Therefore, τ for O2 is equation(5) τO2≈VAV˙A, For the soluble gas N2O, using the values of the above variables given in Gavaghan and Hahn (1995), (4) can be re-written as VA′=VA+0.43. Therefore τ for N2O is equation(6) τN2O=VA+0.43V˙A. We can express the ventilation rate V˙A by (Williams et al., 1994) equation(7)

V˙A=R(VT−VD),where R is Selleck PS 341 the respiration rate in breaths/min, VT is the tidal volume, and VD is the airway dead space volume. At high frequencies ω, the term ω2τ2 dominates the denominator in (2), therefore allowing τ to be estimated using equation(8) ΔFAΔFI→1ωτ,where ΔFA, ΔFI, and ω are known values. The estimated τ is then subsequently used to determine lung volume VA using (3) and (4). Conversely, at low values of ω  , the term λbQ˙PV˙A dominates the denominator in (2), and therefore reveals information concerning Q˙P. This indicates that careful selection of ω   allows the variable determination of both lung volume V  A and lung perfusion Q˙P. Hahn et al. (1993) found that the forcing sinusoidal frequency should be f>1min−1, when N2O is used as the forcing gas. Lung volume VA derived from a continuous ventilation model is greater than the actual VA, due to the assumption that VA is constant. In reality, the lung volume including dead space volume VD varies tidally between (VA + VD) at the beginning of inspiration and (VA + VD + VT)

at the end of inspiration. Sainsbury et al. (1997) showed that subtracting a correction term Vc from the lung volume determined 17-AAG by the continuous ventilation model produces a more realistic estimate of the lung volume, equation(9) Vc=12(VT+VD) Etofibrate In our proposed new system, we have used both O2 and N2O to estimate V  A and Q˙P. With the indicator gas O2 regarded as a non-soluble gas with λb ≈ 0, (2)

therefore becomes equation(10) ΔFAΔFIO2=11+ω2τO22,where (ΔFA/ΔFI)O2ΔFA/ΔFIO2 indicates ΔFA/ΔFI obtained using O2 data. From (5) and (10), we have equation(11) VA=V˙AT2πΔFAΔFIO2−2−11/2where V˙A is given by (7), and T is the forcing sinusoidal period in minutes; i.e., T = f−1 = 2π(ω)−1. Here we have reached the estimate of lung volume VA, using (11). For the soluble indicator gas N2O, (2) can be re-written as equation(12) ΔFAΔFIN2O=11+0.47(Q˙P/V˙A)2+ω2τN2O2From (5), (6), (10) and (12), we have equation(13) Q˙P=V˙A0.47ΔFAΔFIN2O−2−VA+0.43VA2·ΔFAΔFIO2−2+VA+0.43VA21/2−1,where V˙A is given by (7), and VA is given by (11). A set of V  A and Q˙P can be produced at any sinusoidal period T, using (11) and (13) where both O2 and N2O contribute to the estimation. In previous work concerning the continuous ventilation model (Hahn, 1996 and Hamilton, 1998), only one type of indicator gas was used, hence V  A and Q˙P had to be estimated separately. One contribution of the proposed system is that, for the first time, V  A and Q˙P can be estimated at the same time using the continuous ventilation model, and this therefore reduces the time to obtain estimates V  A and Q˙P.

1). Twenty-four hours after the last intratracheal challenge with saline or OVA, animals were sedated (diazepam 1 mg ip), anaesthetized (thiopental sodium 20 mg/kg ip), tracheotomized, paralyzed (vecuronium bromide, 0.005 mg/kg iv), and ventilated with a constant flow ventilator (Samay VR15; Universidad de la Republica, Montevideo, Uruguay) set to the following parameters:

frequency 100 breaths/min, tidal volume (VT) 0.2 mL, and fraction of inspired oxygen (FiO2) 0.21. The anterior chest wall was surgically removed and a positive end-expiratory pressure of 2 cmH2O applied. Airflow and tracheal pressure (Ptr) were measured ( Burburan et al., 2007). Lung www.selleckchem.com/products/ABT-888.html mechanics were analyzed by the end-inflation occlusion method ( Bates et al., 1988). In an open chest preparation, Ptr reflects transpulmonary pressure (PL). Briefly, after end-inspiratory occlusion, there is an initial rapid decline in PL (ΔP1) from the preocclusion value down to an inflection point (Pi), followed by a slow pressure decay (ΔP2), until a plateau is reached. This

