from the general practice, or the date the child left the practice (e.g. child moved practice or died). The study population was therefore a subset of children from England, representing approximately 6% of 0–4 year olds from England in 2013.2.2For each child in the study cohort we identified any recorded thermal injury events occurring during their follow-up time from their primary care (CPRD) and/or hospitalisation records (HES). The CPRD contains information about thermal injuries managed in primary care, but also contains information communicated to the GP about emergency department (ED) attendances and hospitalisations. Previous studies have shown high levels of transcription of information from discharge letters and outpatient summaries into the primary care record 2.3To identify incident events using both CPRD and HES data, it was necessary to exclude duplicate records for the same injury recorded in both data sources, and to exclude repeat records for the same injury event (e.g. repeated dressing changes). We did this by using a time-based algorithm , as prevFor each child we also identified the number of incident thermal injury events that underwent hospitalisation and the number of ‘serious’ thermal injury events. We defined serious thermal injuries as those undergoing hospitalisation for 72 h or more, a definition previously used in a study of traumatic injury 2.4p < 0.01 considered statistically significant.We estimated incidence rates per 10,000 person-years (PY), with 95% confidence intervals (95%CI), for thermal injuries identified in CPRD and/or HES, those undergoing hospitalisation, and serious thermal injuries , by child age, gender, socioeconomic status and calendar time. Socioeconomic status was measured using quintiles of the Index of Multiple Deprivation 2010, an area based measure of deprivation based upon 38 indicators covering income, employment, health, education, crime, access to services and the living environment. Adjusted incidence rate ratios (IRRs) were estimated using Poisson regression, mutually adjusting for child age, gender, socioeconomic status, region and calendar year. We tested for an interaction between socioeconomic status and calendar year using a likelihood ratio test, with To estimate the burden of thermal injuries among children aged 0–4 years old for the whole of England in 2013, we applied our 2013 incidence rates by age and gender to the 2013 mid-year population estimate for England This study was approved by the Independent Scientific Advisory Committee for the Medicines and Healthcare products Regulatory Agency (protocol 13-199R), giving permission for use of both CPRD and HES data.3The study population consisted of 708,050 children aged 0–4 years old who were contributing to the CPRD database between 1998 and 2013, registered across 393 general practices. Of these children, 369,513 (52.2%) were male and 338,537 (47.8%) were female . Median 3.1p = 0.004 test for interaction), with children from the most deprived quintiles having a 60% higher rate of thermal injuries than those in the least deprived quintile in the period 2010–2013, compared to a two-fold increased risk in 1998–2001 , with children from the most deprived quintiles having a 2.5 time higher rate than those in the least deprived quintile in the period 2010–2013 , compared to a nearly four-fold increased risk in 1998–2001  (p = 0.17).Amongst the study cohort, 2170 thermal injuries led to hospitalisation during the study period, of which 413 (19.0%) were admitted for 72 h or more . Patterns by child age and gender were similar to overall incidence . The soc50–5.80) . The soc3.3Based upon our estimated thermal injury incidence rates from CPRD and HES data, and the mid-year population estimate for 2013, we estimated that 17,854 thermal injuries occurred among 0–4 year olds in England in 2013, with 4716 events undergoing hospitalisation. For the period 1998–2002, we estimated that 131,826 thermal injuries occurred among 0–4 year olds in the UK.4This study presents detailed data on the incidence of thermal injuries among a cohort of children aged 0–4 years living in England through the use of linked primary care and hospitalisation data. Thermal injury incidence rates were higher among males, and peaked at the age of 15–17 months. Children from the most deprived quintiles had the highest thermal injury rates, with the socioeconomic gradient steepest for serious thermal injuries. Over time there was a narrowing of socioeconomic inequalities between the most and least deprived quintiles for all thermal injuries and thermal injuries undergoing hospitalisation. Over the study period, there was a 36% reduction in the incidence of thermal injuries identified in CPRD and/or HES, and a 56% reduction in serious thermal injuries (admitted for ≥72 h), but no significant change in the incidence of thermal injuries undergoing hospitalisation.4.1The main strengths of our study are the large study size and use of linked primary care and hospitalisation data. With thermal injuries seen in a range of health care settings, the use of linked health data enables the capture of not only injuries leading to hospitalisation but also more minor thermal injuries , enabling a more complete estimate of thermal injury incidence. While data held in the CPRD are broadly representative of the demographics of the UK population Through the use of routinely collected health data we are limited by the availability and quality of data recorded. We used admissions lasting 72 h or more as a proxy for serious thermal injuries, as the Read and ICD-10 codes used in CPRD and HES do not allow comprehensive assessment of the extent and severity of burns; key information of interest to those working within burns services. Data on mechanism  and place of occurrence (e.g. home) are poorly recorded within UK primary care data ED data are yet to be linked to the CPRD; an important limitation of our study. GPs receive information about their patients’ attendances at EDs, outpatient clinics and hospitalisations. At present, without linked ED data we are relying upon GPs both receiving information about ED attendances and recording this information in the primary care record. The extent to which ED attendances are captured in the primary care record is unknown and difficult to quantify. While not directly comparable (as will not capture primary care attendances but will capture repeat ED attendances for the same injury), data from the HASS/LASS injury surveillance system estimated that for the period 1998–2002 there were 164,153 burns among 0–4 year olds 4.2Existing data on the epidemiology of burns most commonly comes from single-centres Reviews of the epidemiology of burns both in Europe and globally suggest reductions in burn occurrence and severity in high-income countries The observed peak in burns incidence among children aged 15–17 months, with incidence higher among males than females is consistent with existing literature 4.3Using our estimated incidence rates, at least 17,854 thermal injuries occurred among 0–4 year olds in the England in 2013, with 4716 events undergoing hospitalisation. This is likely to be an underestimation, as by using linked primary care and hospitalisation data, we will have only captured ED attendances that were recorded in the primary care record. While our findings show a reduction in the incidence of all thermal injuries (identified in CPRD and/or HES) and serious thermal injuries, this study highlights steep socioeconomic gradients in injury risk, particularly for more severe thermal injuries. In accordance with guidance from the National Institute for Health and Care Excellence We declare that we have no competing interests.DK, EO, LT, TB and RB were involved in the conception and design of the study. RB undertook the analysis and drafted the manuscript. All authors  contributed to interpreting the findings and revising the manuscript.National Institute for Health Research School for Primary Care Research (NIHR SPCR) and The University of Nottingham. The funder had no involvement in the collection, analysis or interpretation of the data. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health.This paper presents independent research funded by the Approval for this study was obtained from the Independent Scientific Advisory Committee for the Medicines and Healthcare products Regulatory Agency in December 2013.


