Patients recovering from major surgery are at high risk of developing life-threatening deep venous thrombosis, which is a key source of postoperative morbidity and mortality. Our objective was to assess the cost-effectiveness of two different thromboprophylactic agents for patients admitted to the ICU after high-risk surgery: intermittent pneumatic compression (IPC) and anti-embolism stockings (AES).A decision model (TreeAge Software 2010) was constructed simulating the impact of AES and IPS on patient outcomes and costs following high-risk surgery in the UK. Probabilities were assessed from published data [Total costs for in-patients receiving AES were £923 and £1,010 for patients treated with IPC. Equipment costs and cost of initial care were higher in patients who received IPC, but this was partly offset by a reduction in costs related to treatment of early (DVT and PE) and late complications (post-thrombotic syndrome and pulmonary hypertension). IPC treatment increased QALY by approximately 0.01 years. The incremental cost-effectiveness of the IPC device was £12,650 per QALY gained. One-way sensitivity analysis revealed that the most sensitive variables were probability of developing a DVT resulting from the insignificant difference in treatment efficacy.Based on UK cost-effectiveness guidelines, our results indicate that IPC stockings should be used for patients at high risk of developing DVT. IPCs decrease the incidence of developing DVT and therefore result in cost savings related to preventive and therapeutic actions. For patients at low risk of developing DVT, AES are favoured due to higher utility and lower maintenance costs associated with AES. Due to the lack of reliable data on the incidence of PE as well as the absence of reliable head-to-head studies between IPC and AES, no generalisable conclusion to favour either strategy can be made.


Antiretroviral treatment (ART) has altered the spectrum of HIV-related eye disease, resulting in a lower prevalence of retinal opportunistic infections (OIs). However, abnormalities in visual function have been reported in HIV-infected individuals despite effective viral suppression and the absence of retinal OIs. These changes may be mediated by an HIV-associated ‘neuroretinal disorder’, characterized by changes in the retinal nerve fibre layer (RNFL). HIV infection may also be associated with accelerated biological aging. The aim of this study was to investigate the relationships between contrast sensitivity, RNFL thickness, HIV infection and frailty in South African adults.Case-control study of 225 HIV-infected individuals without retinal OIs and 203 gender/age-matched HIV-seronegative individuals. Peri-papillary RNFL thickness was determined with spectral domain optical coherence tomography in four quadrants. CS was measured using a Pelli-Robson chart. Frailty was assessed using standard criteria. Multivariable linear and logistic regression were used to assess associations between HIV status and RNFL/CS and frailty.The median age of both groups was similar . 88% of HIV-infected individuals were receiving ART and their median CD4 count was 468 cells/μl. Adjusted CS score was lower in HIV-infected participants compared to HIV-seronegative individuals . Independent predictors of poor CS in the HIV-infected group were positive frailty status and current HIV viral load >2 log copies/ml. Lower CS score was also associated with thin temporal RNFL in HIV-infected individuals (p = 0.04). Superior quadrant RNFL thickness was greatest in ART-naïve participants relative to the HIV-uninfected group (p-trend = 0.04). Longer ART duration was associated with thinning of inferior and nasal RNFL quadrants .Contrast sensitivity is reduced in HIV-infected individuals and functionally associated with frailty and unsuppressed viraemia. This may reflect structural changes in the RNFL that are evident despite the absence of OIs. In well-resourced settings, antiretroviral treatment (ART) has altered the spectrum of HIV-related eye disease in people living with HIV infection, leading to a lower prevalence of retinal opportunistic infections (OIs) such as cytomegalovirus (CMV) retinitis One mechanism that may potentially contribute to HIV-NRD is ‘accelerated biological’ aging that is recognised to be associated with HIV infection We have recently undertaken a case-control study of adults in South Africa, and have shown that HIV infection is associated with several ocular changes i.e. in retinal vessel calibre, lens density and corneal endothelial cell density consistent with accelerated HIV-related aging The study was approved by the Ethics Committees of the London School of Hygiene and Tropical Medicine and the University of Cape Town Faculty of Health Sciences, and adhered to the tenets of the Declaration of Helsinki. Written informed consent was obtained from all participants.HIV-infected participants aged >30 years were enrolled from a community-based HIV treatment centre in Nyanga district in Cape Town 2. In brief physical frailty was defined by the presence of ≥3 of 5 criteria: i) unintentional weight loss (self reported and verified from clinic records where possible) ii) self-reported low physical activity, iii) self-reported exhaustion, iv) weak grip strength and v) slow walking time. Detailed assessment of frailty within this study population has been previously reported Data on age, sex, weight and height, as well as socio-behavioural factors such as housing, income, smoking and alcohol consumption were collected. Data collected for HIV-infected participants included nadir and current CD4 count, peak and current viral load, staging of HIV according to WHO clinical stage, ART status and regimen. Clinical information was obtained from medical case notes as required. Blood pressure (BP) was measured with a digital sphygmomanometer with a cuff of appropriate size. Mean arterial blood pressure (MABP) was defined as two-thirds of the diastolic plus one-third of the systolic BP All participants underwent a full ophthalmic examination including measurement of visual acuity, evaluation by slit lamp microscopy and indirect ophthalmoscopy. Contrast sensitivity was measured with a Pelli-Robson chart under ambient (daylight) conditions as per the recommendation of the manufacturer . All examinations were conducted in the same room under the same lighting conditions. The chart has eight lines of letters with two groups of three letters per line. Testing was performed at 1 m with a 0.75 diopter lens added to the manifest refraction if necessary. The logarithm to the base 10 of the CS measurement was obtained from the Pelli-Robson chart and used in analyses (LogCS). Investigators who conducted the tests were masked to other data. RFNL thickness was obtained using the Spectral OCT/SLO optical coherence tomography machine . OCT scans were performed by one trained operator to reduce inter-observer variation. Only OCT scans that were of sufficient quality  were used. Replicates were only taken if the OCT scans were of insufficient quality. The Spectral OCT/SLO uses a scanning laser diode of 830 nm to provide images of ocular microstructures. A peripapillary protocol inbuilt in the software was used to determine the average and quadrant-specific RNFL thickness .th percentile in the control group to denote ‘poor CS’ (1.65). Further analyses were undertaken using the cut-off of 1.50 as defined by Shah and associates th centile in the control group to denote ‘thin RNFL’ . Logistic regression was used to assess predictors of poor CS in those participants on ART. Multivariable linear regression models were used to examine the relationship of RNFL parameters as the dependent variable, with HIV status and other explanatory variables  as independent variables. Separate models were used for HIV-infected participants to investigate the effects of HIV-related variables. Marginal adjusted means for RNFL parameters were estimated at the mean value of covariates in the model. The Wald test was used to assess statistical significance of the association of each explanatory variable on RNFL thickness. All analyses were performed with Stata 12 .One eye was randomly selected for analysis. Where an eye was not available, for example due to trauma or corneal opacity, the contralateral eye was used. LogCS scores and RNFL were initially analysed as continuous variables. Age and sex-adjusted linear regression was performed to compare logCS score and RNFL parameters respectively by HIV status. A binary categorisation of logCS was defined using the a-priori defined cutpoint of the 25Characteristics of the 225 HIV-infected individuals and 203 HIV-seronegative age/gender frequency matched HIV-seronegative individuals are reported in Data on CS were available for 216 HIV-infected individuals and 215 HIV-seronegative individuals. Unadjusted mean logCS was lower in HIV-infected individuals compared to HIV-seronegative participants  . After adjustment for age, sex, smoking status (yes/no), MABP and BMI, mean logCS values still remained lower in HIV-infected individuals . HIV-infected individuals were also more likely to have ‘poor CS’ (<1.65) compared to their uninfected counterparts .In multivariable analysis among HIV-infected participants on ART, poor CS was associated with positive frailty status   and HIV Among HIV-infected participants increasing age was, as expected, associated with thinning of the RNFL. Increasing duration of ART was associated with reduced thickness of the RNFL in inferior and nasal quadrants  and 2. NFinally, we assessed CS score according to RNFL thickness  in HIV-infected participants. Lower CS was associated with thin temporal RNFL ; the association of temporal RNFL thickness with CS is also depicted in This study provides evidence that HIV infection is strongly associated with poor CS in this South African population. Data from other regions, particularly the USA, demonstrate evidence of an HIV-related ‘neuro-retinal disorder’, comprising subtle vision abnormalities in the absence of opportunistic infections We have previously demonstrated that HIV infection is associated with an increased risk of frailty, providing evidence that this functional phenotype is associated with HIV-related accelerated aging Although the frequency of poor CS was markedly higher in HIV-infected individuals compared to controls, the median visual acuity between the two groups was the same and all participants had visual acuity better than 20/40. Contrast sensitivity loss can be present even when visual acuity and fields are relatively intact In the context of accelerated aging and HIV, reduced thickness of the RNFL in HIV-infected individuals compared to uninfected counterparts of similar age might be expected as the RNFL thins with increasing chronological age Our findings suggest that ART duration is an important factor in determining RNFL thickness  after adjusting for age and other co-variates, and we have previously shown that narrower retinal arterioles are associated with increasing duration of ART, independently of age increase in RNFL thickness in our study population may be biologically plausible. Medzhitov The association of detectable HIV viremia with an A key strength of this study is the inclusion of an age/gender-matched control group with a similar socio-demographic profile as the HIV-infected individuals. By recruiting from the same community, we aimed to reduce the likelihood of differential risk exposure in line with the recommendation for careful study design when investigating premature aging in HIV This study had some limitations. The study design means we cannot infer whether HIV is causally related to poor CS function or changes in RNFL, nor can a temporal relationship be established. The measurement of CS is subjective, however we adhered to standardized protocols  and used the same chart and examiner in the same location. Another potential limitation is that misclassification of smoking and alcohol consumption may have occurred, with HIV-infected participants wanting to demonstrate ‘healthy behaviour’ which could have led to confounding. Finally, in the context of further defining the HIV-neuroretinal disorder it would have been ideal to have data on visual fields and colour vision, however, this initial data provide an informative basis from which to plan further studies in this study population or region. Further investigations such as micro-perimetry and retinal electrophysiology would also help to elucidate possible mechanisms and pathways of HIV-associated neuro-retinal disorder.In summary, HIV-infected individuals in South Africa demonstrate abnormal CS, and changes in RNFL thickness related to viremic status. Longitudinal studies are needed to determine whether changes in RNFL and systemic indicators such as frailty predict change in visual function, and equally importantly, the role of ophthalmic indicators in predicting the biologically aged phenotype in chronic HIV infection.


