Disrupted IKAROS activity is a recurrent feature of some human leukemias, but effects on normal human hematopoietic cells are largely unknown. Here, we used lentivirally mediated expression of a dominant-negative isoform of IKAROS (IK6) to block normal IKAROS activity in primitive human cord blood cells and their progeny. This produced a marked (10-fold) increase in serially transplantable multipotent IK6+ cells as well as increased outputs of normally differentiating B cells and granulocytes in transplanted immunodeficient mice, without producing leukemia. Accompanying T/natural killer (NK) cell outputs were unaltered, and erythroid and platelet production was reduced. Mechanistically, IK6 specifically increased human granulopoietic progenitor sensitivity to two growth factors and activated CREB and its targets (c-FOS and Cyclin B1). In more primitive human cells, IK6 prematurely initiated a B cell transcriptional program without affecting the hematopoietic stem cell-associated gene expression profile. Some of these effects were species specific, thus identifying novel roles of IKAROS in regulating normal human hematopoietic cells.
•IKAROS protein is abundantly expressed in primitive human hematopoietic cells•IK6 enhances human blood stem cell expansion in vivo without causing leukemia•IK6 has a unique profile of lineage-specific effects on human hematopoietic cells•IK6 activates B-lineage transcripts prematurely in human blood stem cells
This study reveals a role for IKAROS in the regulation of normal human hematopoietic stem cells (HSCs). In this report, Eaves and colleagues demonstrate that disruption of IKAROS activity expands human HSCs and enhances their outputs of normally differentiating granulocytic and B-lineage cells, without inducing leukemic transformation.
Hematopoietic stem cells (HSCs) are identified by their ability to sustain prolonged blood cell production in vivo, although recent evidence suggests that durable self-renewal (DSR) is shared by HSC subtypes with distinct self-perpetuating differentiation programs. Net expansions of DSR-HSCs occur in vivo, but molecularly defined conditions that support similar responses in vitro are lacking. We hypothesized that this might require a combination of factors that differentially promote HSC viability, proliferation, and self-renewal. We now demonstrate that HSC survival and maintenance of DSR potential are variably supported by different Steel factor (SF)-containing cocktails with similar HSC-mitogenic activities. In addition, stromal cells produce other factors, including nerve growth factor and collagen 1, that can antagonize the apoptosis of initially quiescent adult HSCs and, in combination with SF and interleukin-11, produce >15-fold net expansions of DSR-HSCs ex vivo within 7 days. These findings point to the molecular basis of HSC control and expansion.
•HSC viability, mitogenesis, and self-renewal are differentially controlled•Stromal cells produce nonmitogenic factors that directly sustain HSC viability•More adult bone marrow cells can produce HSCs than display HSC activity directly•Nerve growth factor and collagen 1 promote serially transplantable HSCs
Wohrer et al. now show that different factors secreted by stromal cells separately control the survival, proliferation, and self-renewal of hematopoietic stem cells. These factors are thus required in combination to stimulate net expansions of these cells with full retention of their original stem cell properties.
Next generation, “deep”, sequencing has increasing applications both clinically and in disparate fields of research. This study investigates the accuracy and reproducibility of “deep” sequencing as applied to co-receptor prediction using the V3 loop of Human Immunodeficiency Virus-1. Despite increasing use in HIV co-receptor prediction, the accuracy and reproducibility of deep sequencing technology, and the factors which can affect it, have received only a limited level of investigation. To accomplish this, repeated deep sequencing results were generated using the Roche GS-FLX (454) from a number of sources including a non-homogeneous clinical sample (N = 47 replicates over 18 deep sequencing runs), and a large clinical cohort from the MOTIVATE and A400129 studies (N = 1521). For repeated measurements of a non-homogeneous clinical sample, increasing input copy number both decreased variance in the measured proportion of non-R5 using virus (p<<0.001 and 0.02 for single replicates and triplicates respectively) and increased measured viral diversity (p<0.001; multiple measures). Detection of sequences with a mean abundance less than 1% abundance showed a 2 fold increase in median coefficient of variation (CV) in repeated measurements of a non-homogeneous clinical sample, and a 2.7 fold increase in CV in the MOTIVATE/A400129 dataset compared to sequences with ≥1% abundance. An unexpected source of error included read position, with low accuracy reads occurring more frequently towards the edge of sequencing regions (p<<0.001). Overall, the primary source of variability was sampling error caused by low input copy number/minority species prevalence, though other sources of error including sequence intrinsic, temporal, and read-position related errors were detected.