Transcript levels of most PIPs down-regulated following TWW irrigation in both soils, but relative gene expression of three PIPs was significantly higher in summer for sandy soil and FW than for clay soil and TWW; their mRNA levels was significantly correlated to Ks root. A pot experiment, which compared short term influences of saline and TWW found that both treatments, compared to FW, reduced root water uptake and PIPs mRNA levels by 2-fold after 20 days, and the decreases continued with time until the end of the experiment. These latter data indicated that salinity had an important influence. Our results suggest that plant hydraulic adjustment to soil texture and water quality occurs rapidly, i.e. within days, and is modulated by PIPs expression.Citrus hydraulic physiology and PIP transcript levels were characterized in heavy (clay) and light (sandy loam) soils with and without treated waste water (TWW) irrigation after a summer irrigation season and at the end of a winter rainy season recovery period. Consistent reductions in clay soils compared to sandy loam were found for fresh water (FW) and TWW irrigation, respectively, in root water uptake, as well as in hydraulic conductivity of whole plant (K In Israel, most fruit tree plantations, including citrus orchards, are irrigated with TWW of various qualities. Depending on the original water source and level of treatment, TWW might result in increased salinity, increased concentrations of organic and inorganic compounds, and increased levels of living organisms as compared to fresh water (FW)3, and references within4. High concentrations of clay particles enhance soil compaction, reduce aeration and available soil water, and adversely affect growth6. Root growth is often slowed by a combination of soil physical stress and water quantity or quality. Stress may vary continually, depending on the location of the root in the soil profile, prevailing soil water conditions and soil texture7.Soils can be highly variable in salt concentration, soil moisture, hydraulic properties, and nutrient availability8. Reductions in root function and water uptake12, may be responsible for deceases in performance of plantations following TWW irrigation, as found for avocado, grapefruit, almond, peach and other fruit trees species15. Usually, the negative effects of TWW irrigation on yield are detected following long term exposure, 5 to 10 years15. Indeed, in a current field experiment, only mild reductions in productivity were detected after 2 years of exposure of mature trees to TWW . Plant hydraulic conductance is greatly affected by soil characteristics and water quality, especially in regards to salt concentration16. In leaves, hydraulic conductance (Ks leaf) is coordinated with leaf water potential17. In stems, hydraulic conductance is usually represented as stem specific conductivity (Ks stem), which is a function of vessel characteristics and embolism18. In roots, hydraulic conductance (Ks root) influences water uptake capacity, which depends on root surface area, root anatomy, and root water permeability22. The dominating driving force for water uptake is the water potential gradient, which depends on osmotic gradients24. While the effects of soil type and water quality on some physiological aspects have been studied extensively, the relationship between hydraulics and gene expression has received less attention.TWW contains high concentrations of saline components, and organic and inorganic suspended particles compared with fresh water (FW), which can lead to a breakdown in soil structure and reduced hydraulic conductivity, increased osmotic potential, decreased aeration and reduced root growth25. Numerous studies have demonstrated the importance of aquaporins to plant water relations and plant hydraulics28. Reduced water uptake capacity in plants grown under abiotic stress, like drought and salinity, has been linked to a decrease in root hydraulic conductance30.Root permeability is thought to be regulated by Aquaporins32. The question regarding their high redundancy was recently reviewed33. Among aquaporin, the PIPs constitute the largest number of genes, and are further divided into PIP1 and PIP2 subgroups according to their amino acid sequence similarity. The Arabidopsis genome contains five PIP1 and eight PIP2 genes, while the citrus genome contains four PIP1 and four PIP2 genes34. The reason for the large redundancy is yet to be identified; however, previous reports suggest that PIP1 and PIP2 are subjected to multiple modes of regulation, including protein phosphorylation, which affect their activity, trafficking and gating40. Moreover, co-expression of PIP1.1 proteins with an isoform from the PIP2 subfamily led to higher membrane permeability than that observed with the expression of a single PIP2 protein, suggesting that interactions between various isoform might affect activity42. Interactions of PIP with other proteins might also play a role in their regulation35.Aquaporin genes are usually divided into seven families, each consisting of multiple gene members: plasma membrane intrinsic proteins (PIPs), tonoplast intrinsic proteins (TIPs), nodulin-26-like intrinsic proteins , GlpF-like intrinsic proteins (GIPs), hybrid intrinsic proteins (HIPs) and X-intrinsic proteins (XIPs)45. A dominating role of aquaporin phosphorylation in governing Ks under various abiotic and nutritional stress conditions has been also described46. However, to the best of our knowledge, the effect of different soil types and irrigation with TWW on the expression of PIPs has not been reported.The effect of environmental stimuli, such as, salinity, heavy metals, droughts, temperature and hypoxia on the expression and activity of aquaporins, mainly PIPs, is extensively described in the literature in many species including citrus8. Root system functionality decreased following exposure to TWW, especially in combination with clay soil, indicating damage, and increased proline and decreased osmotic potentials indicated adaptive responses. Here, the effects on citrus whole plant, root, stem and leaf hydraulic conductivities are described, along with changes in the levels of PIP1 and PIP2 mRNAs. Measurements also included the recovery response after winter rainfall and fresh water irrigation. The results demonstrate the relationships and correlations between root hydraulic conductivity and the expression of three CvPIP1/2 genes We show that although the effects on yield occur after years, significant and important effects on tree physiology, root hydraulics and PIP gene expression occur fast, i.e. within days, which, to the best of our knowledge, is a novel result.We have recently described the effect of TWW irrigation in clay and sandy loam soils on growth, respiration and hydraulic conductivity of citrus root systemsLeaf photosynthesis was significantly higher in sandy loam than in clay soil for both FW and TWW, by 18 and 25%, respectively Fig. . A signiOverall, soil type and water quality did not significantly affect stomatal conductance Fig. . HoweverIn summer, transpiration rates in clay soil were 24% and 20% higher than in sandy loam for TWW and FW irrigation, respectively Fig. ; and TWWLeaf relative water content (LRWC) was not affected by soil type in FW-irrigated trees Fig. . When plUnder FW irrigation, leaf water potentials were unaffected by soil type Fig. . Trees gRoot water uptake was significantly higher in sandy loam than in clay soil under FW and TWW by about 28% and 53%, respectively Fig. . In boths). For trees in sandy loam values were higher than for clay by about 22% for FW and 47% for TWW . A significant decrease was detected in Ks only in trees grown in clay soil irrigated with TWW as compared to trees grown in sandy loam, during the recovery period  as compared to FW, but no significant reduction was detected in Ks,stem. For TWW, Ks,stem and Ks,root were higher in sandy loam as compared to clay soil by 34% and 48%, respectively, but no difference was detected in Ks,leaf between the two soil types. As for most of the other parameters, no difference was detected in Ks,stem and Ks,leaf between the various treatments during the recovery period  and from the Citrus sinensis genome database (http://citrus.hzau.edu.cn/orange/) by performing BLAST using Arabidopsis sequences as queries. Based on the two Citrus genomes, eight members of the PIP gene family were identified. Phylogenic analysis of the Citrus sequences along with their Arabidopsis counterparts  and 4 genes showing homology with the PIP2 gene family of Arabidopsis (named CvPIP2:1–4). The mRNA levels of the eight genes were analyzed in the roots by qPCR following two irrigation seasons , and following a 90 day recovery period of winter rainfall, which leached soil salts .To identify rts Fig.  revealedCvPIP1 genes between the various treatments were relatively small, as compared to changes in the mRNA levels of CvPIP2 genes (see below). The mRNA level of CvPIP1:1 did not vary much between the treatments, and showed a 1.8-fold reduction only in trees grown in sandy loam irrigated with TWW as compared to trees grown in clay soil irrigated with FW. The mRNA level of CvPIP1:2 was reduced 2.3 and 2.8-fold in TWW as compared to FW for clay soil and sandy loam, respectively. Transcript levels of PIP1:3 were reduced 2.2-fold and 1.8-fold in TWW as compared to FW in clay soil and sandy loam, respectively, and those of PIP1:4 were reduced 2.4-fold and 2.9-fold in TWW as compared to FW in clay soil and sandy loam, respectively.Overall, significant changes in the mRNA levels of CvPIP1 genes were usually reduced during the recovery period as compared to the irrigation period, with CvPIP1:1, CvPIP1:2 and CvPIP1:3 showing the largest reductions. As expected, no effect of water quality was detected on the mRNAs levels. mRNA levels of CvPIP1:1 and CvPIP1:2 were induced