As is detailed in the Fulvestrant nmr PCA bi-plot (Fig. 1) the apple juice extracted

from Golden Delicious exhibited a similar flavour profile to that of Granny Smith with high concentrations of volatile compounds related with green-grassy notes (trans-2-hexenal and 1-hexanal and cis-3-hexenol) and low concentrations of acetates. The latter has been also confirmed by Ting et al. (2012) who reported lower concentrations of acetates in the headspace of fresh cut Golden Delicious samples compared to other apple cultivars i.e. Red Delicious, Jonagold or Fuji. Moreover, the aldehyde to alcohol ratio is indicative of ripeness, as aldehydes can be metabolised to alcohols and subsequently esterified with the present carboxylic acids (Defilippi, Dandekar, & Kader, 2005). Based on GC–MS data, the aldehydes and their corresponding

alcohols ratios were higher for Golden Delicious and Granny Smith juices implying a lower level of ripeness for the specific fruit samples. Pink Lady and Braeburn were characterised as having moderate concentrations of most of the identified flavour compounds, apart from a marked elevation in concentration for trans-2-hexenal in Braeburn. Jazz had the greatest fruity-ethereal-flowery flavour type compounds as indicated by the higher concentration of acetates (2-methylpropyl, butyl, 2-methylbutyl, and hexyl acetates) and the low green-grassy odour related compounds (cis-3-hexen-1-ol and trans-2-hexanal). Regardless the cultivar type, acetates find more and more specifically butyl and hexyl acetate were

the dominant esters in the headspace of the apple juices, this has previously been reported in other studies (Aprea et al., 2012, Kato et al., 2003, Komthong et al., 2007 and Ting et al., 2012). 1-Butanol was the most abundant alcohol in the headspace of the juices followed by 1-hexanol. In contrast to esters and aldehydes, alcohols are generally characterised as having higher odour threshold and thus they are considered as secondary contributors to apple flavour perception (Echeverrı́a, Graell, López, & Lara, 2004). It is also interesting that 1-butanol was highly correlated (according to BCKDHA Pearson’s test) with butyl acetate (r = 0.926, p < 0.001), hexyl acetate (r = 0.898, p < 0.001), trans-2-hexenal (r = −0.777, p < 0.001) and hexanal (r = −0.748, p < 0.01) and it could be surmised that these compounds are generated by a similar metabolic pathway during apple ripening. Finally, it should be noted that in the present work the major sesquiterpene found in the headspace of apples e.g. alpha-farnesene was not detected. This could be attributed either to the adopted protocol for the identification and quantification of the volatiles by GC or to the post juice extraction treatments e.g. enzymatic clarification and pectinase inactivation by heating.

Determination of gallic acid, ρ-hydroxybenzoic acid,

ρ-coumaric acid, ferulic acid, caffeic acid, (+)-catechin, (−)-epicatechin, quercetin and kaempferol was performed according to Hakkinen, Karenlampi, Heinonen, Mykkanen, and Torronen (1998). Phenolic compounds were extracted and hydrolysed from 5 g of ground fruit using acidified methanol (35 ml). The extract was stirred in the dark at 35 °C for 24 h, then filtered (Millipore membrane 0.22 μm) and analysed by reverse-phase HPLC in the same system described earlier (for the AA analysis). The mobile phase was composed of A – acidified water (1% acetic acid v/v) and B – 100% methanol. The elution gradient Everolimus in vitro started at 100% A; then linearly went to 60% A at 25 min; held for 2 min; then 95% A at 37 minutes; held for 5 min; and back to the initial conditions. Flow rate was 0.9 ml min−1, and column temperature was kept at 25 °C. Quantification was based on external standard calibration curves for gallic acid, ρ-hydroxybenzoic acid, ρ-coumaric acid, ferulic acid, caffeic selleck chemical acid, (+)-catechin, (−)-epicatechin, quercetin and kaempferol (Sigma–Aldrich) and results were expressed as mg 100 g−1 of fruit fw. The antioxidant capacity was determined using the ABTS assay based on the method described by Re et al. (1999). ABTS radical cation (ABTS +) was produced by reacting 7 mM ABTS solution with 2.45 mM potassium persulphate and allowing the mixture to stand in the