HIV patients on suppressive antiretroviral therapy have undetectable viremia making it impossible to screen plasma HIV tropism if regimen change is required during suppression. We investigated the prevalence and predictors of tropism switch from CCR5-using (“R5”) to non-CCR5-using (“non-R5”) before and after viral suppression in the initially therapy-naïve HOMER cohort from British Columbia, Canada.
We compared pre-therapy and post-suppression viral genotypic tropism in patients who initiated on PI/NNRTI-based antiretroviral regimens between 1996-1999 (n = 462). Virologic suppression was defined as having two consecutive viral loads of <500 copies/mL, which was the sensitivity limit of most viral load assays at the time. Viral tropism was inferred by V3-loop-population-sequencing and geno2pheno[coreceptor] with cutoff at 5.75% false positive rate (FPR).
When virologic suppression was defined as two-consecutive viral loads <500 copies/mL, 34 (9%) of the 397 patients with pre-therapy R5-virus switched to non-R5 at viral load rebound after a median of 19 months (IQR 8–41 months) of undetectable viremia. Duration of viral load suppression was not a predictor of switch, but lower CD4 count during suppression (median 400 versus 250 cells/mL) and an increased prevalence of pre-therapy non-R5 HIV by “deep” sequencing (median 0.2% versus 3.2%) were independently associated with switch (p = 0.03 and p<0.0001, respectively).
R5-to-non-R5 tropism switches in plasma virus after undetectable viremia were relatively rare events especially among patients with higher CD4 counts during virologic suppression. Our study supports the use of pre-suppression tropism results if maraviroc is being considered during virologic suppression in this subgroup of patients.
Accurate and spatially-explicit maps of tropical forest carbon stocks are needed to implement carbon offset mechanisms such as REDD+ (Reduced Deforestation and Degradation Plus). The Random Forest machine learning algorithm may aid carbon mapping applications using remotely-sensed data. However, Random Forest has never been compared to traditional and potentially more reliable techniques such as regionally stratified sampling and upscaling, and it has rarely been employed with spatial data. Here, we evaluated the performance of Random Forest in upscaling airborne LiDAR (Light Detection and Ranging)-based carbon estimates compared to the stratification approach over a 16-million hectare focal area of the Western Amazon. We considered two runs of Random Forest, both with and without spatial contextual modeling by including—in the latter case—x, and y position directly in the model. In each case, we set aside 8 million hectares (i.e., half of the focal area) for validation; this rigorous test of Random Forest went above and beyond the internal validation normally compiled by the algorithm (i.e., called “out-of-bag”), which proved insufficient for this spatial application. In this heterogeneous region of Northern Peru, the model with spatial context was the best preforming run of Random Forest, and explained 59% of LiDAR-based carbon estimates within the validation area, compared to 37% for stratification or 43% by Random Forest without spatial context. With the 60% improvement in explained variation, RMSE against validation LiDAR samples improved from 33 to 26 Mg C ha−1 when using Random Forest with spatial context. Our results suggest that spatial context should be considered when using Random Forest, and that doing so may result in substantially improved carbon stock modeling for purposes of climate change mitigation.
Mouse fetal mammary cells display greater regenerative activity than do adult mammary cells when stimulated to proliferate in a new system that supports the production of transplantable mammary stem cells ex vivo.
