ライフサイエンスコーパス: LCA

1 LCA detected consistently in both cohorts a distinct gro

2 LCA estimated the TVQ sensitivity and specificity as 98.

3 LCA identified five classes, which verified the clinical

4 LCA inventory cutoff criteria evaluation showed the pote

5 LCA is a severe early onset retinal dystrophy.

6 LCA results indicate that selection of an appropriate ph

7 LCA results showed that environmental burden is mostly f

8 LCA revealed a set of benign, symptomatic, and severe at

9 LCA revealed unique AERD subphenotypes, thus corroborati

10 LCA was applied to identify possible AERD subphenotypes.

11 LCA was performed in an international multicenter birth

12 LCA was performed using the following baseline data coll

13 BiS for 1.25% LCA was also significantly correlated with near stereoac

14 Near stereoacuity and BiS for 2.5% and 1.25% LCA were significantly dependent (Pearson chi(2), P = .0

15 demonstrated significantly more BiS in 2.5% LCA of 2.7 (P = .022) and 3.1 (P = .014) letters than di

16 ignificant correlations between BiS for 2.5% LCA with near and distance stereoacuity (P = .006 and P

17 gas emissions, and water consumption for 54 LCA studies that considered algae BioD and RD.

18 ile acid sensor by binding lithocholic acid (LCA).

19 dy visual acuity, Sloan low-contrast acuity (LCA, 2.5% and 1.25%), and Randot stereoacuity 2 months f

20 ng an early and effective diagnosis of AIPL1 LCA patients.

21 mouse model of Lebers congenital amaurosis (LCA) and in a Cpfl1 mouse with Pde6c defect model of ach

22 Leber congenital amaurosis (LCA) and juvenile retinitis pigmentosa (RP) are severe h

23 linical trial of Leber congenital amaurosis (LCA) associated with mutations in the GUCY2D gene.

24 nd patients with Leber congenital amaurosis (LCA) caused by mutations in GUCY2D, the gene that encode

25 Leber congenital amaurosis (LCA) encompasses a set of early-onset blinding diseases

26 gene underlying Leber congenital amaurosis (LCA) in the Spanish population and to describe the assoc

27 Leber congenital amaurosis (LCA) is a hereditary early-onset retinal dystrophy that

28 Leber congenital amaurosis (LCA) is a neurodegenerative disease of photoreceptor cel

29 Leber congenital amaurosis (LCA) is a severe disorder resulting in visual impairment

30 Leber congenital amaurosis (LCA) is an inherited retinal dystrophy that causes child

31 mice [a model of Leber congenital amaurosis (LCA) with rapid cone loss] and cone photoreceptor functi

32 thesis and cause Leber congenital amaurosis (LCA), a severe hereditary blindness occurring in early c

33 tinal blindness, Leber congenital amaurosis (LCA), and renal disease.

34 syndrome (BBS), Leber congenital amaurosis (LCA), and retinitis pigmentosa.

35 cause recessive Leber congenital amaurosis (LCA), juvenile retinitis pigmentosa (RP) and cone-rod dy

36 osomal recessive Leber congenital amaurosis (LCA), the most severe form of inherited retinopathy in e

37 associated with Leber congenital amaurosis (LCA).

38 icularly important aspects for conducting an LCA of CCU are identified and illustrated with CCU examp

39 his review identifies 32 studies that use an LCA framework to evaluate the environmental impact of di

40 rating diffusion modeling techniques with an LCA of emerging technology can provide estimates for the

41 appropriate factors for inclusion within an LCA.

42 ith kappa scores, and latent class analysis (LCA) as an unbiased estimator of test accuracy.

43 years of life using a latent class analysis (LCA) integrating 3 dimensions of atopy: allergen specifi

44 We performed a latent class analysis (LCA) of OC features, cross-sectional tests of associatio

45 A custom latent class analysis (LCA) procedure was developed to identify clinically dist

46 e apply a data-driven latent class analysis (LCA) to model 54 specific health variables from the Nati

47 Latent class analysis (LCA) was used to determine visual field sectors with hig

48 llergic disease using latent class analysis (LCA).

