ライフサイエンスコーパス: BIA

1 BIA 10-2474, but not PF04457845, produced substantial al

2 BIA indicated a greater increase in ICW in 23 (21%) pati

3 BIA is also potentially useful for assessing the hydrati

4 BIA is especially problematic with large changes in body

5 BIA overestimates FFM compared with DXA in those with gr

6 BIA probably holds less promise for detecting small chan

7 BIA was a good predictor of DXA-derived FFM (r = 0.85-0.

8 BIA was conducted on all patients and phase angle was ca

9 BIA, SFTs, and BMI provided unbiased estimates of decrea

10 W were not measured by dilution studies, 158 BIA measurements were taken for determining TBW.

11 Benzylisoquinoline alkaloids (BIAs) are a family of approximately 2500 alkaloids with

12 Benzylisoquinoline alkaloids (BIAs) are produced in a wide variety of plants and inclu

13 ide variety of benzylisoquinoline alkaloids (BIAs), including the pharmaceutical compounds codeine, m

14 biosythesis of benzylisoquinoline alkaloids (BIAs).

15 infold thickness, and bioimpedance analysis (BIA).

16 orptiometry (DXA) and bioimpedance analysis (BIA).

17 on whether bioelectrical impedance analysis (BIA) accurately predicts changes in body composition ass

18 whole-body bioelectrical impedance analysis (BIA) approach for estimating adiposity and body fat is b

19 angle from bioelectrical impedance analysis (BIA) can be interpreted as a surrogate marker for the ca

20 producible bioelectrical impedance analysis (BIA) data.

21 s-specific bioelectrical impedance analysis (BIA) equations of Segal et al. have been shown to be gen

22 utility of bioelectrical impedance analysis (BIA) for assessing changes in body composition and conte

23 Bioelectrical impedance analysis (BIA) has potential in the area of sports and exercise as

24 -frequency bioelectrical impedance analysis (BIA) in 332 subjects, including white, black, and Hispan

25 to include bioelectrical impedance analysis (BIA) in a national nutrition survey.

26 Bioelectrical impedance analysis (BIA) is a promising tool in the evaluation of body compo

27 Bioelectrical impedance analysis (BIA) is an attractive method of measuring pediatric body

28 ass (FFM), bioelectrical impedance analysis (BIA) offers an alternative to physical performance testi

29 (TSF) and bioelectrical impedance analysis (BIA) to estimate changes in body fat over time in childr

30 Bioelectrical impedance analysis (BIA) variables and selected anthropometric characteristi

31 oth cohorts; bioelectric impedance analysis (BIA) was conducted only in preadolescent children.

32 es (SFTs), bioelectrical impedance analysis (BIA), and body mass index (BMI; in kg/m2) were compared

33 thickness, bioelectrical impedance analysis (BIA), and dual-energy X-ray absorptiometry (DXA), and co

34 ermined by bioelectrical impedance analysis (BIA), detects changes in tissue electrical properties an

35 g (HW) and bioelectrical impedance analysis (BIA), in adults.

36 ose, using bioelectrical impedance analysis (BIA), to measure total body water (TBW) and extracellula

37 ptiometry, bioelectrical impedance analysis (BIA), total body potassium, densitometry, and in vivo ne

38 (DWF) and bioelectrical impedance analysis (BIA).

39 ofrequency bioelectrical impedance analysis (BIA).

40 and in a biomolecular interaction analysis (BIA) system.

41 old-thickness measurements (mean: 21.05) and BIA (mean: 21.52).

42 The differences in estimation between AP and BIA and between BIA and HW were not significantly differ

43 s found between short-term weight change and BIA (r = 0.38, p = 0.001).

44 ty of FFM and fat mass determined by DXA and BIA was dependent on the specific BIA equation used.

45 %BF was measured by AP, HW, and BIA.

46 y fat estimates by ADP, TSF measurement, and BIA were compared with those by DXA.