Many normal adult tissues contain rare stem cells with extensive self-maintaining regenerative potential. During development, the stem cells of the hematopoietic and neural systems undergo intrinsically specified changes in their self-renewal potential. In the mouse, mammary stem cells with transplantable regenerative activity are first detectable a few days before birth. They share some phenotypic properties with their adult counterparts but are enriched in a subpopulation that displays a distinct gene expression profile. Here we show that fetal mammary epithelial cells have a greater direct and inducible growth potential than their adult counterparts. The latter feature is revealed in a novel culture system that enables large numbers of in vitro clonogenic progenitors as well as mammary stem cells with serially transplantable activity to be produced within 7 days from single fetal or adult input cells. We further show that these responses are highly dependent on novel factors produced by fibroblasts. These findings provide new avenues for elucidating mechanisms that regulate normal mammary epithelial stem cell properties at the single-cell level, how these change during development, and how their perturbation may contribute to transformation.
Many adult tissues are maintained by a rare subset of undifferentiated stem cells that can self-renew and give rise to specialized daughter cells that have a more limited regenerative ability. The recent identification of cells in the fetal and adult mammary gland that display the properties of stem cells provides a foundation for investigating their self-renewal and differentiation control. We now show that these stem cell properties can be elicited from single mouse mammary cells placed in 3D cultures if novel factors produced by fibroblasts are present. Moreover, a comparison of the clonal outputs of fetal and adult mammary cells in this in vitro system shows that the fetal mammary cells have superior regenerative activity relative to their adult counterparts. The ability to activate and quantify the regenerative capacity of single mouse mammary epithelial cells in vitro sets the stage for further investigations of the timing and mechanisms that alter their stem cell properties during development, the potential relevance of these events to other normal epithelial tissues, and how these processes might be involved in the genesis of breast cancer.
Human immunodeficiency virus type 1 (HIV-1) V3 loop sequence can be used to infer viral coreceptor use. The effect of input copy number on population-based sequencing of the V3 loop of HIV-1 was examined through replicate deep and population-based sequencing of samples with known tropism, a heterogeneous clinical sample (624 population-based sequences and 47 deep-sequencing replicates), and a large cohort of clinical samples from phase III clinical trials of maraviroc including the MOTIVATE/A4001029 studies (n = 1,521). Proviral DNA from two independent samples from each of 101 patients from the MOTIVATE/A4001029 studies was also analyzed. Cumulative technical error occurred at a rate of 3 × 10−4 mismatches/bp, without observed effect on inferred tropism. Increasing PCR replication increased minority species detection with an ∼10% minority population detected in 18% of cases using a single replicate at a viral load of 1,072 copies/ml and in 44% of cases using three replicates. The nucleotide prevalence detected by population-based and deep sequencing were highly correlated (Spearman's ρ, 0.73), and the accuracy increased with increasing input copy number (P < 0.001). Triplicate sequencing was able to predict tropism changes in the MOTIVATE/A4001029 studies for both low (P = 0.05) and high (P = 0.02) viral loads. Sequences derived from independently extracted and processed samples of proviral DNA for the same patient were equivalent to replicates from the same extraction (P = 0.45) and had correlated position-specific scoring matrix scores (Spearman's ρ, 0.75; P ≪ 0.001); however, concordance in tropism inference was only 83%. Input copy number and PCR replication are important factors in minority species detection in samples with significant heterogeneity.
The Malaysian states of Sabah and Sarawak are global hotspots of forest loss and degradation due to timber and oil palm industries; however, the rates and patterns of change have remained poorly measured by conventional field or satellite approaches. Using 30 m resolution optical imagery acquired since 1990, forest cover and logging roads were mapped throughout Malaysian Borneo and Brunei using the Carnegie Landsat Analysis System. We uncovered ∼364,000 km of roads constructed through the forests of this region. We estimated that in 2009 there were at most 45,400 km2 of intact forest ecosystems in Malaysian Borneo and Brunei. Critically, we found that nearly 80% of the land surface of Sabah and Sarawak was impacted by previously undocumented, high-impact logging or clearing operations from 1990 to 2009. This contrasted strongly with neighbouring Brunei, where 54% of the land area remained covered by unlogged forest. Overall, only 8% and 3% of land area in Sabah and Sarawak, respectively, was covered by intact forests under designated protected areas. Our assessment shows that very few forest ecosystems remain intact in Sabah or Sarawak, but that Brunei, by largely excluding industrial logging from its borders, has been comparatively successful in protecting its forests.
