ライフサイエンスコーパス: negative correlation

1 responses in CHB patients, while NEIL3 shows negative correlation.

2 tic patient melanomas revealed a significant negative correlation.

3 ion and transcript levels showed significant negative correlation.

4 hibit fewer small-world properties, and lack negative correlations.

5 ydroperoxides (LHPODs) exhibited significant negative correlation (0.76, 0.74, 0.72; p<0.0001) in sel

6 unctional connectomes) and demonstrated that negative correlations alone are sufficient in understand

7 mical structure, and comprising positive and negative correlations among brain regions.

8 Surprisingly, we identified negative correlations among some satellites, suggesting

9 ns between wet season NBE and precipitation (negative correlation) and temperature (positive correlat

10 ercentages of (+)-catechin as terminal unit (negative correlation), and of (-)-epicatechin and (-)-ep

11 tations are reformatted so that positive and negative correlations arise between representations of d

12 ns typically <|0.05|) but with carbohydrate (negative correlation as low as -0.39).

13 expression measured by RNA sequencing, with negative correlations being more common in 5' UTR and po

14 A negative correlation between 25(OH)D and distance from t

15 Furthermore, there was a negative correlation between 40 Hz ITC and PANSS subscal

16 Also, there is a strong negative correlation between Abeta42-induced DNA damage

17 A negative correlation between age and E2 concentration wa

18 We determined a significant negative correlation between age and NET availability in

19 British and the Icelandic samples, showing a negative correlation between age of samples and levels o

20 Finally, we found a negative correlation between AKT phosphorylation and O-G

21 boundary current dynamics and find a strong negative correlation between AMOC strength and EEA subsu

22 rsus neutral contrast revealed a significant negative correlation between amygdala response and DRN b

23 ents with Alzheimer's disease demonstrated a negative correlation between amyloid-beta and endophilin

24 A negative correlation between antiviral cytokines and IL-

25 A strong negative correlation between basal cold tolerance and de

26 developmental acclimation, whereas a weaker negative correlation between basal cold tolerance and sh

27 cted by the body size hypothesis, there is a negative correlation between body size and substitution

28 We find a negative correlation between branching morphogenesis and

29 Preclinical data suggest a negative correlation between brown adipose tissue (BAT)

30 We found negative correlation between CCR2 and CX3CR1 expressions

31 city, a CD34+ cell nadir 7 days after AMI, a negative correlation between CD11b percentage and postin

32 There was a significant negative correlation between change in ADC and change in

33 There was a negative correlation between choroidal reflectivity and

34 Moreover, we found a negative correlation between circulating levels of these

35 There was a negative correlation between clearance and concentration

36 A negative correlation between CMV load in saliva and mate

37 ogous thiophene systems, indicating that the negative correlation between conductance and aromaticity

38 Negative correlation between cortical thickness and t-ta

39 There was a negative correlation between corticospinal excitability

40 There was a negative correlation between CSF ascorbic acid and CSF a

41 We also observed a strong negative correlation between CT and drive for thinness i

42 lly HBV-infected patients exhibited a strong negative correlation between DDX5 messenger RNA levels,

43 There is a strong negative correlation between DeltaSsolv and DeltaSconf f

44 blished from impedance data which exhibits a negative correlation between drug doses and impedance of

45 for confounders, revealed a significant and negative correlation between duration of fluoxetine inta

46 Our results indicate a strong negative correlation between ENSO variability and zonal

47 EST and body mass index (BMI), as well as a negative correlation between ERalpha expression and BMI.

48 Several studies have reported a negative correlation between estimates of the nonsynonym

49 Furthermore, we observed a negative correlation between exon methylation and the de

50 There was also a significant negative correlation between expression of lncRNA-p19461

51 sequencing of the same tumor set revealed a negative correlation between expression of the Mir216/21

52 There was moderate negative correlation between EZW constriction and age (r

53 There was also a negative correlation between FCD and GCD (r = -0.7; P <0

54 red at the left middle frontal gyrus shows a negative correlation between flow and education, which i

55 onal connectivity analysis, which suggests a negative correlation between fluctuations in the default

56 In healthy, SIV-uninfected RM, we observed a negative correlation between frequencies of TFR and both

57 There was a significant negative correlation between gray matter CVR and lesion

58 A similar negative correlation between H3K36me3 marking and mRNA e

59 We also find a negative correlation between host dependence and symbion

60 orted by clinical data showing a significant negative correlation between hypoxia and PER2.

