CUTS: Neural Causal Discovery from Irregular Time-Series Data

Causal discovery from time-series data has been a central task in machine learning. Recently, Granger causality inference is gaining momentum due to its good explainability and high compatibility with emerging deep neural networks. However, most existing methods assume structured input data and degenerate greatly when encountering data with randomly missing entries or non-uniform sampling frequencies, which hampers their applications in real scenarios. To address this issue, here we present CUTS, a neural Granger causal discovery algorithm to jointly impute unobserved data points and build causal graphs, via plugging in two mutually boosting modules in an iterative framework: (i) Latent data prediction stage: designs a Delayed Supervision Graph Neural Network (DSGNN) to hallucinate and register unstructured data which might be of high dimension and with complex distribution; (ii) Causal graph fitting stage: builds a causal adjacency matrix with imputed data under sparse penalty. Experiments show that CUTS effectively infers causal graphs from unstructured time-series data, with significantly superior performance to existing methods. Our approach constitutes a promising step towards applying causal discovery to real applications with non-ideal observations.Comment: https://openreview.net/forum?id=UG8bQcD3Em

Controllable Formation of the Crystalline Phases in Ge-Ga-S Chalcogenide Glass-Ceramics

We prepared chemically stoichiometric, S-poor and S-rich Ge–Ga–S glasses and annealed them at a temperature that was 20°C higher than its respective glass transition temperature. We aimed at tuning the formation of the different crystals in chalcogenide glass-ceramics. Through systematic characterization of the structure using X-ray diffraction and Raman scattering spectra, we found that, GeS2 and GeS crystals only can be created in S-rich and S-poor glass-ceramics, respectively, while all GeS, Ga2S3, and GeS2 crystals exist in chemically stoichiometric glass-ceramics. Moreover, we demonstrated the homogeneous distribution of the crystals can be formed in the S-rich glass-ceramics from the surface to the interior via composition designing. The present approach blazes a new path to control the growth of the different crystals in chalcogenide glass-ceramicsThis research was supported by the Zhejiang Administration of foreign experts affairs project of China (Z20150650), and the Australian Research Council (ARC) Centre of Excellence for Ultrahigh bandwidth Device for Optical System (CE110001018), ARC Discovery programs (DP110102753

Choice of radiotherapy modality for the combined treatment of non-small cell lung cancer with brain metastases: whole-brain radiation therapy with simultaneous integrated boost or stereotactic radiosurgery

PurposeTo compare Whole-brain radiation therapy with simultaneous integrated boost (WBRT+SIB) to stereotactic radiosurgery (SRS)for non-small cell lung cancer (NSCLC)with brain metastases (BMs)in terms of overall survival (OS), intracranial progression-free-survival(iPFS), toxicity and objective response rate (ORR)MethodsA retrospective review was performed in our hospital of 90 patients diagnosed with NSCLC- BM who received either SRS (n = 48) or WBRT+SIB (n = 42) from January 2016 to January 2022. 76 (84.44%) patients received systemic drug therapy after radiotherapy, including chemotherapy(n=53), targeted therapy(n=40), immunotherapy(n=23), and anti-vascular drug therapy(n=45). OS and iPFS were estimated by the Kaplan-Meier method and compared using the log-rank test. Univariate and Multivariate analysis of the prognostic factors was performed using the Cox proportional hazard regression model.ResultsThe WBRT+SIB cohort had a longer median iPFS (20.0 versus (VS) 12.0 months, P = 0.0069) and a similar median OS (32.0 vs 28.0 months, P = 0.195) than the SRS cohort. Intracranial objective response rates in WBRT +SIB and SRS cohorts were 76.19% and 70.09%, respectively (P = 0.566). Disease control rates were 88.09% and 83.33%, respectively (P = 0.521). Multivariate analysis showed that WBRT+SIB is the only factor affecting iPFS(hazard ratio (HR):0.597 {95%confidence interval(CI):0.370-0.966}, P=0.035). Sex, Liver metastasis and Lymph node metastasis are risk factors for NSCLC-BM.ConclusionIn the context of systemic drug therapy, WBRT+SIB may have better intracranial local control than SRS in NSCLC-BM patients

Construction and validation of a novel prognostic model for intrahepatic cholangiocarcinoma based on a combined scoring system of systemic immune-inflammation index and albumin-bilirubin: a multicenter study