in sandy loam as compared to clay soil, those of CvPIP1:3 were reduced in sandy loam as compared to clay soil, and transcript levels of CvPIP1:4 were not altered by soil type.mRNA levels of the four CvPIP2 genes seemed to be more affected by soil type than those of CvPIP1 genes  of these genes for individual and combined water qualities for both soil types during differential irrigation and recovery periods  and TWW  resulted in significant and important effects on tree physiology, hydraulics and the mRNA levels of most PIPs. Moreover, in the short term pot experiment, 20 days of exposure to TWW resulted also in significant differences in PIP transcripts levels. Considering the long term effects on tree productivity, these data, although indicating mild effects, are surprising, and to the best of our knowledge, are novel. Use of lower quality water may have resulted in a more dramatic effect, but our aim was to mimic, as much as possible, our local conditions.21. The ability to maintain a high photosynthetic rate is considered one of the most important stress resistance characteristics of plants47. Here, photosynthesis and whole plant hydraulic conductance, Ks, was reduced in clay soil and TWW but the reduction was minor in sandy loam soil  plants respond to the osmotic shock and ionic effects of salt by reduced PIP activity, followed by reduced root hydraulics, most likely as an adaptive strategy to eliminate water loss from the roots, under conditions of low osmotic potential in the soil16. Following days of exposure to salt, there was an osmotic adjustment, release of ionic effect, induction in PIP activity and, at least partial recovery of hydraulics. It has been reported that the overexpression of PIPs genes results in rapid water uptake, which dilute the salt concentration54. Sutka et al.21 and Sade et al.55 concluded that enhancing the expression of aquaporin in the roots may provide an approach to compensate for the reduced soil water uptake under stress conditions. In line with this, following 20-days exposure of citrus seedlings to salt stress, all 8 PIP genes showed induction in their mRNA levels, suggesting long-term effects34. The data presented here also describes steady state levels following long-term exposure of the plants to TWW and heavy soil. However, even in the long term, root hydraulics and PIP mRNA levels do not recover to values of FW. Overall, this might suggest that TWW components other than salts, such as BOD and COD, might indeed affect PIP expression in root hydraulics in the long run.Numerous studies have explored the variations in hydraulic conductivity and aquaporin expression in various plant species under normal and stress conditions, especially salt and droughtype Figs  and 7. Oype Figs . Resultsype Figs  demonstr26. Moreover, our data also demonstrated positive relationships, both by correlation test and regression analysis, between transcript levels of group 1 and root hydraulic conductivity. Others also reported good correlations between the expression of various PIPs and root hydraulic conductance58, suggesting their importance in water uptake, especially under beneficial conditions. During recovery period, when water availability and quality were not limiting, the expression of group 1 PIPs was greatly reduced, but still, the expression in sandy loam was higher than in clay soil, suggesting that constraining growth effects imposed by clay soil were mitigated, but only to a certain extend. Similar growth effects were observed in walnut with the induction in the mRNA levels of PIP2:1 and PIP2:2, and in rice59, Zea mays60 and other plants25. Group 2 included only PIP2:4; its transcript levels were remarkably induced in clay soil as compared to sandy loam, but no differences were detected between the two water qualities in both soil type. It might be assumed that this protein plays an important role in the adaptation to inferior soil-related irrigation, but not directly to water quality63. During recovery period, transcript levels in clay soil were greatly reduced, even below that of sandy loam, suggesting that under FW, the effect of the clay was mitigated. Group 3 included PIP1:4 and PIP2:3, their transcripts levels were similar in both soil types under FW, but under TWW, they were higher in clay soil as compared to sandy loam. It is suggested that, similarly to Group 1 genes, these PIPs are mostly operative under relatively high water quality. Interestingly, unlike other PIPs, transcripts levels of Group 3 PIPs during recover period was not altered significantly, as compared to irrigation period, suggesting their importance for water uptake round the year. Group 4 included only PIP1:1, its mRNA levels did not vary between the various treatments, pointing up for its importance for water uptake under all conditions. During recovery period, its mRNA levels were reduced, especially in clay soil, suggesting that constrains resulting from soil type were mitigated. Overall, results of this study show correlations between PIP1 and PIP2 mRNA levels and changes in hydraulic conductivity imposed by the effect of TWW, clay soil and the combination of the two. Therefore, results support the hypothesis that the regulation of root and whole plant hydraulics in different soil textures and water qualities might be largely regulated by aquaporin, PIP1 and PIP2.Considering the combined effect of clay soil and TWW, the various PIP genes responded somewhat differentially, and they could be grouped into a few groups. Group 1 included PIP1:2, PIP2:1 and PIP2:2. Their mRNA levels were reduced under TWW as compared to FW and under clay soil as compared to sandy loam, with the lowest values under both TWW and clay soil. PIP1:3 transcript levels showed the same trend, but the differences between the two soil types were non-significant under both TWW and FW. It is suggested that these PIPs are highly operative under normal growth conditions and reductions in their expressions under TWW and clay soil were consistent with the previous studies showing that PIPs transcripts level decreased under stress conditions, encouraging cellular water conservation by reducing membrane water permeability and limiting loss of cellular waterCitrus paradise Macfadyen) grafted on Volkameriana (Citrus volkameriana Volkamer) rootstock. Trees were grown in lysimeters, which were constructed of plastic barrels 1.2 m deep and 0.5 m in diameter with suitable drainage at the bottom. Sandy loam (Hamra) and clay (Grumosol) soils were used, both with a history of long term TWW irrigation, as described elsewhere64. Irrigation treatments were applied after transplanting one sapling in each of 24 lysimeters8. Two water qualities  were used as treatments in both soils with four replications of each treatment in four randomized blocks8. Each lysimeter with a single tree was considered as a replication, and lysimeters were arranged in blocks. Drip irrigation was applied and excessive drainage was collected from an outlet pipe at the bottom of each lysimeter. Irrigation for clay soil was 7 L Tree−1 and 9 L Tree−1 for sandy soil, applied once every three days during the summer irrigation season. The experiment continued for 90 days  in winter, to check the possibility of recovery of activity following leaching of soil by rainfall  and supplementary fresh water irrigation when needed. Measurements of soil chemistry after winter leaching were performed at the end of the winter rainfall season in the second week of March.The experiment was conducted during 3 years (2013 to 2015) at the Technion Israel Institute of Technology  on saplings (2.5 years old) of Rio Red grapefruit  between 9:00 am and 11:00 am simultaneously with root sampling (see below). Fully expanded leaves were measured at a photon flux density of 1000 mmol met al.65. Fully expanded leaves were weighed immediately after being picked to determine the fresh weight (FrWt). Leaves were floated in distilled water for 6 h, dried with filter paper and weighed to determine the turgid weight (TW). The discs were then dried at 60 °C in a forced-air oven for 78 h to determine the dry weight (DW). The relative water content was calculated as follows,Leaf relative water content (LRWC) was measured as described by Paudel The water potential of the fully expanded leaves was measured as pre-dawn at 5.00–6.00 am and for leaf - between 10:00 am and 12:00 am using a pressure chamber . Each treatment included six replications.66. Kplant per unit leaf area was calculated based on Cohen et al.67 as,Root water uptake was measured with thermal dissipation sap flow sensors installed in the trunk base  were recut under degassed water in the lab to lengths of 10 cm (stem) and 5–7 cm (roots) to avoid excessive branches, and potential artifacts related to cavitationet al.17:bulk is leaf capacitance, Ψ0 is initial water potential, Ψf is final water potential after rehydration and t is time since rehydration began. Cbulk was estimated according to Blackman et al.69.Fresh weight of leaf samples was measured immediately following arrival to the laboratory, after which samples were dipped in distilled water. Leaf hydraulic conductivity was measured using the leaf rehydration kinetics method described by Brodribb C. volcameriana Volckmer) grown in 2 L container filled with sandy loam soil. Irrigation treatments included FW, TWW (similar to the lysimeter experiment) and a treatment where NaCl was added to reach similar salinity level as TWW  according to the manufacturer’s instructions. RNA quantity was analyzed in a NanoDrop ND-1000 Spectrophotometer  and RNA quality was determined by Agilent Bioanalyzer . cDNA was synthesized from 1 μg RNA using OligoT as a primer and M-MLV Reverse transcriptase  in a final volume of 25 μl containing the commercially supplied buffer. Primers were designed based on genomic and EST sequences  using Primer 3 software , and Ultra-Pure water  in a final volume of 12 μl in a Corbett Rotor-Gene 6000 . Reactions were run for 40 cycles of 10 s at 95 °C, 15 s at the annealing temperature for each gene, 20 s extension at 72 °C, and the threshold level was determined. For the dual-labeled probe reactions, real-time PCR was carried out in a reaction mix containing 2 mM gene-specific forward and reverse primers, 2.5 mM dual-labeled probes, 3 μl cDNA (diluted 1:16), TaqMan Universal PCR71 Master Mix  and Ultra-Pure water in a final volume of 12 μl in the Rotor-Gene 6000. Reactions were run for 40 cycles of12 s at 95 °C, 60 s annealing and extension at 60 °C, and the threshold level was determined. Standard curves were generated for each gene using serial cDNA dilutions. Relative concentration of the product was calculated by the algorithm of the Rotor-Gene software using the CT value. Relative expression (RE) was defined as the ratio between the relative concentration of each gene and that of β-actin.Total RNA was extracted from approximately 2 g of fine roots using the CTAB extraction methodre Table . Real-tihttp://www.sas.com). TWO-Way ANOVA was carried out both for soil type and water quality and Tukey’s HSD was used for mean separation when ANOVA results were significant. Fitting X and Y were done for correlation tests and ANOVA was run to test significance.All statistical analysis were carried out using SAS (JMP) software (SAS Institute, Supplementary File