61 Meta-regression showed a negative correlation between ineligibility at standard a

62 Recent studies have shown a negative correlation between infiltration of memory T ce

63 distribution of injection event sizes and a negative correlation between injection size and frequenc

64 We also found a negative correlation between ITCH and M2 marker expressi

65 In individual cells, there was a negative correlation between Kir4.1 currents and GTCs.

66 Additionally, there was a negative correlation between l-DLPFC GABA levels, but no

67 A negative correlation between lake temperature and fish a

68 Moreover, we observed significant negative correlation between levels of miR-122* and Mdm2

69 mporal frequency bias of cone vision and the negative correlation between magnitude and frequency for

70 A number of studies have shown a negative correlation between memory retrieval in alpha a

71 n patterns of high-read genes that exhibit a negative correlation between methylation and expression

72 at autosomal imprinted regions, some with a negative correlation between methylation in the two cont

73 in an excess of low-frequency variants and a negative correlation between minor allele frequency and

74 Here, we show a negative correlation between miR-203 expression and the

75 Furthermore, we show that a negative correlation between miR-339-5p and MDM2 express

76 Data from melanoma patients show a negative correlation between MIR31HG and p16(INK4A) expr

77 This negative correlation between MMP-9 and miR-494 levels wa

78 n the ventral striatum were accompanied by a negative correlation between myelin and iron specific fo

79 Results revealed a negative correlation between neural activity and percept

80 In agreement, we observe a negative correlation between NF-kappaB activity and the

81 Regarding CHX use, there was a negative correlation between nitrite and total bacterial

82 of purified PBMCs from patients indicated a negative correlation between NOS1 expression in melanoma

83 A negative correlation between NOx concentrations and delt

84 In patients with HCV-CV, there was a negative correlation between numbers of IgM+CD21-/low me

85 tic success, which likely contributes to the negative correlation between obesity and ovarian cancer

86 Furthermore, a negative correlation between OX-A and alpha-MSH serum le

87 A negative correlation between particle size and wettabili

88 trate different characteristics with often a negative correlation between PET and MR ADC pixel values

89 lative to controls, as well as a significant negative correlation between pH and lactate levels.

90 e loci are rarer than expected and exhibit a negative correlation between phenotypic effect size and

91 ural correlates with connection strengths: a negative correlation between phonemic perception and an

92 s shows increased PKCdelta expression, and a negative correlation between PKCdelta expression and pro

93 Furthermore, the negative correlation between plague outbreaks and their

94 For BRVO or CRVO, there was a negative correlation between posterior retinal nonperfus

95 There is a negative correlation between PPP1R11 and TLR2 levels in

96 tic dopamine using human imaging measures: a negative correlation between prefrontal glutamate and pr

97 ASE in six genes showed significant negative correlation between promoter methylation and ex

98 ents with pouchitis vs controls; there was a negative correlation between proportion of Faecalibacter

99 There was a significant negative correlation between proportion of the optic dis

100 w divergent selection leads to a genome-wide negative correlation between recombination rate and gene

101 s, among attempters, there was a significant negative correlation between right rostral prefrontal co

102 lly available clinical data sets displayed a negative correlation between RNF31 and p53 target genes,

103 the RS contents or GI values, while a strong negative correlation between RS contents and GI values w

104 re than 500 patients with IBD, we observed a negative correlation between serum levels of tryptophan

105 We found a negative correlation between serum levels of tryptophan

106 There was a strong negative correlation between SET and SDW.

107 At baseline, there was a strong negative correlation between spillover and leg fat (r =

108 A negative correlation between subfoveal choroidal thickne

109 However, we observed a significant negative correlation between TALEN mutagenicity and the

110 We also observed significant negative correlation between task reaction times and hem

111 ect sampling of ants and termites revealed a negative correlation between the abundance of B. chinens

112 We find a negative correlation between the amount of reused text i

113 in cochlear organotypic cultures revealed a negative correlation between the expression levels of mi

114 A prominent example is the negative correlation between the growth rate and the bio

115 eyes, there was a statistically significant negative correlation between the logarithm of the minimu

116 There was also a negative correlation between the mean ESS and the remode

117 There was a negative correlation between the number of segments with

118 There was a negative correlation between the number of suicides and

119 e of tissue lipid content, while a generally negative correlation between the PAH concentration in cu

120 Furthermore, we found a negative correlation between the PCB concentrations in s

121 eding and transfusion, but there is a strong negative correlation between the predicted risk of bleed