plateau corresponds to the elastic recoil pressure of the lung (Pel). ΔP1 selectively reflects the pressure used to overcome airway resistance. ΔP2 reproduces the pressure spent by stress relaxation, or viscoelastic properties of the lung, as well as a minor contribution of pendelluft. Static lung elastance (Est) was determined by dividing Pel by VT. Lung mechanics measurements were obtained 10 times in each animal. All data were analyzed using ANADAT software (RHT-InfoData, Inc., Montreal, Quebec, ABT-263 in vitro Canada). Laparotomy was performed immediately after determination of lung mechanics and heparin (1000 IU) was injected into the vena cava. The trachea was clamped at end expiration and the Akt inhibitor abdominal aorta and vena cava were sectioned, producing massive haemorrhage and rapid terminal bleeding.

The left lung of each animal was then removed, flash-frozen by immersion in liquid nitrogen, fixed with Carnoy solution, and embedded in paraffin. Four-micrometre-thick slices were cut and stained with haematoxylin–eosin. Lung histology analysis was performed with an integrating eyepiece with a coherent system consisting of a grid with 100 points and 50 lines (known length) coupled to a conventional light microscope (Olympus BX51, Olympus Latin America-Inc., Brazil). The volume fraction of collapsed and normal pulmonary areas, magnitude of bronchoconstriction, and number of mononuclear (MN) and polymorphonuclear cells (PMN, neutrophils and eosinophils) in lung tissue were determined by the point-counting technique (Weibel, 1990 and Hsia et al., 2010) across 10 random, non-coincident microscopic fields (Xisto et al., 2005 and Burburan et al., 2007). Collagen (Picrosirius-polarization method) and elastic fibres (Weigert’s resorcin fuchsin method with oxidation) were quantified in airways and alveolar septa using Image-Pro Plus 6.0 (Xisto et al., 2005, Antunes et al., 2009 and Antunes et al.

, 2001 and Piperno and Pearsall, 1998). Culturally this corresponds to the Archaic Period (∼7000–2000/1000 BC; Flannery, 1986, Kennett, 2012 and Voorhies, 2004) in Mesoamerica, a long transitional period between the presumed and poorly defined big-game hunting traditions of the Late Pleistocene and MK-2206 ic50 the rise and proliferation

of agricultural villages during the middle and late Holocene. The primary Mesoamerican cultigens (Zea mays [maize], Cucurbita pepo/Cucurbita argyrosperma [squash], and Phaseolus vulgaris [common bean]) were not domesticated in the Maya Lowlands ( Smith, 1997, Piperno et al., 2009, Kaplan and Lynch, 1999 and Piperno and Smith, 2012), but were introduced from elsewhere in Mesoamerica during the Archaic Period. Each has its own domestication history and eventually they were grown together in fields to obtain symbiotic effects of fertilization ( Flannery, 1973). Changes in the size and character of

these domesticates (e.g., maize cob size) have continually changed through time as a product of human selection. The earliest evidence for squash (C. CSF-1R inhibitor pepo) comes from the central Mexican highlands (8000 BC; Smith, 1997) and C. argyroperma is also found within the Neotropical lowlands early in time ( Piperno and Pearsall, 1998). Molecular evidence places the domestication of beans (P. vularis) in the early Holocene (∼7000 BC; Sonnante et al., 1994), but the earliest macrofossils come from the

highlands of Mexico (1300 BC, Tehuacan Valley; Kaplan and Lynch, 1999). A wide range of other seed and vegetable crops, trees, roots, succulents, condiments, and industrial plants (e.g., cotton) were also domesticated in Mesoamerica ( Piperno and Pearsall, 1998 and Piperno and Smith, 2012). The Classic Maya probably grew many of these in house gardens, but most of these plant species are pollinated by animals, rather than wind dispersal, so they are less likely to accumulate in paleoecological records ( Fedick, 2010). Chile pepper, avocado and chocolate are the best known of these crops. Manioc was also an important early crop in the Maya Lowlands ( Pohl et al., 1996, Pope et al., 2001 and Sheets et al., 2012), but was domesticated in South Hydroxychloroquine America ( Piperno and Smith, 2012). Domesticated animals played a limited role in Mesoamerican subsistence economies (Piperno and Smith, 2012). Only three domesticated animal species, dog (Canis canis), turkey (Meleagris gallopavo gallopavo), and the muscovy duck (Cairina moschata), played a significant role in the Mesoamerican household economy. Domesticated dogs likely entered the Americas with colonizing human populations from Asia ( Leonard et al., 2002). The turkey was domesticated in Mesoamerica sometime during the middle or late Holocene ( Speller et al., 2010). Herd animals similar to the Old World context (e.g.