Background. There is a growing controversy about the use of oronasal masks (ONM) or total facemask (TFM) in noninvasive positive pressure ventilation (NPPV), so we designed a trial to compare the uses of these two masks in terms of effectiveness and comfort. Methods. Between February and November 2014, a total of 48 patients with respiratory failure were studied. Patients were randomized to receive NPPV via ONM or TFM. Data were recorded at 60 minutes and six and 24 hours after intervention. Patient comfort was assessed using a questionnaire. Data were analyzed using t-test and chi-square test. Repeated measures ANOVA and Mann–Whitney U test were used to compare clinical and laboratory data. Results. There were no differences in venous blood gas (VBG) values between the two groups (P > 0.05). However, at six hours, TFM was much more effective in reducing the partial pressure of carbon dioxide (PCO2) (P = 0.04). Patient comfort and acceptance were statistically similar in both groups (P > 0.05). Total time of NPPV was also similar in the two groups (P > 0.05). Conclusions. TFM was superior to ONM in acute phase of respiratory failure but not once the patients were out of acute phase. Oronasal masks (ONM) have historically been the preferred choice in acute cases because of reduced air leak from the mouth, while nasal masks are preferred for prolonged ventilation as they do not cover the patient's mouth and provide more comfort , 2. Howehttp://www.irct.ir/ (IRCT2016051627929N1). This randomized controlled trial was conducted on 48 patients with acute respiratory failure who were referred to Masih Daneshvari Hospital from February to November of 2014. The diagnosis of acute respiratory failure was made based on medical history and thorough clinical examination. Patients were enrolled if they showed at least one of the following signs: tachypnea (respiratory rate ≥ 24), use of accessory muscles of respiration , paradoxical respiration, pH < 7.35 with no metabolic component, and finally PaCO2 > 45 mmHg while breathing room air. Patients with fluctuating mental status, unstable coronary artery disease, arrhythmias with unstable blood pressure (SBP ≤ 90 mm Hg or > 40 mmHg drop in systolic blood pressure), generalized skin lesions, facial trauma, upper airway obstruction, and recent surgery on upper airways, stomach, or esophagus and those who required emergent intubation were excluded. Six patients had problems with using the assigned masks due to previous unpleasant experiences or difficulties in adapting the mask to their face and consequently were excluded after randomization.The study protocol was approved by the ethics committee of Masih Daneshvari Hospital and registered at Patients with acute respiratory failure who were referred to Masih Daneshvari Hospital were divided into two groups, using simple randomization with a table of random numbers. Patients in the first group received NPPV through ONM  while the patients in the second group received NPPV via TFM .2O. Based on the severity of disease and physical symptoms, IPAP and if necessary EPAP were gradually increased within the patient's level of tolerance each time for approximately 2 cm/H2O. The primary goal was to eliminate respiratory distress, decrease the respiratory rate, and decrease the use of accessory respiratory muscles. The second goal was to improve blood gases and particularly PCO2 and pH. Necessary adjustments to NPPV settings were made based on clinical criteria and venous blood gases (VBGs). Supplemental oxygen, 3–15 L/min, was utilized to achieve peripheral oxygen saturation rate of ≥90% while the mask was fitted on the patient's face to minimize air leak. Cardiac monitoring and pulse oximetry as well as noninvasive blood pressure measurements were performed continuously during NPPV, and ventilator parameters (IPAP and EPAP) were recorded.NPPV was delivered by trained personnel in Masih Daneshvari Hospital (ward and emergency room) under the supervision of pulmonary and critical care fellows. The patients played no role in selection of the mask and the statistician was blinded to the group allocation of patients. Ventilator  was used for all patients. NPPV parameters were set based on prior reports for 24 hours continuously. We started with inspiratory positive airway pressure (IPAP) of 10 and expiratory positive airway pressure (EPAP) of 4 cm H2 and VBG parameters  were measured at the time of enrollment and subsequently at 60 minutes and six and 24 hours after NPPV initiation. Support provided by the ventilator was quantified by measuring IPAP and EPAP, as well as total oxygen flow required to maintain peripheral oxygen saturation rate above 90%. Patient comfort while wearing the mask was assessed by two methods, namely, a visual analog scale (VAS) and a questionnaire. In use of a VAS, a score of 5 indicated that the patient was very comfortable while a score of 1 indicated extreme discomfort. Patients were asked about feeling pain in the forehead, nose, cheeks, and chin, air leak at eyes and mouth, dry nose and mouth, and compressive effects of mask on their faces. The patients' answers to the following questions were recorded in a questionnaire and each item was scored 0 to 3 in terms of intensity. The total score was calculated by adding the individual scores of each item mentioned above. Duration of NPPV use, endotracheal intubation rate, length of hospital stay, and in-hospital mortality rate were compared between the two groups as well.Epidemiologic data such as age and sex in addition to clinical and laboratory data including blood pressure, pulse rate, respiratory rate, accessory respiratory muscle use, and SaOt-test and chi-square test considering 95% confidence interval, At P = 0.05 level of significance. Repeated measures ANOVA and Mann–Whitney U test were used to compare clinical and laboratory data between the two groups.We used SPSS version 22 for statistical analysis. Data were analyzed using P > 0.05) in patients between the two groups. Patients in group one (13 men and 11 women) used TFM; 20 patients in this group (83.3%) had chronic obstructive pulmonary disease (COPD) exacerbations, while the rest had bronchiectasis, obstructive sleep apnea, and so forth. The mean age was 63.21 ± 10.22 years. Patients in group 2 (15 men and 9 women) used ONM. There were 20 patients with COPD exacerbation in this group, with a mean age of 67.83 ± 9.46 years. The demographics of the two groups are summarized in The study was conducted between February and November 2014. There were no significant differences in age, sex, or disease severity . At 6 hours, the patients in the TFM group had a significant reduction in their respiratory rate compared to those in the ONM group (P > 0.055).As seen in P = 0.01), other parameters were similar between the two groups . Similarly, the total time of noninvasive ventilation (NIV) was similar in the two groups (P = 0.14) as shown in However, the mean VAS score showed no difference in mask tolerance between the two groups   at zero, one, six, and 24 hours after initiation of NPPV. We observed significant improvements in PCO2 and HCO3 after six hours in TFM group but the overall VBG alterations were the same in both groups. Criner et al. previously reported improved gas exchange in hypercapnic patients who received NPPV via TFM [Concerning clinical and laboratory parameters, we found no obvious change or difference in heart rate or the use of accessory muscles after six hours of NIV, but respiratory rate was significantly lower in TFM users. This was consistent with the results of earlier studies, which showed no difference in heart rate, respiratory rate, or oxygen saturation after six hours of NPPV with TFM or ONM , 11. On  via TFM .We also compared intubation rate and in-hospital mortality between the two groups, and similar to previous reports, we found no difference in either category , 11. We While TFM was more efficacious in reducing PCO2 and HCO3 during the first six hours of treatment, the blood gas alterations were the same in both groups based on repeated measures ANOVA once the patients were out of the acute phase of respiratory failure. Therefore, we may conclude that TFM was superior to ONM in acute phase of respiratory failure but not once the patients were out of acute phase. Our findings indicated that both TFM and ONM should be available in case of patient intolerance for one mask.


