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 determined 7 distinct maternal milk profiles with me

3 LCA in siblings with multiple RAHs is an extremely rare

4 LCA inventory cutoff criteria evaluation showed the pote

5 LCA is a severe early onset retinal dystrophy.

6 LCA methods used in existing policies thus provide contr

7 LCA provides heuristic solutions for population number i

8 LCA results indicate that selection of an appropriate ph

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

10 LCA revealed three distinct NERD subphenotypes.

11 LCA showed a dose and time-dependent selective effect in

12 LCA was applied to 19 variables.

13 LCA was performed using laboratory and clinical variable

14 LCA was performed using the following baseline data coll

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

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

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

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

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

20 -cost consumer grade wearable accelerometer (LCA) to determine patient activity (steps per day) preop

21 Lithocholic bile acid (LCA) has been reported to selectively kill cancer cells

22 n 8 (IL-8) upregulation by lithocholic acid (LCA) in HCT116 colorectal cancer (CRC) cells.

23 The endogenous bile acid lithocholic acid (LCA) inhibits NAPE-PLD activity (with an IC(50) of 68 mu

24 type switch in response to lithocholic acid (LCA) to facilitate gastrointestinal (GI) tract colonizat

25 wo distinct derivatives of lithocholic acid (LCA), 3-oxoLCA and isoalloLCA, as T cell regulators in m

26 tients. We discovered that lithocholic acid (LCA), a secondary bile acid prevalent in the cecum and c

27 deoxycholic acid (DCA) and lithocholic acid (LCA), which accumulate at concentrations of around 500 m

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

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

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

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

32 tinal disorders; Leber congenital amaurosis (LCA) and snowflake vitreoretinal degeneration (SVD).

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

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

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

36 Leber's congenital amaurosis (LCA) is a known inherited retinal disease (IRD) associat

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

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

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

40 Gene therapy for Leber congenital amaurosis (LCA) is becoming available, and therefore it is crucial

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

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

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

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

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

46 thesis and cause Leber congenital amaurosis (LCA).

47 associated with Leber congenital amaurosis (LCA).

48 se non-syndromic Leber congenital amaurosis (LCA).

49 ) mouse model of Leber congenital amaurosis (LCA).

50 RD; 10.94%), and Leber congenital amaurosis (LCA; 3.12%).

51 his morphology was probably retained from an LCA that exhibited knuckle-walking as part of its locomo

52 Application of an LCA model allowed categorization of patient-reported out

53 output data on the overall uncertainty of an LCA result has been debated.

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

55 appropriate factors for inclusion within an LCA.

56 , we developed the Latent Cellular Analysis (LCA), a machine learning-based analytical pipeline that

57 ratory diseases using latent class analysis (LCA) and distinguish each class using classification and

58 re determined using a latent class analysis (LCA) approach.

59 Latent class analysis (LCA) has been used extensively to identify (latent) phen

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

61 A latent class analysis (LCA) model was applied to analyze NEI VFQ-25 data and pa

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

63 Latent class analysis (LCA) provides an unbiased statistical approach to resolv

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

65 de Inpatient Samples, latent class analysis (LCA) was applied to 10 procedure groups and differences

66 llergic disease using latent class analysis (LCA).

67 nts with the means of latent class analysis (LCA).

68 her assessments such as life cycle analysis (LCA) would allow dentistry to identify products or pract

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

70 motor behaviour of the last common ancestor (LCA) of humans and African apes is still a divisive issu

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

72 lved in the bilaterian last common ancestor (LCA).

73 Here we complete the pathway to DCA and LCA by assigning and characterizing enzymes for each of

74 sporogenes, conferring production of DCA and LCA on a nonproducing commensal and demonstrating that a

75 theless, despite the clear impact of DCA and LCA on host physiology, an incomplete knowledge of their

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

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

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

79 ybridization, or complementary use of RA and LCA.

80 ybridization, or complementary use of RA and LCA.