, 2013, Forenbaher and Miracle, 2006, Greenfield, 2008, Legge and Moore, 2011, Manning et al., 2013, Miracle and Forenbaher, 2006, Özdoğan, 2011, Tringham and Krstić, 1990 and Tringham, 2000). Furthermore, current research suggests that the diffusion of food production was not a simple, straightforward process; different regions underwent distinct histories with varying types of farming

adaptations. In some parts of the Balkans, farming appears as a ‘package’ with a full commitment to plant and animal husbandry as a subsistence system and substantial villages with centuries see more (and in some cases millennia) of occupation (e.g., Bailey, 2000, Legge and Moore, 2011, Marijanović, 2009, Moore et al., 2007 and Perlès, 2001). Other areas display a much greater diversity in both subsistence practices and degree of sedentism, such as in the Iron Gates region, where settled farming communities along the Danube emphasized aquatic resources (Bonsall et al., 2008), or parts of Romania where semi-sedentary pastoral gatherers interacted with more sedentary farmers (Greenfield and Jongsma, 2008), and possibly with indigenous hunter-gatherer groups (Bailey, 2000, Borić and Price, 2013 and Tringham, 2000). The connections between these regions and the

variations in the mechanisms are Docetaxel still a matter of debate. Cultural affinities based on ceramic styles point to the Balkans as a departure point for farming traditions throughout Europe, with interior trajectories exemplified by people who produced

Starčevo pottery toward central Europe, and Mediterranean linkages in the form of Impresso wares (pottery decorated with shell and non-shell impressions) throughout the Adriatic and into the Western Mediterranean ( Rowley-Conwy, Staurosporine chemical structure 2011; see also Manning et al., 2013). In this way, the Balkan Peninsula is an ideal area to examine the varied effects of agricultural production on landscapes, human and animal populations, and issues of degradation. This diversity, however, also poses some key challenges in identifying regional trends within the forest of specific or local historicity. In all cases, early farming villages in the Balkans share some basic features of sedentary life and reliance on domesticated plants and animals for subsistence. Specifics in the relative proportions of domestic species in bone assemblages from these sites, the contribution of wild species to diets, and the interplay between species reflect not only variations in cultural adaptations but also ecological dynamics in interior and coastal regions. Table 1 and Fig. 2 summarize the available published data on the relative proportions of wild and domestic animals at a number of Early Neolithic villages in the region.

The tourism infrastructure is dominantly controlled by the Kinh selleckchem majority, while the other minorities mainly deliver labour force to run the tourism industry. In order to evaluate the potential impact of tourism activities on forest cover in Sa Pa, three land cover maps were compiled based on LANDSAT images available from the U.S. Geological Survey archives (http://glovis.usgs.gov). One LANDSAT-patch (path/row 128/45) covers the whole Sa Pa district with a resolution of 30 m by 30 m. The Landsat images

date from Feb 1, 1993 (just after the opening for international tourism), Nov 4, 2006 (midst of the evaluation period) and Jan 02, 2014 (current state). All images were taken in the post-harvest period when the arable fields are bare. All Landsat images in the freely available USGS archive are orthorectified with precision terrain correction level L1T (Vanonckelen et al., 2013). All images were then corrected for atmospheric and topographic effects using the MODTRAN-4 code and the semi-empirical topographic correction implemented in ATCOR2/3 (Richter, 2011 and Balthazar et al., 2012). Then, a supervised maximum likelihood classification was carried out to map the following 5 land cover categories (Fig. 2): forest, shrub, arable land, water body and urban area. Spectral signatures for the different land cover types were identified

by delineating training areas on the basis of field work PF-06463922 carried out in 2010 (Fig. 5). The accuracy of the land cover maps was assessed by comparing the classified land cover with visual interpretations of very high resolution remote sensing data. For 1993, the comparison was done with aerial photographs (MONRE, 1993); for 2006 with a VHR-SPOT4 image (MONRE, 2006) and for 2014 with a VHR-SPOT5 image (MONRE, 2012). Random sampling of validation points was done with n = 219 for the 1993 map, n = 315 for the 2006 map, and n = 306 for the 2014 map. The number of