122 In systemically deafened animals there was a negative correlation between the presence of differentia

123 luzzii females collected from houses shows a negative correlation between the presence of Plasmodium

124 We found a negative correlation between the serum levels of bevaciz

125 A negative correlation between the SFCT and axial length w

126 We found a negative correlation between the tCho and PET results in

127 There was a strong negative correlation between the VEGF concentration and

128 was uniquely in the PBI group a significant negative correlation between the volume of this tract an

129 ifferentially methylated regions (DMRs) with negative correlation between their expression and methyl

130 in fish exposed to 225.9 mug/L linuron and a negative correlation between total cholesterol and linur

131 However, negative correlation between total polyacetylenes and he

132 GLUR3 subunit showed a significant negative correlation between total running distance and

133 determining protein synthesis rates, and the negative correlation between transcript length and both

134 A significant negative correlation between Tregs suppression and the s

135 We found a negative correlation between trophic position and niche

136 sion of the tumor into the stroma, we find a negative correlation between tumor size and BM stiffness

137 Importantly, we identified a negative correlation between uncinate fasciculus integri

138 PLS analysis exhibited both positive and negative correlation between various attributes indicati

139 There was a negative correlation between vascular density and age th

140 Most surprisingly, we discover a strong negative correlation between viral population size and t

141 There was a negative correlation between white matter volume and cor

142 We found a small negative correlation between yeast replicative age and I

143 tigation of AAS use on brain structure shows negative correlations between AAS use and brain volume a

144 of soluble tau (tau-CP13 and tau-Alz50), and negative correlations between Abeta*56 and two postsynap

145 was analyzed over multi-regional network of negative correlations between alpha band power during cu

146 ealed that while RH influences the long-term negative correlations between AOD and precipitation, it

147 the paradox, showing that it is enhanced by negative correlations between degrees of neighboring nod

148 There were negative correlations between endotoxin core IgM and IL-

149 The negative correlations between fear extinction deficits a

150 n these two major value care frameworks, and negative correlations between framework outputs and drug

151 e, a growing number of studies have reported negative correlations between host biodiversity and dise

152 mat enables detection of positive as well as negative correlations between ion intensities and biolog

153 s or 'offshore' sites, and both positive and negative correlations between methylation and expression

154 The negative correlations between MRP and DO is marked (r =

155 SF) levels for both Abeta42 and Abeta40, and negative correlations between plasma Abeta42 and neocort

156 rved nectar concentrations of bat flowers or negative correlations between pollinator body size and a

157 ability was larger with low signal strength (negative correlations between signal strength and peak a

158 There were weak to moderate, negative correlations between TFS-AF thresholds and audi

159 The authors identified significant negative correlations between VAS score and MR imaging b

160 Furthermore, negative correlations between vascular resistance and he

161 gnments and explore the possibility that the negative correlation can be entirely explained by those

162 Both strong and negative correlations could be observed among the inflam

163 in subjects with atopy and asthma, whereas a negative correlation existed between FEV1 and serum leve

164 Simulated PM concentrations show a strong negative correlation (i.e. R = -0.86) with regional wind

165 of RUNX1 isoforms on PCTP expression with a negative correlation in blood between RUNX1 expressed fr

166 For example, we found a unique negative correlation in concentration levels of anthocya

167 BLA circuit activation in EMD animals, and a negative correlation in PRO animals.

168 in the early successional forest, and even a negative correlation in the late successional forest, in

169 over, ~40% of bicistronic transcripts showed negative correlation in the translation levels of their

170 regions as broad as 5 Mb show a significant negative correlation in TMRCA with exon density.

171 to greater frequency of strong positive and negative correlations in activity across sliding windows

172 n eastern Alaska and northwestern Canada but negative correlations in the northwestern U.S.

173 Negative correlations increased the reduction in ecosyst

174 A higher negative correlation is associated with a worse PFS, whi

175 Spatially, a negative correlation is detected between areas with adva

176 This negative correlation is more pronounced for highly expre

177 of author order, while in other sciences the negative correlation is seen only for total citation imp

178 A more significant negative correlation may indicate higher-grade elements

179 on was highly variable, with little and even negative correlation observed at some synapses.

180 Negative correlations occurred in forests where tree gro

181 served change in rainfall, both positive and negative (correlation of 0.69), and can explain most of

182 res of eukaryotic translation, including the negative correlation of both ribosome densities and prot

183 l frontal pole in depressed patients, with a negative correlation of disease severity and duration.