49 gh the application of latent class analysis (LCA).

50 This study uses life cycle analysis (LCA) to evaluate the greenhouse gas (GHG) performance of

51 Lifecycle analysis (LCA) metrics of greenhouse gas emissions are increasingl

52 st gene families, the least common ancestor (LCA) mapping is an optimal solution for the species mapp

53 e better model for the last common ancestor (LCA) of chimpanzees/bonobos and humans.

54 about the mass of the last common ancestor (LCA) of humans and chimpanzees, hominids (great apes and

55 the morphology of the last common ancestor (LCA) of humans and chimpanzees.

56 hotype of the Homo-Pan last common ancestor (LCA).

57 w clear that a further integration of RA and LCA based on dataset completion will remain futile.

58 Blending elements of RA and LCA offers multifaceted opportunities to adapt a given e

59 s as to what should be referred to as RA and LCA, and when to speak of combination, integration, hybr

60 ybridization, or complementary use of RA and LCA.

61 ybridization, or complementary use of RA and LCA.

62 ent case studies blending elements of RA and LCA.

63 tive to the choice of coproduct scenario and LCA allocation scheme, and in select cases can change th

64 search needs in both the climate science and LCA research communities.

65 that voting-based methods, majority vote and LCA*, in the presence of known reference annotations, ar

66 ntroduces a novel framework for anticipatory LCA that incorporates technology forecasting, risk resea

67 es illustrate the potential for anticipatory LCA to prioritize research questions and help guide envi

68 nd heterozygous mutations were identified as LCA-causative in chaperonin-containing TCP-1, subunit 2

69 t (LCIA) in classical life cycle assessment (LCA) aims at analyzing potential impacts of products and

70 A life-cycle assessment (LCA) and cost analysis are presented comparing the envir

71 iented analysis using life cycle assessment (LCA) and cost benefit analysis (CBA) was conducted to an

72 l assessment methods (life cycle assessment (LCA) and hybrid LCA) and environmental input-output data

73 k assessment (RA) and life cycle assessment (LCA) are two analytical tools used to support decision m

74 Life-cycle assessment (LCA) can help identify the purchasing criteria that are

75 While life cycle assessment (LCA) can potentially capture local and global environmen

76 d the factors to five life cycle assessment (LCA) case studies of bioproducts.

77 ue challenges for the life cycle assessment (LCA) community, given the lack of data and inherent unce

78 into a process-based life cycle assessment (LCA) context.

79 pleted whole-building life cycle assessment (LCA) database of NIST was applied to a prototype buildin

80 ts recommend applying life cycle assessment (LCA) early in research and development (R&D) to guide em

81 A life cycle assessment (LCA) focused on greenhouse gas (GHG) emissions from the

82 health impacts using life-cycle assessment (LCA) following the Tool for the Reduction and Assessment

83 od in a consequential life cycle assessment (LCA) framework to estimate the environmental emissions c

84 Life cycle assessment (LCA) has been used by many researchers to evaluate the p

85 odiversity impacts in life cycle assessment (LCA) has recently been significantly improved.

86 Life Cycle Assessment (LCA) is a decision-making tool that accounts for multipl

87 nd utilization (CCU), life cycle assessment (LCA) is considered as suitable metric.

88 e major challenges in life cycle assessment (LCA) is the availability and quality of data used to dev

89 Life-cycle assessment (LCA) is used to quantify greenhouse gas emissions, fossi

90 Life cycle assessment (LCA) measures cradle-to-grave environmental impacts of a

91 In further life cycle assessment (LCA) method developments, common end point units and nor

92 consumption-weighted life cycle assessment (LCA) methodology accounts for both product consumption (

93 rs the application of life cycle assessment (LCA) methodology in evaluating the potential environment

94 A well-to-wheel (WTW) life cycle assessment (LCA) model is developed to evaluate the environmental pr

95 rce engineering-based life cycle assessment (LCA) model, as the reference model for this analysis.