sample points per land cover class varied from 3 to 111, depending on the areal cover of the classes. For all randomly selected points, the land cover was compared with the classified land cover. This comparison allowed to assess the overall accuracy, quantity disagreement unless and allocation disagreement (in %) following the procedures described by Pontius and Millones (2011). In order to analyze land cover change trajectories over 3 timeperiods, the change trajectories were grouped in 6 classes: (1) deforestation (change from any class of forest to non-forest), (2) reforestation (change from non-forest to forest), (3) land abandonment (change from agricultural land to shrub or forest), (4) expansion of arable land (conversion from shrub to arable land), (5) other changes, and (6) no change (Table 1). The original classes ‘water body’ and ‘urban area’ that only occupy a minor fraction of the land were not taken into consideration.

, 2008). The increasing trend BLZ945 in Lower Cuyahoga River sediment load is consistent with increased river flow since 2003, as well as erosion of the river valleys, banks and bed (Richards et al., 2008). A sediment load record derived from dam pool sediment can be used to place potential future impacts from hydrologic regime changes into a long-term context. Since 1950, some regions of the globe have

had a statistically significant increase in the number of heavy precipitation events, with the trend being most consistent in North America (IPCC, 2012, pp. 141–149). In the coming century this trend is projected to increase, especially in high latitudes, tropics, and in the winter in northern mid-latitudes (IPCC, 2012, pp. 141–149). Accompanying an increase in heavy precipitation should be an increase in rain-generated floods that would, in turn alter sediment storage

and transport within catchments. However, coherent spatial scale changes in flood frequency and magnitude is often complicated by anthropogenic regulation of river basins and land use changes (Villarini and Smith, 2010, Villarini et al., 2011 and IPCC, 2012, Galunisertib order pp. 175–178). Because watershed management is often undertaken at the local to regional scale, local to regional assessments of hydrologic regime changes are the most useful. In the U.S. Midwest, changes in precipitation and stream flow have been linked via atmospheric teleconnections to ocean/atmosphere conditions in the Pacific and Atlantic Oceans (Coleman and Rogers, 2003, Rogers and Coleman, 2003 and Rogers

and Coleman, 2004). Within the Cuyahoga River watershed an increase in the number of heavy precipitation events, high river discharge days and sediment erosion have all occurred since 2003 (Liberatore, 2013). These high flow events stand out even in the monthly mean record of Cuyahoga River discharge (Fig. 9). The high flow events and associated increases in sediment load lend 17-DMAG (Alvespimycin) HCl support to watershed management policies aimed controlling storm water runoff. The STEPL model produces a long-term average sediment loading rate for 2006 land use conditions (7490 tonnes yr−1) that compares remarkably well with the measured accumulation rate for 2006 (7520 tonnes yr−1)(Fig. 9). Even comparing the STEPL average loading rate with a decade average of the measured accumulation (6300 tonnes yr−1) indicates the results are quite similar given the differences in methodologies. Water resource/watershed managers rely heavily on models to understand current and future conditions of the water bodies under their charge. They may not have the time and resources to conduct long-term monitoring or detailed sampling on all the water bodies under their management to determine pollutant loading.

The lowest sediment fluxes for the entire dataset was measured in the most isolated lakes like Belciug, an oxbow lake, and Hontzu Lake, even if both are located relatively close to major distributaries (i.e., St. George and Chilia respectively). Our analysis Baf-A1 molecular weight of historical bathymetry between 1856 and 1871/1897 clearly shows that in natural conditions two depocenters were present along the Danube delta coast and they were located close the mouths of the largest Danube distributaries: the Chilia and the St. George. The Chilia distributary,

which at the time transported ca. 70% of the total Danube sediment load, was able to construct a river dominated lobe (Fig. 4a) on the shallow and relatively wave-protected region of the shelf that fronted its mouths (Giosan et al., 2005). Sediment accumulation led to a uniformly ∼20 m thick delta front advance in a quasi-radial pattern, all around the lobe’s coast. Sedimentation rates reached in places values higher than 50 cm/yr especially at Chilia’s northern and central

secondary mouths. The second depocenter belonged to the other active delta lobe, St. George II, which exhibited a wide shallow platform fronting its mouth with an incipient emergent barrier island that was already visible in 1897 (Fig. 4a). Such a platform was conspicuously missing in front of the Chilia lobe. The main St. George depocenter on the delta front was deeper than at Chilia (to ∼−30 m isobath) and was almost entirely offset downdrift of the river mouth Tau-protein kinase but deposition INCB28060 similarly took place in a radial pattern around the delta platform.