184 od acute myeloid leukemia (AML) have shown a negative correlation of IDO-1 mRNA expression with outco

185 ted high levels of iron are accompanied by a negative correlation of iron and myelin in the ventral s

186 g sequence-based miRNA target prediction and negative correlation of miRNA-mRNA profiles helped ident

187 ddition, the results reflected a significant negative correlation of salivary leptin and a positive c

188 Moreover, negative correlations of the ER/GPP ratio with soil temp

189 the additional property of many significant negative correlations outside their own group in the net

190 Time-frequency analyses revealed a negative correlation over sensorimotor cortex between ga

191 1) across three genomes revealed significant negative correlation (P < 0.05) between frequency of opt

192 tofluorescence analyses revealed significant negative correlation (P-value=0.017) between 8-hydroxy g

193 However, there are borderline significant negative correlations (p = 0.08) between the smoking-ass

194 he majority of sampled fibroids had a strong negative correlation (Pearson's r=-0.68 or beyond) betwe

195 m surface area theory, but contradicting the negative correlations predicted by resource-transport ne

196 Our study found a strong negative correlation (R (2) = 0.49) between ice cover in

197 profiled its expression patterns detecting a negative correlation (R = - 0.7) between the expression

198 We also found a negative correlation (r = -0.37, p < 0.001) between R an

199 A robust negative correlation (r = -0.879, p = 0.0001) between CS

200 However, there was a significant negative correlation (r>-0.81; P<0.01) between GI value

201 and 13.1% (SD=1.1%), respectively; a modest, negative correlation (r=-0.17; P=0.003) was found betwee

202 duction in intrinsic viscosity, had a strong negative correlation (r=-0.96) with specific mechanical

203 43 miRNA-mRNA pairs displayed significantly negative correlations (r < -0.8).

204 Strong negative correlation (rs = -0.701; P < .001) between the

205 as a self-similar random process with a weak negative correlation similar to a random walk.

206 deltaCFmin thresholds revealed a pronounced negative correlation (Spearman rho = -0.99, P < 0.001) b

207 and calmodulin-like protein 5 showed strong negative correlation to the AE group, with a correlation

208 admitted that its airborne pollen count has negative correlation to the average temperature.

209 admitted that its airborne pollen count has negative correlation to the rainfall.Artemisia indica ad

210 All elements displayed a significant negative correlation to the wetland coverage, but the in

211 ndependent of later responses, and exhibited negative correlations to several ROS indices.

212 al brain structures that showed prespecified negative correlation values of FA over time of -0.5 or l

213 A negative correlation was detected between changes in ant

214 A negative correlation was determined between IL30 express

215 This negative correlation was eliminated when the very obese

216 and the amplitude of the beta ERS, and this negative correlation was enhanced when other contextual

217 A general strong negative correlation was found between AA and polarity.

218 A negative correlation was found between AL and Kmed (-0.3

219 Negative correlation was found between cellularity and A

220 When all tumors were considered together, negative correlation was found between cellularity and m

221 Negative correlation was found between cellularity and m

222 A negative correlation was found between cognitive functio

223 A negative correlation was found between coliform removal

224 On the other hand, a significant negative correlation was found between EET formation and

225 A negative correlation was found between proNGF, phospho-J

226 A strong negative correlation was found between the left ventricu

227 A negative correlation was found between the logarithm of

228 A negative correlation was found between the percentage of

229 For these groups, significant negative correlation was found between the SSI and the n

230 A negative correlation was found in the brain (r = 20.798;

231 g the autumn and the winter seasons, while a negative correlation was identified over the Maritime Co

232 The negative correlation was not as strong once individuals

233 uring the course of infection, a progressive negative correlation was noted between PD-1 density and

234 d varieties, respectively), whereas a strong negative correlation was observed between eGI and RS (r=

235 A negative correlation was observed between FA in the hipp

236 A negative correlation was observed between fibrosis and e

237 A weak but significant negative correlation was observed between HRQoL score an

238 In patients, a significant negative correlation was observed between right hippocam

239 A significant negative correlation was observed between RUNX2 mRNA lev

240 Furthermore, a robust negative correlation was observed between the degree of

241 ly correlated with flow resistance index and negative correlation was observed between the intensity

242 A negative correlation was observed between WMC and implic

243 The highest negative correlation was shown between the PA and ECW:IC

244 Negative correlations were found between left putamen PE

245 Negative correlations were found between markers of myoc

246 Mostly negative correlations were observed between biopsy eosin

247 Negative correlations were observed between duration of

248 Significant positive and negative correlations were observed between periodontal

249 Strong positive and negative correlations were observed between the periodon

250 Strong negative correlations were observed between uptake of MM

251 btained for severity of abdominal pain had a negative correlation with A (r = -0.55, p = 0.03).