High fidelity carbon mapping has the potential to greatly advance national resource management and to encourage international action toward climate change mitigation. However, carbon inventories based on field plots alone cannot capture the heterogeneity of carbon stocks, and thus remote sensing-assisted approaches are critically important to carbon mapping at regional to global scales. We advanced a high-resolution, national-scale carbon mapping approach applied to the Republic of Panama – one of the first UN REDD + partner countries.
Integrating measurements of vegetation structure collected by airborne Light Detection and Ranging (LiDAR) with field inventory plots, we report LiDAR-estimated aboveground carbon stock errors of ~10% on any 1-ha land parcel across a wide range of ecological conditions. Critically, this shows that LiDAR provides a highly reliable replacement for inventory plots in areas lacking field data, both in humid tropical forests and among drier tropical vegetation types. We then scale up a systematically aligned LiDAR sampling of Panama using satellite data on topography, rainfall, and vegetation cover to model carbon stocks at 1-ha resolution with estimated average pixel-level uncertainty of 20.5 Mg C ha-1 nationwide.
The national carbon map revealed strong abiotic and human controls over Panamanian carbon stocks, and the new level of detail with estimated uncertainties for every individual hectare in the country sets Panama at the forefront in high-resolution ecosystem management. With this repeatable approach, carbon resource decision-making can be made on a geospatially explicit basis, enhancing human welfare and environmental protection.
Biomass; Carbon stock; Carnegie Airborne Observatory; Deforestation; Forest degradation; Forest inventory; Light Detection and Ranging; Panama
HLA class I-associated polymorphisms identified at the population level mark viral sites under immune pressure by individual HLA alleles. As such, analysis of their distribution, frequency, location, statistical strength, sequence conservation, and other properties offers a unique perspective from which to identify correlates of protective cellular immunity. We analyzed HLA-associated HIV-1 subtype B polymorphisms in 1,888 treatment-naïve, chronically infected individuals using phylogenetically informed methods and identified characteristics of HLA-associated immune pressures that differentiate protective and nonprotective alleles. Over 2,100 HLA-associated HIV-1 polymorphisms were identified, approximately one-third of which occurred inside or within 3 residues of an optimally defined cytotoxic T-lymphocyte (CTL) epitope. Differential CTL escape patterns between closely related HLA alleles were common and increased with greater evolutionary distance between allele group members. Among 9-mer epitopes, mutations at HLA-specific anchor residues represented the most frequently detected escape type: these occurred nearly 2-fold more frequently than expected by chance and were computationally predicted to reduce peptide-HLA binding nearly 10-fold on average. Characteristics associated with protective HLA alleles (defined using hazard ratios for progression to AIDS from natural history cohorts) included the potential to mount broad immune selection pressures across all HIV-1 proteins except Nef, the tendency to drive multisite and/or anchor residue escape mutations within known CTL epitopes, and the ability to strongly select mutations in conserved regions within HIV's structural and functional proteins. Thus, the factors defining protective cellular immune responses may be more complex than simply targeting conserved viral regions. The results provide new information to guide vaccine design and immunogenicity studies.
Canopy gaps express the time-integrated effects of tree failure and mortality as well as regrowth and succession in tropical forests. Quantifying the size and spatial distribution of canopy gaps is requisite to modeling forest functional processes ranging from carbon fluxes to species interactions and biological diversity. Using high-resolution airborne Light Detection and Ranging (LiDAR), we mapped and analyzed 5,877,937 static canopy gaps throughout 125,581 ha of lowland Amazonian forest in Peru. Our LiDAR sampling covered a wide range of forest physiognomies across contrasting geologic and topographic conditions, and on depositional floodplain and erosional terra firme substrates. We used the scaling exponent of the Zeta distribution (λ) as a metric to quantify and compare the negative relationship between canopy gap frequency and size across sites. Despite variable canopy height and forest type, values of λ were highly conservative (λ mean = 1.83, s = 0.09), and little variation was observed regionally among geologic substrates and forest types, or at the landscape level comparing depositional-floodplain and erosional terra firme landscapes. λ-values less than 2.0 indicate that these forests are subjected to large gaps that reset carbon stocks when they occur. Consistency of λ-values strongly suggests similarity in the mechanisms of canopy failure across a diverse array of lowland forests in southwestern Amazonia.
