ライフサイエンスコーパス: negative correlation

1 BOD (r = -0.81), while DO exhibited highest negative correlation.

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

3 tic patient melanomas revealed a significant negative correlation.

4 ble and thus non-decodeable, due to spurious negative correlations.

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

6 e positive correlations were largely normal, negative correlations among networks were increased.

7 variations of sea surface temperature (SST, negative correlation) and net primary production indices

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

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

10 antified by causality pairing index showed a negative correlation at progressively lower resolutions

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

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

13 We found a negative correlation between [(18)F]fallypride nondispla

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

15 ptation and subsequently identified a strong negative correlation between AD and VE.

16 Further, we identified a strong negative correlation between ADAM17 and APP gene express

17 A negative correlation between age and E2 concentration wa

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

19 We also found a negative correlation between anxiety-like behavior and a

20 A strong negative correlation between basal cold tolerance and de

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

22 le experimental and field studies-revealed a negative correlation between biodiversity and infectious

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

24 Regression analyses showed a negative correlation between C3 expressing astrocytes an

25 There was a negative correlation between CarCGQoL and PHQ-9 scores (

26 liver samples from obese patients revealed a negative correlation between CDKN2A expression and PPARA

27 There was a negative correlation between choroidal reflectivity and

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

29 There was a negative correlation between corticospinal excitability

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

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

32 There was a strong and negative correlation between DeltaBP(ND) in VST and seve

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

34 we present the first global-scale test of a negative correlation between dispersal and dormancy.

35 However, there was a significant negative correlation between DLPFC GSH and both whole-br

36 tion between ELF5 and FBXW7 expression and a negative correlation between ELF5, FBXW7 and IFNGR1 expr

37 We previously reported a negative correlation between emphysema and circulating g

38 Previous reports have noted a negative correlation between endogenous FeLV (enFeLV) co

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

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

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

42 This negative correlation between fitness and robustness impl

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

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

45 ow that irrigation expansion can explain the negative correlation between global observed changes in

46 ng age as a confounder, there was a moderate negative correlation between GP-to-CA ratio and GBCA dos

47 ed measures correlation analysis indicated a negative correlation between haemoglobin and mean MCAv (

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

49 erfusion curve features, there were a strong negative correlation between hypoxia score, DSC perfusio

50 tizing soft tissue infections demonstrated a negative correlation between IVIG dose and toxin-trigger

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

52 to the Pearson results, acrylamide showed a negative correlation between L* value.

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

54 There was a negative correlation between LA stiffness and %predicted

55 A negative correlation between lake temperature and fish a

56 Our previous work unveiled a positive and a negative correlation between levels of gamma interferon

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

58 mpetitive abilities, there was a significant negative correlation between long distance dispersal abi

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

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

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

62 Finally, we found a negative correlation between METTL3 or METTL14 and STAT1

63 Our measurements reveal a negative correlation between microtubule plus-end densit

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

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

66 Additionally, we found a negative correlation between mitophagy-related proteins

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

68 A negative correlation between negative symptoms and activ

69 A negative correlation between NOx concentrations and delt

70 Additionally, we observed a negative correlation between NOX4 expression and skeleta

71 Here, we found a significant negative correlation between NT-proBNP and GMD in the me

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

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

74 A negative correlation between particle size and wettabili

75 results disclosed statistically significant negative correlation between patient age and diameter of

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

77 There was statistically significant moderate negative correlation between PET-SUV(max) and ADC values

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

79 There was a negative correlation between physicochemical stability a

80 Furthermore, the negative correlation between plague outbreaks and their

81 In addition, we find a significant negative correlation between population size and frequen

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

83 Treatment responders showed a negative correlation between prefrontal grey matter and

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

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

86 There was a negative correlation between protein and transcript leve

87 We show a continuous negative correlation between PTEN and activated Akt in m

88 Results suggest that, there is a negative correlation between PVC and initial porosity, i

89 Some scholars suggest a negative correlation between PVC and initial porosity, w

90 However, there was a negative correlation between rCDI and eAb-B titer on day

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

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

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

94 n SNc-related FC and SMN activity, whereas a negative correlation between RNi-related FC and SMN acti