PhylOTU, a computational workflow that identifies OTUs from metagenomic SSU-rRNA sequence data through the use of phylogenetic principles and probabilistic sequence profiles. Using simulated metagenomic data, we quantified the accuracy with which PhylOTU clusters reads into OTUs. Comparisons of PCR and shotgun sequenced SSU-rRNA markers derived from the global open ocean revealed that while PCR libraries identify more OTUs per sequenced residue, metagenomic libraries recover a greater taxonomic diversity of OTUs. In addition, we discover novel species, genera and families in the metagenomic libraries, including OTUs from phyla missed by analysis of PCR sequences. Taken together, these results suggest that PhylOTU enables characterization of part of the biosphere currently hidden from PCR-based surveys of diversity?Microbial diversity is typically characterized by clustering ribosomal RNA (SSU-rRNA) sequences into operational taxonomic units (OTUs). Targeted sequencing of environmental SSU-rRNA markers via PCR may fail to detect OTUs due to biases in priming and amplification. Analysis of shotgun sequenced environmental DNA, known as metagenomics, avoids amplification bias but generates fragmentary, non-overlapping sequence reads that cannot be clustered by existing OTU-finding methods. To circumvent these limitations, we developed  PhylOTU, a novel computational method that enables accurate characterization of microbial diversity from metagenomic data. We process over 10 million metagenomic sequences obtained from the global open ocean to identify novel Bacterial taxa and reveal the presence of microorganisms overlooked by investigation of PCR-based sequences from the same samples. These results suggest that to fully characterize microbial biodiversity requires a novel bioinformatics toolbox for analysis of shotgun metagenomic data.Microorganisms comprise the majority of the biodiversity on the planet. Because the overwhelming majority of microbes are not readily cultured in the laboratory, researchers often rely on PCR-based investigations of genomic sequence to characterize microbial diversity. These analyses have dramatically expanded our understanding of biodiversity, but due to methodological biases PCR-based approaches may only reveal part of the microbial biosphere. Shotgun sequencing of environmental DNA, known as metagenomics, avoids the biases associated with targeted amplification of genomic sequence and can provide insight into the diversity hidden from traditional investigations. However, the fragmentary, non-overlapping nature of shotgun sequence data makes it intractable to analyze with existing tools. Here, we present  A central goal of ecology and evolution is to understand the forces that shape biodiversity - the variety of life on Earth. It is becoming increasingly clear that global biodiversity is mostly microbial. It is estimated that there are millions of microbial species on the planet, relatively few of which have been isolated in culture Biodiversity science has traditionally focused on comparing species richness across space, time and environments. Out of necessity, microbial diversity studies usually examine the richness (i.e. number) of operational taxonomic units (OTUs), where OTUs are sequence similarity based surrogates for microbial taxa, which can be difficult to define. In addition to richness, OTUs have been used to characterize the abundance, range, and distribution of microbes, thereby improving our understanding of both natural ecosystems and human health The SSU-rRNA sequences for OTU identification are traditionally amplified from a sample via polymerase chain reaction (PCR) using universal primers. Each PCR product is then individually sequenced. One of the biggest drawbacks of this targeted sequencing approach is that it leverages PCR, which has been shown to exhibit sequence-based biases at the level of priming and extension de novo sequence assemblers to build SSU-rRNA contigs , rather than PID, is then used to cluster reads into OTUs in a fashion similar to that utilized for targeted sequencing data. Because the enormous volume of sequence in most metagenomic libraries presents substantial challenges in the form of sequence-alignment quality and the rate of computational through-put, we developed and implemented within PhylOTU a series of data quality control filters and efficient data structures. We also developed an error rate metric for the analysis of clustered data and used simulated sequences to quantify the accuracy of PhylOTU. These investigations enabled us to derive corrections for biases in phylogenetic methods, producing a tool with similar accuracy to existing PID-based methods. We used PhylOTU to describe microbial diversity in the global open ocean by processing the 10,133,846 shotgun reads in the Global Ocean Survey sequence library PhylOTU is freely available for download at github (https://github.com/sharpton/PhylOTU) and BioTorrents (http://www.biotorrents.net) We present PhylOTU, which uses a probabilistic sequence profile to align reads and a phylogenetic tree to infer their similarity.Traditionally, OTUs are identified from a PCR-generated targeted sequence library by aligning all pairs of sequences, calculating each pair's PID-based distance, and using this distance to group sequences using agglomerative hierarchical clustering. Due to the fragmentary nature of shotgun metagenomic reads, this traditional approach is limited to the subset of overlapping sequences; non-overlapping reads cannot be directly aligned to one another. Even when reads can be aligned , one still cannot calculate PID for sequences that do not overlap. To overcome these limitations, we designed PhylOTU employs is to leverage full-length reference sequences to construct a probabilistic sequence profile of SSU-rRNA. The profile is used to align metagenomic reads and reference sequences, and this alignment is in turn used to compute the phylogenetic distance between every pair of reads for input into the clustering algorithm. A general workflow schematic of our method is illustrated in The general strategy BLAST search of every metagenomic read against the small but phylogenetically diverse SSU-rRNA STAP databases First, probabilistic profiles that encode the evolutionary diversity and secondary structure of the SSU-rRNA sequence from Bacteria and Archaea RAxMLpplacerPhylOTU currently employs FastTree as a default method due to its relatively high speed-to-performance ratio and its ability to construct accurate trees in the presence of highly-gapped data MOTHUR into OTUs in a fashion similar to traditional PID-based analysis We use this high quality alignment of metagenomic reads and references sequences to construct a fully-resolved, phylogenetic tree and hence determine the evolutionary relationships between the reads. Reference sequences are included in this stage of the analysis to guide the phylogenetic assignment of the relatively short metagenomic reads. While the software can be easily extended to incorporate a number of different phylogenetic tools capable of analyzing metagenomic data  to compare PD versus PID clustering, 2) to explore overlap between PhylOTU clusters and recognized taxonomic designations, and 3) to quantify the accuracy of PhylOTU clusters from shotgun reads relative to those obtained from full-length sequences.To evaluate the performance of PhylOTU may be used to identify OTUs from overlapping sequences. Therefore we applied both methods to a dataset of 508 full-length bacterial SSU-rRNA sequences  obtained from the Ribosomal Database Project (RDP) ESPRIT, which implements pairwise alignments, to obtain a PID distance matrix for the reference sequences PhylOTU to compute a PD distance matrix for the same data. Then, we used MOTHUR to hierarchically cluster sequences into OTUs based on both PID and PD. For each of the two distance matrices, we employed a range of clustering thresholds and three different definitions of linkage in the hierarchical clustering algorithm: nearest-neighbor, average, and furthest-neighbor.We sought to identify how PD-based clustering compares to commonly employed PID-based clustering methods by applying the two methods to the same set of sequences. Both PID-based clustering and PhylOTU exhibits high true conjunction and true disjunction rates at commonly employed PID thresholds , demonstrating that PD-based clustering accurately recapitulated PID-based clustering at the same threshold  and true disjunction rate  see . PhylOTUhreshold .On the other hand, when applying the same clustering threshold to both distance matrices, PID-based clustering produces a higher richness estimate  than PD-based clustering . CompariPhylOTU, with furthest-neighbor clustering producing richness estimates most similar to PID-based clustering for a given threshold  and true disjunction (99.4%) rates at a clustering threshold of 0.03 , a recently developed, highly parameterized simulation pipeline which expands the function of the MetaSim program in silico shotgun reads from the 50 source sequences with a read length distribution chosen to be similar to a 454-sequence library  similarity between the read and full-length sequence distance matrices, and 2) accuracy at which the algorithm clusters reads into OTUs relative to clusters built from full-length sequences.To investigate the performance of rary see . We simuComparing the PD matrices from metagenomic and full-length data sets, we observe a strong correlation between the pairwise distances computed on reads and full-length sequences. For each of the 25 simulated samples, the read and corresponding full-length-sequence distance matrices show a positive and significant correlation  at a read threshold of 0.09, and 90% accuracy  at a threshold of 0.18. Thus, simulations enabled us to select tuning parameters of the hierarchical clustering algorithm in PhylOTU so that the OTUs generated from shotgun read data closely resemble those that would be identified if full-length PCR products were available for each SSU-rRNA sequence in the read library.We then determined whether the performance of  OTU see . Maximiz OTU see . This rePhylOTU clusters metagenomic reads under relatively simple simulation parameters, we evaluated how PhylOTU performs using more rigorous parameters that are reflective of situations encountered during real studies. First, in some environmental samples, the average read may be quite diverged from its closest reference sequence. Second, in many studies the number of reads will be greater than the number of reference sequences. To investigate these two issues, we first used our simulated sequences to evaluate the relationship between the mean phylogenetic distance from each read to its nearest reference sequence  and the true conjunction rate. We found no significant correlation (Spearman's test). Next, we conducted additional simulations based on sampling reads from full-length Bacterial SSU-rRNA sequences in the SILVA database SILVA database, reflecting the approximate number of SSU-rRNA reads expected when performing one run of next-generation sequencing on a shotgun library. These 1,000 source sequences were then used to simulate metagenomic reads as described above. Reference sequences were pruned from both the source and simulation phylogenies and full-length source sequences and simulated reads were then clustered into OTUs. In these simulations, the average distance between each read and its