Patients diagnosed with severe aplastic anaemia and without a compatible bone marrow transplant donor are treated with immunosuppressive therapy. These patients are found with time to develop a clonal disease such as myelodysplasia or paroxysmal nocturnal haemoglobinuria. However, the development of plasma cell dyscrasias is rare. We report the case here of a patient treated with immunosuppressive therapy who went on to develop myeloma 11 months after being diagnosed with severe aplastic anaemia. We include here a review of the literature. In patients without a compatible sibling or unrelated donor standard immunosuppressive therapy (IT) with anti-thymocyte globulin (ATG) and cyclosporine A (CyA) produces excellent results with a reported response rate of 58–77% and a survival rate of 58% at 11 years ). The moImmunophenotypic analysis with anti-CD19 and anti-CD56 can clearly distinguish between normal plasma cells and myeloma cells. Normal plasma cells are CD19 (+) CD56 (-), whereas in myeloma approximately 65% are CD19 (-) CD56 (+), 30% CD19 (-) CD56 (-) and 5% CD19 (+) CD56 (+) [3, white cell count of 1500/mm3, an absolute neutrophil count of 450/mm3, and reticulocyte count of 0.5%. A provisional diagnosis of aplastic anaemia was made, and the supplementary testing showed; tests for hepatitis A, B, C, and HIV negative, antinuclear, anti-DNA antibodies negative, negative for Epstein-Barr virus and cytomegalovirus. Immunoglobulin (Ig) A 77 mg/dL , IgG 773 mg/dL , and IgM 54 mg/dL (40–230). CD55/CD59 expression normal, bilirubin 0.37 , ferritin 31 , and lactate dehydrogenase 209 IU .A 15-year-old girl presented with a three month history of extensive bruising and hypermenorrhea of up to 18 days. A full blood count showed a haemoglobin of 3.5 g/dL mean corpuscular volume of 111.6 fL, platelets of 6000/mmBone marrow biopsy showed less than 20% cellularity. There were immature and precursor cells of the erythroid and myeloid series in central accumulations and paratrabecular location with very few mature forms. No megakaryocytes were observed.Staining for myeloperoxidase showed positivity in 30% of immature cells which were arranged as paratrabecular sheets, while CD34 staining cells were less than 5%, with a central focus of immature cells staining positive for both CD34 and myeloperoxidase. Staining for PNCA was less than 1% and there was no evidence of fibrosis or lymphoid follicular formation . Bone maA diagnosis of aplastic anaemia was made. A suitable bone marrow donor was unavailable and hence immunosuppressive therapy with anti–thymocyte globulin, methylprednisone, and cyclosporine was started. There was no response at six months and a second cycle was repeated, again failing to achieve a response.Eleven months after the initial presentation, the patient presented with high fever of 40ºC, and bilateral cervical adenopathy without any other localising signs. A CT scan of the neck showed bilateral cervical and jugular chain adenopathy of up to 22 mm with necrosis. Empirical antibiotic therapy was started with amikacin and the combination antibiotic piperacillin–tazobactam with platelet support (hydrocortisone and chlorpheniramine prophylaxis was administered with platelet transfusions). Blood and urine cultures were persistently negative. With the adenopathy increasing in size and to exclude a lymphoproliferative disease, an excisional biopsy of the node was performed along with a repeat bone marrow biopsy.The biopsy of the node showed a conserved structure but with loss of the lymphoid follicles. There was 70% of the lymph node parenchyma being replaced with an infiltration of morphologically mature plasma cells as well as loss of the normal architecture , 3.The infiltrating cells were CD38 positive  and CD19The bone marrow biopsy  showed aThere was a hyper–gammopathy of 10 g/dL , with an IgA lambda monoclonal protein of 4.20 g/dL, total IgG 535m g/dL, and total IgM 32 mg/dL, both IgG and IgM being decreased, and a positive Bence-Jones protein. Serum creatine and calcium levels were normal and a skeletal survey showed a few small osteolytic lesions in the lateral skull x–ray.A diagnosis of plasma cell dyscrasia consistent with myeloma was made. Because of the severe cytopaenia, dexamethasone 40 mg days 1–4 with a 10 day cycle was started. After six cycles, the Bence-Jones protein was undetectable, and the monoclonal protein had decreased to 2.30 g/dL. However, the patient presented with septic shock and died.et al reported a case in 1981 [There are only a few cases in the literature of aplastic anaemia progressing to myeloma. Manoharan  in 1981 , and a sThere are cases reported of aplastic anaemia associated with a minimal serum M–protein  or a marIn the case we describe here, we consider from the initial findings that myeloma was not present. Initial bone marrow biopsy revealed no infiltration with plasma cells  . There wet al [After IT failure, the patient was considered to have developed myeloma based on the 2015 NCCN guidelines. Sahara Studies have reported that low CD56 expression is associated with extensive bone marrow and blood involvement; a more aggressive disease and a significantly shorter survival . It has The differential diagnosis of plasmablastic lymphoma was also considered. However, the lesion being lytic with bone marrow involvement, having morphological characteristics of myeloma rather than a large cell lymphoma, having a monoclonal paraprotein with a positive Bence-Jones protein, and finally being HIV negative, all supported the diagnosis of myeloma rather than lymphoma. Plasmablastic lymphoma is an uncommon diffuse large B–cell lymphoma with a predilection for individuals HIV positive or with immunosuppression. Biopsy of the lymph node in plasmablastic lymphoma shows poorly differentiated plasma cells with low or absent B–cell markers , and positivity for plasma cell markers such as CD38 and CD138 .In summary, our case presents the rare CD19 (+) CD56 (–) phenotype of myeloma arising in a patient treated by IT for aplastic anaemia. Treatment of what is considered to be an aggressive form of myeloma is severely limited in patients with poor marrow reserve and lack of a transplant donor. With only a few cases reported of myeloma arising from aplastic anaemia treated with IT reported in the literature, it is difficult to confirm this association. However, in this case report there did not appear to be evidence of myeloma pre-IT whereas 18 months after the initial diagnosis and two cycles of IT, the evidence suggested the rare phenotype of myeloma.This case study was approved by the Hospital de Carabineros Ethical Committee, complying with the Chilean Law 20,458 of patients’ rights.The authors report no conflicts of interest.


Biological particles deposit on air handling system filters as they process air. This study reports and interprets abundance and diversity information regarding biomass accumulation on ordinarily used filters acquired from several locations in a university environment.DNA-based analysis was applied both to quantify (via DNA fluorometry and qPCR) and to characterize (via high-throughput sequencing) the microbial material on filters, which mainly processed recirculated indoor air. Results were interpreted in relation to building occupancy and ventilation system operational parameters.2 for total DNA, 0.02 to 3.3 ng per cm2 for bacterial DNA and 0.2 to 2.0 ng DNA per cm2 for fungal DNA. The most abundant genera detected on the AHU filter samples were Clostridium, Streptophyta, Bacillus, Acinetobacter and Ktedonobacter for bacteria and Aspergillus, Cladosporium, Nigrospora, Rigidoporus and Lentinus for fungi. Conditional indoor airborne DNA concentrations (median (range)) were estimated to be 13 (2.6–107) pg/m3 for total DNA, 0.4 (0.05–8.4) pg/m3 for bacterial DNA and 2.3 (1.0–5.1) pg/m3 for fungal DNA.Based on accumulated biomass, average DNA concentrations per AHU filter surface area across nine indoor locations after twelve weeks of filter use were in the respective ranges 1.1 to 41 ng per cmConditional airborne concentrations and the relative abundances of selected groups of genera correlate well with occupancy level. Bacterial DNA was found to be more responsive than fungal DNA to differences in occupancy level and indoor environmental conditions. Current building operation design and practice were developed without detailed knowledge about how the accumulation of biological material occurs in various parts of mechanical ventilation systems. It is feasible that processes such as microbial colonization and metabolism contribute to adverse consequences for occupants, such as malodors, allergic reactions, asthma or sick building syndrome ,2.Office buildings in Singapore are commonly equipped with central ventilation and air conditioning systems. In tropical climates, such systems are referred to as providing “air conditioning and mechanical ventilation” (ACMV), because heating is not needed. In common international usage, such systems would be described as “heating, ventilating and air conditioning” (HVAC). In this study, because thermal conditioning is not central to our purposes, we will make reference to the “ventilation” or “air handling” system.Air handling unit (AHU) filters are integrated into ventilation systems as the first line of defence, to protect downstream equipment and (sometimes) building occupants in indoor environments. The accumulation of particulate matter (PM) on these filters is inevitable. Appreciating the importance of ventilation system filters in processing both recirculated indoor air and outdoor air for building occupants, researchers have begun to analyse the biological composition of particulate matter collected on these filters. One of the earliest such studies involving AHU filters was performed in two shopping centres in Singapore . In thatSpecific evidence remains limited regarding factors affecting the presence, abundance, and behavior of biological materials on AHU filters. It is important to study these factors to better understand the strengths and limitations of AHU filters as part of the mechanical ventilation system and to possibly gain insight into the levels and diversity of indoor bioaerosols in occupied spaces. No prior study provides both culture-independent quantitative measurements plus diversity analysis of biomass accumulated on AHU filters serving separate indoor spaces. To report such information for a cross-sectional sample of university buildings in Singapore is the purpose of this paper.Here, we report