dataesr/scientific-paragraphs-categorization huggingface dataset:
Wolbachia-specific Additional Screening Among the five endosymbionts screened, Wolbachia was the only symbiont detected in some W. auropunctata populations (see Results section). We extended our screening of Wolbachia on a larger dataset to more accurately assess the distribution of this endosymbiont among W. auropunctata populations. Together with individuals previously examined, a total of 205 queens and 376 workers were screened following the protocol detailed in the previous section. Altogether, these individuals screened for Wolbachia infection originated from 174 and 248 nests for queens and workers, respectively, from 56 worldwide populations (Table  1  and 2; Figure  1 ). Based on this additional screening, we estimated the prevalence of Wolbachia within populations in the queen and worker castes using the ratio of the number of infected individuals to the total number of screened individuals of the same caste.
Genetic Characterization of the Wolbachia Strains A phylogenetic analysis was performed to characterize the strains of Wolbachia detected in W. auropunctata populations. To this aim, we sequenced a fragment of the wsp gene from 74 individuals from the 17 identified infected populations from both the native and introduced range of the species, using the previously described PCR amplification protocol. PCR products were purified and sequenced on an ABI 3730 DNA sequencer (Applied Biosystems). Electrophoregrams were checked for possible errors using the Seqscape software (Applied Biosystems). Because multiple peaks were observed at some base positions in some individual electrophoregrams, infection by multiple strains was suspected in these cases. The amplification products were hence purified (QIAquick PCR Purification Kit, QIAGEN) and ligated into a plasmid vector (pGEM-T easy vector system, Promega) and transformed into JM109 competent cells (Promega).
Positively transformed cells were boiled, amplified using T7 and SP6 (primers of plasmid) and sequenced with the same primers. The plasmid DNA of six clones per individual was purified and sequenced. Our phylogenetic analysis was performed on unique wsp haplotypes (five haplotypes). We also included 33 additional wsp sequences of Wolbachia strains belonging to the supergroups A and B and isolated from other Formicidae available at the Wolbachia MLST website (http://pubmlst. org/perl/mlstdbnet/mlstdbnet. pl?page = query&file = wo_isolates. xml). The tree was rooted using a wsp sequence from a Wolbachia strain belonging to the supergroup F according to the classification of the MLST database (i. e. infecting the wasp Apoica pallens). All sequences were aligned using clustalW  [38]. The data set was analyzed using the neighbour-joining method with Kimura two-parameter distance measure in MEGA v.
auropunctata. Note: Each Wolbachia sequence is labeled with the name of its host species and the allelic number of the wsp sequence according to the MLST database in bold. The country of origin of each identified strain is indicated in parenthesis. Only bootstrap values (computed from 1,000 replicates) of nodes are figured for values. 50%. Wolbachia strains found in sexual and clonal populations of W. auropunctata are highlighted in red and orange, respectively. Location of origin of the samples is indicated between parentheses. doi:10. 1371/journal. pone. 0058467. g002 In conclusion, this study revealed that, except Wolbachia, none of the reproductive parasite screened in the present study infect wild populations of W. auropunctata. Furthermore, presence or absence of Wolbachia infection is unlikely to explain the reproductive system polymorphism found in W.
FigureS1NJ tree based on the gatB nucleotide alignment of the different Wolbachia strains infecting native and introduced populations of W. auropunctata. Note: Wolbachia strains found in sexual and clonal populations of W. auropunctata are highlighted in red and orange, respectively. Each other Wolbachia sequence is labeled with the name of its host species and its respective GenBank Accession number in bold. Location of origin of the samples is indicated between parentheses. Only bootstrap values (computed from 1,000 replicates) of nodes are figured for values. 50%. (DOC)FigureS2NJ tree based on the fbpA nucleotide alignment of the different Wolbachia strains infecting native and introduced populations of W. auropunctata. Note: Wolbachia strains found in sexual and clonal populations of W.
auropunctata are highlighted in red and orange, respectively. Each other Wolbachia sequence is labeled with the name of its host species and its respective GenBank Accession number in bold. Location of origin of the samples is indicated between parentheses. Only bootstrap values (computed from 1,000 replicates) of nodes are figured for values. 50%. (DOC)FigureS3NJ tree based on the CoxA nucleotide alignment of the different Wolbachia strains infecting native and introduced populations of W. auropunctata. Note: Wolbachia strains found in sexual and clonal populations of W. auropunctata are highlighted in red and orange, respectively. Each other Wolbachia sequence is labeled with the name of its host species and its respective GenBank Accession number in bold.