nearest source is an order of magnitude greater than that observed in our previous simulation analysis (0.182 versus 0.010 mean read-to-reference distance), which is expected given that the SILVA database is highly populated and comprised of phylogenetically diverse sequence data. Evaluating the accuracy of PhylOTU under these conditions reveals high true disjunction rates, similar to those observed in the RDP reference library based simulations. True conjunction rates are somewhat lower, but still meet our accuracy standards. For example, at a read threshold of 0.15, PhylOTU clusters metagenomic reads with an 80% true conjunction rate and a 98.8% true disjunction rate  metagenomic read library PhylOTU to discover novel taxa in shotgun data by comparing the OTUs identified from metagenomic reads to those identified from full-length PCR data from these six sites. We applied PhylOTU to both data sets and corrected for the difference in sequence types by adjusting the read threshold relative to the full-length sequence threshold according to our simulation analysis. Specifically, we used a read threshold of 0.15 and a full-length sequence threshold of 0.03 to evaluate diversity at approximately the species level. We compared the number of OTUs identified per sequence across methods by conducting a rarefaction analysis .The GOS project also generated 6,413 full-length SSU-rRNA sequences via targeted sequencing of PCR products from six of the 73 geographical sites surveyed analysis  [39]. FoPhylOTU reveals a shared set of OTUs as well as unique OTUs missed by each method  to cluster reads into OTUs in place of PID. Building a phylogenetic tree requires that at least some of the sequences within the input alignment overlap. Thus, we incorporate high-quality, full-length reference sequences into the SSU-rRNA sequence alignment to guide the phylogenetic placement of metagenomic reads. The accuracy of this approach is constrained, at least in part, by the phylogenetic diversity of the reference sequences and the means by which the phylogenetic algorithm processes missing data. For example, it is challenging to assess distances between non-overlapping shotgun reads derived from a similar place in the phylogeny, even via comparison to full-length reference sequences. We determined the robustness of our method by evaluating the OTU assignment accuracy of simulated metagenomic reads relative to their full-length sources, finding that the relative PD between a pair of reads is on average highly consistent with the relative PD between full-length sources. This result indicates that metagenomic reads can be assigned to OTUs with high accuracy by simply scaling the clustering threshold.We also tested whether clustering based on PD could accurately recapitulate clustering based on PID for full-length reads where both methods may be applied. Processing 508 full-length reference sequences via both algorithms reveals that PD accurately assigns sequences into OTUs when compared to the PID OTUs. However, this analysis also reveals that PD results in lower richness estimates relative to PID. This phenomenon appears to be due to a difference in the relative distances between sequences. Specifically, the phylogenetic approach appears to shorten the estimated distance between closely related sequences, relative to the PID approach. This is likely due to the fact that the PD approach employs a weighted substitution model when calculating distances, while the PID approach treats all substitutions with equal weight. Thus, while the hierarchical structure of the clusters is generally consistent between the two methods, as revealed by the cluster composition accuracy analysis, sister OTUs in the PID analysis tend to be merged together via the PD approach. For this reason, it may be necessary to take into account this systematic difference in order to compare the diversity results from a PD-based study with a PID-based study.PhylOTU clusters sequences relative to a commonly adopted interpretation of taxonomy.A similar pattern is observed when the PD-based and PID-based OTUs are compared to OTUs constructed from GenBank taxonomy terms. Specifically, both methods accurately cluster the 508 full-length reference sequences at the species and genus level. Both methods also tend to underestimate the richness, though PID produces an estimate more in line with the taxonomy-guided clusters. Though this analysis serves as a useful benchmark, a more thorough investigation of richness estimation may be warranted in future work for several reasons. First, GenBank taxonomy terms do not necessarily recapitulate the true taxonomic signal or correspond to monophyletic clades. Second, there are known errors in taxonomic assignment and annotation of GenBank sequences PhylOTU to the Global Ocean Survey (GOS) metagenomic library. Previous characterizations of SSU-rRNA diversity found in the GOS library were limited to full-length sequences amplified via PCR and full-length contigs produced from high-confidence read assemblies PhylOTU clusters metagenomic reads into OTUs belonging to several Bacterial Phyla overlooked by the PCR-generated sequences. We were not able to detect the presence of completely conserved universal PCR priming sites for some of these sequences, which supports the theory that some faction of the microbial biosphere may be hidden from the view of PCR-based investigation. Deeper sequencing of either library could erode the signal of library-specific OTUs. Nonetheless, the distinct taxonomic composition of the metagenomic-only OTUs compared to the shared and PCR-only OTUs  masking columns that encoded over 75% gaps, 2) removing any sequence where over 15% of its characters corresponded to an insert state relative to the profile, 3) removing any sequence with over 50 internal (sequence bounded) gap characters, and 4) removing any sequence whose cmalign score per residue was less than 1  and generates a fully-resolved tree from which branch lengths can be extracted. Phylogenetic lineages representing full-length reference sequences were pruned from the trees and the total path length between all remaining pairs of lineages was used to create all-versus-all PD distance matrices. PD distance matrices were then queried by MOTHURQuality controlled alignments were subjected to phylogenetic analysis via PhylOTU's accuracy to increased phylogenetic diversity and read abundance.The 508 full-length RDP Bacterial reference SSU-rRNA sequences served as the pool for simulated data. Simulated reference data sets were generated by randomly sampling without replacement 423 of the RDP sequences. This was done five distinct times to create five different simulated reference data sets, or batches. For each batch, the remaining 85 full-length sequences were appropriated as source sequences. Simulated reads were generated from each batch of source sequences five times, resulting in five simulation sets for each of the five batches . To account for reads that run off the ends of the SSU-rRNA gene, we also created simulations, with the same settings, in which source sequences were concatenated to a 500-bp poly-N sequence pad at the 5′ and 3′ ends, before generating reads. We additionally created simulations from 1000 full-length Bacterial SSU-rRNA sequences drawn at random from the SILVA database MetaPASSAGE , which utilizes MetaSimPhylOTU through the alignment quality-control stage. Simulated reads that passed the quality-control filter were subjected to additional random subsampling to obtain data sets containing one simulated read per source sequence. For the simulations based on the reference sequence database, the remaining 35 source sequences, i.e., those sources not represented in the final set of simulated reads, were added back to the reference data set for that simulation.For a single simulation set, source sequences were used to simulate an average of 5 reads per source via PhylOTU. We assessed the extent to which the OTUs based on simulated reads recapitulated the OTUs based on full-length sequences as follows. We noted that two types of errors (relative to the full-length clustering) occur when partitioning the simulated reads into OTUs: they can be incorrectly grouped together in the same OTU , or they can be incorrectly separated into different OTUs . To specify the nature of these errors more precisely, let PhylOTU on input PhylOTU with input R is given byEach set of simulated reads and their corresponding full-length source sequences were independently partitioned into OTUs using and the rate of false disjunctions is given byNote thatR is a random quantity (generated by a stochastic process), so the quotients in Expressions (1) and (2) are random variables. The error rates of PhylOTU at the threshold values PhylOTU is given by one minus these error rates. PhylOTU algorithm outperformed the following clustering random algorithm:We checked whether the PhylOTU algorithm.Given a threshold value, partition reads into OTUs using the Randomly permute the OTU assignments of the read.PhylOTU algorithm; if not, a substantial deficiency in the PhylOTU algorithm would be indicated.We expected that this algorithm would have much higher error rates than the The weighted path difference metric relative PD errorwhere The normalization implies that PhylOTU is written in Perl and requires, in addition to the aforementioned software packages, various R packages plus Perl and BioPerl modules. A full list of requirements can be found on the software download website at github (https://github.com/sharpton/PhylOTU).Figure S1Example showing how false conjunction and disjunction rates are calculated. In the example, two samples of reads are possible, one consisting of reads A, B, C, D, and E, and another consisting of reads C, D, F, G, and H. In reality, the set of possible samples and reads would be much larger, but for simplicity, we have chosen this smaller set. For the purposes of this example, we suppose that the probabilities of observing samples I and II are 0.3 and 0.7, respectively. At the top of each panel in grey, the partitions into OTUs based on the full length sequences are shown, while the partitions based on the simulated reads are shown in blue. The conjoined and disjoined columns give the pairs of reads placed in the same OTU and different OTUs, respectively, for the partition based on the full-length sequences. The pairs highlighted in blue are correctly conjoined or disjoined in the sample partitions. The rates of false conjunction for Samples I and II are 3/4 and 1/2, respectively, while rates of false disjunction are 2/6 and 0, respectively. Because the probabilities of the samples are 0.3 and 0.7, the average rate of false conjunction is (0.3)(3/4)+(0.7)(1/2) = 0.575, and the average rate of false disjunction is (0.3)(2/6)+(0.7)(0) =  0.1. The average rates provide a useful characterization of a clustering algorithm under a given sampling scenario.(0.40 MB PDF)Click here for additional data file.Figure S2PD-based clustering is accurate relative to PID-based clustering. This graph illustrates the change in the True Conjunction Rate (solid line) and the True Disjunction Rate (dashed line) of full-length sequences clustered using PhylOTU and PD relative to the clustering obtained when the same sequences are clustered via percent identity (shown here is the PID cutoff of 0.03). Average-neighbor hierarchical clustering, the default PhylOTU setting, was used to generate these results.