81 ent case studies blending elements of RA and LCA.

82 t months 1 and 3 (P < .001), whereas TCA and LCA showed a significant decrease only at the 1-month fo

83 Baseline mean TCA and LCA were 2.30 +/- 1.41 mm(2) and 1.23 +/- 0.73 mm(2), re

84 in CMT and SFCT, while reductions in TCA and LCA were only noted at the 1-month follow-up interval.

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

86 The clinical implication of applying LCA to CDI is to report Ct values assigned to probabilit

87 horoidal area (TCA), luminal choroidal area (LCA), and stromal choroidal area (SCA) were analyzed.

88 coronary artery (RCA), left coronary artery (LCA) and left anterior descending artery (LAD).

89 A pair of siblings diagnosed as LCA who presented with RAH with no extraocular symptoms

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

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

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

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

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

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

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

97 Even so, a life cycle assessment (LCA) case study illustrates practical application of our

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

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

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

101 ults of a comparative life cycle assessment (LCA) for algal biorefineries to compare the sustainabili

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

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

104 support tools such as life cycle assessment (LCA) increasingly aim to account for impacts on biodiver

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

106 Life cycle assessment (LCA) is a reference methodology for appraising the envir

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

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

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

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

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

112 bal, locally resolved life cycle assessment (LCA) model to assess the potential effects on soil quali

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

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

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

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

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

118 Seventy-one unique life cycle assessment (LCA) studies that quantify the environmental impacts thr

119 ials commonly used in life cycle assessment (LCA) studies.

120 he hybrid approach in Life Cycle Assessment (LCA) that uses both input-output and process data has be

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

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

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

124 This study uses Life Cycle Assessment (LCA) to investigate the environmental performance and im

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

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

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

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

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

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

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

132 developed for use in life cycle assessment (LCA).

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

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

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

136 ncreasing interest in Life Cycle Assessment (LCA).

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

138 sed with conventional life cycle assessment (LCA).

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

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

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

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

143 Metformin was demonstrated to block LCA-stimulated ROS production, in turn suppressing NF-ka

144 PLD activity (with an IC(50) of 68 mum), but LCA is also a highly potent ligand for TGR5 (EC(50) 0.52

145 podocytes are significantly less affected by LCA (at dosages < 200 um).

146 n to prevent IL-8 upregulation stimulated by LCA; this prevention thus obstructed endothelial cell pr

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

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

149 E6 activity, confirming these variants cause LCA.

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

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

152 Patients with CMB/LCA (n = 45) had 37% 5y-PFS, 62% 5y-OS, and 39% 5y-CSI-f

153 non-wingless (WNT)/non-SHH disease with CMB/LCA was not improved by local radiotherapy.

154 id not improve survival in patients with CMB/LCA.

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

156 in Lrat(-/-)Opn1sw(-/-) mice (a pure M cone LCA model, Opn1sw encoding S-opsin) for at least 12 mont

157 ng modeling approach relies on consequential LCA (cLCA).

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

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

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

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

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

163 This shows that the current LCA framework is not yet sufficient to support decision-

164 More broadly, DCA, LCA and their derivatives are major components of the re

165 eded to verify our results before dismissing LCA as an anti-cancer drug.

166 the most relevant variable in distinguishing LCA-classes.

167 ted the most likely variables distinguishing LCA-classes.

168 However, current policies that employ LCA as a quantitative measure are not adequate for asses

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

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

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

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

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

174 ns for the current gene therapy strategy for LCA that emphasizes the need for combinatorial therapies

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

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

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

178 ) that have traditionally been excluded from LCA.

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

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

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

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

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

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

185 lessly integrates MOO with integrated hybrid LCA.

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

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

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

189 or 13 impact categories commonly analyzed in LCA studies.

190 metrics of biodiversity impact assessment in LCA are poor at capturing the complexities of biodiversi

191 avelength cone photoreceptor degeneration in LCA is unknown.

192 s-retinal deficiency to cone degeneration in LCA.