The accumulation rates were even higher than for the Chilia depocenter (up to 70–80 cm/yr) even if the feeding distributary, the St. George, was transporting at the time only ∼20% of the total sediment load of the Danube. This suggests that the St. George depocenter was an effective temporary sediment trap rather than a point of continuous sediment redistribution toward the rest of the lobe’s coast. The nearshore zone between the Chilia lobe and St. George mouth, corresponding largely to the partially abandoned Sulina lobe, was erosional all along (Fig. 4a) to the closure depth (i.e., ∼5 m in wave protected regions and ∼10 m on unprotected stretches of the shoreline – Giosan et al., 1999) and even deeper toward the south. The third distributary of the Danube, the Sulina branch, discharging less than 10% of the Danube’s sediment load, could not maintain its own depocenter. However, together with the Chilia plume, Sulina probably contributed sediment to the stable distal offshore region (>5 m depth) in front of its mouth (Fig. 4a). Further downdrift, the nearshore zone to Perisor, outside the frontal St. George depocenter, was stable to accreting, protected from the most energetic waves coming from the northeast and east by the St. George lobe itself (Fig.

The second control group did not perform any task but waited for the equivalent duration of the car racing tasks between the two MRI scans. Because the active control group played a different track in each trial (different lengths and scenery), evaluating

their improvement during the task necessitates normalization. This normalization was crucial because the tracks were randomized PD-1/PD-L1 tumor between active control subjects. The normalization procedure, performed for each subject, included normalizing the lap time to the track length and dividing by the performance in the first trial. The same procedure was applied to the learning group. MRI was performed at the Tel Aviv Sourasky Medical Center with a 3T (GE, Milwaukee, WI, USA) MRI system. All subjects underwent two series of scans approximately 2 hr apart. Between the two sessions a task was administered to the learning group and the first control group; the second control group

did not perform any task. The MRI protocol of the first series of scans included conventional anatomy sequences, and DTI was acquired with an eight-channel head coil. In the second series only DTI scans were administered. T1-weighted images were acquired with a 3D spoiled gradient-recalled echo (SPGR) sequence with the following parameters: up to 155 axial slices (whole-brain coverage), TR/TE = 9/3 ms, resolution 1 × 1 × 1 mm3, scan time 4 min. In addition to the T1 scan, T2-weighted images (TR/TE = 6,500/85) and FLAIR images (TR/TE/TI = 9,000/140/2,100) were acquired. The entire anatomical data set was used for radiological screening. Double-refocused, DNA Damage inhibitor either spin-echo diffusion-weighted,

echo-planar imaging sequences were performed with up to 70 axial slices (to cover the whole brain), and resolution of 2.1 × 2.1 × 2.1 mm3 was reconstructed to 1.58 × 1.58 × 2.1 mm3 (field of view was 202 mm2, and acquisition matrix dimension was 96 × 96 reconstructed to 128 × 128). Diffusion parameters were Δ/δ = 33/26 ms; b value of 1,000 s/mm2 was acquired with 19 gradient directions, and an additional image was obtained with no diffusion weighting (b0 image). The double-refocused sequence was used in order to minimize eddy currents and susceptibility artifacts. The DTI scan was repeated three times to increase signal-to-noise ratio. For details on the DTI analysis routine, please refer to section 1.2 (Image analysis) of the Supplemental Experimental Procedures. VBA is a whole-brain technique that allows regionally specific differences in quantitative MRI indices (such as FA or MD) to be computed on a voxel-by-voxel basis. The statistical VBA design included three groups (learning and controls) and two scan times (with repeated measures on the second factor). On this design we applied the following procedures. (1) A paired t test on the learning group only (comparing the pre and post-learning scans). To avoid partial volume bias in the statistical analysis, we applied a non-cerebrospinal fluid (CSF) mask.