(0.09 MB PDF)Click here for additional data file.Figure S3Distribution of corresponding PD and PID pairwise distances. This figure illustrates the relationship between PD and PID distances (less than 0.2) calculated for all pairs of the 508 references sequences used in our study. The red line indicates identical distances estimated by PD and PID methods. The blue and green lines identify the clustering threshold distance of 0.03 for PD and PID, respectively. The mass of points above the red line for PD distances less than 0.03 indicates that among those pairs that are closely related as per the PD calculation, the PID method tends to estimate a larger corresponding distance (notably the points above the green line and to the left of the blue line). This observation could account for the difference in the estimated richness between the two methods. Conversely, when estimated PD distances are larger , the corresponding PID distance tends to be smaller. These observations are likely the result of how distances are calculated in the two approaches: PD leverages a weighted substitution model that down-weights similar substitutions and corrects for multiple substitutions, while the PID method weights all substitutions equally.(0.26 MB PDF)Click here for additional data file.Figure S4PhylOTU clustering of full-length sources and simulated reads is positively correlated. For each of the 25 RDP reference library-based simulations, we compared the source and simulation PD distance matrices produced by PhylOTU using a Mantel test. All 25 tests reveal a significant (p<0.05) and positive correlation coefficient. The above histogram reveals the distribution of the correlation coefficients identified through this analysis.(0.09 MB PDF)Click here for additional data file.Figure S5Derivation of methodological accuracy. Accuracy plots, which capture the change in the true conjunction and true disjunction rate as the simulated shotgun read clustering threshold increases relative to a fixed full-length sequence clustering threshold, were generated for several full-length sequence thresholds. We show here the accuracy plot of the source threshold of 0.03 as an example. The median true clustering and true cutting rates are represented by the solid and dashed black lines, respectively. The red line indicates the minimum tolerated accuracy, which we designate to be 80%. The most accurate read threshold is indicated by the solid blue line, which represents the point where the true clustering rate is controlled at the minimum accuracy and the true cutting rate is maximized. At least three interpretations of an optimal thresholds could be identified from this analysis, contingent upon the application: 1) the threshold where the true conjunction rate (TCR) is fixed at a controlled minimum accuracy and the true disjunction rate (TDR) is maximized, 2) the threshold where the TCR and TDR intersect, and 3) the threshold where the TDR is controlled and the TCR is maximized. The standard hypothesis testing approach is to control the type I error, which corresponds to controlling the TCR in this analysis  and resu(0.11 MB PDF)Click here for additional data file.Figure S6Relationship between full-length sequence clustering threshold and adjusted shotgun read clustering threshold. The relationship between full-length clustering thresholds and the corresponding shotgun read clustering threshold that maximizes the True Disjunction Rate while controlling the True Conjunction Rate is plotted in black. Specifically, this curve represents a loess smoothing of the most accurate thresholds we identified from the reference library-based simulation analyses across a series of full-length sequence clustering thresholds using the procedure described in (0.08 MB PDF)Click here for additional data file.Figure S7Change in accuracy as the full-length sequence clustering threshold increases. The accuracy of clustering reads via an adjusted threshold (black line) remains high, even at relatively large full-length sequence clustering thresholds. The solid red line represents the minimum tolerated True Conjunction Rate (TCR) of 80%.(0.07 MB PDF)Click here for additional data file.Figure S8Accuracy with which PhylOTU clusters shotgun sequences simulated from the SILVA database relative to a full-length cutoff of 0.03. We used the SILVA-based simulation data to construct accuracy plots as described in (0.11 MB PDF)Click here for additional data file.Figure S9The clustering threshold affects the rate of discovery of unique and non-unique OTUs per sequence. We randomly sampled 1000 sequences from the PCR (blue lines) and shotgun (red lines) sequence libraries and counted the total number of distinct OTUs (solid lines) as well as the number of OTUs unique to each sequence library (dashed lines) identified by the sample across clustering thresholds (100 bootstraps). In regards to the total number of OTUs identified by each library, this analysis reveals that the number of OTUs discovered per sequence depreciates at similar rates in both libraries as the threshold increases. Conversely, we find that the rate of change of unique OTU discovery is not consistent between libraries: more unique OTUs per sequence are discovered in the PCR-generated sequence library at thresholds below 0.05, while the inverse is true at thresholds greater than or equal to 0.05. Notably, the number of unique OTUs per PCR sequence declines as the threshold increases at a rate similar to the total number of OTUs discovered per PCR sequence. This is not the case with shotgun data, where the slope of the unique OTUs discovered per read is much flatter. This may be the result of the increased phylogenetic diversity discovered in the shotgun library and suggests that PCR sequences tend to contribute less unique phylogenetic branch length than shotgun reads.(0.09 MB PDF)Click here for additional data file.Figure S10Partial alignment of shotgun sequence from uniquely metagenomic OTUs that overlap a universal SSU-rRNA primer site. Of those sequences that cluster into OTUs that are uniquely identified via analysis of shotgun sequence data (clustering threshold of 0.15), 18 overlap a universal SSU-rRNA primer site in the alignment. Here, we show the result of aligning those 18 sequences as well as the 8F and 27F primers to the INFERNAL SSU-rRNA model used in PhylOTU. We find that two sequences contain a shared C->T substitution that differentiates them from all other sequences in the alignment (red column) directly adjacent to the degenerate site in the 27F primer sequence (blue column). Incorporation of a degenerate base at this position in the universal primer sequence may enable more rigorous characterization of those lineages that harbor this C->T transition.(0.02 MB PDF)Click here for additional data file.Table S1Hierarchical clustering algorithms affect both clustering accuracy and richness estimates. Full-length SSU-rRNA sequences were clustered via both PID and PD approaches using three difference linkage definitions in the hierarchical clustering algorithm: nearest-neighbor (nn), average (avg), and furthest-neighbor (fn). Here, we show the results of comparing each the PD clusters (threshold of 0.03) to each of the PID clusters (threshold of 0.03) using the True Conjunction Rate (TCR) and True Disjunction Rate (TDR) calculations described in the (0.02 MB DOC)Click here for additional data file.Table S2Both PID and PD clustering accurately recapitulates taxonomy-guided clusters. Full-length reference sequences were clustered based on their GenBank taxonomy at the species level. These same sequences were then clustered using both the PID and PD methods by employing a distance threshold of 0.03 across three hierarchical clustering algorithms: nearest-neighbor (nn), average-linkage (avg), furthest-neighbor (fn). Each of the PID and PD clusters were compared to the taxonomy guided clusters using the True Conjunction Rate (TCR) and True Disjunction Rate (TDR) calculations described in the (0.02 MB DOC)Click here for additional data file.Table S3Accuracy of adjusted shotgun read clustering cutoff relative to full-length clusters when controlling the true conjunction rate and maximizing the true disjunction rate (TDR). Data was obtained from the RDP reference library-based simulations.(0.02 MB DOC)Click here for additional data file.Table S4Accuracy of adjusted shotgun read clustering cutoff relative to full-length clusters when controlling the true conjunction rate and maximizing the true disjunction rate (TDR). Data was obtained from the SILVA-based simulations.(0.02 MB DOC)Click here for additional data file.Table S5Taxonomic distribution of OTUs identified via comparison of GOS PCR-generated and shotgun-generated SSU-rRNA sequences. This table documents the frequencies at which major Bacterial taxonomic clades  were represented by sequences clustered into three different sets of OTUs identified by PhylOTU: those unique to PCR-generated SSU-rRNA (PCR), those unique to shotgun sequenced SSU-rRNA (WGS), and those reveal by both sequence libraries. The RDP taxonomy classifier was used to determine the classification of each sequence in question. Major Bacterial clades were excluded from this table if their frequency was not greater than or equal to 0.1% in at least one of the three sets of OTUs.(0.02 MB DOC)Click here for additional data file.Text S1Alignment quality control filters.(0.01 MB DOC)Click here for additional data file.Text S2MetaSim run time setting used during the PhylOTU simulation analysis.(0.01 MB DOC)Click here for additional data file.


Raw materials are a critical part of any cell culture medium; therefore, it is of utmost importance to understand and characterize them for high-quality product. The raw material characterization (RMC) program at SAFC focuses on individual screening of raw materials both analytically and biologically. The goal of the program is to develop the best-in-class knowledge base of the raw materials used in SAFC’s media formulations and their impact on performance of products. A prioritized list of 100 “high-risk” raw materials was developed based on a risk assessment performed within SAFC. This poster will focus on the analytical screening of certain “high-risk” raw materials within the prioritized list to identify any variability and critical contaminants present. In order to achieve this, orthogonal methods were used that include ultra-high performance liquid chromatography-mass spectrometry (U-HPLC/MS) for non-volatile polar components and gas chromatography-mass spectrometry (GC/MS) for volatile non-polar materials. Inductively coupled plasma-optical emission spectrometry (ICP-OES) was also used to identify any trace metal contamination present. In addition, the solubility of the raw materials is also tested to identify any variability within a vendor or between different vendors.Figure The orthogonal methods cited to characterize raw materials have proven to be robust and reliable for the intended purpose. The solubility experiment described for amino acids illustrates a significant difference in solubility limits of amino acids and establishes intra- and inter-vendor variability. This program has helped SAFC get better insight into their suppliers’ manufacturing processes. This is a long term initiative within the organization and the most important goal through the program is to develop a better understanding of raw materials to deliver superior products of the finest quality.