dark at room temperature for 16 h. The ABTS + solution was then diluted with ethanol until absorbance measured at 734 nm was 0.70 ± 0.02. After addition of 10 μl of sample or Trolox (0–1.5 mM) standard to 990 μl of diluted ABTS + solution, absorbance at 734 nm was measured at exactly 7 min. Results were expressed as trolox equivalent antioxidant capacity (TEAC). Six major ester volatiles typical of strawberry flavour were identified by GC–MS (Shimadzu QP-5000) and quantified by GC (Varian 3800; Palo Alto, CA, USA) equipped with flame ionisation detector (FID). All extractions were performed manually using 0.75 μm carboxen-PDMS SPME fibers (Supelco, Bellefonte, PA, USA). A Cyclic nucleotide phosphodiesterase two gram fruit sample, spiked with 2 μl of an internal standard solution, was placed in a 16 ml vial

and volatiles were collected using a headspace collection mode (with a distance from the liquid surface of 20 mm) at 30 °C for 15 min (equilibrium) and 45 min under stirring. After extraction, the SPME device was introduced in a splitless mode and was thermally desorbed for one minute. The capillary column was a DB-5 (30 m × 0.25 mm i.d. × 0.25 μm; J&W Scientific, Folson California, USA). Helium was used as a carrier gas at a flow rate of 1.0 ml min−1. The injector and detector temperatures were both set at 280 °C. The temperature program started at 35 °C (held for 10 min) and ramped to 210 °C at 1 °C min−1, then held for 10 min. Volatile compounds were identified using a quadrupole mass selective detector. Mass spectral ionisation was set at 180 °C.

The carcasses were thawed just before necropsy. The subcutaneous fat pad between the hind legs was dissected and check details weighed. Body condition was defined as the weight of the subcutaneous fat (g) divided by total body weight (kg). Liver tissue was removed for chemical analysis and refrozen. Aging was performed

by teeth cementum analysis by Matson’s laboratory (Milltown, Montana, USA). As the mink kits are born in the beginning of May (Hansson, 1947), a birth date of 1st of May was assumed. The mink were assigned to three different age categories: juvenile (3–12 months old, n = 51), one year old (13–24 months, n = 32) and two or more years old (older than 24 months, n = 18). Hours of daylight at

the specific capture date and site for each mink was used to construct three seasonal groups; autumn (from 17 to9 h of daylight before winter solstice, n = 42), winter (< 9 h daylight, n = 29) and spring (from 9 to17 h of daylight after winter solstice, n = 30). More detailed information about age, weight of subcutaneous fat, body weight and Antidiabetic Compound Library cost body length of the mink from the four different areas that were included in this study has been published earlier ( Persson et al., 2013). Liver samples were homogenized and a sub-sample of 1 g was transferred to a 50 mL centrifuge tube. The mass-labeled internal standards (see Ergoloid Supplementary data) were added followed by 10 mL acetonitrile. The mixture was vortex mixed and ultrasonicated for 30 min and

the supernatant acetonitrile phase was removed after centrifugation (10,000 ×g, 30 min). The extraction procedure was repeated once. The acetonitrile fractions were combined and diluted with water. After mixing and centrifugation the solution was put through a WAX solid phase cartridge (Waters, Milford, MA, USA) previously conditioned with 4 mL methanol followed by 4 mL water. After loading the sample, the WAX cartridge was washed with 4 mL 25 mM sodium acetate (pH 4) and 4 mL 40v% methanol in water, followed by drying the SPE cartridge under vacuum. A final wash with 8 mL methanol was employed before the PFAAs were eluted with 2 mL 2% ammonium hydroxide in methanol into a tube with 50 mg ENVI-Carb and 100 μL acetic acid. After mixing and filtration recovery standards, 2 mM ammonium acetate in water was added to the extract. The analysis was performed using an Acquity UPLC coupled to a Quattro Premier XE (Waters Corporation, Milford). Details on the analysis and quantification are presented in the Supplementary data. The analytical method used has previously been evaluated for PFCAs and PFSAs in an interlaboratory study on fish muscle with satisfactory Z-scores (z < 2) (van Leeuwen et al., 2009).