baseline quantitative measurements and microbial composition of biological materials accumulated on used AHU filters from several locations in modern buildings in a tropical climate. We also aim to perform interpretive analysis on how indoor conditions affect the quantity and diversity of bioaccumulation on these filters. Measurements were made using culture-independent DNA-based analysis techniques. To satisfy the above research goals, we assessed the biomass concentration recovered from normally used ventilation-system filters. We investigated the influence of occupancy on bioaccumulation on these filters in different indoor environments and undertook high-throughput sequencing that targeted bacterial 16S rDNA and fungal internal transcribed spacer (ITS) sequences to analyse the microbial composition on the ventilation system filters.Ventilation system filters from nine air handling units (AHU) at Nanyang Technological University (NTU), Singapore, were acquired for this study. The filter samples were collected with permission from the Facilities Management office in NTU and their partner for air conditioning services in Singapore. The nine indoor environments were three libraries , five university staff office environments  and one classroom (Classroom). All filters were indoor secondary filters . As we intended to sample actual used AHU filters, the nine environments were carefully selected to minimize in-situ differences for relevant indoor comparisons. These AHUs used the same type of filter, operated during the same periods of time and were reasonably close to each other .In Singapore, owing to the consistently high latent heat load, central air conditioning systems generally operate with a very high proportion of recirculated air and a correspondingly small proportion of outside air. For the buildings studied here, the sampled air-handling filters processed air that was a blend of >90% recirculated air and <10% outdoor air. In accordance with Singapore regulations, filters in mechanical ventilation systems are replaced within six months of installation. The filters in this study were routinely replaced every three months. All filters analyzed in this study were collected at the end of the customary three-month period of service.Several recent studies have documented that human occupants can act as major primary and secondary sources of indoor bioaerosols, through shedding and resuspension , 9–12. TN. Note that each observation during the hourly counts of one occupant was estimated to contribute one person-hour to the cumulative weekly occupancy for that space.The operating hours of the AHUs varied according to the opening hours of the indoor spaces. The offices followed a fixed schedule with Office C and Office 1 operated on average 60 h/wk; the student and staff offices  were open for an average of 91 h/wk. The classroom’s AHU operated on average 26 h/wk. The three libraries operated on different schedules with average durations of 73 h/wk, 56 h/wk and 73 h/wk for Library 1, Library 2 and Library 3 respectively. The total numbers of occupants observed each day were tallied and the weekly average value is reported as an estimated integral measure in units of person-hours per week, Af, m2) and the respective airflow speed (m/s) to estimate the volumetric supply air flow rate . Detailed descriptions of the air flow speed measurement methods, metadata describing the indoor environments, and the population counts are available in the Supporting Information  from the used filter on site with sterilized scissors immediately before the filter was removed from its mount for replacement. Each sampled filter piece was transferred into a sterile 50 mL falcon tube and transported to the lab on ice for DNA extraction. At least seven filter pieces of the same size were collected from each location to provide material for backup and replication. All unprocessed filters were stored at -20°C.2 filter pieces was placed into a 5 mL bead beating tube of MOBIO Power Water kit  for DNA extraction. The DNA extraction steps followed the manufacturer’s protocol with some modifications to improve DNA yield [2 filter pieces that were cut from the same filter panel.Each of the 10-cmNA yield . BrieflyThe total DNA in each sample was measured by a fluorescent dye dsDNA binding assay . The Qubit high sensitivity (HS) dsDNA kit was used for processing all samples.forward primer BAC338F (5’–ACTCCTACGGGAGGCAG–3’), the reverse primer BAC805R (5’–GACTACCAGGGTATCTAATC–3’), and the Taqman probe BAC516F (6FAM–TGCCAGCAGCCGCGGTAATAC–3’–BBQ). The primers used for fungi targeted the fungal 18S rRNA gene [forward primer FungiQuant-F (5’–GGRAAACTCACCAGGTCCAG–3’), the reverse primer FungiQuant-R (5’–GSWCTATCCCCAKCACGA–3’) and the Taqman probe FungiQuant-PrbLNA (6FAM–TGGTGCATGGCCGTT–3’–BBQ).Bacterial and fungal DNA levels were quantified by means of qPCR  using Applied Biosystems Taqman master mix and a set of universal bacterial and fungal primers and probe. The primers for bacteria targeted the 338 to 805 region of 16S rRNA with the RNA gene  with theEscherichia coli (ATCC 15597) and Aspergillus fumigatus (ATCC 26644), respectively. DNA was extracted from suspensions of both organisms in water and a dilution series  was prepared. The DNA concentrations of the suspensions were measured by both fluorometry (ng DNA/μL) and qPCR (Ct) to establish standard curves with which to relate DNA concentrations to Ct values. Final DNA concentrations are presented in terms of DNA mass per AHU filter surface area (ng or pg DNA/cm2).We established standard curves for bacteria and fungi with DNA extracts from As a negative control, clean (unused) AHU filters were briefly installed in each AHU and immediately extracted using the same protocol. The quantities of DNA from blank samples were below the detection limits of Qubit and no amplification was detected in the qPCR run with 35 thermal cycles, suggesting that there was no significant contribution of biomass from the maintenance company personnel during filter replacement, from the researchers during sampling and analysis of the filter pieces, or from the AHU filter materials themselves.primers were 5’-CCTACGGGNBGCASCAG-3’ for the forward primer 341f and 5’-GACTACNVGGGTATCTAATCC-3’ for the reverse primer 805r [5’-GCATCGATGAAGAACGCAGC-3’ for the forward primer ITS3 and 5’-TCCTCCGCTTATTGATATGC-3’ for the reverse primer ITS4 [Only five samples  met the minimum DNA abundance requirement for sequencing. Bacterial 16S rDNA and fungal ITS regions were targeted for DNA sequence analyses. The sequences of universal bacterial mer 805r . The seqThe poly N tails were removed from the sequences by Trimmomatic version 0.33 . The reaFor the fungal ITS sequences, taxonomic assignments were performed using BLASTN version 2.2.28+  against For the bacterial 16S rDNA sequences, taxonomic assignments were performed using the RDP Naïve Bayesian Classifier  with 0.8p < 0.05.In addition to microbial assemblage descriptions, correlations between occupant intensity in the indoor environments (described in a subsequent section) and the combined relative abundances of selected groups of human associated genera as well as Shannon diversity index were calculated to judge if these human-related genera would tend to be more abundant/diverse in spaces with higher occupancy. Spearman’s rank correlation coefficients were calculated and the correlations were tested for significance at Df, in units of mass per week) was achieved by upscaling the amount of DNA extracted from the small filter area  to the actual filter area (including pleats) in the AHUs . The DNA concentrations measured by Qubit fluorometry (ng/μL) and qPCR (pg/μL) were first converted to extracted DNA mass  based on the elution volume used during extractions. Total rates of accumulated DNA masses were then obtained from the following equation:Estimating the total DNA accumulation rate and its apportionment  on the ventilation system filter  was normalized by the average quantity of air estimated to have passed through the filter during each week . The volumetric air-sampling rate was estimated by multiplying the determined volumetric air-flow rate  by its weekly cumulative operating duration  for each environment  that occupants are important contributors to the airborne DNA accumulating on ventilation system filters that process recirculated air; and (b) for a given category of indoor environment, the total effective occupancy-associated emission rate of DNA should scale with the occupancy level.In addition to determining effective time-averaged DNA concentrations, C, against a measure of occupancy normalized by ventilation rate, Nd (person-h per m3). N) to the airflow volume per week flowing through the AHU filter (Vs).The exploration of the occupancy-induced contribution to DNA accumulation on the filter was achieved by regressing the inferred concentration, C, against the normalized occupancy, Nd. The slope, E (DNA mass per person-h of occupancy) represents an estimate of the occupancy-associated effective emission factor for DNA that accumulates on the AHU filter. We applied this analysis for total DNA as well as for bacterial and fungal DNA.For all indoor environments, we regressed the inferred DNA concentration, C and Nd. In this analysis, both Pearson correlation coefficient (R) and its significance were calculated. A correlation was considered significant when the Pearson correlation coefficient satisfied the required value for p < 0.05 at n = 9.Pearson correlation was applied to determine the statistical significance of the association between C and E to number of cells for bacterial DNA and to number of spores equivalent (SE) for fungal DNA based on the conversion method of Qian et al. [E. coli (the standard that we used) has seven 16S RNA operon copies for each genome and that the average number of 16S RNA gene operon copies in a general bacterial genome is estimated to be four [A. fumigatus has fifty-five operon copies of 18S rRNA gene per genome [A. fumigatus spores equivalent (SE). On average, 0.0027 pg and 0.030 pg of DNA [We also converted DNA mass values for n et al. . For bac be four . For funr genome . As the g of DNA  is equiv2 for total DNA, 0.02 to 3.3 ng per cm2 for bacterial DNA, and 0.2 to 2.0 ng DNA per cm2 for fungal DNA. In addition to microbial  DNA, the total DNA includes contributions from human, plants or animal cells that accumulated on the filter. On average, the measured microbial DNA contributed approximately 17% (1.5 out of 8.9 ng/cm2) of total DNA mass accumulated on the AHU filters. In the classroom and offices, the proportional contribution of fungi to total DNA was substantially larger than in the libraries. In contrast, the proportional contribution of bacterial DNA to total DNA was substantially larger in the libraries as compared to the classroom and offices.2; for fungi, the corresponding range was 6400 to 66,000 SE/cm2.The estimated bacterial cell and fungal spore equivalent (SE) densities in Clostridium (11%), Streptophyta (10%), Bacillus (6.7%), Acinetobacter (5.0%) and Ktedonobacter (3.6%). (See Deinococcus (3.5%), Corynebacterium (2.7%) and Pseudomonas (1.2%). To our knowledge, genera Gp1, Gp4, Gp6 and Gp16 have not been reported in previous indoor bioaerosol studies. These genera belong to phylum Acidobacteria, which are commonly found in soil or plant roots [In total, 385 bacterial and 783 fungal genera were detected from the five DNA samples that were sequenced . 