However, these composites fall short of the toughness needed for permanent implants. Significant impediment to improvement has been the requisite use of conventional destructive mechanical testing, which is necessarily retrospective. Here we show quantitatively, through the novel use of calorimetry, terahertz (THz) spectroscopy and neutron scattering, how GIC's developing fracture toughness during setting is related to interfacial THz dynamics, changing atomic cohesion and fluctuating interfacial configurations. Contrary to convention, we find setting is non-monotonic, characterized by abrupt features not previously detected, including a glass–polymer coupling point, an early setting point, where decreasing toughness unexpectedly recovers, followed by stress-induced weakening of interfaces. Subsequently, toughness declines asymptotically to long-term fracture test values. We expect the insight afforded by these  Bioactive cements are widely used in dentistry and medicine. Here, using a variety of novel experimental techniques, the authors uncover the atomic and vibrational contributions to the mechanical toughness of bioactive cement during the setting process. Worldwide demand for durable biomaterials emanates from population ageing and from emergent developing countries. Historically, the implantation of foreign materials into the body has been dentistry led. However, the optimisation of tooth replacements remains incomplete, problems stemming from conflicts between mechanical toughness, biocompatibility, adhesion and appearance. For commonly used mercury–silver amalgams, this is compounded by toxicity and disposal. The United Nations Environment Programme assesses mercury to be ‘a global threat to human and environmental health,' listing amalgams as a source3456710121415KC and yield strength σY, both traditionally measured by destructive methodsKC versus log σY plot follows the Ashby schemeKC values greater than 1 MPa m1/2; brittle materials such as glasses have KC values less than this. Indeed the yield strength σY of glassy materials covers many decadesKC and σY values of GICs cluster around those of dentine and amalgam, but clearly have less toughness and strength than either.Damage tolerance is assessed through fracture toughness KC and σY develop during setting, starting out as highly deformable and incompressible slurries that subsequently harden to form rigid, inflexible cements. The compressibility κ relates directly to the shape of the interatomic potentials of a given systemG and lower κ, but most importantly tend to have a higher G·κ, and to be brittle. In particular, Poisson's ratio ν , as a function of ν, this forms a clear sigmoid, with an inflection point (at ν≈0.33)ν>∼0.33) from brittle (ν<∼0.33) materials . The Cp of fresh G338 sample (red curve) exhibits the effects of water loss, after which (blue curve) three sharp glass transitions can be deciphered. Following 62 h of setting, the Cp of the GIC (green curve) demonstrates the evolution of the glass-transition regions of the remaining glass.To make our extended er glass , in reguer glass . Figure Coherent terahertz spectroscopy (CTS)KC atomically, we have turned to in situ neutron Compton scattering (NCS)p measures the atomic cohesion. The development of Δp during setting at 300 K is clearly oscillatory G(r) G(r) . This ex4+, P5+, with the majority being Al3+. Al3+ can be charge-compensated for tetrahedral configuration by P5+, and also by Na+ and Ca2+, which, as network-modifiers, can promote the formation of non-BOs within the BO alumina-silicate network43+ coordinates both to BOs and F−  and Al(VI) configurations also occur, particularly at the developing interfaces, with the proportions changing during cement setting28The G338 glass is chemically complex, containing ingredients for cementation , mineralization (phosphate and fluoride), dental caries resistance (fluoride) and opal appearance (Ca+F-rich particles). The network-forming ions are Si F− ref. , while F1), in which are embedded 30–50-nm spherical rosette domains (GP2), decorated by 5–10-nm droplets (GP3). GP2 and GP3 are highlighted by large and small dashed circles, respectively, and are generally seen throughout this image and those of other particles. All three GPs are neutron amorphous (Tg1 (701 K), Tg2 (732 K) and Tg3 (782 K). The small size of GPs and overlaying within TEM images prevents measurement of phase compositions to correlate with Tgs. However, as amorphous phase separation is the primary source for bulk crystalline nucleation in glass ceramicsFig. 2b37Tg1) and the nanophase droplets to a Ca-F-P-rich GP (GP3 Tg3). From the glass composition  the remaining 30–50-nm spherical domains suggest a Ca-F-rich GP (GP2 Tg2). These attributions to the phase-separated components have been confirmed in a recent parallel studyThe as-received G338 glass powder (Methods) comprises micron-sized particles  exhibiti17morphous  and the morphous . These r1, GP2 and GP3 2+ is released from the glass, however, subsequent signal recovery over the first 1 h traces the polymer's progressive chelation of Ca2+ at the interface, until Al3+ emerges from the glass network at ∼1.5 h, initiated by a sharp drop in reflectance continuing to ∼5 h. As the polymer is increasingly localized into a percolating matrix around the glass powder4We observe time-dependent changes in the sub-THz range using CTS2930pi of individual atom types i, measured by NCS . This might be the desirable point for cementation to halt. However, there is then a minimum at ∼15 h, where atomic cohesion momentarily drops before recovering. We later identify this, from changes in S(Q)  , as an ipav is lower, average atomic cohesion is also lower, interatomic potentials shallower and wider and thus the material is tougher, and vice versa. Accordingly, we expect that Δpav and fracture toughness KC might be inversely related for groups of materials. This is demonstrated in pav values for this GIC composite measured at 24 h are plotted, together with Δppolymer, Δpglass measured separately, as well as those of related compounds . The spread of the KC values around these asterisked points for other glasses, GICs and polymer systems extend to smaller or larger values. These are smallest for oxide glasses and largest for phosphate glasses. Fracture toughness of the GIC glass falls midrange defining the value used in KC is much larger for polymers, where KC is strongly governed by molecular weight Mn  to Al with the lowest (∼0.3 MPa m1/2). Elemental values can be interpreted as imparting different degrees of fracture toughness at the atomistic level, with H and Al, for example, possibly contributing toughness and brittleness, respectively. The reaction points CP, ISP and ISZ are again evident. However, H, F and Al exhibit oscillatory changes in KCi (and Δpi) with setting time (KCav. These may be associated with developments in hydration (KCH), fluorination (KCF) and chelation (KCAl), respectively. This sensitivity to differing chemical bonding is illustrated by hydrogen , but greater than ZrH2 (4.15 Å−1) or NaH (3.32 Å−1)3450The elemental momentum widths Δpi  analysedpi  can be ctionship . These ationship  and sharip  binding OH−; (B) PAA carboxylation at the interfaces (COOH↔COO−+H+) freeing H+ or H3O+. (A) is likely to be linked with gelation at CP, and (B) with subsequent chelation of Al at the ISP that follows at the interfaces. This is consistent with the first minima (binding of OH−) and maxima (release of H3O+) in KCH with setting time  hydration of the alumino-silicate GP GP1  (where Q is the neutron scattering vector) and total radial distribution functions G(r)  and next NN (NNN)) for the GIC, glass and polymer components measured separately are compared in S(Q) for the GIC and polymer include artefacts in amplitude, relating to the featureless, but substantial, incoherent scattering of hydrogen (Methods). The peak positions on Q axis in S(Q) and in G(r), though are reliable. Deuteration was avoided in this study, because this would have adversely affected diffusion and cement-setting processes.Time-averaged structure factors S(Q)s exhibit an initial peak—known as the first sharp diffraction peak (FSDP). This directly reflects the average length of intermediate-range order domain rIRO in oxide glassesQFSDP (2π/rIRO) is composition- and pressure dependent. The fluctuating position of the FSDP  by Porod scattering from interfaces2) is ∼50 nm in size  from 0.5 to 1 Å in size , equivalrecovers .QFSDP) constrained by the increasingly rigid surrounding matrix. This is followed by overall stress release, where density contrast at the interfaces observed from SANS and pressure from the decrease in QFSDP is restored, and suggests interfacial failure develops over the later stages of the ISZ. Indeed, indentation studies have shown that macroscopic cracks occur at GIC hybrid interfaces3+ linkages, as an alternative to fracture propagation at ionic sites within the polysalt complex, which has also been suggested3+ bonding may also play an important role.Taken together, these variations in nanoscopic structure start with decreased density contrast pointing to tension at the interfaces (SANS) as the glass compresses (increase in FSDP G(r)s (G(r)s (G(r)s also masks the unreacted glass and polymer components, highlighting changes in local atomic structure at the interfacial regions during cementation.To ascertain whether