Acknowledgments JF would like to thank  A. Cubier  and  C. Charlut  for support. The authors want to thank  M. Weill  for providing Wolbachia-infected Culex pipiens samples. Some of the data analyzed here, including the genetic data in particular, were generated at the molecular genetic analysis technical facilities of the  Environment and Biodiversity IFR 119 at Montpellier (France). Data Archiving Sequence  data have been submitted to GenBank: accession numbers  JX499039-JX499070.
jgi. doe. gov/). Sequence alignments were done by CLUSTALW and the tree was constructed with the neighbourjoining method in MEGA 5. 0 software  (Tamura et al. , 2011). The robustness of the branches was assessed by the bootstrap method with 500 replications. The scale marker represents 0. 2 substitutions per residue. It is largely admitted than the main activity of these enzymes is the catalysis of a glutathione adduct onto electrophilic molecules, the specificity of these enzymes remaining usually very weak. However, two classes of GSTs called omega (GSTO) and glutathionyl hydroquinone reductase (GHR) possess in their catalytic site a cysteinyl residue conferring to these proteins the ability to remove glutathione from various structurally different molecules  (Garcera et al. , 2006; Xun et al.
Based on this observation and the data obtained from the Fungal Cytochrome P450 database (http://p450. riceblast. snu. ac. kr/species. php), a direct correlation between P450ome and GSTome contents can be observed suggesting a close link between phase I and phase II detoxification processes (Fig. 4B ). However, this correlation with CytP450 does not exist when considering the GST classes individually. This suggests that compensatory effects between GST gene copy numbers could exist to relay the first detoxification step. Both protein families are largely expanded in wood-interacting fungi. For instance, the symbiotic Laccaria bicolor exhibits a weak ability to degrade recalcitrant organic matter in correlation with relatively restricted xenomic content. In contrast, Paxillus involutus, another symbiotic basidiomycete, possesses an extracellular oxidative system  (Rineau et al.
Background: Overactive bladder (OAB) is associated with high healthcare costs, which may be partially driven by drug treatment. There is little comparative data on antimuscarinic drugs with respect to resource use and costs. This study was conducted to address this gap and the growing need for naturalistic studies comparing health economics outcomes in adult patients with OAB syndrome initiating treatment with different antimuscarinic drugs in a primary care setting in Spain. Methods: Medical records from the databases of primary healthcare centres in three locations in Spain were assessed retrospectively. Men and women ≥18 years of age who initiated treatment with fesoterodine, tolterodine or solifenacin for OAB between 2008 and 2010 were followed for 52 weeks. Healthcare resource utilization and related costs in the Spanish National Health System were compared.
Design and objectives In this observational, multicenter, post-marketing, longitudinal, retrospective study, existing medical records (computerized databases with de-identified data) of outpatients and inpatients with a diagnostic code of OAB in three different locations in Spain were extracted and reviewed. The main objectives of the study were to compare healthcare resource utilization related to the clinical management of OAB syndrome and corresponding costs in patients treated with fesoterodine, tolterodine, or solifenacin for the first time in the primary care setting in Spain's NHS.
Study population The study population consisted of patients from three geographical areas of two autonomous regions (Catalonia [Badalona and Barcelona locations] and the Balearic Islands  [Mallorca] ). These regions were selected because of the existence of available healthcare provider databases and because one region (Catalonia) is continental and large while the other (the Balearic Islands) is insular and small, meaning that the varied geographical composition of the country is reflected in the study and thus may be considered representative of Primary Care settings in Spain. Eighteen primary health care centres (PHC), 7 in Badalona, 2 in Barcelona and 9 in Mallorca, and their corresponding referral hospitals (three) participated in the study. The population assigned to these centres is mostly urban and industrial and low-to middle-class socioeconomic status.
