IB-UQ: Information bottleneck based uncertainty quantification for neural function regression and neural operator learning

We propose a novel framework for uncertainty quantification via information bottleneck (IB-UQ) for scientific machine learning tasks, including deep neural network (DNN) regression and neural operator learning (DeepONet). Specifically, we incorporate the bottleneck by a confidence-aware encoder, which encodes inputs into latent representations according to the confidence of the input data belonging to the region where training data is located, and utilize a Gaussian decoder to predict means and variances of outputs conditional on representation variables. Furthermore, we propose a data augmentation based information bottleneck objective which can enhance the quantification quality of the extrapolation uncertainty, and the encoder and decoder can be both trained by minimizing a tractable variational bound of the objective. In comparison to uncertainty quantification (UQ) methods for scientific learning tasks that rely on Bayesian neural networks with Hamiltonian Monte Carlo posterior estimators, the model we propose is computationally efficient, particularly when dealing with large-scale data sets. The effectiveness of the IB-UQ model has been demonstrated through several representative examples, such as regression for discontinuous functions, real-world data set regression, learning nonlinear operators for partial differential equations, and a large-scale climate model. The experimental results indicate that the IB-UQ model can handle noisy data, generate robust predictions, and provide confident uncertainty evaluation for out-of-distribution data.Comment: 27 pages, 22figure

Association of Base Excision Repair Gene Polymorphisms with ESRD Risk in a Chinese Population

The base excision repair (BER) pathway, containing OGG1, MTH1 and MUTYH, is a major protector from oxidative DNA damage in humans, while 8-oxoguanine (8-OHdG), an index of DNA oxidation, is increased in maintenance hemodialysis (HD) patients. Four polymorphisms of BER genes, OGG1 c.977C > G (rs1052133), MTH1 c.247G > A (rs4866), MUTYH c.972G > C (rs3219489), and AluYb8MUTYH (rs10527342), were examined in 337 HD patients and 404 healthy controls. And the 8-OHdG levels in leukocyte DNA were examined in 116 HD patients. The distribution of MUTYH c.972 GG or AluYb8MUTYH differed between the two groups and was associated with a moderately increased risk for end-stage renal disease (ESRD) (P = 0.013 and 0.034, resp.). The average 8-OHdG/106 dG value was significantly higher in patients with the OGG1 c.977G, MUTYH c.972G or AluYb8MUTYH alleles (P < 0.001 via ANOVA). Further analysis showed that combination of MUTYH c.972GG with OGG1 c.977GG or AluYb8MUTYH increased both the risk for ESRD and leukocyte DNA 8-OHdG levels in HD patients. Our study showed that MUTYH c.972GG, AluYb8MUTYH, and combination of OGG1 c.977GG increased the risk for ESRD development in China and suggested that DNA oxidative damage might be involved in such process

A Scheme for Verification on Data Integrity in Mobile Multicloud Computing Environment

In order to verify the data integrity in mobile multicloud computing environment, a MMCDIV (mobile multicloud data integrity verification) scheme is proposed. First, the computability and nondegeneracy of verification can be obtained by adopting BLS (Boneh-Lynn-Shacham) short signature scheme. Second, communication overhead is reduced based on HVR (Homomorphic Verifiable Response) with random masking and sMHT (sequence-enforced Merkle hash tree) construction. Finally, considering the resource constraints of mobile devices, data integrity is verified by lightweight computing and low data transmission. The scheme improves shortage that mobile device communication and computing power are limited, it supports dynamic data operation in mobile multicloud environment, and data integrity can be verified without using direct source file block. Experimental results also demonstrate that this scheme can achieve a lower cost of computing and communications

The valproate mediates radio-bidirectional regulation through RFWD3-dependent ubiquitination on Rad51