The a1 isoform is found in synaptic vesicle membranes ( Morel et al., 2003), which is also present in the presynaptic membrane. In addition to having a role in acidifying intracellular membrane-bound compartments (Figure 1B), Zhang et al. provide evidence that vATPase speeds up endocytosis by alkalinizing the cytoplasm

(Figure 1C). This protein, or several of its subunits, may also have other functions related to exocytosis. The V0 domain of the vATPase interacts with another protein of the synaptic vesicle membrane, synaptobrevin (Figure 1D), one of the core SNARE proteins, and with the SNARE complex in different model systems (Galli et al., 1996 and Morel et al., 2003). Recently, Di Giovanni et al. (2010) have demonstrated a Ca2+/calmodulin regulated direct protein-protein interaction in synaptic vesicles between synaptobrevin (the v-SNARE) and the c subunit of V0. Furthermore, PI3K inhibitor the perturbation of this interaction produces a substantial decrease in the probability www.selleckchem.com/products/BEZ235.html of neurotransmitter release. It has been suggested ( Di Giovanni et al., 2010) that the cis interaction between synaptobrevins and the c subunits of the V0 domain may prevent the formation of the SNARE complex, which implies that dissociation of this complex (regulated by Ca2+/calmodulin)

must precede fusion. Under this hypothesis it may also be possible that the c subunits may help orient synaptobrevin molecules as they enter SNARE complexes with SNAP-25 and syntaxin. More than two decades ago, Israel et al. (1986) reported the isolation of a proteolipid pore complex (c subunit), which they named mediatophore, from synaptosomes formed from Torpedo electroplaques, and they

suggested that it mediates calcium-dependent ACh release. Since then, additional evidence has accumulated that the V0 domain of the vATPase participates in membrane fusion downstream of SNAREs ( Peters et al., 2001 and Hiesinger et al., 2005). One idea is that after a vesicle is fully loaded with neurotransmitter, the cytoplasmic V1 domain dissociates from the intramembrane V0 domain of the vATPase. The naked V0 domain can then dimerize with another V0 domain located in the plasma membrane, and (like a gap junction) create a pore Phosphoprotein phosphatase that allows the passage of neurotransmitter from vesicle lumen to synaptic cleft ( Figure 1E). Recent reports support this hypothesis. For example, in a loss-of-function mutation in Drosophila V0 domain, neurotransmitter loading and synaptic vesicle acidification were not altered, while synaptic vesicle fusion with the presynaptic membrane was blocked downstream of the SNARE complex formation ( Hiesinger et al., 2005). It is been proposed that the SNARE complex helps to align the two opposed V0 proteolipid rings, which, when joined together, participate in the formation of the fusion pore.

Those who reported recovery had a mean BPPT elbow extension angle of 25.1 ± 15.8 while those who did not report recovery had a mean BPPT elbow extension angle of 58.4 ± 15.9. The VAS score was 1.8 ± 1.1 for recovered subjects and 2.7 ± 1.1 for non-recovered. There was a moderate correlation (Spearman’s rank correlation coefficient) between self-reported recovery and BPPT elbow extension angle (−0.44) and a lower correlation between self-reported recovery and VAS score (−0.30). This study shows that self-reported recovery correlates well with the physical examination findings of the BPPT. Both could be used interchangeably to assess recovery, or the inclusion of the BPPT

may give this website the practitioner additional information on which to make treatment decisions. Clearly the use of a self-report recovery question alone is simpler for the busy clinician. The problem with the BPPT is that there is as yet no normative database in the

healthy population for this test. At best, we have limited samples of control groups with which to compare.2 All one may find is that groups differ in terms of the BPPT results, i.e., recovered subjects have different results than non-recovered subjects. The BPPT results from this study agree in some aspects with other cohorts.2 The recovered group of this study and that reported by Sterling et al.2 have similar BPPT results. The non-recovered subjects of the current study have significantly more abnormal BPPT results than reported for non-recovered subjects Tyrosine Kinase Inhibitor Library datasheet studied by Sterling et al.2 but small sample sizes, and the different time points of assessment (3 months in this study vs. 6 months with Sterling et al.2) do not allow for reliable, direct comparisons of these data. If central sensitization is an important mechanism in chronic pain after whiplash injury, it is important to understand its correlation to self-reported recovery. Given the constraints of primary practice, practitioners can most

easily assess recovery by asking a single question: “Do you feel you have recovered fully from your accident injuries?” with responses of “yes”, “no”, or “not sure”. Those Suplatast tosilate who report self-recovery will have essentially a “more normal” BPPT test, and might not be labelled as having central sensitization by this test. On the other hand, those who do not report recovery will have significantly higher BPPT angles and VAS scores. Perhaps, if central sensitization persists in those reporting non-recovery, then treatment directed at central sensitization may be important to assist recovery; although, the best way to treat central sensitization is unknown, and even whether we should treat it is unclear. This study is limited by the fact that there were no other physical examination findings, such as spine range of motion taken into consideration. Yet, spine range of motion at a single assessment may not be relevant if previous range is unknown.