Database information Clinical data on patients treated with fesoterodine, tolterodine or solifenacin (Anatomical Therapeutic Chemical Classification System  [33] ) were obtained from claim databases using the same informatics system for filing and handle health data (ONMI-AP software). These databases are owned by Badalona Serveis Assistencials (BSA), a healthcare provider in Badalona (Barcelona), Sagrada Familia Primary Care Health Centre in Barcelona Spain, and the Primary Health Care Directorate of ib-Salut, the healthcare provider for Mallorca. The choice of specific medicine and dose was determined by the patients' physicians as part of routine primary care. Data on prescribed doses of fesoterodine (4 and 8 mg), solifenacin (5 and 10 mg) and tolterodine (2 and 4 mg) and treatment time (in weeks) during follow-up were recorded in the database.
Costs of acute, chronic and on-demand prescriptions were calculated using the retail price per pack at the time of prescribing. Direct non-health costs (disease-associated out-of-pocket costs paid by patients and their families) were not included in the study because these are not captured in the database, and the database does not provide direct access to patients. Overall costs by drug were assessed for a 52-week follow-up period. Baseline healthcare resource use and associated costs were also determined for 1 year prior to antimuscarinic initiation.
Data confidentiality and ethics statement This was a retrospective observational study using existing data on patients included in a claim database. Data confidentiality was respected at all times by means of de-identification thus ensuring anonymity according to Spanish Organic Law (Law 15/1999 of 13 December on the Protection of Personal Data). Thus no data which could reveal patient identity was extracted. The database was then prepared and closed for statistical analysis, not allowing further manipulation of data. The study, its design and procedures was classified by the Spanish Medicines Agency (AEMPS) as a Post-Authorisation Study -Other Designs (EPA-OD) trial type and was subsequently approved by the Clinical Research Ethics Committee of Hospital Clinic I Provincial of Barcelona. Based on its design, it was exempt under Spanish law from requiring written informed consent (Law 29/2006 of 26 July and Royal Decree 1344/2007 of 11 October; see http://www.
The data are presented as adjusted mean differences between treatments with corresponding 95% CIs calculated using re-sampling techniques (bootstrapping) corrected for bias, given the non-normal distributions of the variables with respect to resource utilization and costs. The analysis was performed using the statistical package SPSS for Windows version 19. Statistical significance was established as P < 0. 05, all tests were 2-sided. Unit drug costs were obtained from prices listed at the time of prescription, which is an approximation because drug prices may have varied during follow-up. We performed a secondary analysis by applying a 40% reduction in the cost of tolterodine and 7. 5% reduction in the costs of solifenacin and fesoterodine. The 40% reduction in the price of tolterodine is justified by the recent (3 rd quarter 2012) loss of exclusivity of this drug; the reduction was applied to the price at the time described above.
In all cases these potential biases are likely to have affected the three study drugs equally. Direct non-health costs (i. e. out-ofpocket costs paid by the patient that are not funded by the NHS) could not be assessed, because none of the three databases analyzed accounts for these costs. Outof-pocket costs of OAB can be substantial, particularly for non-funded absorbent products. Because only 10% of the records analyzed were on occupationally active patients, an economic analysis that considers effects on productivity could not be performed. Furthermore it was not possible to assess OAB severity among patients for any of the antimuscarinic drugs prescribed; significant differences among groups could have influenced outcomes. However the fact that no significant differences in resource use and/or healthcare costs were found in the year prior to the index date suggests that symptom severity was similar among treatment groups.