96 This paper reports a life cycle assessment (LCA) of a high-capacity LIB pack using SiNW prepared via

97 nges in environmental life cycle assessment (LCA) of crop production is the nonlinearity between nitr

98 Consequently, the life cycle assessment (LCA) of indoor wooden products conducted using these inv

99 ature, we completed a life cycle assessment (LCA) of the decentralized water system of a high-perform

100 ks to human health in life cycle assessment (LCA) of wastewater and sludge management systems, as thi

101 support tools such as life cycle assessment (LCA) requires spatially explicit models, but existing ap

102 Life cycle assessment (LCA) results are inevitably subject to uncertainties.

103 While several life cycle assessment (LCA) studies have assessed such products, only a few of

104 n analysis (MCDA) and life cycle assessment (LCA) to address technology alternative selection decisio

105 is study, we utilized life-cycle assessment (LCA) to analyze the energy consumption and greenhouse ga

106 y, this research uses life cycle assessment (LCA) to evaluate how the scale of implementation impacts

107 Many companies use life cycle assessment (LCA) to evaluate their sustainability, yet commonly-used

108 was benchmarked using Life Cycle Assessment (LCA) to provide a comprehensive assessment.

109 sed using an advanced life cycle assessment (LCA) tool(9), yielding metrics of environmental impact,

110 PWB) recycling chain, life cycle assessment (LCA) was applied to a formal recycling chain that includ

111 evel, cradle-to-grave life cycle assessment (LCA) was conducted based on a functional unit of 10,000

112 To this end, a life cycle assessment (LCA) was performed to evaluate the environmental impact

113 Hybrid life cycle assessment (LCA) was used to quantify environmental emissions from f

114 By combining life cycle assessment (LCA) with multiobjective optimization (MOO), the life cy

115 pplied to comparative life-cycle assessment (LCA), in which products with the same function but diffe

116 ons of scenario-based life cycle assessment (LCA), we develop a multiobjective optimization model to

117 mmonly assessed using life cycle assessment (LCA), whereas pathogen risk is evaluated with quantitati

118 re rarely included in life cycle assessment (LCA).

119 ncreasing interest in Life Cycle Assessment (LCA).

120 s were compared using life cycle assessment (LCA).

121 , is still lacking in life cycle assessment (LCA).

122 were calculated using life cycle assessment (LCA).

123 ncertainty factors in life cycle assessment (LCA).

124 le of a magazine with Life Cycle Assessment (LCA).

125 with a well-to-wheel life cycle assessment (LCA).

126 ion indicators within life cycle assessment (LCA).

127 n analysis and hybrid life cycle assessment (LCA).

128 in the literature, in life cycle assessment (LCA).

129 isk analysis (RA) and life-cycle assessment (LCA).

130 sidered a priority in life cycle assessment (LCA).

131 g robust comparative life cycle assessments (LCA) by leveraging uncertainty.

132 ue for testing the supremacy of the assigned LCA* taxonomy.

133 the treatment of not only CEP290-associated LCA but potentially many other subtypes of retinal dystr

134 The mechanism of CRX-associated LCA is not understood.

135 -free introduction of LCA of CCU directed at LCA novices.

136 sed allocation methods used in attributional LCA estimate that recovering CO2 leads to 19 and 11 time

137 nology, illustrate the need for policy-based LCA measures when informing policy decision making.

138 pplications are developed upon process-based LCA, which results in system boundary truncation and und

139 results and representative technology-based LCA measures, which do not account for the policy instru

140 gand molecules is crucial for VDR agonism by LCA.

141 Clinical phenotypes were well supported by LCA analysis.

142 h for consequential life cycle assessment (C-LCA) of large scale policies, more specifically mobility

143 Here, we present a statistic called LCA* inspired by Information and Voting theories that us

144 of the retina-specific phenotypes in CEP290 LCA patients and potential strategies for therapeutic in

145 Despite the associated challenges, LCA methods must be developed for transformative technol

146 ion to select three in function of classical LCA.