6%). See . Other pnt roots –30. Thesptophyta %, Bacillptophyta %, Bacillnt roots –32.Basidiomycota (42%). The five most abundant fungal genera and their mean relative abundances were Aspergillus (11%), Cladosporium (7.4%), Nigrospora (4.9%), Rigidoporus (3.7%) and Lentinus (2.9%) (Penicillium (2.2%). These findings generally conform to previous results, with Aspergillus, Penicillium and Cladosporium being abundant in both indoor and outdoor air across regions [Cladosporium), Sordariomycetes (contains genus Nigrospora) and Agaricomycetes (contains genera Rigidoporus and Lentinus) as the dominant fungi detected in filter dust samples.As illustrated in s (2.9%) . Another regions –35. Howeiomycota 2%. The fAlternaria [Cryptococcus and Epicoccum [Stenotrophomonas [Methylobacterium [Overall, the observed similarities substantiate the value of AHU filters in reflecting the microbial composition of the corresponding indoor air. More in-depth future studies on AHU filters are encouraged to better distinguish the specific causes of variability that has been reported among studies. For example, Proteobacteria in this study were more abundant in the locations with high occupancy (as described in subsequent sections), which seems contradictory to a previous observation that Proteobacteria on AHU filters are unlikely to be of human origin . Fungal ternaria , Cryptocpicoccum  and bactphomonas  and Methacterium  were detWhile similarities were seen between our findings and previously reported investigations of indoor microbes, it is unknown whether correlations can be detected between the abundances of selected bacterial and fungal genera and potentially influential indoor conditions. Because the nature of the underlying distributions is unknown, we applied nonparametric Spearman’s rank tests. With a limited number of samples, the findings in this section are mainly intended to provide preliminary insight so as to guide the design of future studies that might use AHU filters as convenient samplers related to indoor environmental quality.ρ) correlating occupant intensities (Nd) to relative abundances of selected groups of bacterial and fungal genera and to the α diversity index in the five locations. The group of human-related bacterial genera consists of Corynebacterium, Propionibacterium, Enterobacter, Staphylococcus, Streptococcus, Fusobacterium and Veillonella as skin or gut microflora [ρ = 0.5) was found between relative abundances of the group of human-related bacterial genera and human occupancy levels. Genera that are frequently detected in highly occupied spaces include Lactococcus, Pseudomonas and Streptococcus [ρ = 1.00, p < 0.05). A positive correlation was also found between occupant intensity levels and the Shannon’s diversity index of bacterial assemblages (ρ = 0.60), indicating that the bacterial taxa on ventilation system filters tended to be more diverse with increasing occupancy levels. These findings regarding bacterial abundance and its correlation to occupancy are widely consistent with the understanding of human presence as a major source of bacterial emissions indoors.Human-associated genera and genera known to be frequently detected in highly occupied spaces were selected to evaluate how their assemblages may vary on AHU filters in relation to human occupancy levels. croflora –10. A potococcus . We alsoρ = 0.90) was found between human occupancy levels and relative abundances of a group of human-related fungal genera of Malassezia, Trichosporon, Rhodotorula, Cryptococcus, Pichia and Candida [Aspergillus, Penicillium and Cladosporium [ρ = -0.10). One possible explanation for this finding is because, as a secondary carrier, human occupants carry the same fungi from the outdoor environment and would not contribute to the diversity of accumulated fungi. Concurrently, as primary contributor, the small proportions of human related fungal genera relative to the total fungi on the filter are expected to have little influence on the Shannon index values, which account for both richness and evenness of a microbial assemblage.For fungal taxa, a strong positive correlation  based on AHU filter sampling. In addition, correlations between C and occupant intensity (Nd) are assessed as a basis for estimating occupancy-associated emission factors for indoor bioaerosols that accumulate on AHU filters (E).Utilizing AHU filters as indoor air samplers is an attractive approach for indoor environmental quality studies. As shown by previous studies –4, 7, itC as the time-averaged indoor air concentration of DNA for the AHU’s operating hours. First, as indicated by Haaland and Siegel [Before presenting results, we would first state two cautions in interpreting d Siegel , an impod Siegel . Such acd Siegel , 38 suggC and E) should be considered as “conditional” findings, which are indicative of true circumstances, but which are also subject to uncertainties that cannot be quantified with available knowledge and information.Although it is probable that the collection efficiency and DNA conservation of the filters analyzed were not 100%, for the quantitative comparisons made in this section, we make the approximation that collection efficiency is effectively 100% and that DNA collected on AHU filters is conserved. Two lines of reasoning support these assumptions. First, the target contaminants for all filters are the same: DNA that one expects to find mainly in coarse-mode particles, which can be captured with relatively high efficiency by MERV 8 filters. Second, to minimize in-situ and temporal variations, we carefully selected nine AHUs, which had the same filter type, operated during the same periods, and served rooms located in close proximity to one other. A few other cautions are noted that could also limit the accuracy of the interpretation. (a) Although most of the air passing through the filter is recirculated indoor air, there is a small contribution (< 10%) of outdoor air, so some of the accumulated DNA would have originated outdoors. (b) There may be transport losses that influence the relationship between room average concentrations and those in the return air passing through the AHU filter. Owing to all of these considerations, the reported airborne DNA concentrations and the occupancy-associated emission factors (C) based on the analysis of ventilation-system filters. For total DNA, airborne concentrations in the nine locations varied between 2.6 pg/m3 and 107 pg/m3. There was a tendency for higher total DNA concentrations to be found in the libraries, with these sites exhibiting three of the highest four individual levels, the highest overall level, and an average (48 pg/m3) that was more than 4× the corresponding mean for offices and the classroom (11 pg/m3). Average airborne bacterial DNA concentrations were in the range 0.05–8.4 pg/m3 with an overall average across all indoor environments of 1.6 pg/m3. For fungal DNA, the concentrations span a narrower range, 1.0–5.1 pg/m3 and exhibit an average of 2.5 pg/m3. The bacterial and fungal DNA concentrations were also converted to bacterial cells and fungal spore equivalents to provide additional perspective. The time-averaged conditional airborne bacteria and fungi concentrations ranged from 20 to 3100 cells/m3 (average = 580) and from 33 to 173 SE/m3 (average = 83), respectively.C) and the ventilation-rate-normalized occupancy level (Nd) for total, bacterial and fungal DNA. Overall, the values of Pearson correlation coefficients (R) indicate statistically significant moderate to high positive correlations across all three plots, indicating that the accumulation of the three categories of DNA are all positively related to this measure of occupancy in indoor locations.E, ng DNA/(person-h)). As illustrated in The slopes of the three correlations can be used to estimate the occupant-associated DNA emission factor for bioaccumulation on AHU filters (Worth noting is the possibility for the two groups of locations (libraries and offices + classroom) to have different human associated emission factors. Based on the positions of the white and black dots in 2 for total DNA, 0.02 to 3.3 ng/cm2 for bacterial DNA and 0.2 to 2.0 ng/cm2 for fungal DNA. The accumulation of all DNA types generally showed good correlation with occupancy level. Bacterial DNA was the most sensitive in relation to indoor occupancy.This study is the first to provide baseline culture-independent abundance and diversity information on biomass that accumulated on AHU filters in several normally functioning office, classroom, and library environments in a university in a tropical climate. After 12 weeks of use, accumulated DNA masses per AHU filter surface area across nine indoor locations were determined to be in the respective ranges 1.1 to 41 ng/cmProteobacteria, Actinobacteria and Firmicutes were the most abundant bacterial phyla detected and Corynebacterium, Pseudomonas, Bacillus, Streptophyta and Acinetobacter were among the most abundant bacterial genera. The most abundant fungal phylum detected on our AHU filters was Ascomycota, while the most abundant fungal genera were Aspergillus, Cladosporium, Nigrospora, Rigidoporus and Lentinus. Overall, changes in occupancy level were well reflected in the relative abundances of human-related bacterial and fungal genera.In agreement with previous indoor biome studies, In the context of indoor bioaerosol studies, our findings provide qualified support for the potential use of AHU filters as an indoor air quality probe. As recently noted by Haaland and Siegel , AHU filS1 File(XLSX)Click here for additional data file.