Survival analyses We tested the effect of the treatment on the probability of survival for adult females, juvenile males and juvenile females. Survival estimates were obtained independently of capture probabilities, using a capture-mark-recapture method based on the open population model of Cormack-Jolly-Seber. This model produces apparent survival estimates resulting from mortality and emigration. We used the program MARK version 6. 0 to fit models  (White & Burnham 1999) , and models were compared with Akaike Information Criterion corrected for small sample size (AICc  (White & Burnham 1999) ). The best model is the most consistent with the data while using the fewest number of parameters, i. e. giving the lowest AICc. It is considered that two models differ when their difference of AICc is higher than 2  (Burnham & Anderson 1998).
Statistical analysis In Experiment 1, P4 concentration in blood was normally distributed and no data transformation was needed. The repeated-measures analysis was performed using the procedure MIXED of SAS  (Littell et al. , 1996). The cross-over model included the effects of replicate, treatment, sampling time, the interaction between treatment and time, and cow, which was treated as a random effect and was the subject for the repeated measures. The area under the curve for all treatments was calculated by the trapezoid method and analyzed using the procedure MIXED of SAS. In Experiment 2, a binomial distribution was assumed for binary response variables such as pregnancy per AI (P/AI) after the 1st and 2nd breedings and analyzed using the procedure GLIMMIX of SAS (SAS/STAT version 9. index from proc GLIMMIX.
Therefore, variables and oneway interactions kept in the final models for Experiment 2 were treatment, lactation number, interaction between treatment and lactation number, and DIM at breeding. Cow and farm were included in all models as random effects. The logit link was used for the analyses of these binary variables and the resulting values were converted back to probabilities by the formula P = 1/(1 + e -(b 0 +b 1 X 1 +b 2 X 2 +•••+b i X i ) ) using the ilink option in the GLIMMIX procedure of SAS. Pregnancies per AI were analyzed in relation to continuous variables such as BCS and circulating P4 on D0 by using the Interactive Data Analysis feature in SAS 9. 3. A probability of P < 0. 05 was considered to be significant, and probabilities between 0. 05 and 0. 10 were discussed as tendencies.
In this paper, our goal is to propose a novel clustering algorithm for wireless sensor networks in which each sensor node sends its data to its cluster head (potentially through Multihop paths) based on the context of the Binhathinks project. In this context, cluster heads collect data from all sensors in their cluster and send them through their GPRS link. Since activating the GPRS consumes more energy than peer-to-peer communications (as shown in Table  1 , Section 6), each node should take the cluster head role in turn in order to allow the network to be operational as long as possible without too much communication overhead and structure modiications. Data aggregation is performed at every hop towards the cluster head. he clustering scheme should also provide a good trade-of between the number of clusters (the more clusters, the more GPRS activations) and the size of the cluster radius (the bigger radius, the more peer-to-peer communications to reach the cluster head).
Problem Statement, Context, and Motivation his paper is conforming the Binhathinks project. he project aim is to ease the collection and recycling of waste and reduce its cost. In order to reduce the distance traveled by the garbage truck and to limit manipulations made by operators, Binhathinks adds intelligence to dustbins. Dustbins are equipped with wireless sensors able to wirelessly communicate with each other and with a base station in order to send information about dustbin location, their illing level (does this garbage need to be emptied?), accuracy of the recycling, adequate content, and so on. All these data are processed by the garbage truck to dynamically optimize on-line the collect path by operators to reduce useless manipulations of empty or dangerous dustbins. One scenario of the project is to equip dustbins with both: (1) a wireless module to allow wireless peer-to-peer communications, (2) a GPRS modules for longer range communications with the base station.
Since GPRS consumes much more power than a peer-to-peer communication chip, it is not wise to use it on all nodes all the time. Equipping nodes with GPRS chip can be costly in terms of hardware and subscription plan, but negotiations for machine to machine subscription plan are possible. Indeed, the idea defended in Binhathinks is as follows. In order to reduce power consumption for each node, a clustering organization is run over the network. Each node sends its data to its cluster head. Onceallda taarega thered, the cluster head aggregates them and sends them to a base station or the garbage truck using its GPRS module. By doing so, only the cluster head activates its GPRS module and drains more energy (mainly because of the use of GPRS module). BLAC proposes a dynamic energy-eicient trade-of between the size and the number of clusters.