Rat middle cerebral artery occlusion (MCAO) model is the most commonly used animal model in ischemic stroke studies. In the model, to increase the amount of stem cells or drugs to enter the brain after delivery into the internal carotid artery (ICA), the pterygopalatine artery (PPA) is occluded. However, PPA occlusion is a technically demanding procedure which often causes complications.In this study, we developed an ICA injection needle to facilitate easy and efficient delivery of stem cells to the ischemic brain through the ICA without the need of PPA occlusion. We injected methylene blue and fluorescence dye DiI-labeled human mesenchymal stem cells (DiI-hMSCs) into the ICA in rats with the ICA injection needle (without PPA ligation) or the conventional micro-injection needle (with PPA ligation) and assessed their distributions.When methylene blue was injected, evident blue stains were found in the brain of the injection side particularly the middle cerebral artery (MCA)-supplied areas but not in the PPA supplied areas. Similarly, when DiI-hMSCs were injected, the cells largely appeared in the MCA-supplied tissues, which were similar in quantity compared to conventional micro-injection needle injection with PPA occlusion. Moreover, hMSCs injected with the ICA needle or the micro-injection needle similarly improved the functional recovery of the infarcted brain.Our results indicate that the ICA injection needle is easy to use and efficient in delivering cells to the ischemic brain tissue in rat MCAO model. Stroke is a leading cause of death and disability. Stem cells have demonstrated profound potential in the repair and regeneration of the injured brain tissue . The theRat ischemic stroke models have been used extensively to evaluate the benefit of stem cells and to study the underlying mechanisms. Since ischemic stroke in patients is mostly caused by the occlusion of the middle cerebral artery (MCA), intraluminal suture MCA occlusion (MCAO) has become the most commonly used model in the investigation of stroke in rodents . The revIn this study, we developed an ICA injection needle according to the anatomic features of the ICA and the PPA. The needle has a closed end to occlude the PPA and a lateral opening to deliver stem cells into the ICA. We tested the needle by injecting methylene blue and fluorescence dye DiI-labeled human mesenchymal stem cells (hMSCs) into the ICA in rats and assessing their distribution. Our results showed that no blue stain was found in the PPA-supplied regions and similar amounts of DiI-hMSCs appeared in the MCA-supplied brain tissues compared to the PPA occlusion technique.The ICA injection needle is similar to a regular syringe needle, but has several modifications. The needle is 3.0 to 4.0 cm long, with external diameters of 0.3 to 0.5 mm. The tip of the needle is blunt and closed ended. At 5 mm from the tip, there is a 27G opening, which serves as the exit of injected materials through the needle Figure A. The frThe ICA injection needle was designed based on the anatomic structure of the ICA and the PPA in rats Figure B-C. In rThe ICA injection needle was inserted into the ICA from the external carotid artery. First, the external carotid artery was ligated with a nylon suture and nicked at a 45-degree angle. Then the external carotid artery was pulled to make it straight to the ICA Figure A. The neFemale Sprague–Dawley rats  were used in the study. Rats were maintained in a temperature controlled environment (20 ± 1°C) with access to food and water throughout the experiment. All procedures were performed with the approval of the Animal Ethics Committee of Tsinghua University.After anesthesia with 10% chloral hydrate  injection, Sigma-Aldrich), rats were subjected to transient focal ischemia for 120 minutes by the intraluminal suture technique as described previously [Rats were divided into three groups and each group had four animals. In group 1, the PPA was ligated with a 6–0 silk suture. A total of 200 μl methylene blue  was injected with a 30G micro-injection needle (Hamilton) into the common carotid artery with preserved flow in the common carotid artery and ICA. In group 2, 200 μl methylene blue was injected with the ICA injection needle into the internal carotid artery. The needle was inserted into the ICA from the external carotid artery stump and advanced towards the head of the rat, so the closed-ended needle tip was inserted into the PPA to occlude the PPA, thus preventing the methylene blue from entering the PPA, and the methylene blue was delivered into the ICA via the lateral opening of the needle thus facilitating its entry into the brain. In group 3, the ICA was ligated. A total of 200 μl methylene blue was injected into the PPA with a micro-injection needle. Rats were scarified immediately after injection of methylene blue. The skin of the head was removed to observe the distribution of methylene blue in facial tissues. Then the brain was exposed to observe the distribution of methylene blue. Finally, coronal sections through the brain were cut into seven equally spaced blocks  to examine methylene blue distribution inside the brain.Human MSCs were isolated and characterized in our laboratory as previously described . Briefly4 cells was counted. Thirty microscopic fields were randomly selected (10 fields/group).Immediately after cell transplantation, the left hemisphere of the brain of the rats was removed carefully and the cerebral tissues were cut into six equally spaced (2 mm) coronal blocks. Fresh tissues of the third block were weighed, ground in a cell strainer and washed with a digestion buffer (0.1% trypsin-ethylenediaminetetraacetic acid (EDTA)) to generate a single cell suspension. DiI-hMSCs were visualized under a fluorescence microscope and the number of hMSCs per 10The left hemisphere of the brain was removed carefully on day 7 after cell transplantation and the cerebral tissues were cut into six equally spaced (2 mm) coronal blocks. The fourth block was fixed in 4% paraformaldehyde (PFA), embedded in optimal cutting temperature compound (OCT) and cut into 10-μm-thick sections, which included the MCA perfused territory. Tissue sections were visualized under a fluorescence microscope for the presence of DiI-hMSCs and representative fields were photographed. For quantification of DiI-hMSCs in the ischemic boundary zone, cells positive for DiI per microscopic field (×200) were counted, and 10 fields per tissue section were randomly selected. Three tissue sections per sample were examined (n = 4).Rats were subjected to a modified Neurological Severity Scores (mNSS) test at 0, 1, 3, 5, 7, 9, 11 and 14 days of MCAO as described previously [P) value <0.05 was considered significant.All data were expressed as mean ± standard deviation (SD). Results were analyzed using one-way or repeated measures analysis of variance (ANOVA) with independent variables of treatment groups and days of testing, followed by the Bonferroni post-hoc test for multiple comparisons between treatment groups at each time point. A probability . To further quantify the number of the DiI-hMSCs in the brain, equal amounts of brain tissues around the infarct (immediately after cell transplantation) were digested into single cell suspensions, and the number of DiI-positive cells was counted under a fluorescence microscope [see Additional file To further examine whether the ICA injection needle could efficiently deliver stem cells to the damaged brain without PPA ligation, we compared the number of DiI-hMSCs in tissue sections of the MCA-supplied region of the brain in rats with MCAO seven days after cell injection. Similar amounts of DiI-hMSCs were found in the brain of rats injected with the conventional micro-needle plus PPA ligation or with the ICA needle without PPA ligation, but many fewer DiI-hMSCs were found in the brains of rats injected with a conventional micro-needle without PPA ligation . However, at 11 and 14 days post MCAO, rats that had received hMSCs via the conventional micro-needle plus PPA ligation or the ICA needle exhibited significant improvement in neurological function as indicated by the mNSS compared to rats that received only the PBS injection . There were no significant differences in mNSS between rats injected with the conventional micro-needle plus PPA ligation and rats injected with the ICA needle .The severity of neurological defects was evaluated in rats with MCAO after transplantation of hMSCs using different methods. Prior to MCAO, mNSS scores indicated that there was no neurological defect in any of the rats. One day after MCAO and before MSC transplantation, no significant differences were found in mNSS score among the groups MEM: (Dulbecco’s) modified Eagle’s medium; CCA: Common carotid artery; DiI: 1, 1′-dioctadecyl-3, 3, 3′, 3′-tetramethylindocarbocyanine perchlorate; DiI-hMSCs: DiI-labeled human mesenchymal stem cells; ECA: External carotid artery; ICA: Internal carotid artery; MCA: Middle cerebral artery; MCAO: Middle cerebral artery occlusion; mNSS: Modified neurological Severity Scores; MSCs: Mesenchymal stem cells; PBS: Phosphate-buffered saline; PPA: Pterygopalatine artery.The authors declare they have no competing interests.LG conceived and designed the study, prepared the MCAO model and injections, provided animal care and performed data acquisition, analysis and manuscript writing and revision. JFG provided animal care and performed data acquisition. SW performed the isolation and expansion of MSCs. YZ and XXW performed sample preparation, data entry and manuscript writing. The study was conducted in the laboratory of YJW and he was responsible for supervision of the study and manuscript writing and revision. All authors read and approved the final manuscript.The distribution of methylene blue in coronal sections of the brain. (A) Injection of methylene blue into the ICA with a micro-injection needle after ligation of the PPA. (B) Injection of methylene blue into the ICA with an ICA injection needle without PPA ligation. (C) Injection of methylene blue into the PPA with a micro-injection needle.Click here for file6 DiI-hMSCs were injected into the left ICA with a micro-injection needle plus PPA ligation (Mi-N), the ICA injection needle without PPA ligation (ICA-N) or a micro-injection needle without PPA ligation (PPA) in rats with left MCAO. Immediately after cell transplantation, a block of the cerebral tissue in the left MCA-supplied territory per rat was harvested and digested into a single cell suspension, which was subjected to analysis under a fluorescence microscope for the presence of DiI-hMSCs (red) in each field. (A) A representative microscopic field from each group is shown. Nuclei were stained with Hoechst (blue). (B) Quantitation of DiI-hMSCs in the single cell suspensions of a given amount of tissue (n = 4).hMSCs distribution. 10Click here for file


The assessment of physiotherapy various models to the clinical examination results – short-term observation during the stationary intensive rehabilitation.Thirty-five girls with AIS double major  were divided for two randomized groups. In group A was applied only standard DoboMed .In-group A-plus was applied triple method . The derotation manual therapy techniques and Meditrac were used in DoboMed preparation phase. Meditrac was used only in the part of lumbar spine once a day during 30 minutes. The stationary intensive rehabilitation for both groups have been continued during 3 weeks.Before and after observation have been analyzed: the respiratory system function , the strength of respiratory muscles , the trunk morphology and function .MIP and spine flexion values were increased significantly in both groups during therapy. In the group A-plus was observed more significant changes of parameters. Increasing of PEF, kyphosis, spine extension and lateral flexion values and decreasing of ATR were observed.In the short time were observed functionally and morphology improvement in-group of patients treated by DoboMed with OMT Kaltenborn-Evjenth and Dynamic Brace System –Meditrac. These additional methods have been used successfully in DoboMed preparation phase for AIS double major patients.