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

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

97 We found a negative correlation between serum levels of tryptophan

98 Abnormal lacuno-canalicular network and negative correlation between serum osteocalcin and Cobb

99 ystolic blood pressure (r = .37, P = .01), a negative correlation between serum posaconazole levels a

100 systolic blood pressure (r =.37, P=0.01), a negative correlation between serum posaconazole levels a

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

102 percentage of TEs it contains, as well as a negative correlation between size and the CpG observed/e

103 division cycle and reaffirm that there is a negative correlation between size at cell birth and G1 d

104 potic mixed-species groups revealed a strong negative correlation between subcutaneous fat stores and

105 A negative correlation between subfoveal choroidal thickne

106 s compared to controls and PD - HS, showed a negative correlation between subjective value of the del

107 Specifically, we found a nonsignificant negative correlation between T2D and POAG (r(g) = -0.14;

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

109 c factors, with a cooling-driven extinction (negative correlation between temperature and extinction)

110 separated the ASD participants by gender, a negative correlation between thalamic GABA/Water and AQ

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

112 There was also a negative correlation between the amount of tight junctio

113 A negative correlation between the calcium nitrite admixtu

114 There was a strong negative correlation between the CSF tau368/t-tau ratio

115 e gene expression profiles, we found a clear negative correlation between the EGFR diffusivities and

116 We found a negative correlation between the expression of NAT1 and

117 On the other hand, we found a strong negative correlation between the extent of cell-ECM adhe

118 A strong negative correlation between the GPD percentage and the

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

120 NSCLC RNA-seq and microarray data revealed a negative correlation between the loss of the Y chromosom

121 We find a strong negative correlation between the mean shell size of biva

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

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

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

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

126 A negative correlation between the SFCT and axial length w

127 We also found significant negative correlation between the time of the last migrai

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

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

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

131 We found a negative correlation between tolerance and resistance am

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

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

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

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

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

137 two subpopulations that display positive and negative correlations between a pair of queried genes.

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

139 Negative correlations between age and both choroidal thi

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

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

142 Addictions were characterized by negative correlations between DA and discounting, but ot

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

144 a number of previously unknown positive and negative correlations between developmental genes and de

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

146 Results showed strong negative correlations between leaf midrib thickness and

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

148 alyses of human breast tissue samples reveal negative correlations between PAR3 and SNAI1 protein lev

149 ve correlation between PHF8 and PKCalpha but negative correlations between PHF8 and PTEN and between

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

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

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

153 There were statistically significant negative correlations between the Ct values and duration

154 ered demographic compensation in the form of negative correlations between the means of plant vital r

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

156 Furthermore, negative correlations between vascular resistance and he

157 Conceivably, the ubiquitous negative correlations enable the differentiation of func

158 In contrast, a negative correlation existed between dopamine(+) GCs and

159 A strong negative correlation exists between average gHFI and ave

160 A weak negative correlation exists between OAG and AD diagnosis

161 A negative correlation exists between OAG and ALS diagnosi

162 In clonal cells, we observed a negative correlation for the expression of sense-antisen

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

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

165 jects), with an almost complete loss of this negative correlation in cognitively impaired participant

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

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

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

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

170 Negative correlations increased the reduction in ecosyst

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

172 This negative correlation is more pronounced for highly expre

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

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

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

176 nd 0.52, respectively, p value < 0.0001) and negative correlation of Cho/Cr ratio (R -0.5, p value 0.

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

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

179 We also found a statistically significant negative correlation of intratumoral remodeling with met

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

181 The negative correlation of REs with specific genomic repeat

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

183 Here, we demonstrate stereotyped negative correlation of somatostatin and parvalbumin tra

184 An unexpected negative correlation of the average blocking temperature

185 A moderate negative correlation of the difference of FSS and 6MWT a

186 The negative correlation of the O(2) respiration rate with t

187 icrosirius red staining revealed significant negative correlations of entropy with G (d) (r = -0.69,

188 tion than did the Non-CM group and confirmed negative correlations of gray matter volume (GMV) in the

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

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 h would explain its survival and the general negative correlation (R = - 0.3) observed between male a

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

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

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

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

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

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

201 43 miRNA-mRNA pairs displayed significantly negative correlations (r < -0.8).