Ionizing radiation (IR) can induce DNA double-strand breaks (DSBs) in tumor cells during radiotherapy (RT), but the efficiency of RT is limited because of the toxicity to normal cells. Locating an adjuvant treatment to alleviate damage in normal cells while sensitizing tumor cells to IR has attracted much attention. Here, using the 7,12-dimethylbenz[α]anthracene (DMBA)-induced malignant transformed MCF10A cells, we found that valproate (VPA), a histone deacetylase inhibitor (HDACi), radiosensitized transformed cells while alleviated IR-induced damage in normal cells at a safe dose (0.5 mM). We further demonstrated the decrease of homologous recombination (HR)-associated Rad51 in the transformed cells was related to the increase of its ubiquitination regulated by E3 ligase RFWD3 for the radiosensitization, which was opposite to normal cells, indicating that RFWD3-dependent ubiquitination on Rad51 was involved in the VPA-mediated radio-bidirectional effect. Through DMBA-transformed breast cancer rat model, VPA at 200 mg/kg radiosensitized tumor tissue cells by increasing RFWD3 and inhibited Rad51, while radioprotected normal tissue cells by decreasing RFWD3 and enhanced Rad51. In addition, we found high-level Rad51 was associated with tumorigenesis and poor prognosis in breast cancer patients. Our findings uncovered RFWD3-dependent Rad51 ubiquitination was the novel mechanism of VPA-mediated radio-bidirectional effect, VPA is a potential adjuvant treatment for tumor RT

SDSS J013127.34−-032100.1: A newly discovered radio-loud quasar at z=5.18z=5.18 with extremely high luminosity

Only very few z>5 quasars discovered to date are radio-loud, with a radio-to-optical flux ratio (radio-loudness parameter) higher than 10. Here we report the discovery of an optically luminous radio-loud quasar, SDSS J013127.34-032100.1 (J0131-0321 in short), at z=5.18+-0.01 using the Lijiang 2.4m and Magellan telescopes. J0131-0321 has a spectral energy distribution consistent with that of radio-loud quasars. With an i-band magnitude of 18.47 and radio flux density of 33 mJy, its radio-loudness parameter is ~100. The optical and near-infrared spectra taken by Magellan enable us to estimate its bolometric luminosity to be L_bol ~ 1.1E48 erg/s, approximately 4.5 times greater than that of the most distant quasar known to date. The black hole mass of J0131-0321 is estimated to be 2.7E9 solar masses, with an uncertainty up to 0.4 dex. Detailed physical properties of this high-redshift, radio-loud, potentially super-Eddington quasar can be probed in the future with more dedicated and intensive follow-up observations using multi-wavelength facilities.Comment: 5 pages, 3 figures, accepted to ApJ

Correlation Between Protein Primary Structure and Soluble Expression Level of HSA dAb in Escherichia coli

Izoelektrična točka, duljina molekule, molekularna masa i slijed aminokiselina bitno utječu na topljivost proteina. U ovom smo se radu fokusirali na sastav aminokiselina i ispitali one koje najviše utječu na razinu ekspresije topljivog protutijela albumina iz ljudskog seruma (HSA dAb). Grupiranjem i primjenom linearnog modela analizirana je topljivost 65 varijanti proteina. Bitan utjecaj na ekspresiju topljivog protutijela dAb imale su specifične kombinacije aminokiselina, i to (S, R, N, D, Q) u supernatantu, (G, R, C, N, S) u lizatu peleta i (R, S, G) u ukupnom topljivom protutijelu dAb. Od 20 aminokiselina, arginin je imao negativan, a glicin i serin su imale pozitivan učinak na razinu ekspresije topljivog proteina. Preciznost linearnog modela predviđanja topljivosti proteina bila je 80 %. Zaključeno je da se povećanjem udjela polarnih aminokiselina, osobito glicina i serina, te smanjenjem udjela arginina bitno povećala ekspresija topljivog proteina HSA dAb.It is widely accepted that features such as pI, length, molecular mass and amino acid (AA) sequence have a significant influence on protein solubility. Here, we mainly focused on AA composition and explored those that most affected the soluble expression level of human serum albumin (HSA) domain antibody (dAb). The soluble expression and sequence of 65 dAb variants were analysed using clustering and linear modelling. Certain AAs significantly affected the soluble expression level of dAb, with the specific AA combinations being (S, R, N, D, Q), (G, R, C, N, S) and (R, S, G); these combinations respectively affected the dAb expression level in the broth supernatant, the level in the pellet lysate and total soluble dAb. Among the 20 AAs, R displayed a negative influence on the soluble expression level, whereas G and S showed positive effects. A linear model was built to predict the soluble expression level from the sequence; this model had a prediction accuracy of 80 %. In summary, increasing the content of polar AAs, especially G and S, and decreasing the content of R, was helpful to improve the soluble expression level of HSA dAb