252 mong wet basins, TNMA emissions had a strong negative correlation with average gas production per wel

253 Its mortality showed a similarly negative correlation with both indices.

254 d with neuritic plaque score but did display negative correlation with Braak staging.

255 a Severity Score (rs = 0.33; P < .001) and a negative correlation with central corneal thickness (rs

256 that the velocity of ultrasonic waves had a negative correlation with coal permeability, and the fre

257 ME, ADCSE, and ADCDKI all showed significant negative correlation with cytoplasmic and cellular fract

258 n the left nucleus accumbens, which showed a negative correlation with disease duration and overlappe

259 l disability, and handicap dimensions showed negative correlation with esthetics.

260 ing protein levels only showed a significant negative correlation with ex vivo production of interleu

261 us and oscillation yield stress, displayed a negative correlation with FALs and a positive correlatio

262 The TPC had a negative correlation with fungal occurrence whilst the t

263 Pack-years of smoking have significant negative correlation with goblet cell density (r = -0.17

264 changes (P <0.05), whereas adipsin showed a negative correlation with IPGTT area under the curve val

265 sociated with cognitive function; however, a negative correlation with IQ at age 11 years (beta=-0.08

266 Nutrient supply by fishes also showed a negative correlation with juvenile coral density, likely

267 8 expression was shown to exhibit a strongly negative correlation with lymph node invasion, distant m

268 xpression in obese human subjects exhibits a negative correlation with measures of insulin sensitivit

269 lved oxygen, while the same analysis found a negative correlation with metals and CVOC concentrations

270 The expression of AP2-1 target showed a negative correlation with miR172c expression.

271 e during W and maximally active during PS in negative correlation with muscle tone.

272 n controls, whereas in the SP group it had a negative correlation with NAAc and no significant relati

273 d-(18)F-FMT tumor-to-blood pool ratio had a negative correlation with overall survival (P = 0.050),

274 umen (rho = 0.43 and 0.50, respectively) and negative correlation with percentage area of nuclei (rho

275 mph node metastasis, which has a significant negative correlation with Pin1 expression.

276 Negative correlation with Positive and Negative Syndrome

277 n with lactoferrin and IL-1ra and a stronger negative correlation with Rothia.

278 Temporal lobe volume had a negative correlation with serum IL-1RA level (P= .012) a

279 rogenase activity, and lipase activity and a negative correlation with soil pH, conductivity, and cat

280 ovariates, the coefficient had a significant negative correlation with the air dose rate in the dwell

281 ation concentration (CCC) displayed a strong negative correlation with the carbon number in fullerene

282 h absorbance values at OD294 and OD420 but a negative correlation with the CIB L( *) value of a solut

283 ciated peptides displaying a significant and negative correlation with the degree of fibrosis.

284 "fight-club hubs" characterized by a marked negative correlation with the expression profiles of nei

285 However, MAG:PLP1 showed a significant negative correlation with the level of EDN1, which we pr

286 tient satisfaction may have little or even a negative correlation with the quality of surgical care,

287 h elevation and latitude, delta(13)Croot was negative correlation with them at high altitude (3000~50

288 , and delta(13)Croot and delta(13)Csoil were negative correlation with them at low altitude (0~2000m)

289 itive correlation with the PPO activity, but negative correlation with TP, AC and AA.

290 sponse to hypercortisolaemia showed a strong negative correlation with waist to hip ratio (Spearman's

291 CDC42 nuclear expression revealed negative correlations with basal (CK5) and HER family bi

292 becular and cortical bone densities revealed negative correlations with BMI, SAT, and VAT.

293 tions with percent large bran particles, and negative correlations with bran starch content.

294 and TH2 cytokine (IL-4 and IL-5) levels and negative correlations with differentiation products (lor

295 malignant GCT cells, confirming significant negative correlations with let-7 levels.

296 Organic aerosol emissions had negative correlations with MCE, whereas the oxidation st

297 ntrations) values were comparable and showed negative correlations with nitrogen concentration, load

298 , HK:HAA, and HK:KA showed markedly stronger negative correlations with PLP than did HK alone (Spearm

299 on network and the motor-control network and negative correlations with the default-mode network.

300 s of the CA2/3, CA4 and hippocampal tail had negative correlations with the number of manic episodes.