The Ebola virus (EBOV) outbreak in West Africa during 2013–2016 demonstrated the need to improve Ebola virus disease (EVD) diagnostics and standards of care. This retrospective study compared laboratory values and clinical features of 3 nonhuman primate models of lethal EVD to assess associations with improved survival time. In addition, the study identified laboratory values useful as predictors of survival, surrogates for EBOV viral loads, and triggers for initiation of therapeutic interventions in these nonhuman primate models. Furthermore, the data support that, in nonhuman primates, the Makona strain of EBOV may be less virulent than the Kikwit strain of EBOV. The applicability of these findings as potential diagnostic and management tools for EVD in humans warrants further investigation. The Ebola virus (EBOV) outbreak in West Africa during 2013–2016 highlighted the need to improve Ebola virus disease (EVD) diagnostics and standards of care , using the same institutional standard operating procedures and processes, the same laboratory instruments, and the same standardized EBOV challenge .Macaca mulatta; 3 groups of 6 animals, male and female, weighing 3.71–7.26 kg) with a target titer of 1,000 PFU of the Kikwit strain of EBOV . Next, we IM inoculated 6 cynomolgus macaques  with a target titer of 1,000 PFU of EBOV Kikwit . The EBOV Kikwit strain we used is a USAMRIID stock virus, EBOV H.sapiens-tc/COD/1995/Kikwit-9510621; this virus was primarily the 7U (7 uridylyls) variant at the mRNA editing site. This challenge virus was propagated from a clinical specimen by using cultured cells for a total of 4 passages. Last, we IM inoculated 6 rhesus macaques  with a target titer of 1,000 PFU (back titration titer 800 PFU) of the USAMRIID stock virus EBOV H.sapiens-tc/LBR/2014/Makona (EBOV Makona); this virus was also primarily the 7U variant at the mRNA editing site. This challenge virus was propagated from a clinical specimen by using cultured cells for a total of 2 passages.We collected blood samples from all 30 NHPs immediately before virus challenge (day 0) and at 3, 5, and 7 days postinoculation (dpi). Methods for EBOV challenge of the NHPs have been described in detail  to analyze serum chemistries; an Advia 120 Hematology Analyzer  with multispecies software to analyze hematology parameters; and a Sysmex CA-1500 (Siemens) for coagulation analyses. The samples yielded a panel of 46 routine clinical laboratory values  to determine viral RNA copy numbers in plasma samples collected at prespecified time points , we used linear and logistic regression models with Microsoft Excel  and Stata 12 . We used p value thresholds of <0.05 for statistical tests and included an adjusted p value of ≤0.001, based on a simplified Bonferroni correction, for multiple comparisons Table 1.10 plasma viral load RNA concentrations obtained at 3, 5, or 7 dpi to predict infection. The combinations of routine laboratory values analyzed were chosen on the basis of the characteristics of individual laboratory values, clinical relevance, and likely access to the test in a field Ebola treatment unit. Day 0 laboratory values were used as baseline values. Because blood samples for viral RNA assessment and routine laboratory analysis were obtained before virus challenge, day 0 values were used to represent uninfected animals. Values obtained at 3, 5, and 7 dpi were used to represent infected animals because all NHPs were experimentally IM inoculated with EBOV , and plasma viral RNA was detected in a sample from at least 1 sampling event for all NHPs included in this analysis. As part of this analysis, we combined the following variables: AST; lactate dehydrogenase (LDH); C-reactive protein (CRP); and the combination of AST, LDH, CRP, and hemoglobin (Hgb). A combined variable C was defined as the mean value of all normalized variables and iv:iv was normalized by dividing the sum of its mean and standard deviation of baseline values . is is 1 (or −1) for variables whose value increases (or decreases) after infection. m is the number of independent variables to be combined. Values of variable C were calculated for each sample on each day (including day 0) after iμ, iσ, and is were determined. We denote the 2 combined variables as (AST+LDH+CRP) and (AST+LDH+CRP−Hgb) because AST, LDH, and CRP values increase after infection, whereas Hgb decreases after infection.We used the receiver operating characteristic (ROC) curve to illustrate a predictor’s performance in 2 metrics, with 1 as a tradeoff of another ; we obtained the ROC curve by varying the laboratory threshold values of a tested predictor. Using ROC area under the curve (AUC), we evaluated the ability of routine laboratory values  and logAnimal research at USAMRIID was conducted under an Institutional Animal Care and Use Committee–approved protocol in compliance with the Animal Welfare Act, US Public Health Service policy, and other federal statutes and regulations relating to animals and experiments involving animals. The facility where this research was conducted is accredited by the Association for Assessment and Accreditation of Laboratory Animal Care, International and adheres to principles stated in the Guide for the Care and Use of Laboratory Animals, National Research Council, 2011.10 RNA values (4.50 RNA copies/mL [range <3.0 to 6.54]) than the EBOV Makona–infected rhesus macaques, all of whom had log10 RNA values below the limit of detection , and at 5 dpi, when the EBOV Kikwit–infected rhesus macaques had higher mean log10 RNA values (8.94 RNA copies/mL [range 5.94 to 10.47]) than the EBOV Makona–infected rhesus macaques .Similarities and differences in baseline summary characteristics of the 3 groups of NHPs are worth noting , 2 as weIn the EBOV Kikwit–infected rhesus macaques, the median survival time was significantly different between animals with high viral loads (214.6 h) and those with low viral loads (148.0 h) (p = 0.013) . In gene10 plasma concentrations of viral RNA were significantly higher among EBOV Kikwit–infected rhesus macaques (8.94 RNA copies/mL) than among EBOV Makona–infected rhesus macaques .Among rhesus macaques, survival time was longer for those infected with EBOV Makona (337.5 hours) than those infected with EBOV Kikwit  . Clinica3/mm3) than cynomolgus  macaques  and cynomolgus (175.2 hours) macaques. In addition, at 5 and 7 dpi, we found no significant difference in clinical findings between these 2 groups . Howevermacaques .10 plasma concentrations of viral RNA correlated significantly with survival time at peak viremia (5–7 dpi) and at 3, 5, and 7 dpi . Similar to what has been reported in human EVD  was not significant; rhesus macaques survived longer. Of interest, at 7 dpi, cynomolgus macaques demonstrated increased impairment of renal function (as determined by BUN and creatinine levels) compared with that for rhesus macaques. This finding does not appear to be associated with a significant observable difference in oral fluid consumption between the animals, and the pathogenesis merits further study.The search for reliable biomarkers for early diagnosis of EBOV infection and predictors of survival has been a high priority (>1.5°C above baseline for 1 hour as a prespecified trigger to treat (Currently, there are no standardized triggers for the initiation of treatment of EBOV-infected NHPs in therapeutics studies. Various time points after virus exposure have been used for therapeutics initiation in NHP models of EBOV infection (Our finding that, in lieu of viral load, laboratory values at 5 dpi could potentially predict survival duration is not entirely surprising given that Warren et al. (LDH is abundant in the cytoplasm of all human cells and helps catalyze the conversion of pyruvate to lactate, the last step of glycolysis (Kortepeter et al. (<0.001 on the basis of a simplified Bonferroni correction for multiple comparisons.A key caveat to our analysis is that our data reflect a retrospective analysis of NHPs used as controls in 5 different studies of IM administered EBOV. The trajectory of early increases in clinical laboratory values, especially CPK and LDH, could be affected by the IM route of EBOV administration. However, Johnson et al. (Much can be learned from a critical analysis of EBOV NHP models. Our data support the finding that the virulence of the EBOV Makona strain used in our study may be decreased as compared to that of the EBOV Kikwit strain we used. We did not find a statistically significant difference in survival time when comparing rhesus to cynomolgus macaques in the EBOV Kikwit model, although there were subtle differences in some of the laboratory values. In addition, our data support EBOV studies in humans that indicate basic laboratory values could potentially be used as surrogate markers for viral load and, thus, disease detection and survival. However, validation of this approach in the human clinical setting would also require a comparison with clinical laboratory values associated with endemic diseases present in a given geographic area, such as malaria, rickettsial illnesses, and diseases caused by other hemorrhagic fever viruses. In addition, a combined score of AST, LDH, CRP, and Hgb values could be further evaluated as a trigger to treat NHPs in therapeutics studies of IM administered EBOV. Further work in the NHP model of EVD with regard to clinical and laboratory markers would ideally lead to improvements in predicting survival time in EBOV-infected NHPs and enhancements in the treatment of disease in NHPs, with potential applicability to the management of human EVD.Additional materials and methods and results of various analyses in a study of clinical laboratory values as early indicators of Ebola virus infection in nonhuman primates.