Drosophila presents features conserved in its mammalian counterparts. InR is required for growth; it is expressed in the central and embryonic nervous system and modulates the time of differentiation of the eye photoreceptor without altering cell fate. We show that the InR is required for the formation of the peripheral nervous system during larval development and more particularly for the formation of sensory organ precursors (SOPs) on the fly notum and scutellum. SOPs arise in the proneural cluster that expresses high levels of the proneural proteins Achaete (Ac) and Scute (Sc). The other cells will become epidermis due to lateral inhibition induced by the Notch (N) receptor signal that prevents its neighbors from adopting a neural fate. In addition, misexpression of the InR or of other components of the pathway  induces the development of an abnormal number of macrochaetes that are Drosophila mechanoreceptors. Our data suggest that InR regulates the neural genes ac, sc and sens. The FOXO transcription factor which is localized in the cytoplasm upon insulin uptake, displays strong genetic interaction with the InR and is involved in Ac regulation. The genetic interactions between the epidermal growth factor receptor (EGFR), Ras and InR/FOXO suggest that these proteins cooperate to induce neural gene expression. Moreover, InR/FOXO is probably involved in the lateral inhibition process, since genetic interactions with N are highly significant. These results show that the InR can alter cell fate, independently of its function in cell growth and proliferation.The Insulin Receptor (InR) in  Each organ grows by controlling cell number and cell size to reach its final dimensions. This process is tightly regulated and modulated by environmental factors such as nutrient availability.Drosophila insulin pathway is highly conserved from mammals to Drosophila. In Drosophila the InR regulates a number of functions linked to metabolism, organ growth, cell number and cell size, and mutants of the pathway present size defects The The InR pathway described extensively in dilp1–8, for Drosophila insulin-like peptides (DILP). dilp2 is the most closely related to mature insulin and is the only DILP with broad expression in imaginal discs. Overexpression of dilp2 increases both cell number and cell size of different organs Extracellular ligand homologues to insulin regulate InR activity during development. Eight genes have been identified, FOXO mutant lacking Akt phosphorylation sites, remains in the nucleus, and is constitutively active. This is the case of the human 3a-TMhFOXO mutant, which induces growth arrest in Drosophila when overexpressed, by specifying cell number but not cell size 4E-BP and InR that are regulated by FOXO, confirming that FOXO is a transcriptional regulator in different developmental processes A major component of the insulin signaling cascade, the transcription factor FOXO is phosphorylated by Akt leading to its cytoplasmic localization and thus inhibition of its transcriptional activity. The S6K mutants display developmental delay and reduction in body size with smaller cells. Thus the InR/TOR pathway is finely tuned to be particularly sensitive to nutrients and environmental changes. This is achieved by different intracellular feedback loops . ck loops . AnotherDrosophila, indicating that InR is required for temporal control of development It has been shown that the InR/TOR pathway plays a role in controlling timing of neural differentiation, and that activation of this pathway leads to the precocious acquisition of neuronal cell fate, whereas loss of function delays differentiation but does not alter cell fate. This was observed in photoreceptor formation but also in the chordotonal organs of the leg of InR null homozygote embryos are defective in the central and PNS ac and sc and form the proneural field. These genes play a key role in the process and allow the cluster to become competent to become a SOP. Inactivation of the genes induces disappearance of some of the macrochaetes while ectopic expression leads to additional bristles. ac and sc are at the top of the hierarchy of genes involved in macrochaete formation. The SOP is selected from a few cells that accumulate higher concentrations of the proneural proteins (Ac/Sc) than their neighbors and occupy stereotyped positions within the proneural cluster. Cell-cell signaling within the cluster is mediated by N in one cell and Delta (Dl), the ligand, in the other cell The EGFR signaling pathway plays an important role in macrochaete formation and is activated at different stage of the sensor organ development. The EGFR and Ras which transduces the pathway , positiv4E-BP.Here we have investigated the function of the InR/FOXO pathway in bristle development and show that InR and FOXO are necessary for SOP determination, independently of the InR function in growth. A combined role of the EGFR/Ras pathway with the InR pathway is postulated. However the TOR pathway does not seem to be involved in the process suggesting that InR/FOXO acts on other target genes than on ac, senseless (sens) and several enhancers of sc show that the InR increases the number of SOP in the proneural field independently of its role in cell proliferation, by regulating ac and sc expression. This is confirmed by genetic interactions between the InR/FOXO and both sc and N. The results indicate that the EGFR/Ras pathway could cooperate with InR/FOXO in this process.The results obtained examining the expression of InR null mutants are mostly lethal at the homozygote state and the few escapers do not show a phenotype at the level of the PNS, we tried to generate null clones, but the clones recovered were usually very small or absent y,w Ubx-Flp; FRT82B), FRT82B, EX15dInR, which is an InR null allele. Flies lacking macrochaetes mainly DC macrochaetes were obtained  DC and (a) SC. Overexpression of InR RNAi, driven by sca-GAL4 (scabrous and designated here sca>InR RNAi), in the proneuronal cluster led mainly to lack of SC macrochaetes (DNInR strain driven by sca-GAL4 resulted in the absence of both (a) DC and (a) SC macrochaetes (Since obtained . To moniochaetes . The InRochaetes .sca-GAL4. Different constructs were used: the WTUAS-InRexelUAS-InR (exelexis), and an activated form actUAS-InRWTUAS-InR construct  led to the most spectacular phenotype (decapentaplegic (dpp)-GAL4 was used, ectopic SC macrochaetes could be detected , additional aSC macrochaetes appeared at 25°C  significantly suppresses the InR phenotype  increase in the number of macrochaetes is observed compared to the overexpression of InR only  regulatory sequences. Excess aSC macrochaetes were observed with sca>UAS-FOXO RNAi (pnr>UAS-FOXO RNAi mainly extra microchaetes were detected (EX15/ FOXO21InR is completely wild type (data not shown). However, we constructed a double homozygote strain null both for InR and FOXO that displays at times an excess but generally a lack of macrochaetes  or in apoptosis  were tested by overexpression experiments alone or also with overexpression of InR. No significant interactions were observed  putting the strain at the permissive temperature every 8 hours. The results show that InR acts at an early stage, at the end of the second instar and early third instar just prior to SOP formation (data not shown).To examine at what stage the InR activates genes involved in PNS formation, tests were undertaken using a At this stage, proliferation induced by the InR is very low and no significant difference in wing disc size is observed with and without induction of the receptor.InR was overexpressed in the dpp domain. Wing discs were stained with Ac antibodies to identify the proneural clusters, and stained with Sens antibodies to detect SOPs.To visualize the effect of InR and FOXO on SOP formation and proneural gene expression Acquired confocal images were used to visualize expression of Ac and Sens '. A signInR was overexpressed. No staining was observed at the end of the second larval instar. In early wild type and InR overexpressed larvae third instar (35–40h before puparium formation (BPF)) the cluster marked with Ac was clearly stained with higher Ac staining in the future SOP. No Sens staining was observed. No differences between the two strains were observed , of sca>InR, of 3a-TM,sca>hFOXO of 3a-TMsca>Inr, hFOXO and of sca>FOXO RNAi genotypes and stained mid third instar wing discs with Ac and Sens antibodies. The number of Ac and Sens-cells corresponding to each genotype were quantified on confocal images .To better understand the effect of InR and FOXO on SOP formation we estimated the size of the proneuronal cluster in third instar larvae of the l images , 6A. Whesca>InR provides an estimation of the rate of proliferation of these cells, and of the decrease when FOXO is overexpressed. Were proliferation to only explain the increase of bristle number in sca>InR, the increase in the number of Ac and of Sens-positive cells should be comparable. This is not the case and the increase in Sens-positive cells is much higher than would be expected if only proliferation were to account for the phenomenon. The number of cells expressing Ac is fairly similar in the control strain and in the UAS-InR,sca-GAL4 genotype, but the ratio of the number of Sens-expressing cells over Ac-expressing cells increased by 543% for DC and by 254% for SC when InR was overexpressed  antibodies in mid third instar larvae . Quantification of the number of voxels in each cell for the two fluorochromes (Cy3 and Cy5) corresponding to Ac and Sens expression was performed . Once the background had been subtracted, 3 different levels of intensity were arbitrarily chosen from 105 to 107 intensity units per cell. 5 intensity unit per cell, Ac or Sens staining are physiologically significant. So far it had been shown that Sens is highly expressed in 2 SOPs in DC macrochaetes and in 2 SOPs in SC macrochaetes in the third larval instar sca>GFP). Looking at the numbers  was identical for the two strains at this stage. In addition most of these 3.8 kb sc-lacZ were also Sens positive, and represent potential SOPs  antibodies that marked pIIb cells. tsUAS-InR,tub-GAL80 flies were used and InR was induced at the mid second instar. In wild-type wing discs, no Pros staining could be detected at the level of either DC or SC SOPs in late third instar larvae (data not shown). Staining appeared only in early pupae. On the contrary in sca>InR both DC and SC were marked, and in mid third instar larvae, Pros staining was already detected in DC SOP . Female heterozygotes for 10-1sc presented a normal number of macrochaetes   , as prop1sc males are viable and present normal DC macrochaetes but lack some aSC and almost all pSC macrochaetes , but in addition, the number of DC macrochaetes was significantly increased  not only in the 55e11/+N females but also compared to the overexpressed InR in an +N genetic background (p<0.001). Moreover in sca>InR RNAi (p<0.001) a significant increase of aSC macrochaetes was observed in the 55e11/+N background. Surprisingly, the knock-down of InR in the N heterozygotes similarly caused enhanced bristle formation, indicating that manipulation of InR signaling in a N sensitized background can have counter intuitive effects and that the integration of N and InR signaling is likely complex. These interactions could indicate that InR can accentuate the neurogenic phenotype of