complementary changes in real-space structure occur, we have turned to time-dependent total radial distribution functions, G(r)s . Becauses (G(r)s . FurtherG(r)s for GIC, glass and polymer exhibit two well-resolved peaks, due to NN and NNN interatomic distances, respectively  with setting, however, enhanced with differencing, which effectively removes unreacted components in the bulk (G(r)  , coincidund 15 h  and the und 15 h .pi  was Na9.7 ref. , the pro0 values .TEM was performed at the NanoVision Centre at QMUL using scanning electron microscopy and TEM facilities. The G338 glass powder was dried before mounting. With an average particle size range of ∼4 μm , many smCp) data for both G338 and the GIC sample subjected to the 62 h setting and subsequent first DSC up- and downscans (−1 to 873 K and then cooled back to 523 K at 20 K min−1. Scan 2 followed the same procedure. Cp was determined using a sapphire reference.The isobaric heat capacity (ownscans  were colCp) and the mass change of the GIC sample, which was subjected to a 62-h setting. The sample was upscanned in argon at 20 K min−1. The first upscan curve in Spectra of G338, Chemflex and the setting cement  were obt−1, the impulse approximation is validni(p) of each element i present in the sample.NCS spectra were obtained using VESUVIO spectrometer at the ISIS neutron source, with sample sizes of 55 g glass, 20 g polymer and 14 g cements (10 g glass+4 g polymer—to give 2.5:1 mix ratios), and repeated at differing temperatures . Under the conditions of high neutron energy transfer, 1–30 eV, and wavevector transfer, 30–200 Åpi for GIC elements present as shown, taking advantage of the instrument's ability to probe single-particle momentum distribution55pi was calculated in Å–1 as full width at half maximum  for setting at 280, 300 and 320 K, Δp280 K, Δp300 K, Δp320 K, from which KCav plots in Calibration was first done by measuring the empty beam and the empty sample holder. The empty sample holder spectrum and the multiple scattering were always subtracted before any data analyses. Multiple scattering was calculated using the assessed Monte Carlo code DINSMS maximum , followi maximum . The setData were collected using NIMROD at ISISF(Q) measured in the absolute units of barn per steradian per atom is defined as follows:The total-scattering structure factor cα and cβ are the concentrations of atom type α and β; bα and bβ are their corresponding neutron scattering lengths; δαβ is the Kronecker delta function to avoid double-counting interactions between like-atom pairs; Aαβ(Q) are the Faber–Ziman partial structure factors.Where S(Q) was obtained by normalizing F(Q):Structure factor Where Q region in polymer S(Q) in Q region of F(Q) during normalization. This negative swing is thus not shown in There is a negative swing at the low-G(r) is obtained by the direct Fourier transform of F(Q):The total radial distribution function ρ is the atomic density of the material.where S(Q) and G(r) for the polymer are consistent with a fixed hydrogen content. Due to the effect of high hydrogen content of the GIC, conventional pair-distribution analysis of G(r) was replaced by differencing .Supplementary Figures 1-6


This investigation examined whether adopted children with prenatal exposure to a wide variety of recreational drugs exhibited higher scores (i.e. more problems) with executive function and psychiatric symptomology. Caregivers of children ages 5 to 18 completed an online survey with items about use of alcohol, nicotine, or methamphetamine during pregnancy followed by the Behavior Rating Inventory of Executive Function  or the Child Behavior Checklist . Relative to a comparison group of children raised by their biological parents, adoptive children that were polysubstance exposed during prenatal development exhibited higher rates of academic difficulties and were behind their classmates in math and reading. Adoptive children had statistically and clinically significant higher BRIEF ratings and this pattern was similar for boys and girls. CBCL ratings were significantly increased in adoptive children, particularly for Externalizing and Attention problems. Adoptive children with a history of polysubstance exposures including alcohol, nicotine, and methamphetamine are at heightened risk for difficulties with executive function as well as various psychopathologies. These findings suggest that increased monitoring to identify and implement remediation strategies may be warranted for adopted children with a history of  An extensive and long-standing literature has thoroughly documented that adoptive children are over-represented in clinical settings and have academic difficulties in utero exposure to a wide variety of recreational drugs, most prominently alcohol Executive function refers to neurocognitive processes responsible for generating and regulating behavior which includes selective attention, forming plans, working memory, solving problems, and mental flexibility. Executive function elements show a dose-dependent sensitivity to Caregivers of children ages 5 to 18  or 6 to 18  were recruited for a child behavior investigation which was displayed on the volunteer and community sections of Craigslist (craigslist.org) as well as the Oregon Post-Adoption Resource Center website (orparc.org) and newsletter. Paper flyers were prominently and frequently posted on community boards throughout Oregon Health Science University (OHSU), the Portland metro area, and western Oregon/western Washington . Participants were not offered an incentive for their participation. This anonymous online survey was administered by Research Electronic Data Capture (REDCap), version 1.3.9, an application for procuring online databases with maximal security for sensitive information After completing an online consent, the caregivers began the survey which typically took about twenty minutes. The first half of the items were organized from less to more sensitive and included questions about maternal and child demographics , academic performance , and child psychiatric and neurological conditions (e.g. diagnosis of Attention Deficit Hyperactivity Disorder). An additional item was added for study II (What percent of your child’s life have they lived with you?). Questions on maternal drug use were organized into two periods: during pregnancy and specifically during the third trimester. Because pre-adoption histories may not be known with certainty in all cases, the response options for the drugs most likely to be used during pregnancy  were, yes, no, suspect, or don’t know. The Behavior Rating Inventory of Executive Function (BRIEF) accounted for the remaining 86 items in Study I and the Child Behavior Checklist (CBCL) accounted for the final 118 items in Study II. As data collection was anonymous, there is no simple method to determine if any parents from Study I also participated in Study II.50 scores) were calculated based on age/sex norms with higher scores indicating greater severity. A small (4.7%) portion of the BRIEF standardization sample  consisted of grandparents and adoptive/foster parents. The BRIEF has excellent internal consistency  and very good test-retest reliability (r>0.70) The BRIEF is a rating instrument completed by parents for the neuropsychological assessment of children and adolescents which focuses on the child’s everyday activities at home and at school. Each behavior is rated as never, sometimes, or often a problem  in the last six months. The eight BRIEF scales form two measures of executive functioning  and these are totaled for an overall measure . The Metacognition Index consists of the following five scales: 1) Working Memory, the capacity to hold information to complete a task; 2) Monitor, self-monitoring habits; 3) Organization of Materials, the extent of orderliness of play and work areas; 4) Plan/Organize, the capability to foresee future events, construct goals, and implement the appropriate steps to complete a task; and: 5) Initiate, the ability to act independently to produce ideas, responses, or problem solving strategies. The Behavioral Regulation Index is composed of three scales: 1) Emotional Control, the ability to regulate emotions appropriately; 2) Shift, the capability to change from one activity to another; and 3) Inhibit, the capacity to regulate one’s behavior at the appropriate time and not act on impulse. Negativity scale scores were obtained by summing the number of select items (maximum = 9) with an “often” response. An inconsistency scale score was determined by calculating the difference between ten item pairs (range = 0 to 20) with a score ≥9 interpreted as inconsistent. Standardized  so were not included in this report. Respondents were divided into two groups, Adoptive (N = 59) and a Comparison group (N = 378) composed of biological mothers (N = 366) or biological fathers (N = 12) for Study I. Similarly, Study II consisted of an Adoptive (N = 54) group and a Comparison group (N = 485) with biological mothers (N = 469) and biological fathers (N = 26). Please note that demographic information and child ratings from the biological mothers is reported elsewhere 50≥65) problems in that domain. CBCL analyses were conducted using the total (raw) scores and using the percentage meeting clinically significant thresholds (i.e. age and sex corrected). Additional analyses were completed for children (age<13) and adolescents (age≥13) separately. Categorical level analyses were completed with a chi-square, or Likelihood ratios if the N/cell was <5. The Odds Ratio (OR) was listed only for significant associations among dichotomous variables. The data for Study I and Study II are available as d) with values of ≈0.20, ≈0.50, or ≥0.80 interpreted as small, medium, or large, respectively.Statistical analyses were completed with the Systat , version 13.0, with data expressed as mean ±SD for tables with ±SEM for figures, and 2(1) = 24.4, p<.001). The majority of respondents were from Oregon (48.9%) or Washington (15.2%). Approximately two-thirds (65.8%) of the Comparison group were recruited from Craigslist relative to only one-third (32.2%) of Adoptive parents (χThe majority (76.3%) of adoptive parents were able to confidently provide information about illicit drug exposures including methamphetamine, marijuana, or cocaine. Two-thirds of the birth mothers of Adoptive children relative to only one out of every twenty-five Comparison moms used methamphetamine during pregnancy (OR = 41.0). The biological mothers of Adoptive children more commonly smoked cigarettes (OR = 25.9) and marijuana (OR = 6.2) as well as consumed alcohol (OR = 30.4) during pregnancy. Examination of maternal drug use patterns specific to the third-trimester revealed continued polysubstance use, particularly of nicotine and alcohol . Academi±2.1, Comparison = 3.3±1.9) but Adoptive (2.5±2.2) children scored higher than Comparison (1.1±1.8) children on Negativity (t(435) = 5.59, P<.0005). Similarly, Negativity scores were more likely to be Highly Elevated (≥7) among Adopted (8.5%) than Comparison (1.6%) children (χ2(1) = 9.87, P<.005). Adopted boys exhibited statistically significant elevations on the total , both broadband scores (d = .64 to .66), and all scales (d = .42 to .79). The mean BRIEF scores were in the clinically significant (T50≥65) range for Adopted boys on all scales except Organization of Materials (d = .42) and Emotional Control , the broadband scores , and the narrowband scales (d = .53 to 1.42). Notably, only Organization of Materials (d = .53) was below the clinical cut-off (t(55) = 2.45, P<.05). Among the Comparison group, boys were rated as having more problems on Organization of Materials (t(374) = 2.00, P<.05) and Shift (t(373) = 2.19, P<.05). The same general pattern of group differences between Adoptive and Comparison children was retained when the children with ADHD were excluded (d = .61 to 1.19). There was no evidence that these group differences dissipated with increasing age. In fact, the effect size was larger in adolescents relative to children on ten out of eleven BRIEF scales  on the Global Executive Composite . Adopted children were more likely to have a wide variety of psychiatric, neurological, and other medical conditions including Fetal Alcohol Syndrome (OR = 30.0), an Attachment Disorder (OR = 23.4), an Anxiety Disorder (OR = 2.4) specifically Post-Traumatic Stress Disorder (OR = 10.0), a Cognitive Delay (OR = 8.0), Sensory Integration Disorder (OR = 7.8), Tourette Disorder (OR = 6.3), Bipolar Disorder (OR = 5.5), a visual impairment (OR = 3.3), or ADHD (OR = 2.6). The birth mother of Adoptive children had lower incomes and education but family income did not currently differ between Adoptive and Comparison children. Only half of Adoptive respondents were able to provide information about prenatal exposures to illicit drugs  and even fewer could definitively answer items regarding alcohol or nicotine. The majority of Adoptive, relative one fifth or less of Comparison children, had been exposed to alcohol, nicotine or methamphetamine during pregnancy. Prenatal marijuana, cocaine, barbiturates, and Oxycontin exposures were also more common among Adoptive children. Methamphetamine and nicotine exposures were also prevalent in Adopted, but not Comparison, children in the third trimester . rimester .d = .86), Externalizing (d = .91), and Internalizing (d = .63) problems than Comparison boys. Other group differences included Aggressive Behavior (d = .98), Impulsivity (d = .97), Social Problems (d = .97), and Anxiety/Depression , Externalizing (d = .71), and Internalizing (d = .38) problems than Comparison girls (d = 0.89 to 1.27). Among Comparison children, boys showed the anticipated increase in Attention Problems (t(482) = 2.91, P<.005), specifically Inattention Problems (t(486) = 2.45, P<.05) as well as Thought Problems (t(481) = 2.13, P<.05) relative to Comparison girls. Conversely, Comparison girls exhibited the expected increase relative to boys for Anxiety and Depression (t(486) = −2.77, P<.01). However, no sex differences were present among Adopted children. Adopted boys and girls more frequently had clinically significant Attention and Aggression problems but only boys had more Social and Anxiety/Depression problems and only girls had more Thought Problems (P>.11).Adopted boys were rated at having more Attention  and Internalizing (d = 0.16) in adopted, relative to nonadopted children d = .16) and anxiety/depression (d = .16) but no significant elevations at this age (3 and 5) in Attention or Externalizing problems The principal findings of this report are that adoptive children, the majority of whom had a history of prenatal exposure to methamphetamine, nicotine, and alcohol, exhibited a pronounced and diffuse elevation in problems with executive function as well as psychiatric symptomology. Importantly, adoptive children have been included in the samples of several behavioral teratology reports 50<55) among school aged children unless they were adopted after age 1.5 in which case the averages were still below the clinical cut-off Polysubstance exposed adoptive children also exhibited statistically and clinically significantly higher (i.e. more problematic) executive function ratings. In contrast to the substantial wealth of prior research with the CBCL, the available information using the BRIEF is much more limited. Importantly, the preschool version of this instrument has been employed to examine internationally adopted children, albeit with an unknown prenatal history, and identified relatively subtle group differences. Only 11% of adoptees from a variety of countries fell into the problem range on the Global Executive Composite The large group difference identified between Adopted/polysubstance exposed and comparison children is also of interest when considering findings observed following exposure to other recreational drugs and at different ages. There were significant BRIEF elevations among methamphetamine/alcohol/nicotine exposed children (ages 7 to 9) living with their birth parents which tended to be more severe among adoptive/exposed children Sex differences are clearly evident in the prevalence of a wide variety of psychiatric conditions including disorders like ADHD which rely on executive function There are many ambiguities and uncertainties associated with studies of adopted children and some limitations as well as future directions are noteworthy. One ongoing challenge in determination of the risks associated with recreational drug use during pregnancy, and particularly among children who were subsequently adopted, is the veracity of information about the timing and intensity of substance abuse. Although hair analysis provides a long window of detection (months) and this technology is rapidly advancing for detection of methamphetamine In conclusion, adoptive children with histories of prenatal exposure to recreational drugs had statistically and substantially greater difficulties with executive (or self-regulatory) and behavioral functioning as assessed by parent ratings relative to a nonadopted comparison group, and the proportion of adopted children with clinically significant psychopathology  was also much greater. The CBCL and BRIEF have been employed previously with adopted children and do not show group differences of the magnitude reported here indicating that other factors are responsible. Adoptive children are not a homogenous group Figure S1Behavioral Rating Inventory of Executive Function  and Child Behavior Checklist  ratings with of Adoptive (filled bars) and Comparison (open bars) with ADHD children excluded . BRIEF Indexes and Scales: Global Executive Composite (GEC), Behavioral Regulation Index (BRI), Inhibit (INH), Shift (SHI), Emotional Control (EC), Metacognition Index (MI), Initiate (INI), Working Memory (WM), Plan Organize (PO), Organization of Materials (OM), and Monitor (MON). CBCL Indexes and Scales: Attention (Att), Inattention (Ina), Impulsivity (Imp), Social (Soc), Thought (Tho), Externalizing (Ext), Rule Breaking (RB), Aggression (Agg), Internalizing (Int), Anxious-Depressed (Anx), Withdrawn-Depressed (Wtd), Somatic Complaints (SC), or Other Problems (OP).(TIF)Click here for additional data file.Table S150) scores by offspring age and parental relationship.Behavioral Rating Inventory of Executive Function standardized (T(DOCX)Click here for additional data file.Table S250>63) problems on the Child Behavior Checklist by offspring age and parental relationship.Percentage of Adopted and Comparison children with clinically significant (T(DOCX)Click here for additional data file.Data S1Raw data from Study I.(SYZ)Click here for additional data file.Data S2Raw data from Study II.(SYZ)Click here for additional data file.Materials S1(PDF)Click here for additional data file.


