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Science
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Disponibilidad
| Institución detectada | Período | Navegá | Descargá | Solicitá |
|---|---|---|---|---|
| No detectada | desde mar. 1997 / hasta dic. 2023 | Science Journals |
Información
Tipo de recurso:
revistas
ISSN impreso
0036-8075
ISSN electrónico
1095-9203
Editor responsable
American Association for the Advancement of Science (AAAS)
País de edición
Estados Unidos
Fecha de publicación
1880-
Cobertura temática
Tabla de contenidos
SFXN1 is a mitochondrial serine transporter required for one-carbon metabolism
Nora Kory
; Gregory A. Wyant
; Gyan Prakash
; Jelmi uit de Bos
; Francesca Bottanelli; Michael E. Pacold
; Sze Ham Chan
; Caroline A. Lewis
; Tim Wang; Heather R. Keys
; Yang Eric Guo; David M. Sabatini
<jats:title>Mitochondrial serine transporter identified</jats:title> <jats:p> One-carbon (1C) metabolism is a universal metabolic process that is required for purine synthesis and supports the high levels of proliferation in cancer cells. The transport of serine into mitochondria supplies most of the 1C units needed for biosynthesis. Kory <jats:italic>et al.</jats:italic> used a genetic screen to identify the long-sought-after mitochondrial serine transporter. Elucidating the key step of serine transport is important for our understanding of metabolism and has potential implications for cancer treatment. </jats:p> <jats:p> <jats:italic>Science</jats:italic> , this issue p. <jats:related-article xmlns:xlink="http://www.w3.org/1999/xlink" ext-link-type="doi" related-article-type="in-this-issue" xlink:href="10.1126/science.aat9528">eaat9528</jats:related-article> </jats:p>
Palabras clave: Multidisciplinary.
Pp. No disponible
Comment on “Predicting reaction performance in C–N cross-coupling using machine learning”
Kangway V. Chuang
; Michael J. Keiser
<jats:p> Ahneman <jats:italic>et al</jats:italic> . (Reports, 13 April 2018) applied machine learning models to predict C–N cross-coupling reaction yields. The models use atomic, electronic, and vibrational descriptors as input features. However, the experimental design is insufficient to distinguish models trained on chemical features from those trained solely on random-valued features in retrospective and prospective test scenarios, thus failing classical controls in machine learning. </jats:p>
Palabras clave: Multidisciplinary.
Pp. No disponible
Molecular, spatial, and functional single-cell profiling of the hypothalamic preoptic region
Jeffrey R. Moffitt
; Dhananjay Bambah-Mukku
; Stephen W. Eichhorn
; Eric Vaughn; Karthik Shekhar; Julio D. Perez
; Nimrod D. Rubinstein; Junjie Hao; Aviv Regev
; Catherine Dulac
; Xiaowei Zhuang
<jats:title>Mapping the brain, one neuron at a time</jats:title> <jats:p> Spatial transcriptomics can link molecularly described cell types to their anatomical positions and functional roles. Moffitt <jats:italic>et al.</jats:italic> used a combination of single-cell RNA-sequencing and MERFISH (multiplexed error-robust fluorescence in situ hybridization) to map the identity and location of specific cell types within the mouse preoptic hypothalamus and surrounding areas of the brain (see the Perspective by Tasic and Nicovich). They related these cell types to specific behaviors via gene activity. The approach provides an unbiased description of cell types of the preoptic area, which are important for sleep, thermoregulation, thirst, and social behavior. </jats:p> <jats:p> <jats:italic>Science</jats:italic> , this issue p. <jats:related-article xmlns:xlink="http://www.w3.org/1999/xlink" ext-link-type="doi" related-article-type="in-this-issue" xlink:href="10.1126/science.aau5324">eaau5324</jats:related-article> ; see also p. <jats:related-article xmlns:xlink="http://www.w3.org/1999/xlink" ext-link-type="doi" issue="6416" page="749" related-article-type="in-this-issue" vol="362" xlink:href="10.1126/science.aav4841">749</jats:related-article> </jats:p>
Palabras clave: Multidisciplinary.
Pp. No disponible
Reform and cooperation in China
Manfred Horvat
<jats:p>Since it was established as a science funding organization in 1986, the National Natural Science Foundation of China (NSFC) has seen its annual budget grow from CNY 80 million to 28.04 billion in 2018, as China underwent rapid transformation and became a global player in research. Now under the new leadership of President Li Jinghai, the NSFC has engaged in consultations about its future. To promote international dialogue, the NSFC convened representatives from 15 funding agencies around Europe to solicit feedback on proposed reforms. This September meeting in Paris marked a first major step by the NSFC to align its new strategies and policies with those of international partners and demonstrate its commitment to cooperation.</jats:p>
Palabras clave: Multidisciplinary.
Pp. 727-727
News at a glance
<jats:p>A roundup of weekly science policy and related news.</jats:p>
Palabras clave: Multidisciplinary.
Pp. 728-730
Vote heralds fresh start for science panel
Jeffrey Mervis
<jats:p>Democratic win of House of Representatives will bring new tone to research issues.</jats:p>
Palabras clave: Multidisciplinary.
Pp. 731-732
Eruption made 536 ‘the worst year to be alive’
Ann Gibbons
<jats:p>Core from glacier reveals the Icelandic volcano that plunged Europe into darkness.</jats:p>
Palabras clave: Multidisciplinary.
Pp. 733-734
Obesity gives unexpected boost to anticancer drugs
Jocelyn Kaiser
<jats:p>Drugs revive immune cells exhausted by obesity hormone.</jats:p>
Palabras clave: Multidisciplinary.
Pp. 734-734
Fresh fights roil evidence-based medicine group
Gretchen Vogel
<jats:p>Expelled Cochrane co-founder Peter Gøtzsche is suspended as head of the Nordic Cochrane Centre.</jats:p>
Palabras clave: Multidisciplinary.
Pp. 735-735
Reprogrammed cells could tackle brain damage
Kelly Servick
<jats:p>Turning astrocytes into neurons improves symptoms in preliminary mouse studies.</jats:p>
Palabras clave: Multidisciplinary.
Pp. 736-737