Nodes are placed on streets and next to building areas using OpenStreetMap data (http://www. openstreetmap. org) in order to get realistic topologies. Figure  6  shows the topologies we used to run the simulations; red dots represent nodes. In order to use a realistic model for transmitting and receiving costs in both peer-to-peer and GPRS communications, we consider the Texas Instruments CC2420 Zig-Bee chip (http://focus. ti. com/lit/ds/symlink/cc2 20. pdf)and the LEON-G100 GSM/GPRS module from u-blox (http:// www. u-blox. com/en/wireless-modules/gsm-gprs-modules/ leon-gsm-module-family. html), respectively. he former one consumes 0. 77 mW when idle, 35. 6 mW for receiving (Rx), and 31. 32 mW for transmitting (Tx). he latter one consumes 6. m Ww h e ni d l ea n d1. 2 5Wf o rr e c e i v i n g( Rx)o rt r a n smitting (Tx).
BLAC-bg and BLAC-rg present a slightly improvement compared to BLAC-bs and BLAC-rs, respectively, regarding the lifetime as they keep more nodes alive during the decreasing phase. his is due to the overall number of clusters built by every scheme. Indeed, BLACbg and BLAC-rg build less clusters than their corresponding variant and thus propose a diferent balance between the number and the size of cluster heads that perform a little bit better. In addition, note that we did not consider in LEACH power consumption the costs relative to node synchronization. 6. 2. Delivery Ratio. Figure  8  displays the delivery ratio of every algorithm with regards to time for 100 nodes and 250 nodes in urban environment and 250 nodes in rural environment. Delivery ratio is computed as the amount of data received divided by the amount of data generated on all nodes.
Cross-sectional studies in high-risk adolescent type 2 diabetes populations have found microalbuminuria in 18-72% of patients within 10 years of diabetes  (6). Youth with type 2 diabetes have significantly higher rates of microalbuminuria as well as increased incidence and progression of nephropathy when compared with type 1 diabetic patients with similar diabetes duration  (7). It is likely that a higher degree of insulin resistance contributes both to a diagnosis of type 2 diabetes at a younger age and to early microalbuminuria and hypertension. Predictors of susceptibility to nephropathy as well as longitudinal data on renal disease occurrence and progression in youth with type 2 diabetes are needed. The multicenter Treatment Options for type 2 Diabetes in Adolescents and Youth (TODAY) clinical trial recruited youth from a wide cross-section of geographic and ethnic populations to provide a cohort representative of the target population.
Annual microalbumin measurements were obtained thereafter on ACE therapy. Additional medications were added as needed after maximal ACE therapy at the discretion of the local study clinician, applying a TODAY study treatmentrecommended algorithm for adding calcium channel blocker, diuretic, and/or angiotensin receptor blocker therapy. Treatment was monitored by a safety oversight process using central data to enhance study site compliance and consistency with treatment protocols. Treatment was altered for elevation of liver enzymes or pregnancy. Study investigators blinded to the treatment arm reviewed all BP and urine results and tracked their treatment to assure adherence to the standardized algorithms. Safety and risk management were monitored by an independent data and safety monitoring board appointed by the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK).
Statistical methods The proportion of participants with hypertension or microalbuminuria was computed overall and by study treatment arm, sex, and racial/ethnic group; effects were analyzed using a x 2 test. The minimal differences in incidence rates of hypertension or microalbuminuria between treatment groups during the study allowed for further analysis of other factors contributing to these complications (Fig. 1A  and Fig. 2A ). Risk of developing hypertension or microalbuminuria was assessed in separate models using time-to-event analysis with the log-rank test. Participants were considered at risk from study enrollment until either diagnosis (hypertension or microalbuminuria) or the last visit date on which a measurement (BP or urine microalbumin) was collected; data for six participants who elected to undergo bariatric surgery were included up to the day of surgery.