We investigated whether a relationship between small airways dysfunction and bronchial hyperresponsiveness (BHR), expressed both in terms of ease of airway narrowing and of excessive bronchoconstriction, could be demonstrated in asthma.1 92% pred ±14; FEV1/FVC 75% ± 8) underwent the methacholine challenge test (MCT). The degree of BHR was expressed as PD20 (in μg) and as ∆FVC%. Peripheral airway resistance was measured pre- and post-MCT by impulse oscillometry system (IOS) and expressed as R5-R20 (in kPa sL−1).63  stable, mild-to-moderate asthmatic patients (FEV20 < 1600 μg) with a PD20 geometric (95% CI) mean value of 181(132–249) μg and a ∆FVC% mean value of 13.6% ± 5.1, ranging 2.5 to 29.5%. 30 out of 63 patients had R5-R20 > 0.03 kPa sL−1  and showed ∆FVC%, but not PD20 values significantly different from the 33 patients who had R5-R20 ≤ 0.03 kPa sL−1  μg vs 207 (134–322) μg, p = 0.382). In addition, ∆FVC% values were significantly related to the corresponding pre-  and post-MCT  R5-R20 values.All patients showed BHR to methacholine (PDOur results show that in asthmatic patients, small airway dysfunction, as assessed by IOS, is strictly associated to BHR, expressed as excessive bronchoconstriction, but not as ease of airway narrowing. The two groups of patients significantly differed in ∆FVC% value (p < 0.01), but not in PD20, in DRS and in spirometry values   and that of patients with poorly controlled asthma (ACT ≤ 19) were significantly lower in patients with R5-R20 > 0.030 kPa s l−1, as compared to the patients with R5-R20 ≤ 0.030 kPa s l1 .When patients were categorized by R5-R20 upper limit of normality , 30 out 25–75 values. In addition, according to the ROC curve method, the plot of the true positive rate in function of the false positive rate for different cut-off points of ∆FVC% with respect to R5-R20 > 0.03 kPa s l-1, as threshold value, showed a 0.758 (p < 0.01) area under curve value. The ∆FVC% cut-off point, which maximized sensitivity and specificity, was ≥ 14.5% (0.67 sensitivity and 0.76 specificity).In all patients, ∆FVC% values were significantly related to the corresponding pre-  and post-MCT  R5-R20 , which in turn were smaller than small-particle (1.06 μM) PC20 values. These findings imply that the airway hyperresponsiveness degree is dependent on the particle size of the inhaled broncoconstrictor agent and, in this case, that small airways also do not show a similar severity of hyperresponsiveness compared to large airways. In our study, we used the MB3 Mefar Dosimeter, a largely used dosimeter, which at the recommended driving pressure of 180 kPa can assure an output with particle size within the respirable range (<5 μM) [Methacholine challenge testing is being used to assess hyperresponsiveness of the entire bronchial tree both in the clinical and research setting. However, whether deposition and effect of inhaled particles of the bronchoconstrictor agent may occur even in the small airways is still open to debate, by relying on different factors, such as inhalation manoeuver and particle size, which is in turn mainly determined by the nebulizer output. In patients with asthma, Cohen et al.  investig (<5 μM) . Accordi20 value is measurable in the vast majority of asthma patients during the methacholine challenge, a significant ∆FVC% value is not always detectable in asthmatic patients. In the present study, the ΔFVC values ranged from 2.5 to 29.5% with a mean value of 13.6% ± 5.1 and a normal frequency distribution. Our findings are very similar to those by Gibbons et al. [20 values. Patients with the same value of PD20 may show different falls in FVC during methacholine challenge (Figure in vivo is a composite functional disorder and that the mechanisms underlying excessive bronchoconstriction and ease of airway narrowing during the methacholine challenge are different. In our study, we also found that the ΔFVC% was significantly higher in patients with poorly controlled disease, as compared to well-controlled patients. These results are consistent with the findings of previous studies [While a PDs et al. , who pres et al. , we also studies  that rel−1, patients with R5-R20 > 0.030 kPa s l−1 had a high likelihood to be associated to a ∆FVC% greater than 14.5% during a methacholine-induced bronchoconstriction. Moreover, in all patients we found a significant relationship between the baseline values both of the peripheral airway resistance and reactance, expressed respectively by R5-R20 and X5, and ∆FVC%. Three mechanical factors are called upon to explain the excessive airway narrowing in asthma: an increased contractility of airway smooth muscle induced by humoral mediators or abnormalities in neural control; a lack of a normal inhibiting factor which can prevent further shortening when the smooth muscle begins to shorten, so that the muscle never develops maximum force and degree of shortening; a decrease in elastic load, provided by cartilage and the surrounding parenchyma, so that it is easier to narrow an asthmatic bronchus as compared to a normal bronchus [in vivo, the small airway reactivity to histamine was significantly enhanced in asthmatic patients relative to normal controls with Isoproterenol being able to completely reverse the increase in peripheral airway resistance in the latter, but not in the former [In the present study, we provide the first evidence that in asthmatic patients excessive bronchoconstriction expressed by ΔFVC% is strictly associated to small airway dysfunction, as assessed by IOS. As compared to patients with R5-R20 ≤ 0.030 kPa s lbronchus . It is cbronchus –30 and rbronchus ,32. Thuse former .1 and FEV1/SVC. This is not surprising since patients with severe asthma may show similar airflow obstruction, but significantly increased air trapping, as compared to patients with non severe asthma [In line with previous studies, which showed a relationship between small airway dysfunction, as assessed by IOS, and uncontrolled disease, both in adults ,3 and ine asthma . Moreovee asthma . Interese asthma . Air trae asthma .The present study shows that mild-to-moderate asthmatic patients with small airway dysfunction, as assessed by IOS, have excessive bronchoconstriction during the methacholine challenge, which is an important index of disease severity. Though association does not imply causality, the results of our study suggest a significant contribution of small airways in the pathophysiology of bronchial hyperresponsiveness. This fact may have implications for the treatment of asthmatic patients by increasing in importance the small-particle aerosols.