147 The combined LCA and RA approach considers environmental impacts of p

148 Using a policy-based consequential LCA, we find that the lifecycle emissions impacts of fou

149 arket-based allocation used in consequential LCA.

150 GTW and could be excluded with consequential LCA system boundaries.

151 vehicles are then used to derive consistent LCA results, representing the consequences of the polici

152 oup) conducted in a Local Authority Council (LCA) in the United Kingdom.

153 To do so, we coupled LCA methodologies on freshwater consumption, freshwater

154 ongenital stationary night blindness (CSNB), LCA, Stargardt disease, and blue cone monochromacy.

155 A, and compare the new method with a current LCA method based on a French life cycle inventory databa

156 ucts, two alternative ways of simplifying (E)LCA are discussed.

157 t to the baseline scenario of -26 ecopoints (LCA) and -173 USD (CBA) annually pr. household.

158 omic input-output life cycle assessment (EIO-LCA) method.

159 ed to construct scenario models that enhance LCA of emerging technologies.

160 to 10 highway drainage projects to evaluate LCA methodological choices by characterizing environment

161 We examine LCA greenhouse gas (GHG) emissions models to test the re

162 However, existing LCA practices are ill-suited to support these recommenda

163 ent with risk screening approaches to extend LCA to include near-field chemical sources (e.g., those

164 The best-fitting LCA model identified the following 4 OC classes: unaffec

165 We present advances for LCA that integrate spatially explicit modelling of land

166 neration in Lrat(-) (/-), a murine model for LCA, by genetic ablation of S-opsin.

167 The hypothesis-free LCA phenotypes were a useful reference for comparing cli

168 ing a mouse model carrying the most frequent LCA-associated mutation (R91W), we found that the mutant

169 A R91W substitution, the most frequent LCA-associated mutation, results in a severe decrease in

170 the ecology/conservation literature (20 from LCA, 11 from non-LCA fields) according to a set of crite

171 ) that have traditionally been excluded from LCA.

172 could potentially be incorporated into fuel LCA models, such as GREET, to allow users to further und

173 This article (part 2) presents a full LCA for two model systems (with agricultural utilization

174 A detailed gate-to-gate LCA model of EOR was developed and incorporated into a c

175 scores are calculated using a cradle-to-gate LCA.

176 Most GUCY2D-LCA patients failed to perform the orientation task with

177 ometry sensitivity in the majority of GUCY2D-LCA patients provided another objective efficacy outcome

178 nted by methods more specific to this GUCY2D-LCA population.

179 Two GUCY2D-LCA patients demonstrated remnant cone vision but at a l

180 Twenty-eight patients with GUCY2D-LCA (aged 2-59 years) were studied clinically and with c

181 O2 eq) per product), analyzed using a hybrid LCA framework.

182 hods (life cycle assessment (LCA) and hybrid LCA) and environmental input-output databases (E3IOT, Ex

183 lessly integrates MOO with integrated hybrid LCA.

184 elimination of uncertainties is impossible, LCA results should be complemented by an uncertainty ana

185 at can be implemented immediately to improve LCA models based on existing approaches in the literatur

186 od presented in this study provides improved LCA of crop production at the catchment scale.

187 compartment requires particular attention in LCA.

188 ential impacts on human health considered in LCA is detailed in part 2 of this article series.

189 ential impacts on human health considered in LCA.

190 s-retinal deficiency to cone degeneration in LCA.

191 n outlook is given on recent developments in LCA that aim to cover all pillars of sustainability (peo

192 te the recent methodological developments in LCA, most LCO applications are developed upon process-ba

193 used to inform toxicity impact estimates in LCA and highlights needs for future research.

194 y values of baseline transportation fuels in LCA models, this study has shown that the determination

195 ional exposure to chemicals by inhalation in LCA.

196 that enables the results to be integrated in LCA.

197 ntial toxic impacts of TiO2 nanoparticles in LCA studies, we therefore recommend the use of our calcu

198 e phenotypes are similar to that observed in LCA and juvenile RP patients.