Accurate, high-resolution mapping of aboveground carbon density (ACD, Mg C ha-1) could provide insight into human and environmental controls over ecosystem state and functioning, and could support conservation and climate policy development. However, mapping ACD has proven challenging, particularly in spatially complex regions harboring a mosaic of land use activities, or in remote montane areas that are difficult to access and poorly understood ecologically. Using a combination of field measurements, airborne Light Detection and Ranging (LiDAR) and satellite data, we present the first large-scale, high-resolution estimates of aboveground carbon stocks in Madagascar.
We found that elevation and the fraction of photosynthetic vegetation (PV) cover, analyzed throughout forests of widely varying structure and condition, account for 27-67% of the spatial variation in ACD. This finding facilitated spatial extrapolation of LiDAR-based carbon estimates to a total of 2,372,680 ha using satellite data. Remote, humid sub-montane forests harbored the highest carbon densities, while ACD was suppressed in dry spiny forests and in montane humid ecosystems, as well as in most lowland areas with heightened human activity. Independent of human activity, aboveground carbon stocks were subject to strong physiographic controls expressed through variation in tropical forest canopy structure measured using airborne LiDAR.
High-resolution mapping of carbon stocks is possible in remote regions, with or without human activity, and thus carbon monitoring can be brought to highly endangered Malagasy forests as a climate-change mitigation and biological conservation strategy.
aboveground carbon density; biomass; carbon stocks; Carnegie Airborne Observatory; CLASlite; LiDAR; REDD; tropical forest
Initial in vitro studies of bevirimat resistance failed to observe mutations in the clinically significant QVT motif in SP1 of HIV-1 gag. This study presents a novel screening method involving mixed, clinically derived gag-protease recombinant HIV-1 samples to more accurately mimic the selection of resistance seen in vivo. Bevirimat resistance was investigated via population-based sequencing performed with a large, initially antiretroviral-naïve cohort before (n = 805) and after (n = 355) standard HIV therapy (without bevirimat). The prevalence of any polymorphism in the motif comprising Q, V, and T was ∼6%, 29%, and 12%, respectively, and did not change appreciably over the course of therapy. From these samples, three groups of 10 samples whose bulk sequences were wild type at the QVT motif were used to generate gag-protease recombinant viruses that captured the existing diversity. Groups were mixed and passaged with various bevirimat concentrations for 9 weeks. gag variations were assessed by amplicon-based “deep” sequencing using a GS FLX sequencer (Roche). Unscreened mutations were present in all groups, and a V370A minority not originally detected by bulk sequencing was present in one group. V370A, occurring together with another preexisting, unscreened resistance mutation, was selected in all groups in the presence of a bevirimat concentration above 0.1 μM. For the two groups with V370A levels below consistent detectability by deep sequencing, the initial selection of V370A required 3 to 4 weeks of exposure to a narrow range of bevirimat concentrations, whereas for the group with the V370A minority, selection occurred immediately. This approach provides quasispecies diversity that facilitates the selection of mutations observed in clinical trials and, coupled with deep sequencing, could represent an efficient in vitro screening method for detecting resistance mutations.
University of Maryland School of Pharmacy was in a quandary: its comprehensive mission required meeting state workforce needs while increasing educational quality, expanding research, and responding to service needs, but state resources were declining, faculty members were stressed, construction of a long-needed new building was stalled, and pressure to increase doctor of pharmacy (PharmD) enrollment was growing. A sharp challenge from the Board of Regents mobilized the school to quickly launch a growth initiative to accelerate PharmD program expansion through a satellite campus. Within 4 months, a plan was approved that not only led to enrollment growth, but also to a significant expansion of the faculty and staff, increased operating and capital budgets, and ground breaking for an $83 million new building. This case study illustrates how seemingly competitive needs such as teaching, research, and service can be woven together synergistically to accomplish multiple goals.
satellite campus; planning; finance; distance education; enrollment; expansion
To compare the attributes of US colleges and schools of pharmacy and describe the extent of change to the pharmacy education enterprise associated with the addition of new schools.