47 total body protein by using a DXA system and BIA unit was developed and compared with NAA as proof of

48 ce was found between underwater weighing and BIA in estimating the fat-free mass of the obese and non

49 approach--the Bayesian Ising Approximation (BIA)-to rapidly calculate posterior probabilities for fe

50 Binding-inhibition assays (BIAs) were reproducible, and the 2 assays had a high lev

51 in estimation between AP and BIA and between BIA and HW were not significantly different between the

52 different from %BF(HW) (25.1+/-7.7%) or %BF(BIA) (23.9+/-7.7%), and %BF(AP) was significantly correl

53 %BF(HW) (r = 0.944, P < 0.001) and with %BF(BIA) (r = 0.859, P < 0.01).

54 Whole-body BIA data suggest an increase in appendicular body cell m

55 Whole-body BIA was assessed at 50 KHz.

56 verall, greatest relative reactivity in both BIA and adherence inhibition assays was demonstrated aga

57 TSF measurement (Dezenberg equation) and by BIA (Suprasongsin and Lewy equations).

58 eliability was greatest for DXA, followed by BIA and skinfold-thickness measurement.

59 between resistance and reactance measured by BIA and body composition has led to the development of e

60 Body cell mass (BCM) was measured by BIA.

61 Data obtained by BIA indicated limited reactivity of a panel of high-tite

62 ody fat were systematically overestimated by BIA equations (1.37 +/- 6.98%; P < 0.001).

63 with BCM (-0.9 kg/log RNA; P = 0.03), TBF by BIA (-1.4 kg/log RNA; P = 0.05) and by DWF (-1.6 kg/log

64 Comparisons were made by using different BIA equations.

65 Almost all documented BIA-ALCL cases have been associated with a textured devi

66 DXA, BIA, SFTs, and BMI are comparably accurate for evaluatin

67 The differences between DXA, BIA, and SKF in the determination of fat mass and FFM ar

68 ias) for estimates of changes in %BF by DXA, BIA, SFTs, and BMI were similar (range: +/-2.0-2.4% of B

69 mptomatic malaria when measured using either BIA.

70 nobese and obese fatness-specific equations (BIA average method) could be used in lieu of the skinfol

71 Only a few BIAs accumulate readily in plants, which limits the phar

72 FFM(BIA) and FFM(DXA) were significantly different (P: < 0.0

73 The difference between FFM(DXA) and FFM(BIA) was significantly greater with greater weight and b

74 There is, however, a tendency for BIA to overestimate percentage body fat, and more so in

75 The variance in percentage of fat values for BIA was significantly smaller than that for the other tw

76 ediction equations for body composition from BIA measures and anthropometry, and factors associated w

77 -calibration protein (DC-TBPro) derived from BIA water, bone mass, and body volume.

78 Poor correlation of TBW derived from BIA with TBW by deuterium dilution was found (r = 0.36,

79 and %BF from whole-body DXA, resistance from BIA, and anthropometric measures were made in 27 obese w

80 To assess how BIA-ALCL develops, its risk factors, diagnosis, and subs

81 BOX as a multifunctional oxidative enzyme in BIA metabolism.

82 catalysis is not known for NMTs involved in BIA metabolism.

83 yltransferases (NMTs) play critical roles in BIA biosynthesis, but the molecular basis of substrate r

84 nmental factors have been shown to influence BIA.

85 fatty acid amide hydrolase (FAAH) inhibitor BIA 10-2474 led to the death of one volunteer and produc

86 The INNO BIA AlzBio3 multiplex immunoassay was used to measure CS

87 The CSF biomarkers were measured by INNO-BIA AlzBio3 immunoassay (Abeta1-42, T-tau, and P-tau181;

88 Tetrapolar, single-frequency (50 kHz) BIA was included in the third National Health and Nutrit

89 The leg-to-leg BIA system accurately assessed fat-free mass in obese an

90 to determine the validity of the leg-to-leg BIA system in 1) estimating body composition in obese an

91 t-associated anaplastic large cell lymphoma (BIA-ALCL), a rare peripheral T-cell lymphoma, is increas

92 kness, skinfold-derived percentage fat mass, BIA-derived percentage fat mass, BMI, and BMI-defined ov

93 view details the current status of microbial BIA synthesis and derivatization, including rapid develo

94 BI measurements were made with a model BIA-101 apparatus (RJL Systems, Detroit).

95 the bilingual interactive-activation model (BIA+).