Choice between the approaches may simply be a matter of preference PD-1/PD-L1 inhibitor drugs or convenience or data availability. Similarly, no important differences were found between spatial and non-spatial models (Biging and Dobbertin, 1995 and Windhager, 1999). Nevertheless, some notable

features emerged. Particularly good performance seems to coincide with strengths of certain models with respect to functional form or data used. For example, Moses, which uses open-grown tree relationships, performs particularly well for the prediction of open-grown trees. The strength of Prognaus is the prediction of poor sites, because it was fit from national inventory data. Silva and BWIN are considerably better in the prediction of pine than Moses and Prognaus, probably because pine is better represented in their datasets. We found that the expected general patterns of height:diameter ratio development are predicted well by all four individual-tree growth models. This indicates that

all four simulators were built using a general scientific concept that is logical and biologically reasonable. However, the results are highly variable, depending on the geographic region. There is excellent fit in some areas, whereas the fit in other areas is rather poor. It is interesting to note that areas of good fit seem to coincide for all four individual-tree growth models (e.g., Arnoldstein), Compound C clinical trial even though they use a different model structure and were fit from different data. Probably frequently occurring growth patterns are well represented, whereas patterns of local importance are not so well described. Deviations in diameter increment models, height increment models, and crown ratio models are within a reasonable range for all four Sulfite dehydrogenase simulators. Model performance depends strongly on the region where it is applied (compare Arnoldstein

vs. Litschau). Similarly, Schmid et al. (2006) found that efficiencies of the same model in different study areas can range from 0.583 (indicating very good model performance) to −0.911 (indicating bias). Coefficients of determination in their study between observed and predicted values ranged from 0.031 to 0.680, underlining highly variable performance. Height:diameter ratios can be a rather sensitive measure, because moderate deviations in either the height growth model or the diameter growth model can cause comparatively large discrepancies. Differences between observed and predicted height:diameter ratios can be as much as 13 units on average. This is large, given that differences between light and heavy thinning in growth and yield experiments can be as little as 1.8 at the beginning of the experiment and are as large as 25.3 units at the end (Röhle, 1995).

In later WBC, the therapist targeted implementing the contingency management plan, completing morning

exposures, and helping Lance use DBT skills to complete the morning routine and exposures. For example, coaching often focused on helping the parents use the Walking the Middle Path skills to help Lance get out of bed and to execute the rewards plan faithfully. selleck kinase inhibitor Mindfulness was also used, particularly with the mother, who was coached to use the “Describe” skill and to avoid judgments when discussing other family members’ behavior. The mother was also coached to use Wise Mind, particularly by staying focused on the present moment, when implementing the reward plan. During WBC in which Lance was particularly tired or distressed, Lance was coached in using self-soothe with music and in opposite action. Video 2 demonstrates a range of skills used during WBC sessions with Lance’s family. Parents reported that having WBC scheduled in the morning helped to keep Lance accountable for getting out of bed and starting his morning routine. Waking at a consistent time to participate in WBC may have helped Lance regulate his sleep. In addition, it appeared that daily WBC increased his parents’ coordination of childcare, and it helped parents follow Dasatinib mouse through with treatment recommendations. Unscheduled phone coaching was often used when Lance had difficulty getting to therapy.

These calls often focused on helping Mom regulate her emotions, encouraging his parents to use Validate and Cheerlead, and coaching his parents to follow through with the contingency management plan. It is notable that a significant portion of treatment focused on implementing contingency management plan, helping

balance dialectical dilemmas in the family, and helping the mother regulate her emotions. At posttreatment and follow-up assessments, Anidulafungin (LY303366) Lance no longer met criteria for any diagnoses or SR. This article describes the development and conceptual underpinnings of a novel DBT-SR program and provided two illustrative case examples. DBT-SR is unique in that it uses DBT strategies to target the significant emotional and behavioral dysregulation observed in youth with SR behavior, even when the primary underlying disorders are internalizing in nature (anxiety, depression). DBT-SR also incorporated web-based conferencing technology to increase dose and ecological validity of its interventions, placing the therapist directly into the trenches in the client’s primary time of need. This pilot trial demonstrated promise in feasibility and acceptability of DBT-SR and raised questions to consider as development continues. Who Is the Client? Parents and other family members are almost always involved in any youth-based treatment, whether to provide psychoeducation, reinforce skills at home, provide direct parent management training, or intervene at the family interaction level.