Attributes analyzed included whether the college or school of pharmacy was old or new, public or private, secular or faith-based, and on or not on an academic health center (AHC) campus; had 3- or 4- year programs; and had PhD students enrolled. PharmD student enrollment-to-faculty ratios and junior-to-senior faculty ratios also were examined.
Of the new colleges/schools, 76% were private and 79% were not located on a campus with an AHC; 6% had PhD enrollment compared with 80% of old colleges/schools. Faculty ratios were related to several college/school attributes, including the presence or absence of PhD students and whether the college/school was public or private.
Attributes of new colleges and schools of pharmacy have changed the overall profile of all colleges and schools of pharmacy. For example, smaller percentages of all colleges and schools of pharmacy are public and have PhD enrollees.
pharmacy education; faculty-to-student ratio; college/school attributes
This paper presents a discussion of a three year study to improve the quality of drug use in nursing homes. Prescribing criteria were developed for five classes of drugs: diuretics, sedative-hypnotic/antianxiety agents, laxatives, analygesics for mild to moderate pain, and digoxin. Physicians from 27 nursing homes in the Baltimore metropolitan area were randomly assigned to one of seven treatment combinations (including a pure control group). A computerized drug use review system has also been developed, which compares data abstracted from the patient's medical record to the above mentioned criteria, and produces summary prescribing reports which are then sent to the prescribing physicians, some of whom also receive educational newsletters which were developed using the criteria as a basis. Some change in prescribing was noted after the first intervention.
This paper describes an operational computer-based system for conducting Drug Prescribing Review (DPR). The system was designed to: arrive at specific judgements about the potential problems of drug orders taking into account the characteristics of the patient and their medical conditions; be relatively independent of the structure of the data base; and be capable of expressing and evaluating any DPR criteria. This was accomplished by developing a hierarchical, rule-based system for expressing and evaluating DPR criteria. This system was then linked with a specific patient data base for implementation. Drug orders for 65 patients have been evaluated and the results agree with expert judgement. The rule-based DPR system appears to be a feasible method of evaluation of drug orders.
This paper describes a rule-based software system for Drug Prescribing Review (DPR) which considers patient characteristics as well as concomitant therapy and prescription parameters. Its purpose is to screen drug orders to determine if potential problems exist. This DPR system evaluates the drug orders parameters in terms of the patient's diagnoses, age, sex, laboratory test values and concurrent drug therapy. The DPR criteria are formulated as a rule-based inference system. The system is a three level hierarchy of testable assertions, rules and screens. Each screen corresponds to a misjudgment that can occur in the process of prescribing drug therapy. This DPR system is currently implemented in a 3 year study of drug use in long term care facilities as one of several factors intended to influence physician prescribing. A principle outcome of this study in 1983 will be an evaluation of the effectiveness of rule-based, computerized DPR in influencing the physician's prescribing behavior in long term care facilities.
Genomic and phenotypic analyses indicate extensive intra- as well as intertumoral heterogeneity in primary human malignant cell populations despite their clonal origin. Cellular DNA barcoding offers a powerful and unbiased alternative to track the number and size of multiple subclones within a single human tumour xenograft and their response to continued in vivo passaging. Using this approach we find clone-initiating cell frequencies that vary from ~1/10 to ~1/10,000 cells transplanted for two human breast cancer cell lines and breast cancer xenografts derived from three different patients. For the cell lines, these frequencies are negatively affected in transplants of more than 20,000 cells. Serial transplants reveal five clonal growth patterns (unchanging, expanding, diminishing, fluctuating or of delayed onset), whose predominance is highly variable both between and within original samples. This study thus demonstrates the high growth potential and diverse growth properties of xenografted human breast cancer cells.
Cancer cells within the same tumour are heterogeneous in their tumorigenic potential, differentiation status and sensitivity to treatments. Here Nguyen et al. use a sensitive DNA barcoding method to characterize the diversity of clonal growth behaviour within human breast tumours.