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

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

204 ssion and methylation show both positive and negative correlation, suggesting a complex transcription

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

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

207 A negative correlation was determined between IL30 express

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

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

210 A significant negative correlation was found between all symptoms and

211 A negative correlation was found between coliform removal

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

213 A significant negative correlation was found between IBW and OIL (P =

214 A strong negative correlation was found between the left ventricu

215 A negative correlation was found between the logarithm of

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

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

218 The negative correlation was not as strong once individuals

219 Negative correlation was noted between sleep scores and

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

221 A negative correlation was observed between FA in the hipp

222 A negative correlation was observed between fibrosis and e

223 Negative correlation was observed between motor thalamus

224 ved between log S and the uptake rate, and a negative correlation was observed between p K(a), log D,

225 Interestingly, a negative correlation was observed between parasite load

226 A significant negative correlation was observed between RUNX2 mRNA lev

227 On the contrary, a negative correlation was observed between surface fat an

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

229 A negative correlation was observed between WMC and implic

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

231 Negative correlations were found between left putamen PE

232 Negative correlations were found for the tibial nerve co

233 Negative correlations were found for the tibial nerve co

234 Negative correlations were found with sural nerve conduc

235 For most sugar-parameters, negative correlations were found with the total precipit

236 Significant negative correlations were identified between Th2 measur

237 Negative correlations were observed between arm function

238 Mostly negative correlations were observed between biopsy eosin

239 Negative correlations were observed between duration of

240 Negative correlations were observed between the global r

241 ded alpha/beta power, we found a significant negative correlation which indicated that as post-stimul

242 (all Spearman coefficients 0.289-0.464), and negative correlation with 1 factor: mean kidney waiting

243 (all Spearman coefficients 0.289-0.464), and negative correlation with 1 factor: mean kidney waiting

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

245 4e-08; Pcohort2 = 0.00205) and a significant negative correlation with age of SLE onset (Pcohort1 = 1

246 ion with age, whereas other parameters had a negative correlation with age: astigmatism (r = -0.09; P

247 The LARS score showed negative correlation with all five of the QLQ-C30 functi

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

249 ated with CXCL10 levels identified a strong, negative correlation with bacterial burden, suggesting t

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

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

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

253 GA showed a significant negative correlation with CFT, IRT, ORT, foveal SCP-VD,

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

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

256 diabetic patients, ECD showed a significant negative correlation with diabetes duration (p = 0.028).

257 ion Engine, and shortlisted those that had a negative correlation with differential gene expression o

258 ase of TEWL was observed, with a significant negative correlation with EI, demonstrating that EI chan

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 e not associated with rapid EMs, displayed a negative correlation with gamma activity, and were also

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

265 IFG and target regions (p = 0.0002), due to negative correlation with IFG-LINS (p = 0.0003) and IFG-

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

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

268 ramadol, atenolol, and pregabalin had strong negative correlation with IRSAD.

269 RS had strong negative correlation with its estrogen module (rho = -0.

270 At baseline, T1 values showed a negative correlation with left ventricular mass ( r=-0.7

271 nor-specific antibodies (DSAs) have a strong negative correlation with long-term survival in solid or

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

273 cules and IFN response pathways and a strong negative correlation with Myc transcriptional signature.

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

275 Asian population (r = 0.38, P < .001) and a negative correlation with obesity (r = -0.36, P < .001),

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

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

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

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

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

283 f the test (or production) data has a strong negative correlation with the quality of error correctio

284 In patients with T2D, hsTNT showed a negative correlation with the sciatic nerve's FA (r = -0

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

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

287 C) fractions, whereas laccase activity had a negative correlation with those fractions.

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

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

290 ientwise) = 0.50 and 0.70, respectively) and negative correlations with ADC (r (voxelwise) = -0.19 an

291 blurring strength (r = -0.31; P < 0.001) had negative correlations with age.

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

293 Subsequent voxelwise analyses revealed negative correlations with FC between the hCd and the do

294 nd moderate levels of physical activity, and negative correlations with higher cognitive performance,

295 dataset revealed lower abundances in IBD and negative correlations with inflammation and host sphingo

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

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

300 ns were also functionally connected, through negative correlation, with regions in the left frontal c