, 2009 and Olivant Fisher et al., 2012). In contrast, iNOS is expressed in white blood cells in response to pathogens, resulting in overproduction of nitric oxide and a

pro-oxidant state Quizartinib cell line (Gutteridge and Mitchell, 1999). In the present study, no significant differences were observed in iNOS expression between CLP–SAL and CLP–DEXA groups, which may be attributed to the moment of dexamethasone administration, early in the course of inflammation (Thakur and Baydoun, 2012). Even though it has been described that dexamethasone may regulate iNOS expression exclusively through NF-κB (Jantz and Sahn, 1999), a recent study reported that dexamethasone enhanced iNOS gene expression but repressed iNOS protein with no noticeable effects on NF-κB (Thakur and Baydoun, 2012). OA increased expression of SOD and prevented an increase in iNOS, with no significant changes in Nrf2, GPx, and CAT. In this context, recent studies have shown that increases in SOD (Siedlinski et al., 2009 and Olivant Fisher et al., 2012) and decreases in iNOS (Soejima et al., 2000 and Pittet et al., 2001) correlate

with a reduction in lung damage. Additionally, OA is a free radical scavenger, acting through direct chemical reactions (Wang et al., 2010) and iNOS inhibition, preventing the overproduction of nitric oxide and depletion of intracellular glutathione and cytotoxicity (Abdel-Zaher et al., 2007). The unchanged pattern of Nrf2 expression after OA administration (Fig. 3) contradicts the findings of previous in vitro ( Reisman et al., 2009 and Wang et al., 2010) and in vivo ( Liu et al., 2008)

studies showing an BKM120 mw increase in the expression of Nrf2. These divergent results may be attributed to the dose and frequency of OA administration. In agreement with the present study, GPx levels were not found to change in a CLP-induced sepsis model ( Andrades et al., 2011) or in septic patients ( Lang et al., 2002), which may be explained by a delay in GPx upregulation ( Comhair et al., 2001). Even though GPx and CAT are the most important H2O2 scavenging enzymes, other enzymes, such as glutaredoxins, peroxiredoxins, and thioredoxins, may play a role in H2O2 degradation in the lung ( Kinnula and Crapo, 2003). In the model of CLP-induced sepsis used HSP90 herein, IL-6 and KC did not change after OA administration, but reductions were observed in other ARDS models (Lee et al., 2010 and Santos et al., 2011). Accordingly, in our previous study (Santos et al., 2011), oleanolic acid reduced IL-6 in experimental ARDS induced by paraquat, which results in a pro-oxidative model (Dinis-Oliveira et al., 2008). These differences can be explained by the timing of analysis and choice of model, since the pathophysiology of ARDS may differ according to the primary insult. Dexamethasone decreased IL-6 and KC, but did not modify oxidative stress mediators.

These concepts are essential to understanding why anthropogenic sediment is

click here located where it is, how it behaved over the Anthropocene, and how it may behave in the future. The concept of inheriting a legacy from the past is pervasive in the environmental science literature, and LS is a logical outgrowth of that perspective. Over the first decade of the new millennium, the term, legacy sediment (LS) began to be used with increasing frequency in a variety of contexts. A partial Internet sample of published scientific papers or reports that contain the phrase ‘legacy sediment’ indicates that use of the term has proliferated, especially in the eastern USA, and across a range of disciplines including geomorphology, hydrology, ecology, environmental toxicology, and planning ( Table 1). The earliest occurrence of the term was in 2004 and was concerned with the effects of copper contamination from legacy sediment on water quality ( Novotny, 2004). By 2007, LS had appeared in several studies of historical alluvium in the eastern USA. The use of LS to describe historical floodplain alluvium increased greatly with

the findings of legacy mill-pond surveys in Pennsylvania, USA ( Walter and Selleck PD0325901 Merritts, 2008 and Merritts et al., 2011). Although these two publications do not use the phrase, it was used by the authors and others as early as 2005 in abstracts and field trip logs in association with sediment trapped in legacy mill ponds. The use