the N mutant perturbing lateral inhibition. In parallel, underexpression of FOXO either in sca>FOXO RNAi or in a 25/+FOXO heterozygote background, induced, as does InR, a very significant increase in the neurogenic phenotype at the level of the aSC macrochaetes  compared to 3a-TMsca>hFOXO in a wild type background. However, surprisingly, overexpression of InR RNAi increases the number of aSC macrochaetes.Moreover in InR and FOXO interact genetically both with sc and N. Nevertheless, the possibility that the effect of the InR/FOXO pathway on N might indirectly be the consequence of the action of these genes on sc expression, can be postulated.These results strongly suggest that EGFR mutants display a decrease of DC macrochaetes but sometimes macrochaete duplication is observed EGFR, overexpressed in sca sequences sc loop The EGFR and the Ras/Raf pathway are involved in PNS formation. EGFR RNAi transgene were overexpressed with sca-GAL4, few duplications of aSC and aDC macrochaetes were observed  in the number of cells positive for Ac. If the possibility that proliferation is somehow involved in cluster size cannot be discarded, it does not account for the effects observed since the ratio of Sens-positive cells when InR is overexpressed over the control strain is much higher than the ratio of Ac-positive cells. A similar role for FOXO in apoptosis could also be discarded on the same basis. No clear interactions were observed between FOXO and genes involved in inhibition of apoptosis like 1diap.Several arguments indicate that the phenotypes observed when sca>InR strain.Along the same line it has been shown by Bateman sca>InR; this is not observed in the control strain. In addition in sca>FOXO RNAi wing discs it also leads to Pros staining. This indicates that the time of differentiation is advanced in the InR strain through the absence of nuclear FOXO. However we verified that in very early third instar larvae the first scutellar SOP appears at the same time in the control and in the overexpressed strains and that no differences were observed in mid third instar.Using Pros staining that marks pIIb cells, we show that staining appears in the late third instar larvae at the level of DC SOPs in sca>InR is independent of the TOR pathway since none of the members induces a similar phenotype as does InR or interacts either with InR or FOXO in this process  induce exactly opposite phenotypes. This is also true for overexpression experiments with InR and 3a-TMhFOXO. Moreover overexpression of both transgenes leads to an intermediate phenotype, very different from the control phenotype  When InR is overexpressed the level of Ac is significantly higher. This is confirmed by the IMARIS technique that estimated that in this genotype, the number of cells with the highest scores (106 and 107 units) is larger than in the control strain. These “highly Ac-positive cells” seem to also be Sens positive cells indicating a correlation between the two events. (iii) In sca>InR the level of Sens, measured by the IMARIS technique is higher than in the test raising the possibility that InR regulates several neural genes independently. However another possibility would be that this high Sens expression level would be indirectly due to the induction by InR of a Sens-positive regulator such as sc. (iv) Several sc enhancers are regulated by InR, the sc promoter, and the SRV and DC enhancers. As sc is auto-regulated through its different enhancers, it is difficult to evaluate if a specific enhancer is involved although the effect on the 3.8 kb sc promoter is the most striking  Overexpression of both InR and sc leads to a significant increase in the effect of a single transgene. This indicates that both transgenes have a common target; one of them could be sc itself. An opposite effect is observed with 3a-TMhFOXO. This favors the model whereby InR and FOXO act in opposite ways on the sc target in SOP formation. (vi) Highly significant genetic interactions are observed between sc and InR, and sc and FOXO. (vii) Another gene charlatan (chn) which is both upstream and downstream of scInR (data not shown).Several relevant arguments exist suggesting that InR is necessary for SOP formation and regulation of neural gene expression. (i) The phenotype of the overexpression experiments either with Table in . For FOXN is mutated, cell fate changes and extra macrochaete singling appear. Using the N deletion (55e11N) to test possible genetic interaction with InR and with FOXO in heterozygote females, interaction was observed with the InR RNAi strain. Moreover strong interaction is observed with InR overexpression. This indicates that InR impairs lateral inhibition and cooperates with N in this process. In parallel, as for Inr overexpression, the absence of nuclear FOXO either using 25FOXO homozygotes (or even heterozygotes) or FOXO RNAi overexpression induces an increase in the neurogenic phenotype. With this latter strain, tufted microchaetes were observed, indicating that FOXO could also act later in development ) which transduces the N pathway, is expressed with or without the EGFR mutants and EGFR null clones display macrochaete phenotypes EGFR hypomorphic mutants the level of Sc is reduced in some clusters and increased in others suggesting a different requirement of EGFR for the different SOPs V12Ras was overexpressed with an ubiquitous driver, sc was ectopically expressed Strong genetic interaction exists between the InR and the EGFR/Ras pathways. EGFR has also been implicated in macrochaete development argos, rhomboid and pointedsc in a synergic manner and this further overrules the lateral inhibition mechanism induced by N. The fact that overexpression of V12Ras in an InR null heterozygote background significantly lowers the phenotype observed with V12Ras only, is in agreement with this hypothesis. The interactions observed with the EGFR RNAi strain seem to be FOXO independent  and MD237-GAL4pnr (a gift of F. Schweisguth UAS-WTInRUAS-exelInR (exelexis), UAS-DNInRUAS-PTEN RNAi, UAS-EGFR RNAi, UAS-raptor RNAi, UAS-Rheb RNAi, UAS-diap1 and UAS-GFP (used as driver control) lines as well as the 55e11N and s1c or s10-1c mutants were from the Bloomington Stock Center. Other RNAi lines, UAS-InR RNAi, UAS-PTEN RNAi, UAS-FOXO RNAi and UAS-4E-BP RNAi, were from the Vienna Drosophila RNAi Center (VDRC) Stock Center. The UAS-dFOXO A and UAS-dFOXO B were already described UAS-3ahFOXOTM-UAS-dilp2UAS-dAkt121dFOXO and 25dFOXO mutants UAS-Tsc1, UAS-Tsc2UAS-S6KUAS-E2F-DP,UAS-P35SRV-lacZDC-lacZ (a gift of P. Simpson). The UAS-EGFRUAS-V12Ras3.8kb sc-lacZFruit flies were raised on a standard InR activates genes involved in PNS formation, InR overexpression was performed using a strain bearing tub-tsGAL80 (Bloomington Stock Center), the tub-ts,UAS-InRGAL80 line, that we crossed with the sca-GAL4 driver strain. Fly crosses, embryonic and larval development were carried at 21°C, and larvae at different stages were transferred to 29°C to allow the expression of GAL4. Somatic clones were obtained using the FLP/FRT recombination system ex15FRT82B-InR line y,w; Ubx-FLP; FRT82B-ubi-nls::GFP  on fly hemi-thoraces was counted at each position on the notum. The results were divided into 6 classes, and the average for each position is presented. As some values were small and some null, we chose the Fisher Exact Test to calculate p-values, with the “R” programming language. The letters indicate the strains that are compared. Different colors are used: blue letters for 0.05<p<0.01, red letters for 0.01<p<0.001, and black letters for p<0.001.Imaginal disc dissections were performed on wandering 3rd instar larvae in phosphate-buffered saline (PBS). Discs were kept on ice until fixation in 4% paraformaldehyde in PBS Primary antibodies were used at the following dilutions, monoclonal anti-Ac (mouse) 1:5, (DSHB); polyclonal anti-Sens (guinea pig) 1:3000, gift of H. Bellen; polyclonal anti-PH3 (rabbit) 1:500, (Upstate Biotech); monoclonal anti-β-Gal (mouse) 1:200 (DSHB). Fluorescence FITC, Cy3 and Cy5 (1:200) conjugated anti-rabbit, anti-guinea pig or anti-mouse secondary antibodies were purchased from Jackson Immunoresearch Laboratories. Stained specimens were mounted in Citifluor AF1 solution (CITIFLUOR Ltd) antifade Reagent and images were obtained with an LSM 710 confocal microscope. Images were processed with ImageJ and Photoshop.To score the differences in the level of Ac and Sens expression between the genotypes, a relative quantification on confocal-acquired images was performed after immunofluorescence labeling conducted simultaneously. Images were made on an LSM 710 confocal microscope with a 40x objective and a Z step of 0.5 µm for a correct sampling. Three dimensional representations of confocal image stacks were generated using the software package, Imaris . After the confocal image stack was loaded into Imaris, intensity threshold for each channel was adjusted. The 3D images generated made it possible to identify cells and quantify the number of voxels in each cell for two fluorochromes (Cy3 and Cy5) corresponding to Ac and Sens expression. Quantity generated of signal measured in cells located next to the cluster was considered as background, and was eliminated from the intensity of the signal scored in each cell in the SC or DC clusters.Supporting Information S1Details of . The number of the four kinds of macrochaetes (expressed as percentage) are detailed. The numbers go from zero to five and more. (XLS)Click here for additional data file.Supporting Information S2(A) An InR overexpressed clone in a FOXO null background. Tufted chaetes were observed that are never detected in a FOXO wild-type background. (B) The same genotype induces a much stronger phenotype on the thorax that only InR overexpression. (C)sca>EGFR thorax at 25°C. Some supernumerary macrochaetes were observed. In (D) both EGFR and InR were co-overexpressed. A significant increase in macrochaetes is observed compared to a single transgene either EGFR or InR. (E)sca>E2F-DP,GFP flies. No effect is observed on the thorax. Additional very thin macrochaetes are detected on the scutellum due to proliferation. (F)sca>InR,Dap thorax. The cross is lethal; the picture represents pupae. The number of supernumerary macrochaetes is comparable to overexpression of InR alone. (G)sca>InR, DIAP genotype. No effect is observed. (H)21/FOXO25FOXO flies at 25°C. A supernumerary macrochaete is detected. A similar phenotype could also be observed in heterozygotes (see otes see .(TIF)Click here for additional data file.Supporting Information S3 or with Sens and Ac  of the sca>GFP (control)  or sca>InR genotype . No major differences between A and B. Overexpression of InR does not cause earlier Sens expression. At a later larval stage (20 h BPF) (C–D'), the number of SENS expressing cells in SC and DC clusters is much higher in sca>InR genotype  than in sca>GFP.SC and DC clusters  stained with Sens (TIF)Click here for additional data file.Supporting Information S4Quantification of the level of Ac and Sens per cell in DC and SC clusters by the IMARIS technique. In sca>GFP) and the sca>InR genotype were evaluated. The Figure presents the number of cells in each cluster containing >105; >106; >107 intensity units/cell.(TIF)Click here for additional data file.Supporting Information S5Genes involved in growth are not required for macrochaete development. As in (TIF)Click here for additional data file.