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

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

195 ective WSmix (P-WSmix) for implementation in LCA and water footprint studies as well as regional wate

196 ional exposure to chemicals by inhalation in LCA.

197 active oxygen species (ROS) were involved in LCA-induced IL-8 upregulation through activation of the

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

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

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

201 to operationalize consequential thinking in LCA practice.

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

203 For implementation of the P-WSmix in LCA, a P-WOmix database is provided for 74 countries on

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

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

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

207 B) or large-cell/anaplastic medulloblastoma (LCA).

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

209 ies with a level of detail suitable for most LCA studies in support of policy decisions.

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

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

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

213 Importantly, the ability of LCA to learn from representative subsets of the data pro

214 dizing truncated inputs improves accuracy of LCA results without compromising their precision, and pr

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

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

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

218 function variants of Kir7.1 are one cause of LCA.

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

220 of the study was to evaluate the effects of LCA on nephroblastoma.

221 To test the effects of LCA, nephroblastoma cell line WT CLS1 was used.

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

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

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

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

226 Experimental evolution in the presence of LCA yielded mutations in the essential two-component kin

227 ts, in a way that increases the relevance of LCA across a wider range of areas.

228 The midpoint results of LCA show that CEPT with anaerobic digestion (AD) for slu

229 nventory and the impact assessment stages of LCA, helping to disentangle the relationship between bio

230 ted Nape-pld with potency similar to that of LCA.

231 emissions of PFASs can have large effects on LCA results.

232 the pathway was present in the panarthropod LCA.

233 this study, we selected an existing process LCA, performed a Monte Carlo simulation after hybridizin

234 velop a methodology for applying prospective LCA to emerging production technologies from the laborat

235 r-step approach for implementing prospective LCA is applied to the case of electrochemical formic aci

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

237 While using prospective LCA, the underlying modeling approach relies on conseque

238 Using 266,586 eligible records, LCA resulted in two classes of hospitalizations, namely,

239 Six LCA models were generated to determine CDI probability u

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

241 S-LCI framework resulted in a site-specific LCA that aids decision-makers on choosing between higher

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 is robust, accurate, and powerful by comparison with

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

251 The study showed that LCA has a strong, yet unselective effect on all used in

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

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

254 The LCA classified predominantly by type and multiplicity of

255 The LCA method identified seven distinct periodontal profile

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

257 The LCA results provide environmental information for the im

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 Looking beyond the LCA domain can lead us to new ways of advancing the cove

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

264 f including P-WSmix in LCI databases for the LCA of infrastructures or products with a long life span

265 ill the most parsimonious hypothesis for the LCA, despite diverse conflicting lines of evidence.

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

267 equired to fully include these models in the LCA framework.

268 significantly improved cone survival in the LCA model mice.

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

270 ells, and eicosanoids were considered in the LCA.

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

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

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

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

275 Divalent cations reversed this LCA-induced switch to chaining and biofilm formation.

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 ttributional and consequential approaches to LCA.

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

280 rmediate syndromic phenotype with respect to LCA and lethality.

281 However, traditional LCA approaches do not suggest this solution and are esti

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

283 We used LCA to derive wheeze phenotypes among 3167 participants

284 ype of wheeze phenotypes identified by using LCA in longitudinal data.

285 terns of maternal HMOs were determined using LCA.

286 R cycle threshold (Ct) were identified using LCA: CDI likely (>90% probability), equivocal (<90% and

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

288 and used to derive OC classes identified via LCA.

289 The most common clinical diagnosis was LCA and/or early onset severe retinal dystrophy in 82% (

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

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

292 However, a plant-wide LCA considering up-concentration primary treatment and l

293 ing biochemical process models combined with LCA data.

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

298 treated with metformin and then treated with LCA lost all stimulatory effect on endothelial cell prol

299 (CM) derived from HCT116 cells treated with LCA, CM derived from HCT116 cells pretreated with metfor

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