199 onship between fuel and chemical products in LCA models.

200 logy with intent to include pathogen risk in LCA and facilitate a comparison with other potential imp

201 novices as a checklist through all steps in LCA of CCU: from defining the LCA purpose and the system

202 Probability-based decision support in LCA is a way to help stakeholders in their decision-maki

203 to operationalize consequential thinking in LCA practice.

204 for TiO2 nanoparticles (TiO2-NP) for use in LCA.

205 ance of integrating indoor environments into LCA, which ensures a more holistic account of all exposu

206 A case study is presented to juxtapose LCA and risk screening approaches for a chemical used in

207 While RA works with threshold levels, LCA assumes that every toxic emission causes an incremen

208 ervices in a Land-Use Change Improved (LUCI)-LCA.

209 r maize and sugarcane, we find that the LUCI-LCA approach yields results opposite to those of standar

210 ia) and guanylate cyclase 2e-deficient mice (LCA with slower cone loss) were used to determine whethe

211 cts from both the Aipl1-null mouse mimicking LCA and the Aipl1-hypomorphic mice mimicking a slow prog

212 nism underlying retinal degeneration as most LCA-associated NMNAT1 mutants had normal enzymatic activ

213 rvation literature (20 from LCA, 11 from non-LCA fields) according to a set of criteria reflecting (i

214 Here we report the novel LCA mutations in CCTbeta and the impact of chaperon disa

215 Using the canine NPHP5-LCA model we compared human and canine retinal phenotype

216 phenotype, we performed detailed analysis of LCA-associated NMNAT1 mutants, including the expression,

217 om technical research inhibit application of LCA to developing technologies.

218 ase subjects with an atypical association of LCA with early-onset hearing loss, we identified two het

219 The most frequent genetic cause of LCA is an intronic mutation in CEP290 (c.2991 + 1655A >

220 identified for the first time as a cause of LCA, segregating in 2 families.

221 However, the high costs of LCA and the problems associated with the comparability o

222 Expression of LCA-associated dominant CRX frameshift mutations in mous

223 tudy clearly shows that the extrapolation of LCA results for the circulating fleet at national scale

224 s that have not been applied in the field of LCA and approaches for characterizing uncertainty in tho

225 or CRX lead to an autosomal dominant form of LCA.

226 nvironmental impacts within the framework of LCA.

227 l review gives a jargon-free introduction of LCA of CCU directed at LCA novices.

228 Phenotypes were defined by means of LCA in 680 children of the Multizentrische Allergiestudi

229 The unique binding mode of LCA provides clues for the development of new chemical c

230 tion in the mutation knock-in mouse model of LCA.

231 Because verification of the results of LCA GHG emissions is often not possible by direct measur

232 To enhance the use of LCA of CCU, this tutorial review gives a jargon-free int

233 One LCA binds to the canonical ligand-binding pocket, and th

234 chnology development; therefore, prospective LCA results can be used to anticipate potential unintend

235 This paper presents a regionalized LCA-based multiobjective optimization model of building

236 g at least 3 test points located in the same LCA-derived 10-2 visual field sector progressing faster

237 aspects, phrased as action items, can serve LCA novices as a checklist through all steps in LCA of C

238 ss in early hominins from a chimpanzee-sized LCA.The pattern of body size evolution in hominids can p

239 her frequency of LCA5 mutations in a Spanish LCA cohort than in other populations.

240 A studies via www.usetox.org and in standard LCA software.

241 ctors are made available for use in standard LCA studies via www.usetox.org and in standard LCA softw

242 yields results opposite to those of standard LCA for greenhouse gas emissions and water consumption,

243 evelop an approach that utilizes streamlined LCA methods, together with linear programming, to determ

244 lies in MT behavior and describe a syndromic LCA unrelated to ciliary dysfunction.