96 Moreover, BIA methods show great promise for portable analysis bec

97 nctional genomics platform to identify novel BIA biosynthetic and regulatory genes in opium poppy has

98 AH inhibitors, that off-target activities of BIA 10-2474 may have played a role.

99 ted oral doses (2.5 to 20 mg for 10 days) of BIA 10-2474 had been administered to 84 healthy voluntee

100 rent technology, the utility and efficacy of BIA merit evaluation in large, longitudinal studies if o

101 rologic disorder occurred after ingestion of BIA 10-2474 at the highest dose level used in a phase 1

102 termine the protein interaction landscape of BIA 10-2474 in human cells and tissues.

103 gned to placebo (2 participants) or 50 mg of BIA 10-2474 per day (6 participants).

104 Values derived from use of BIA and skinfold thickness, estimated by using the Jacks

105 These procedures negate the use of BIA as a fast and simple method.

106 Our results showed that the biosynthesis of BIAs (e.g. morphine, thebaine) was significantly reduced

107 umerous NMTs involved in the biosynthesis of BIAs and other specialized metabolites.

108 Prediction equations based on BIA have been validated and cross-validated in children,

109 Data on BIA-ALCL, such as pathophysiology, patient demographics,

110 ickness (mean difference: 6.33 +/- 12.3%) or BIA (mean difference: -6.55 +/- 13.6%) and 18O.

111 ly, but ADP performed better than did TSF or BIA.

112 within 3.5%BF compared with 24-59% for other BIA equations.

113 BIA average method, was compared with other BIA equations published previously for 602 American Indi

114 te the performance of 13 published pediatric BIA-based predictive equations for total body water (TBW

115 mpartment methods had the highest precision; BIA had the lowest.

116 Presently, BIA does not appear to be a useful clinical technique fo

117 both synthetic and viral vectors to regulate BIA metabolism and biosynthesis.

118 ed as a simple index (stature2/ resistance), BIA is more sensitive and specific for grading average a

119 Shifting BIA production to microbial sources could provide a scal

120 Among men, no single BIA equation was more highly predictive of fat mass and

121 by DXA and BIA was dependent on the specific BIA equation used.

122 for the differential occurrence of specific BIAs in each cultivar as demonstrated using the biochemi

123 After SPR-BIA the tagged peptides were either eluted from the bios

124 nance biomolecular interaction analysis (SPR-BIA).

125 Detection limits for both SPR-BIA and MALDI-TOF were at the low-femtomole to subfemtom

126 Standard BIA equations may not accurately estimate FFM and fat ma

127 erent investigators follow the same standard BIA procedures and use the same population and criterion

128 In a phase 1 study, BIA 10-2474, an orally administered reversible FAAH inhi

129 (P < 0.005) lower regional body fat and TBF (BIA: -9.5 kg; DWF: -7.3 kg) but nonsignificantly lower B

130 CM (-1.7 kg) but nonsignificantly lower TBF (BIA: -1.3 kg; DWF: -1.83 kg) than did men without such i

131 This study confirms that BIA prediction models may not be appropriate for individ

132 and S2/R (R = 0.53 to 0.85), indicating that BIA and FFM derived from skinfold thicknesses are better

133 The BIA approach is most appropriate for estimating adiposit

134 The BIA system with amperometric detection using a glassy-ca

135 cal results illustrating the accuracy of the BIA on some simple regression problems.

136 lly, we demonstrate the applicability of the BIA to high-dimensional regression by analyzing a gene e

137 odeling equation was less important than the BIA measurements.

138 urately estimated within 3.5%BF by using the BIA average method whereas only 71% and 46% were accurat

139 ific equations, used in combination with the BIA average method, was compared with other BIA equation

140 Thus, BIA is not particularly useful for performance predictio

141 articles, and any other articles relevant to BIA-ALCL were included.

142 rs, but it is advisable to use untransformed BIA measurements rather than to convert resistance measu

143 ment, DXA, TBW(VRJ), 3-compartment, Db(VRJ), BIA, air displacement plethysmography body density, and

144 ies from the Framingham Heart Study in which BIA was first compared with dual-energy X-ray absorptiom

145 mass, and percentage body fat estimated with BIA and underwater weighing before and after 12 wk of in