Noticeably, the SnC2Cl, SnC2Br, and SnC2I are QSH insulators with a bulk gap of ~0.2 eV, while the SnC2H and SnC2F can be transformed into QSH insulator under the tensile strains. A single pair of topologically protected helical edge states is established for the edge of these systems with the Dirac point locating at the bulk gap, and their QSH states are confirmed with topological invariant Z2 = 1. The films on BN substrate also maintain a nontrivial large-gap QSH effect, which harbors a Dirac cone lying within the band gap. These findings may shed new light in future design and fabrication of large-gap QSH insulators based on two-dimensional honeycomb lattices in spintronics.Quantum spin Hall (QSH) insulators feature edge states that topologically protected from backscattering. However, the major obstacles to application for QSH effect are the lack of suitable QSH insulators with a large bulk gap. Based on first-principles calculations, we predict a class of large-gap QSH insulators in ethynyl-derivative functionalized stanene (SnC To date, quantized conductance through QSH state has only been experimentally observed in HgTe/CdTe79Topological insulators (TIs)123135Generally, a good QSH insulator should be easily synthesized and have a large bulk band gap to realize the spin transport at high temperatures. Controlling the chemical bonding at atomic levels to induce the band inversion by orbital selection3811121314161820233), another organic molecule, has also been suggested as a promising tool to stabilize 2D systems, such as methyl-functionalized germanane (GeCH3)3)3 film has been synthesized in recent worket al.2H) can be applied to stabilize stanene by decoration on its surface, and its band gap in TI states reaches up to 0.3 eV. However, the QSH phase is not intrinsic, but driven by the external strain, thus is unfavorable for practical applications in spintronics. Here, we extend these into ethynyl-derivative functionalized films , making the experimental observation facile. The SnC2Cl, SnC2Br, and SnC2I are all QSH insulators with a bulk gap of ~0.2 eV, while the SnC2H and SnC2F can be transformed into QSH insulator under the tensile strains. The topological characteristic of these films is attributed to s-pxy band inversion related to the honeycomb symmetry, while the effect of SOC is only to open up a large gap. We also propose high-dielectric BN as an ideal substrate for the experimental realization of these films, maintaining its nontrivial topology. These results have potential applications in low-power quantum electronics and may enable topological quantum computing based on Majorana fermionsRecently, the small molecule functionalization has been the focus to enhance the geometric stability and nontrivial band gap of new 2D films. For instance, Methyl  is the anti-binding s state. Thus, no inverted band order is observed, suggesting that it is a trivial TI phase. However, if applying the tensile strain (ε = 4%), the s-p band inversion appears, with an indirect-gap of 0.22 eV opened under SOC effect, as illustrated in 2 invariants v, as listed in 1  and M2  are both 1, while at the M3  shows −1, which give Z2 = 1. Therefore, it directly confirms the existence of QSH insulator state.To get a preliminary insight into the topological properties, we present the calculated band structures of SnC2H maintaining the crystal symmetry by changing its lattices as ε = (a − a0)/a0, where a (a0) is the strained (equilibrium) lattice constants. In what follows, we systematically investigate the effects of both uniaxial and biaxial strains on topological properties of SnC2H. EΓ) at Γ point and bulk gap  as a function of the biaxial strain. One can see that, both the direct and indirect band gaps in TI phase decrease steadily with respect to strain, especially Eg and EΓ being equal to strain beyond 30%. Remarkably, for ε = 3%, we find the largest gap of ~0.33 eV opened at Γ point, along with a global indirect band gap of ~0.22 eV, which is significantly greater than kBT (~26 meV). While the biaxial strain is compressed to ε = −4%, we find that no inverted band order is observed, suggesting that it is a trivial QSH insulator (ε = 18%), which is almost twice the one of biaxial strain. Further analysis of the parity eigenvalue gives Z2 = 1, which suggests that the uniaxial strain is also efficient way to tune QSH state in these films.The buckled configuration generally sustain a larger mechanical strain than planner one, thus we explore the variations of electronic structure with respect to the mechanical strain30313233nsulator . On the 2F, -C2Cl, -C2Br, and -C2I. We thus perform calculations for SnC2X  films to check their topological properties. 2H, for SnC2F, it is a trivial QSH phase at the equilibrium state, but can be driven to QSH phase at the biaxial tensile strain ε > 2%. However, for the other SnC2X  films, they are TI phases at the equilibrium state with Z2 = 1, as listed in 2Cl, SnC2Br, and SnC2I are 0.19, 0.20, and 0.23 eV, respectively, . Also, as can be seen in Fig. S3, the systematically investigate the effects of both uniaxial and biaxial strains on topological properties of SnC2F, SnC2Cl and SnC2I, respectively, which are sufficiently tunable ranges of strain for practical applications at high temperature.The calculated band structures of SnCl strain , we cons2H and SnC2Br with the external strain ε = 2% and ε = 0%, respectively, to introduce edges on stanene by forming the zigzag-type nanoribbons, as shown in 2X  films, where a Dirac point at the Γ point is located inside the band gap with a high velocity of ~1.0 × 105 m/s and ~2.0 × 105 m/s, comparable to that of 5.5 × 105 m/s in HgTe/CdTe quantum well4 m/s in InAs/GaSb quantum well2X  are also displayed in Fig. S4. All these band structures maintain topologically protected conducting edge states that are helical, thus providing enticing concepts for novel quantum electronic devices with low energy dissipation.The QSH phase should support topologically protected conducting edge states that are helical with the spin-momentum locked by TRS. To demonstrate these edge states explicitly, we take SnC2X  films under the critical strain are presented in Fig. S3 in s-px,y band order is not changed and in agreement with those obtained from PBE, indicating the PBE results are qualitatively reasonable and reliable.It is known that GGA method usually underestimates the band gap, we thus carried out test computations based on the hybrid functional HSE06372X films. s and Sn-5px,y orbitals. Thus, the chemical bonding between Sn-Sn atoms makes them split into the bonding and antibonding states, i.e., s± and px,y±, where the superscripts + and − represent the parities of corresponding states, respectively. At zero strain in px,y+ and s−, with the s− being above the px,y+, indicating a normal band order, as shown in SnC2H. When considering the tensile strain, as seen in s− level and raises px,y+ level accordingly. Thus, depending on the strength of interatomic coupling, the band gap of SnC2H can be continuously reduced, with the band order being reversed at critical point, making it a topological insulator with Z2 = 1. Taken together, the level crossing leads to a parity exchange between occupied and unoccupied bands, inducing a TI phase transition. While for SnC2Br, the lattice constant at equilibrium state is equal to strain-induced SnC2H (ε = 4%), thus it is a QSH insulator. As a result, the s-p band inversions-px,y band inversion is caused mainly by the strength of interatomic coupling, the SOC is still indispensable because it makes the px,y+ orbital split into p+x + iy, ↑ & p+x−iy, ↓ and p+x−iy, ↑ & p+x+iy, ↓, opening a larger band gap. In previous works, the topological states are usually originated from pz system such as graphene and silicene of which the nontrivial gaps are often very smallpx,y orbitals on Sn atoms, where the large SOC is from the on-site SOC, instead of the next-nearest-neighbor SOC in the pz casesTo better understand the physical origin of QSH states, we next do an orbital analysis around the Fermi level for SnC2X films are obtained in free-standing structure, their nontrivial QSH would be robust when they are on the substrate, because their band inversion occurs at Γ point rather than at K point, as well as the full saturation of Sn-pz orbitals ensures a weak interaction with the substrate. Here, we select h-BN as a possible substrate to form SnC2Br@BN heterostructure (HTS), where the lattice mismatch is only about 1.19% (SnC2Br) in comparison to h-BN(2 × 2) sheet, showing that they are feasible to grown on the h-BN substrate. To correctly describe the effect of van der Waals (vdW) interaction, we employ a dispersion-corrected DFT method (optB88-vdW)41d) between adjacent layers is 3.278 Å. The calculated binding energy is found to be −71 meV, suggesting a typical vdW HTS. In 2Br film. Bader analysis2Br film. In comparison to the free-standing film, little difference is observed between them. As a result, it is indeed a robust QSH insulator with band inversion not being affected by the h-BN substrate. Similar