245 The canine disease is a non-syndromic LCA-ciliopathy, with normal renal structures and no CNS

246 adway drainage and other stormwater systems, LCA methodology must be evaluated because stormwater sys

247 To assess impacts of an emerging technology, LCA should be coupled with additional methods that estim

248 tor algorithm popularized by MEGAN, and that LCA* taxonomy strikes a balance between specificity and

249 We show that LCA models tend to perform worse than those from ecology

250 These results suggest that LCA-associated NMNAT1 mutants are more vulnerable to str

251 The LCA case studies showed that the total life cycle GHG em

252 The LCA classified predominantly by type and multiplicity of

253 The LCA method identified seven distinct periodontal profile

254 The LCA mutants of CCTbeta, T400P and R516H, are biochemical

255 The LCA results provide environmental information for the im

256 The LCA results show that over 50% of most characterized imp

257 The LCA study is conducted based on the average U.S. driving

258 The LCA* algorithm identifies a sufficiently strong majority

259 The LCA* has been implemented as a stand-alone Python librar

260 put parameters are two main issues among the LCA calculation process.

261 We first apply the LCA to the MM, identifying five health classes different

262 uel yielded negative net effects in both the LCA and CBA (85 ecopoints and 176 USD), even when positi

263 d the performance of 31 models from both the LCA and the ecology/conservation literature (20 from LCA

264 h all steps in LCA of CCU: from defining the LCA purpose and the system boundaries, over data collect

265 However, there is little consensus for the LCA, with proposed models ranging from African ape to or

266 significantly improved cone survival in the LCA model mice.

267 carbon change was also accounted for in the LCA studies.

268 d categorizes ten factors that influence the LCA results of transformative technologies in order to p

269 igits ratio required little change since the LCA, and was acquired convergently with other highly dex

270 , contrary to previous suggestions, that the LCA of all hominoids lived in an environment that favore

271 osure to chemicals fully compatible with the LCA framework by including the supply chain of a given p

272 ons in terms of their compatibility with the LCA framework, outline near-term practical guidelines an

273 Interactions within the LCA calculation model and correlations within Life Cycle

274 This LCA applies the methodology of the California Low Carbon

275 This LCA study provides a guide to the research and developme

276 d that, compared to the current method, TNT2-LCA allows delineation of more appropriate temporal limi

277 In this study, we present a new method, TNT2-LCA, that couples the topography-based simulation of nit

278 Such an anticipatory approach to LCA requires synthesis of social, environmental, and tec

279 ttributional and consequential approaches to LCA.

280 cilium protein that has also been linked to LCA.

281 inking roadway drainage design parameters to LCA and life cycle costing (LCC) under uncertainty.

282 activator peptide reveals the binding of two LCA molecules by VDR.

283 uate their sustainability, yet commonly-used LCA methodologies lack the spatial resolution and predic

284 The findings suggest PPC and TPC using LCA can provide robust periodontal clinical definitions

285 and used to derive OC classes identified via LCA.

286 stewater and drinking water systems to which LCA is more frequently applied.

287 azard in a specific exposure scenario, while LCA seeks a holistic estimation of impacts of thousands

288 luene from printed matter when assessed with LCA, using the USEtox method complemented with indoor ch

289 At least 19 genes are associated with LCA, which is typically recessive; however, mutations in

290 ing biochemical process models combined with LCA data.

291 sh VDR ligand binding domain in complex with LCA and the SRC-2 coactivator peptide reveals the bindin

292 been identified in 6 unrelated families with LCA by homozygosity mapping or Sanger sequencing.

293 some 6 and in 173 unrelated individuals with LCA or EORP.

294 ransfer and transformation (TNT2) model with LCA, and compare the new method with a current LCA metho

295 ining process-based N simulation models with LCA, but none accounted for nitrate (NO3(-)) flows acros

296 cone survival and function in patients with LCA caused by RPE65 mutations.

297 ty mapping was performed in 44 patients with LCA using genome-wide single nucleotide polymorphism (SN

298 of screening-level risk assessment (RA) with LCA.

299 concepts complement existing methods within LCA to inform proactive environmental management of emer

300 ing approach, to aid method selection within LCA.