The JADES Transient Survey: Discovery and Classification of Supernovae in the JADES Deep Field

The JWST Advanced Deep Extragalactic Survey (JADES) is a multicycle JWST program that has taken among the deepest near- and mid-infrared images to date (down to ∼30 AB mag) over ∼25 arcmin2 in the GOODS-S field in two sets of observations with 1 yr of separation. This presented the first opportunity to systematically search for transients, mostly supernovae (SNe), out to z > 2. We found 79 SNe: 38 at z < 2, 23 at 2 < z < 3, 8 at 3 < z < 4, 7 at 4 < z < 5, and 3 with undetermined redshifts, where the redshifts are predominantly based on spectroscopic or highly reliable JADES photometric redshifts of the host galaxies. At this depth, the detection rate is ∼1–2 arcmin–2 yr–1, demonstrating the power of JWST as an SN discovery machine. We also conducted multiband follow-up NIRCam observations of a subset of the SNe to better constrain their light curves and classify their types. Here, we present the survey, sample, search parameters, spectral energy distributions, light curves, and classifications. Even at z ≥ 2, the NIRCam data quality is high enough to allow SN classification via multiepoch light-curve fitting with confidence. The multiepoch SN sample includes a Type Ia SN at z spec = 2.90, a Type IIP SN at z spec = 3.61, and a Type Ic-BL SN at z spec = 2.83. We also found that two z ∼ 16 galaxy candidates from the first imaging epoch were actually transients that faded in the second epoch, illustrating the possibility that moderate/high-redshift SNe could mimic high-redshift dropout galaxies

Muscle inactivation of mTOR causes metabolic and dystrophin defects leading to severe myopathy

Mammalian target of rapamycin (mTOR) is a key regulator of cell growth that associates with raptor and rictor to form the mTOR complex 1 (mTORC1) and mTORC2, respectively. Raptor is required for oxidative muscle integrity, whereas rictor is dispensable. In this study, we show that muscle-specific inactivation of mTOR leads to severe myopathy, resulting in premature death. mTOR-deficient muscles display metabolic changes similar to those observed in muscles lacking raptor, including impaired oxidative metabolism, altered mitochondrial regulation, and glycogen accumulation associated with protein kinase B/Akt hyperactivation. In addition, mTOR-deficient muscles exhibit increased basal glucose uptake, whereas whole body glucose homeostasis is essentially maintained. Importantly, loss of mTOR exacerbates the myopathic features in both slow oxidative and fast glycolytic muscles. Moreover, mTOR but not raptor and rictor deficiency leads to reduced muscle dystrophin content. We provide evidence that mTOR controls dystrophin transcription in a cell-autonomous, rapamycin-resistant, and kinase-independent manner. Collectively, our results demonstrate that mTOR acts mainly via mTORC1, whereas regulation of dystrophin is raptor and rictor independent

Muscle inactivation of mTOR causes metabolic and dystrophin defects leading to severe myopathy

mTor, acting mainly via mTORC1, controls dystrophin transcription in a raptor- and rictor-independent mechanism

The JADES Transient Survey: Discovery and Classification of Supernovae in the JADES Deep Field

The JWST Advanced Deep Extragalactic Survey (JADES) is a multi-cycle JWST program that has taken among the deepest near-/mid-infrared images to date (down to $\sim$30 ABmag) over $\sim$25 arcmin$^2$ in the GOODS-S field in two sets of observations with one year of separation. This presented the first opportunity to systematically search for transients, mostly supernovae (SNe), out to $z$$>$2. We found 79 SNe: 38 at $z$$<$2, 23 at 2$<$$z$$<$3, 8 at 3$<$$z$$<$4, 7 at 4$<$$z$$<$5, and 3 with undetermined redshifts, where the redshifts are predominantly based on spectroscopic or highly reliable JADES photometric redshifts of the host galaxies. At this depth, the detection rate is $\sim$1-2 per arcmin$^2$ per year, demonstrating the power of JWST as a supernova discovery machine. We also conducted multi-band follow-up NIRCam observations of a subset of the SNe to better constrain their light curves and classify their types. Here, we present the survey, sample, search parameters, spectral energy distributions (SEDs), light curves, and classifications. Even at $z$$\geq$2, the NIRCam data quality is high enough to allow SN classification via multi-epoch light-curve fitting with confidence. The multi-epoch SN sample includes a Type Ia SN at $z_{\mathrm{spec}}$$=$2.90, Type IIP SN at $z_{\mathrm{spec}}$$=$3.61, and a Type Ic-BL SN at $z_{\mathrm{spec}}$$=$2.845. We also found that two $z$$\sim$16 galaxy candidates from the first imaging epoch were actually transients that faded in the second epoch, illustrating the possibility that moderate/high-redshift SNe could mimic high-redshift dropout galaxies.Comment: 43 pages, 15 figures, 15 tables. Submitted to ApJ. Appendix A (64 MB) is available at https://drive.google.com/file/d/1xs5jXUVOvdDPgdghK72KR1FMGvPcK7dv/view?usp=sharing . Appendix B (81 MB) is available at https://drive.google.com/file/d/18ImLT80pQdPzXCZA-KEy21DaE2CQiGz1/view?usp=sharing . References updated, typos fixed, minor restructurin

A pathway approach to investigate the function and regulation of SREBPs

The essential function of sterol regulatory element-binding proteins (SREBPs) in cellular lipid metabolism and homeostasis has been recognized for a long time, and the basic biological pathway involving SREBPs has been well described; however, a rapidly growing number of studies reveal the complex regulation of these SREBP transcription factors at multiple levels. This regulation allows the integration of signals of diverse pathways involving nutrients, contributing to cellular lipid and energy homeostasis. This review attempts to integrate this knowledge. The description of the SREBP pathway is Web-linked as it refers to the online version of the pathway on wikipathways.org, which is interactively linked to genomics databases and literature. This allows a more extensive study of the pathway through reviewing these links

Mathematical programming model for subsea, wet-gas transmission pipeline design, A

Includes bibliographical references