electronic properties of SnC2X@BN  HTSs are obtained, as shown in Fig. S6.On the experimental side, choosing the suitable substrate material is a key factor in device application, since a free-standing film must eventually be deposited or grown on a substrate. It is known that the QSH features in pristine graphene and germanene12131415162X films with sizable bulk gaps, making the experimental observation facile. Noticeably, the SnC2Cl, SnC2Br, and SnC2I are all QSH insulators with global gaps of ~0.2 eV, while the SnC2H and SnC2F can be transformed into QSH insulator under the tensile strains. This large-gap opening is mainly attributed to the result of the strong SOC related to the px and py orbitals of Sn atoms at Γ point, significantly different from that of the pz orbital as in pristine group IV ones. A single pair of topologically protected helical edge states are established for the edge of these systems with the Dirac point locating at the bulk band gap, and their QSH states are also confirmed with Z2 = 1. Also, these films on h-BN substrate are observed to support a nontrivial large-gap QSH, which harbors a Dirac cone lying within the band gap. These findings may shed new light in future design and fabrication of large-gap QSH insulators based on 2D honeycomb lattice in spintronics.To conclude, on the basis of first-principles calculations, we predict a class of new QSH insulator of SnC2X films, we employed state-of-the-art ab initio simulations, based on density functional theory (DFT) as implemented in VASP44−6 eV. The Brillouin zone was sampled by using a 21 × 21 × 1 Gamma-centered Monkhorst-Pack grid. The vacuum space was set to 20 Å to minimize artificial interactions between neighboring slabs. SOC was included by a second vibrational procedure on a fully self-consistent basis. With the optimized structures, the more sophisticated HSE06 hybrid functional372 index of the inversion symmetric 2D materials, the invariants v can be derived from the parities of wave function at the four TRIM points Ki, namely one Γ point and three equivalent M points in the Brillouin zone. The topological invariant ν was determined based on the Fu-Kane’s formulaTo study the structural and electronic properties of SnCδ is the product of parity eigenvalues at the TRIM points, ξ =  ±1 are the parity eigenvalues and N is the number of the occupied bands. According to the Z2 classification, ν = 1 characterizes a QSH insulator, whereas ν = 0 represents a trivial band topology.where How to cite this article: Zhang, R.-w. et al. Room Temperature Quantum Spin Hall Insulator in Ethynyl- Derivative Functionalized Stanene Films. Sci. Rep.6, 18879; doi: 10.1038/srep18879 (2016).


Intelligence is an important human feature that strongly affects many life outcomes, including health, life-span, income, educational and occupational attainments. People at all ages differ in their intelligence but the origins of these differences are much debated. A variety of environmental and genetic factors have been reported to be associated with individual intelligence, yet their nature and contribution to intelligence differences have been controversial.APOE) genotype, which is associated with the risk for Alzheimer’s disease, as well as demographic and lifestyle characteristics, to the variation in intelligence.To investigate the contribution of apolipoprotein E  was used to determine the intelligence level of participants. Demographic and lifestyle characteristics data were obtained from self-administered questionnaires.APOE polymorphic alleles and different intelligence quotient (IQ) measures. Interestingly, a portion of demographic and lifestyle characteristics, including age, smoking and sleep quality were significantly associated with different IQ measures.No significant association was found between APOE genotype, are associated with intelligence measures among young Chinese college students. Thus, although APOE ε4 allele is a strong genetic risk factor for Alzheimer’s disease, it does not seem to impact intelligence at young ages.Our findings indicate that demographic features and lifestyle characteristics, but not  APOE), a strong genetic risk factor for Alzheimer’s disease (AD), are more likely to have faster cognitive decline [Intelligence is the ability to learn from experience and to learn and adapt to changing environment. It predicts a wide range of social outcomes. People with higher intelligence tend to perform better in educational attainment, income, health and longevity . Individ decline , 10.APOE gene exists as three polymorphic alleles—ε2 , ε3 , and ε4 —which have a worldwide frequency of 8.4%, 77.9% and 13.7%, respectively [APOE polymorphic alleles are the main genetic determinants of AD risk [APOE dramatically increases the risk of developing AD in a gene dose-dependent manner. The mean age of onset and frequency of AD are 68 years and 91% in ε4 homozygotes, 76 years and 47% in ε4 heterozygotes, 84 years and 20% in ε4 non-carriers [APOE has a protective effect against developing AD [APOE ε4 allele also accelerates cognitive decline in elderly non-demented individuals [APOE genotype influences cognitive function or related measures at early ages is less clear.ApoE is a major cholesterol carrier and plays an important role in maintaining brain lipid homeostasis . The hums—ε2 Cys1, Cys158, AD risk . The ε4 s—ε2 Cys1, Cys158,oping AD –18, and oping AD , glucoseoping AD , neuroinoping AD , and mitoping AD , 24. Mecoping AD . In addiividuals . HoweverAPOE alleles on cognition at an early age is of particular interest as it would potentially aid mechanistic understanding of the function of apoE; however, there have been relatively few studies examining the association of APOE polymorphic alleles with cognitive function in young adults. Within the few existing literature, there remain large discrepancies concerning the effect of APOE genotype on cognitive performance in early life [APOE genotype and intelligence-test scores among Chinese college students aged 18 to 25 years old. We also examined the associations of demographic and lifestyle characteristics with intelligence-test scores to further understand the mechanism underlying individual intelligence differences.Studying the influence of rly life –29. TherApproval for this study was obtained from the ethics committees of Xiamen University and AnFang College. All individuals who participated in this study gave written informed consent.A total of 607 Chinese college students aged 18 to 25 years old from Xiamen University (N = 433) or AnFang College (N = 174) in the southeast city of Xiamen, Fujian Province were included in this prospective observational study. In addition to intelligence-test scores , demographic and lifestyle characteristics data were obtained from self-administered questionnaires. Demographic information was collected regarding age, gender, height, weight, and body mass index (BMI). Lifestyle factors that were collected included personality (introvert or extrovert), smoking (No or Yes), alcohol consumption (No or Yes), physical exercise , and sleep quality .The Chinese revision of Wechsler Adult Intelligence Scale  was used to determine the intelligence level of participants. The scores are summed into four indexes  and one Full Scale IQ which ranges from the lowest 72 to the highest 152 points.APOE SNPs (rs429358:T/C and rs7412:C/T) was carried out using the APOE SNP genotyping kits  and the Applied Biosystems® 7500 Real-Time PCR Systems . Data analysis was performed by measuring the allele-specific fluorescence. The genotyping analysis had been repeated at least twice, and was blind to different investigators. Additionally, three samples with known APOE genotypes were included in each assay. Finally, 10% of the total samples were randomly selected and retested with 100% concordance.Genomic DNA was extracted from saliva samples using a DNA extraction kit . Genotyping of the two APOE ε4. Similarly, since only 4 students had an ɛ2/ɛ2 genotype, a dominant model was used in all analyses where the focus was APOE ɛ2. We examined the associations of APOE ε4 allele with Full Scale IQ and each of the four indexes using single variable (i.e. unadjusted) and multivariable linear regression models. Multivariable models were adjusted for school (Xiamen University or AnFang College), age, gender, height, weight, BMI, personality, smoking, drinking, physical exercise, and sleep quality in order to account for the potential confounding influences of these variables. Associations between APOE ε2 and IQ measures were evaluated in a similar manner.Continuous variables were summarized with the sample median, minimum, first quartile, third quartile, and maximum. Due to the small number of students with an ε4/ε4 genotype (N = 7), we utilized a dominant model  in all analyses where the primary interest was APOE ε4 or ε2 with IQ measures (5 tests of association were performed for ε4 or ε2), while p-values of 0.005 or lower were considered as significant when examining associations of demographic and lifestyle characteristics with IQ measures (10 tests of association were performed for each IQ measure). All statistical analysis was performed using SAS .Associations of demographic and lifestyle characteristics with Full Scale IQ and each of the four indexes were also evaluated using single variable and multivariable linear regression models, where multivariable models were adjusted for age, gender, height, weight, BMI, personality, smoking, drinking, physical exercise, and sleep quality. Regression coefficients and 95% confidence intervals (CIs) were estimated in all linear regression analysis, where regression coefficients are interpreted as the change in the mean IQ measure corresponding to the specified increase (continuous variables) or presence of the given characteristic . In order to adjust for multiple testing, we utilized a Bonferroni correction separately for each group of similar tests. Specifically, p-values of 0.01 or lower were considered as statistically significant when evaluating the associations of APOE genotype distributions were ε2/ε2 for 4 students (0.7%), ε2/ε3 for 72 students (11.9%), ε2/ε4 for 12 students (2.0%), ε3/ε3 for 412 students (67.9%), ε3/ε4 for 100 students (16.5%), and ε4/ε4 for 7 students (1.2%). Therefore, allele frequencies for ɛ2, ɛ3 and ɛ4 were 7.6%, 82.0%, 10.4%, respectively.As shown in Associations of demographic and lifestyle factors with the five different IQ measures from multivariable analysis are displayed in APOE ε4 allele and each of the five different IQ measures was shown in APOE ε4 and Full Scale IQ (P = 0.70), VCI (P = 0.43), WMI (P = 0.44), PSI (P = 0.57), PRI (P = 0.94). This lack of an association between APOE ε4 and the different IQ measures was consistent in multivariable analysis which adjusts for the potential confounding influences of school, age, gender, height, weight, BMI, personality, smoking, drinking, physical exercise, and sleep quality  [Human apoE is polymorphic with three common isoforms that have different effects on lipid and neuronal homeostasis. ctively) .APOE ε4 has extensive deleterious effects on several biological processes. The possession of at least one ε4 allele increases three-fold for the risk of AD [APOE ε4 appears to be less efficient in delivering cholesterol and essential lipids for maintenance of synaptic integrity and plasticity than APOE ε2 and ε3 [APOE ε4 has also been experimentally related to exacerbated pro-inflammatory and/or reduced anti-inflammatory functions [APOE ε4 seems to be protective against infectious diseases such as hepatitis C virus and malaria [APOE ε4 allele on cognitive function in the elder people is well-characterized [APOE ε4 on cognitive abilities in young population reported inconsistent results. Young adults and children carrying the ε4 allele were reported to exhibit better cognitive performance compared to non-ε4 carriers [APOE genotype.Numerous studies have demonstrated that sk of AD . Moreove2 and ε3 , 32. APOunctions , 33. How malaria , 35. Thecterized , 10, butcarriers , 27, 36.carriers –39. The We found evidence of associations between demographic and lifestyle characteristics with different IQ measures. Intriguingly, smoking was found to be associated with significantly lower IQ scores. The relatively small sample size of our studied population would not allow us to distinguish heavy or light smokers according to the amount of cigarette consumption. Nonetheless, our results are consistent with previous report that smoking was associated with impairments in cognitive function . We alsoAPOE ε4 allele, a major genetic risk factor for AD, is not notably associated with IQ scores in a cohort of 607 Chinese college students aged 18 to 25 years old. Although we cannot exclude the possibility of a small association between APOE ε4 and IQ scores given our results, based on 95% confidence limits we can reasonably conclude that a moderate or strong association is unlikely. Similarly, the APOE ε2 did not appear to be associated with any of the IQ measures that were examined. However, we did identified several significant associations of demographic and lifestyle characteristics with the different IQ measures. This study partially advances the understanding of individual intelligence differences and might help to ameliorate declines in cognitive function by adjusting lifestyles.In summary, the results of our current study indicate that the S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.


Acinonyx jubatus, 1–45 kg for leopard Panthera pardus, 32–632 kg for lion Panthera leo, 15–1600 kg for spotted hyaena Crocuta crocuta and 10–289 kg for wild dog Lycaon pictus. An assessment of carnivore diets throughout Africa found these accessible prey weight ranges include 88±2% (cheetah), 82±3% (leopard), 81±2% (lion), 97±2% (spotted hyaena) and 96±2% (wild dog) of kills. These descriptions of prey weight preferences therefore contribute to our understanding of the diet spectrum of the five large African carnivores. Where datasets meet the minimum sample size requirements, the segmented model approach provides a means of determining, and comparing, the prey weight range preferences of any carnivore species.Broad-scale models describing predator prey preferences serve as useful departure points for understanding predator-prey interactions at finer scales. Previous analyses used a subjective approach to identify prey weight preferences of the five large African carnivores, hence their accuracy is questionable. This study uses a segmented model of prey weight versus prey preference to objectively quantify the prey weight preferences of the five large African carnivores. Based on simulations of known predator prey preference, for prey species sample sizes above 32 the segmented model approach detects up to four known changes in prey weight preference (represented by model break-points) with high rates of detection  and accuracy (within 1.3±4.0 to 2.7±4.4 of known break-point). When applied to the five large African carnivores, using carnivore diet information from across Africa, the model detected weight ranges of prey that are preferred, killed relative to their abundance, and avoided by each carnivore. Prey in the weight ranges preferred and killed relative to their abundance are together termed “accessible prey”. Accessible prey weight ranges were found to be 14–135 kg for cheetah  Carnivore numbers are declining globally, with a reduction in distribution and abundance leading to almost a quarter of species now being threatened with extinction Acinonyx jubatus, leopard Panthera pardus, lion Panthera leo, spotted hyaena Crocuta crocuta and African wild dog Lycaon pictusThe concept of prey preference is useful in identifying which prey are likely to be targeted by a predator, as it identifies prey which comprise a greater proportion of a predator’s diet than expected according to the prey item’s relative abundance in the prey community Despite the questionable accuracy of these weight ranges, they are serving as a point of departure for a wide range of applications, including ecological studies Commonly used preference indices such as the forage ratio and Ivlev’s electivity index ip  and the proportion of carnivore kills that prey species i comprises, i,r to a value between +1 and −1. The literature was reviewed by Hayward and colleagues J.I. standardizes the relationship between a prey species’ relative abundance at a site, To explain our approach for determining the preferred prey weight range of each large carnivore, we use two hypothetical predators which have 10 prey species available to them, each differing in weight by 1 kg and weighing between 51 kg and 60 kg. First we consider a situation in which a predator displays equal preference for all 10 species. If the mass of each prey species was regressed against a measure of prey preference  for that species plus the preference values of all smaller species, this regression would be positive and linear , this is unlikely to be the norm in real prey communities. Let us again consider a hypothetical predator which has ten prey species weighing between 51 and 60 kg available to it, and which prefers those weighing 51 to 55 kg twice as much as those weighing more than 55 kg. Consider a prey community in which the prey masses are not evenly distributed, with seven of the ten species weighing 53 kg or less. In such a situation, break-points representing changes in slope do not reflect changes in preference alone (as intended), but are confounded by prey mass groupings which influence the slope of the relationship . In ordeCalculating the predator’s preference for identified weight ranges section below). Changes in preference, and thus break-points in the relationships, therefore exist between these prey groups. For each simulation, we randomly selected a total prey species sample size between six and 100, and these species were randomly allocated between the preference groups (between two and five preference groups). For each break-point assessment (one to four breaks) we conducted 1000 simulations. For each simulation, we assigned a categorical integer value