of ‘legacy sediment’ in publications grew at about the same time as the use of ‘legacy contaminants’ and ‘legacy pollution.’ An Internet search of publications with the phrases “legacy contam*” and “legacy pollut*” in Wiley Online and Science Direct indicate a much larger number of uses of those terms than LS, but a similar—perhaps slightly earlier—timing of rapid growth ( Fig. 1). The contexts in which LS is used in publications vary widely from sources of legacy contaminations in toxicological studies (Bay et al., 2012), to sediment budgets (Gellis et al., 2009), Acetophenone to fluvial geomorphic and ecological processes (Hupp et al., 2009). This paper examines questions of geographic location, age, stratigraphic nomenclature, and genetic processes, in an attempt to clarify the concept of LS and avoid vague, obscure, or conflicting uses of the term. Ultimately, a definition of LS is suggested with broad applicability to sedimentary bodies generated by anthropogenic depositional episodes. Much usage of the term LS has gone without an explicit definition and relies on preconceived understandings or implications that may vary between disciplines. The primary implied meanings apparently are the historical age or the anthropogenic origin of the sediment. One consideration in defining LS is to examine the etymology of legacy.

, 2010). As we could expect it, the highest contamination levels (total 134+137Cs activities exceeding 100,000 Bq kg−1) Trametinib were measured in sediment collected along the coastal rivers (i.e., Mano and Nitta Rivers) draining the main radioactive plume (Fig. 2). Contamination levels were logically much lower in sediment collected along the Abukuma River that drains less contaminated areas. The analyses conducted by the Japanese Ministry of Environment (MoE) provided an additional temporal insight into contaminated sediment exports in this area. Our samples were collected in November 2011, whereas samples provided by MoE showed that contamination of sediment was systematically the highest

in material collected in September 2011. The presence of contamination hotspots close to Fukushima City and behind a large dam located upstream of the city is likely due to the rapid wash-off of radionuclides on urban surfaces during the first series of rainfall events that followed the accident, to their concentration in urban sewers systems (Urso et al., 2013) and their subsequent export to the rivers. This rapid export of radionuclides Topoisomerase inhibitor shortly after the accident along the Abukuma River is confirmed

by data collected by the MoE (Fig. 2) showing a peak of contamination in sediment collected in September 2011, and then a huge decrease to low activities even during snowmelt. Along the Hirose River, the snowmelt (in March 2012) led in contrast to an increase in sediment contamination. At the light of those first results outlining a very rapid wash-off of radionuclides obtained following the accident in the Abukuma River

basin, we decided to focus the next fieldwork campaigns on the coastal basins where radionuclide activities PI-1840 in sediment were the highest. We extended sampling to the Ota River catchment, closer to FDNPP, where access was unauthorized during the first campaign (Fig. 1b). Whilst 137Cs and 134Cs gamma-emitting radioisotopes constitute by far the most problematic contaminants (with total activities in soils ranging from 50 to 1,110,000 Bq kg−1), 110mAg was also identified and measured in most samples (with activities ranging from 1 to 3150 Bq kg−1). Because of these low activities, contribution of 110mAg to the global dose rates was considered to be negligible. It appeared from the analysis of the MEXT soil database that the initial fallout pattern of 110mAg displayed significant spatial variations that were not observed for the radiocaesium fallout pattern at the scale of the entire Fukushima Prefecture. Soil activities in 110mAg were the highest within the main radiocaesium contamination plume as well as at several places along the coast located between 40 and 50 km to the north of the power plant (MEXT, 2011b). Most interestingly, the 345 values of 110mAg:137Cs ratio in MEXT soil samples strongly varied across the entire region (0.0004–0.15 with a mean of 0.006; Fig.

Deficits were

exhibited by all subgroups for acoustic, linguistic and affective dimensions of prosodic analysis. The finding of impairment at the level of the basic acoustic building blocks of prosodic contours and the correlation between acoustic and linguistic prosody performances argue for the involvement of early perceptual mechanisms that cascade to higher levels of prosodic processing in PPA. Whereas prosodic variation in syllables and words typically extends over tens to hundreds of milliseconds, prosodic contours typically extend over hundreds to thousands of milliseconds: the prosodic subtests used here (syllable pairs/word R428 stress vs contour/intonation) might index the processing of prosodic structure over shorter versus longer timescales, respectively. Contour discrimination was significantly more impaired than pair discrimination and intonation discrimination was significantly more impaired than stress discrimination at the phrasal level: this pattern suggests that the representation of longer range prosodic structure may be relatively more vulnerable in PPA. While this pattern might be at least partly attributable to an associated working memory impairment, the

lack of correlation between prosodic and short-term memory and executive performance on most of the tasks argues for an additional specific deficit of receptive prosody in PPA. Within the domain of affective prosody, recognition of certain emotions (in particular, disgust and fear) was relatively more impaired. Comparison of vocal emotion recognition with recognition selleck inhibitor of emotions in another modality (facial expressions) here suggested non-uniform involvement of emotion processing mechanisms between modalities in PPA: recognition of vocal emotions was significantly Venetoclax nmr inferior to recognition of facial expressions in patients (but not healthy controls), and the relative degree of impairment of particular emotions differed for vocalisations versus facial expressions.