BackgroundThe degree of inflammation and immune status is widely recognized to be associated with intrahepatic cholangiocarcinoma (ICC) and is closely linked to poor postoperative survival. The purpose of this study was to evaluate whether the systemic immune-inflammatory index (SII) and the albumin bilirubin (ALBI) grade together exhibit better predictive strength compared to SII and ALBI separately in patients with ICC undergoing curative surgical resection.MethodsA retrospective analysis was performed on a cohort of 374 patients with histologically confirmed ICC who underwent curative surgical resection from January 2016 to January 2020 at three medical centers. The cohort was divided into a training set comprising 258 patients and a validation set consisting of 116 patients. Subsequently, the prognostic predictive abilities of three indicators, namely SII, ALBI, and SII+ALBI grade, were evaluated. Independent risk factors were identified through univariate and multivariate analyses. The identified independent risk factors were then utilized to construct a nomogram prediction model, and the predictive strength of the nomogram prediction model was assessed through Receiver Operating Characteristic (ROC) survival curves and calibration curves.ResultsUnivariate analysis of the training set, consisting of 258 eligible patients with ICC, revealed that SII, ALBI, and SII+ALBI grade were significant prognostic factors for overall survival (OS) and recurrence-free survival (RFS) (p < 0.05). Multivariate analysis revealed the independent significance of SII+ALBI grade as a risk factor for postoperative OS and RFS (p < 0.05). Furthermore, we conducted an analysis of the correlation between SII, ALBI, SII+ALBI grade, and clinical features, indicating that SII+ALBI grade exhibited stronger associations with clinical and pathological characteristics compared to SII and ALBI. We constructed a predictive model for postoperative survival in ICC based on SII+ALBI grade, as determined by the results of multivariate analysis. Evaluation of the model’s predictive strength was performed through ROC survival curves and calibration curves in the training set and validation set, revealing favorable predictive performance.ConclusionThe SII+ALBI grade, a novel classification based on inflammatory and immune status, serves as a reliable prognostic indicator for postoperative OS and RFS in patients with ICC

Integrated microwave photonic true-time delay with interferometric delay enhancement based on Brillouin scattering and microring resonators

True-time delays are important building blocks in modern radio frequency systems that can be implemented using integrated microwave photonics, enabling higher carrier frequencies, improved bandwidths, and a reduction in size, weight, and power. Stimulated Brillouin scattering (SBS) offers optically-induced continuously tunable delays and is thus ideal for applications that require programmable reconfiguration but previous approaches have been limited by large SBS gain requirements. Here, we overcome this limitation by using radio-frequency interferometry to enhance the Brillouin-induced delay applied to the optical sidebands that carry RF signals, while controlling the phase of the optical carrier with integrated silicon nitride microring resonators. We report a delay tunability over 600 ps exploiting an enhancement factor of 30, over a bandwidth of 1 GHz using less than 1 dB of Brillouin gain utilizing a photonic chip architecture based on Brillouin scattering and microring resonators.Office of Naval Research Global (N62909-18- 1-2013); U.S. Air Force (FA2386-16-1- 4036); Australian Research Council (LP170100112)

Molecular Evolution and Stress and Phytohormone Responsiveness of SUT Genes in Gossypium hirsutum

Sucrose transporters (SUTs) play key roles in allocating the translocation of assimilates from source to sink tissues. Although the characteristics and biological roles of SUTs have been intensively investigated in higher plants, this gene family has not been functionally characterized in cotton. In this study, we performed a comprehensive analysis of SUT genes in the tetraploid cotton Gossypium hirsutum. A total of 18 G. hirsutum SUT genes were identified and classified into three groups based on their evolutionary relationships. Up to eight SUT genes in G. hirsutum were placed in the dicot-specific SUT1 group, while four and six SUT genes were, respectively, clustered into SUT4 and SUT2 groups together with members from both dicot and monocot species. The G. hirsutum SUT genes within the same group displayed similar exon/intron characteristics, and homologous genes in G. hirsutum At and Dt subgenomes, G. arboreum, and G. raimondii exhibited one-to-one relationships. Additionally, the duplicated genes in the diploid and polyploid cotton species have evolved through purifying selection, suggesting the strong conservation of SUT loci in these species. Expression analysis in different tissues indicated that SUT genes might play significant roles in cotton fiber elongation. Moreover, analyses of cis-acting regulatory elements in promoter regions and expression profiling under different abiotic stress and exogenous phytohormone treatments implied that SUT genes, especially GhSUT6A/D, might participate in plant responses to diverse abiotic stresses and phytohormones. Our findings provide valuable information for future studies on the evolution and function of SUT genes in cotton

6G Network AI Architecture for Everyone-Centric Customized Services

Mobile communication standards were developed for enhancing transmission and network performance by using more radio resources and improving spectrum and energy efficiency. How to effectively address diverse user requirements and guarantee everyone's Quality of Experience (QoE) remains an open problem. The Sixth Generation (6G) mobile systems will solve this problem by utilizing heterogenous network resources and pervasive intelligence to support everyone-centric customized services anywhere and anytime. In this article, we first coin the concept of Service Requirement Zone (SRZ) on the user side to characterize and visualize the integrated service requirements and preferences of specific tasks of individual users. On the system side, we further introduce the concept of User Satisfaction Ratio (USR) to evaluate the system's overall service ability of satisfying a variety of tasks with different SRZs. Then, we propose a network Artificial Intelligence (AI) architecture with integrated network resources and pervasive AI capabilities for supporting customized services with guaranteed QoEs. Finally, extensive simulations show that the proposed network AI architecture can consistently offer a higher USR performance than the cloud AI and edge AI architectures with respect to different task scheduling algorithms, random service requirements, and dynamic network conditions

The gut microbiome in atherosclerotic cardiovascular disease

The gut microbiota may play a role in cardiovascular diseases. Here, the authors perform a metagenome-wide association study on stools from individuals with atherosclerotic cardiovascular disease and healthy controls, identifying microbial strains and functions associated with the disease