to each prey species, commencing at 1 for the first randomly generated species in the first group and ending with the last randomly generated species in the last group. We fitted a segmented model to the relationship between prey preference  and prey categorical value and determined how many break-points were detected and at what prey categorical value they were detected. We calculated the percentage of simulations in which the correct number of break-points was detected and related this to the minimum number of species occurring within a preference group. The ability of the segmented model to detect all break-points increased with an increase in the minimum number of species within any preference group. Therefore, the accuracy of break-point detection can be assessed as a function of the total minimum sample size, determined by multiplying the minimum sample in the smallest preference group by the number of groups. Break-point detection accuracy was assessed by calculating, for each simulation which met the minimum sample size requirements, the absolute difference in prey species categorical value between the known break-point and the detected break-point. These models were conducted in the open source statistical package R (R Development Core Team 2012) using the segmented generalized linear model function in the “segmented package” . We simulated prey preference datasets with one, two, three and four known changes in preference, as four was the maximum number of break-points detected for the five large African carnivores (see results). Predator prey preference was simulated by randomly generating between two (for one change in preference) and five (for four changes in preference) sets of J.I. values. The first and fifth (where relevant) sets of J.I. values were randomly generated between −1 and −0.3; the second and fourth (where relevant) sets with J.I. values between −0.3 and 0.3 and the third (where relevant) set with J.I. values between 0.3 and 0.85 . These sets represent prey groups that are avoided (first and fifth set), killed relative to their abundance (second and fourth set) and preferred  and censused prey community (ip) in each prey weight range i at each site listed in As a segmented model was the best-fit function for all five carnivores, mass-ranks at which the best-fit model detected break-points were then translated back into actual prey masses , prey species weighing between 14 kg and 40 kg are preferred , prey species weighing between 40 kg and 135 kg are killed relative to their abundance in the prey community  and prey species weighing more than 135 kg are avoided . These occur at a prey species mass-rank of 12.8, 21.3, 32.8 and 39.8, corresponding to a prey species mass of 14 kg, 40 kg, 135 kg and 319 kg, respectively . Prey spt = −2.07, d.f. = 15, p = 0.06), prey species weighing between 15 kg and 45 kg are preferred  and prey species weighing more than 45 kg are avoided . These occur at a prey species mass-rank of 18.5, 28.0 and 41.8, corresponding to a prey species mass of 15 kg, 45 kg and 325 kg, respectively . Prey spW = 1, n = 10, p<0.01; 13 kg to 32 kg: J.I. = −0.63±0.07, W = 55, n = 42, p<0.001), prey species weighing between 32 kg and 92 kg are killed relative to their abundance , prey species weighing between 92 kg and 632 kg are preferred  and prey species weighing more than 632 kg are avoided . These occur at a prey species mass-rank of 5.4, 12.0, 19.6 and 30.4, corresponding to a prey species mass of 13 kg, 32 kg, 92 kg and 632 kg, respectively . Prey spW = 9, n = 13, p = 0.01), prey species weighing between 15 kg and 91 kg are consumed relative to their abundance , prey species weighing between 91 kg and 139 kg are preferred  and prey species weighing more than 139 kg are consumed relative to their abundance . These occur at a prey species mass-rank of 6.2, 17.9 and 20.7, corresponding to a prey species mass of 15 kg, 91 kg and 139 kg, respectively . Prey spW = 7, n = 11, p = 0.02), prey species weighing between 10 kg and 31 kg are preferred , prey species weighing between 31 kg and 289 kg are killed relative to their abundance  and prey species weighing more than 289 kg are avoided . These occur at a prey species mass-rank of 7.0, 14.7 and 34.6, corresponding to a prey species mass of 10 kg, 31 kg and 289 kg, respectively . Prey spt = −6.37, d.f. = 13, p<0.001; leopard: t = −7.10, d.f. = 20, p<0.001; lion: t = −9.01, d.f. = 31, p<0.001; spotted hyaena: t = −22.72, d.f. = 6, p<0.001; wild dog: t = −3.26, d.f. = 6, p = 0.01; The accessible prey weight ranges identified in this study account for, on average, more than 80% of each carnivore’s diet at test sites, with standard errors less than 4% . The accThis study’s use of a segmented model to recalculate the prey weight preferences of the five large African carnivores is objective. It is based on statistically determined changes in prey preference, adhering to minimum species sample size requirements determined using simulations of known prey preference. In contrast, the previously used distance-weighted-least-squares method is subjective and based on a non-statistical, subjectively determined “most preferred” prey weight range Obtaining a broad-scale understanding of predator prey preference requires the use of data from multiple sites. Determining the accuracy of prey species abundances in such data is challenging. For this reason, this study utilizes data from a large sample of studies , and meaWhile variables besides prey size will also influence prey preference at a local scale , broad-scale models such as those presented here provide robust departure points against which hypotheses regarding predator-prey interactions at a finer scale can be formulated e.g. . SimilarPreferred prey are likely to be those that a predator has evolved to optimally hunt By additionally determining which prey are consistently avoided, this study quantified the upper prey mass threshold, above which the cost of prey capture outweighs the benefit of consuming these large-bodied prey species, thus making them generally inaccessible to the predator. Of the five large African carnivores, only spotted hyaena did not display this avoidance for prey above a certain mass-threshold. Spotted hyaena are known to scavenge, and therefore may consume prey larger than that which they could physically capture While lion, cheetah and wild dog kill data did not include scat analyses, observation data can also include scavenged prey in instances where data are from observations of carnivores on a kill, as opposed to making a kill. This is unlikely to be an issue for the prey weight preference findings of cheetah and wild dog, who rarely scavenge This study further quantified the lower prey mass-thresholds for each large carnivore, below which the energetic costs of seeking out and killing prey outweigh the energetic benefits of consuming these small-bodied individuals, resulting in prey below this threshold being consistently avoided. Such a threshold was evident for all carnivores except leopard, who hunt prey as small as birds and rodents Hippotragus equinus are within the weight range preferred by lion, but are usually protected from predation through their scarcity Equus zebra zebra is within the preferred prey weight range of lion. This knowledge highlights the need to mitigate Cape mountain zebra predation by lion that have recently been reintroduced at the Karoo and Mountain Zebra National Parks The prey preferences of large carnivores are a useful tool with which to predict the success of carnivore reintroductions based on the availability of prey within the preferred prey weight range The prey preferences of the five large African carnivores have been used to develop predator-prey abundance models, intended to serve as a tool for estimating sustainable numbers for reintroduced carnivores Panthera tigrisPanthera unciaCuon alpinus, jaguar Panthera onca, coyote Canis latrans, puma Puma concolor, Eurasian lynx Lynx lynx and clouded leopard Neofelis nebulosa (Hayward pers comm).The segmented model method proposed by this study can be used to determine and compare the prey weight preferences of other predators, with the resolution of prey preference findings dependent on the sample size of prey species available Click here for additional data file.Table S2Prey species masses, mass-ranks and mean Jacob’s Index (J.I.) values used in segmented model analyses.(XLSX)Click here for additional data file.Table S3Details of carnivore kill and prey abundance data used to test preferred and accessible prey weight ranges. The sources, location and timing of African studies, and the number of kills recorded in each, used to assess the mean percentage of the diet accounted for by the preferred and accessible prey weight ranges determined in this study.(XLSX)Click here for additional data file.Code S1Code used to generated segmented linear relationships using the segmented generalized linear function in the segmented package  of the open source statistical program R (R Development Core Team 2012).(R)Click here for additional data file.