Taken together, the data suggest a generic deficit of emotion recognition in PPA, but further suggest that this may be modulated by modality-specific (possibly perceptual) factors. Whereas vocal expressions of emotions such as sadness and surprise can be conveyed vocally from relatively coarse perceptual cues (e.g., large shifts in intensity or pitch), the perception of vocal expressions of other negative emotions is likely to be relatively more dependent on accurate encoding of fine-grained perceptual features ( Juslin and Laukka, 2003 and Hammerschmidt and Jürgens, 2007). Healthy subjects may be better able to exploit discriminatory acoustic features of emotional prosodic utterances, or alternatively, there may be an additional specific deficit in processing particular vocal emotions in PPA: the present data do not resolve this issue. Perception of prosody has been little studied in degenerative disease.

The solution was spread on tryptone sucrose medium containing at 50 μg mL− 1

of kanamycin. In the second round of screening, each of the reduced virulence mutant candidates was inoculated to three JG30 plants. For each plant, at least three fully expanded leaves were inoculated. Two weeks after inoculation, the lesion lengths on the inoculated leaves were measured. Disease symptoms were scored as lesion length. Xoo strains were cultured on TSA plates with appropriate antibiotics, pelleted down, re-suspended in SDW www.selleckchem.com/products/cobimetinib-gdc-0973-rg7420.html at OD600 0.5, and then individually infiltrated into leaves of N. benthamiana with needleless syringes. At 36 to 72 h post-infiltration, HR triggered by Xoo in the form of necrotic regions at the area of inoculation was recorded. The experiments were repeated three times. Xoo strains were incubated in PSA medium (polypeptone, 10 g L− 1; sucrose, 10 g L− 1; and glutamic acid, 1 g L− 1; pH 6.8–7.0) and shaken at 250 r min− 1 and 28 °C for 42 h. Bacterial suspensions were adjusted to a concentration of about 1 × 109 CFU mL− 1 (OD600 1.0) with SDW and infiltrated into fully expanded leaves of 4-week-old JG30 plants with needleless syringes. For each strain, three plants were inoculated, and three 1-cm2 leaf disks from different infiltrated leaves

were harvested as one sample. After sterilization in 70% ethanol, the disks were ground in a sterilized mortar INK1197 concentration with a pestle in 4 mL SDW, and plated at different concentrations to determine the CFU cm− 2. Serial dilutions were spotted in triplicate onto TSA plates with appropriate antibiotics.

The plates were incubated at 28 °C for 3 to 4 days until colonies could be counted. The experiments were repeated three times. Total genomic DNA of PXO99A and its mutant were isolated as described by Leach et al. [13]. The polymerase chain reaction (PCR) was performed to check the inserted Tn5-DNA fragment using primers Tn5F and Tn5R (Table 1), and the expected PCR product was 569 bp in length. The solution (20 μL) contained 50 ng of template DNA, 1 × PCR buffer, 0.3 mmol L− 1 dNTPs, 0.3 μmol L− 1 each primer, 6-phosphogluconolactonase and 1.0 U KOD Taq polymerase (TOYOBO, Japan). PCR was initiated at 95 °C for 3 min followed by 34 cycles of amplification at 94 °C for 40 s, 60 °C for 40 s, 72 °C for 1 min, and a final extension at 72 °C for 10 min. For Southern blotting, genomic DNA of Xoo strains was digested with SphI (TaKaRa), separated on 1.2% (W/V) agarose gel by electrophoresis, alkali-denatured and transferred onto Hybond-N+ membranes. The DNA probe was amplified from an EZ-Tn5 Tnp Transposome DNA template by PCR using the primers Tn5F and Tn5R. The probe was labeled with [α −32P] dCTP using Random Primer DNA Labeling Kit (TaKaRa) according to the manufacturer’s instruction. Prehybridization, hybridization, and posthybridization washes were carried out as described by Wang et al. [11].