Oral cancer requires considerable utilization of healthcare services. Wide resection of the tumor and reconstruction with free flap are widely used. Due to high recurrence rate, close follow-up is mandatory. This study was conducted to explore the relationship between the healthcare expenditure of oncological surgery and one-year follow up and provider volume.From the National Health Insurance Research Database published by the Taiwanese National Health Research Institute, the authors selected a total of 1300 oral cancer patients who underwent tumor resection and free flap reconstruction in 2008. Hierarchical linear regression analysis was subsequently performed to explore the relationship between provider volume and expenditures of oncological surgery and one-year follow-up period. Emergency department (ED) visits and 30-day readmission rates were also analyzed.The mean expenditure for oncological surgery was $11080±4645  and $10129±9248 for one-year follow up. For oncological surgery expenditure, oral cancer patients treated by low-volume surgeons had an additional $845 than those in high-volume surgeons in mixed model. For one-year follow-up expenditure, patients in low-volume hospitals had an additional $3439 than those in high-volume hospitals; patient in low-volume surgeons and medium-volume surgeons incurred an additional expenditure of $2065 and $1811 than those in high-volume surgeons. Oral cancer patients treated in low-volume hospitals incurred higher risk of 30-day readmission rate .After adjusting for physician, hospital, and patient characteristics, low-volume provider performing wide excision with reconstructive surgery in oral cancer patients incurred significantly higher expenditure for oncological surgery and one-year healthcare per patient than did others with higher volumes. Treatment strategies adapted by high-volume providers should be further analyzed. Oral cancer is among the 10 most common forms of cancer The fact that increased case load is associated with improved outcomes has been noted for three decades in many areas of health care, including acute myocardial infarction, many types of high-risk operations and cancer surgery At present, there is little information on resection and reconstruction and follow-up expenditure for oral cancer This was a retrospective analysis of hospital and ambulatory visit administrative data provided by the National Health Research Institute for all patients with newly diagnosed oral cancer in 2008. This study was initiated after approval by the Institutional Review Board of Buddhist Dalin Tzu Chi General Hospital, Taiwan. Since all identifying personal information was stripped from the secondary files before analysis, the review board waived the requirement for written informed consent from the patients involved.We used data from 2008 to 2009 from the National Health Insurance Research Database (NHIRD), which covered medical benefit claims for over 23 million people in Taiwan (approximately 99 percent of the island’s population). The database contains a registry of contracted medical facilities, a registry of board-certified physicians, and monthly summaries of all inpatient and ambulatory visits claims. All oral cancer patients  in 2008 were included. In total, there were 1300 patients with oral cancer who underwent wide excision with free-flap reconstruction performed by 196 surgeons and 37 hospitals in 2008.Surgeons were sorted by their total patient volume using unique surgeon identifiers in this database. The 1300 patients were sorted into three approximately equal groups based on surgeon volume: ≦8 cases (low), 9–21 cases (medium), and 22–96 cases (high)  [16], [1The key dependent variable of interest was the expenditure of each hospital admission for oncological surgery , and one-year follow-up expenditure. The expenditure included actual resources utilization, and charges which were paid by the patients and Bureau of National Health Insurance in Taiwan. The key independent variables were the oral cancer resection with reconstruction volume groups  for the surgeons and hospitals. Patient characteristics included age, gender, individual socioeconomic status (SES), urbanization and region of patients’ residence and medical illness. The recoding and definition of SES and urbanization of residence was mentioned in our previous study We further reported the visits to the emergency department (ED) and readmission to the hospital within 30 days after discharge from oncological surgery as the outcomes of care between different caseload groups in order to confirm whether lower costs may lead to higher ED visits or readmission rate in the follow-up period The SPSS version 15  was used to analyze this data. The hierarchical linear regression model was used to analyze the relationship between the main outcomes of the different caseload groups and those of the reference group after adjusting for hospital, surgeon characteristics and patient demographics. In this study, the hierarchical linear regression method was used because of concern for the potential clustering effect in a hospital. A hospital-level random effect might account for possible correlations between hospitalization costs within a hospital’s panel simply because of hospital policies, procedures, or physician compensation mechanisms that were unique to that hospital. Multiple logistic regression model was performed to explore the association of provider volume and 30-day readmission rate and ED visits. A two-tailed value of p<0.05 was used to determine statistical significance.Patient characteristics are detailed in The mean expenditure for oncological surgery was $11080±4645  and healthcare expenditure for 12-month follow-up period was $10129±9248 . Figure After adjusting for physician, hospital, and patient characteristics, the hierarchical linear regression revealed that the cost for oncological surgery per patient for low-volume surgeons was $845 higher than those of high-volume surgeons (P = 0.03), and $2065 higher than those of high-volume surgeons in healthcare expenditures for the 12-month follow-up period (P = 0.007) . Oral caOral cancer patients treated in low-volume hospitals incurred higher rate of 30-day readmission event; however, oral cancer patients treated by low-volume surgeons had higher ED visits . After aWe found significantly higher adjusted expenditure for oncological surgery of oral cancer patients treated in low-volume surgeons and more healthcare expenditure for additional 12-month follow-up period treated by low-volume surgeons and low-volume hospitals. Low-volume surgeons had an additional 8% higher expenditure for oncological surgery and 20% higher expenditure for 12-month follow-up expenditures than high-volume surgeons after adjusting other factors; oral cancer patients treated by low-volume hospitals incurred an additional 34% higher spending for 12-month follow up than those in high-volume hospitals. Patients treated in low-volume hospitals incurred higher 30-day readmission rate. Given the high worldwide health care costs for oral cancer, our findings have significant implications for professional organizations and policy makers.The strengths of our study are that it is based upon a large population (n = 1300), the population experienced almost complete follow-up of OPD visits and hospitalization (99%) and had routine monitoring of diagnosis accuracy by the National Health Insurance Bureau of Taiwan. Previous study explored the expenditure for oncological surgery alone in oral cancer Surgeons and hospitals caseload could affect the spending or complications through different mechanism. Gruen et al. stated that surgeon caseload may affect the outcomes through patient selection, preoperative and intraoperative decision making, and surgical techniques Our study revealed some points that may be useful for policy intervention. Research organizations and payers could sponsor clinical quality improvement research to identify the care and treatment strategy differences among low-, medium-, and high-volume providers. Treatment strategies of the high-volume surgeons should be analyzed and utilized more widely in the country in order to decrease hospitalization costs and follow-up expenditure. For high-volume surgeons, payers may encourage them or consider additional reimbursement for them to serve as expert consultants to low-volume surgeons in order to improve healthcare quality and save costs. The organization of care system, practice protocols of high-volume hospitals may be further explored.Our study has several limitations. First, the diagnosis of oral cancer, and any other co-morbid conditions are completely dependent on ICD codes. Nonetheless, the National Health Insurance Bureau of Taiwan has randomly reviewed the charts and interviewed the patients in order to verify the accuracy of the diagnosis. Hospitals with outlier chargers or outlier practice may undergo an audit and subsequent heavy penalties when malpractice or discrepancies are found. Second, the medical illness of oral cancer patients was evaluated with the Charlson Comorbidity Index score alone. The stages of oral cancer, which may be associated with different surgical procedures, were not included in the database. Third, the details of expenditure such as procedure, tests, and imaging can’t be clearly estimated from the present dataset. Future work related to this field is necessary in order to explore the difference of medical evaluation behaviors of different caseload surgeons and hospitals. Fourth, 30-day readmission rate and ED visits were used a proxy of quality measurement in our series. More detailed outcomes, such as quality of life and flap success rate may be needed to be explored in the future. Fifth, our series explored the direct cost or expenditure derived from the NHIRD and indirect cost such as time lost from work, and support person time lost from work can’t be extracted from this dataset After adjusting for physician, hospital, and patient characteristics, low-volume provider incurred significantly higher costs and more follow-up expenditure per patient than did other providers with higher volumes. Treatment strategies, organization of care system, and practice protocols adopted by high-volume providers should be further analyzed and utilized more widely.Appendix S1Methods for defining the caseload category of surgeons.(DOC)Click here for additional data file.Appendix S2Expenditure and additional information for the oral cancer patients.(DOC)Click here for additional data file.