Combining Artificial Intelligence with Traditional Chinese Medicine for Intelligent Health Management

The growth of artificial intelligence (AI) is being referred to as the beginning of "the fourth industrial revolution". With the rapid development of hardware, algorithms, and applications, AI not only provides a new concept and relevant solutions to solve the problem of complexity science but also provides a new concept and method to promote the development of traditional Chinese medicine (TCM). In this study, based on the research and development of AI technology applications in biomedical and clinical diagnosis and treatment, we introduce AI technologies in current TCM research. This can have applications in intelligent clinical information acquisition, intelligent clinical decision, and efficacy evaluation of TCM; intelligent classification management, intelligent prescription, and drug research in Chinese herbal medicine; and health management. Furthermore, we propose a framework of "intelligent TCM" and outline its development prospects

miRecords: an integrated resource for microRNA–target interactions

MicroRNAs (miRNAs) are an important class of small noncoding RNAs capable of regulating other genes’ expression. Much progress has been made in computational target prediction of miRNAs in recent years. More than 10 miRNA target prediction programs have been established, yet, the prediction of animal miRNA targets remains a challenging task. We have developed miRecords, an integrated resource for animal miRNA–target interactions. The Validated Targets component of this resource hosts a large, high-quality manually curated database of experimentally validated miRNA–target interactions with systematic documentation of experimental support for each interaction. The current release of this database includes 1135 records of validated miRNA–target interactions between 301 miRNAs and 902 target genes in seven animal species. The Predicted Targets component of miRecords stores predicted miRNA targets produced by 11 established miRNA target prediction programs. miRecords is expected to serve as a useful resource not only for experimental miRNA researchers, but also for informatics scientists developing the next-generation miRNA target prediction programs. The miRecords is available at http://miRecords.umn.edu/miRecords

Radar Sensing via OTFS Signaling: A Delay Doppler Signal Processing Perspective

The recently proposed orthogonal time frequency space (OTFS) modulation multiplexes data symbols in the delay-Doppler (DD) domain. Since the range and velocity, which can be derived from the delay and Doppler shifts, are the parameters of interest for radar sensing, it is natural to consider implementing DD signal processing for radar sensing. In this paper, we investigate the potential connections between the OTFS and DD domain radar signal processing. Our analysis shows that the range-Doppler matrix computing process in radar sensing is exactly the demodulation of OTFS with a rectangular pulse shaping filter. Furthermore, we propose a two-dimensional (2D) correlation-based algorithm to estimate the fractional delay and Doppler parameters for radar sensing. Simulation results show that the proposed algorithm can efficiently obtain the delay and Doppler shifts associated with multiple targets.Comment: ICC-2023 Accepte

Population Effect Model Identifies Gene Expression Predictors of Survival Outcomes in Lung Adenocarcinoma for Both Caucasian and Asian Patients

Background: We analyzed and integrated transcriptome data from two large studies of lung adenocarcinomas on distinct populations. Our goal was to investigate the variable gene expression alterations between paired tumor-normal tissues and prospectively identify those alterations that can reliably predict lung disease related outcomes across populations. Methods: We developed a mixed model that combined the paired tumor-normal RNA-seq from two populations. Alterations in gene expression common to both populations were detected and validated in two independent DNA microarray datasets. A 10-gene prognosis signature was developed through a l1 penalized regression approach and its prognostic value was evaluated in a third independent microarray cohort. Results: Deregulation of apoptosis pathways and increased expression of cell cycle pathways were identified in tumors of both Caucasian and Asian lung adenocarcinoma patients. We demonstrate that a 10-gene biomarker panel can predict prognosis of lung adenocarcinoma in both Caucasians and Asians. Compared to low risk groups, high risk groups showed significantly shorter overall survival time (Caucasian patients data: HR = 3.63, p-value = 0.007; Asian patients data: HR = 3.25, p-value = 0.001). Conclusions: This study uses a statistical framework to detect DEGs between paired tumor and normal tissues that considers variances among patients and ethnicities, which will aid in understanding the common genes and signalling pathways with the largest effect sizes in ethnically diverse cohorts. We propose multifunctional markers for distinguishing tumor from normal tissue and prognosis for both populations studied

Electromagnetic Source Imaging via a Data-Synthesis-Based Convolutional Encoder-Decoder Network

Electromagnetic source imaging (ESI) requires solving a highly ill-posed inverse problem. To seek a unique solution, traditional ESI methods impose various forms of priors that may not accurately reflect the actual source properties, which may hinder their broad applications. To overcome this limitation, in this paper a novel data-synthesized spatio-temporally convolutional encoder-decoder network method termed DST-CedNet is proposed for ESI. DST-CedNet recasts ESI as a machine learning problem, where discriminative learning and latent-space representations are integrated in a convolutional encoder-decoder network (CedNet) to learn a robust mapping from the measured electroencephalography/magnetoencephalography (E/MEG) signals to the brain activity. In particular, by incorporating prior knowledge regarding dynamical brain activities, a novel data synthesis strategy is devised to generate large-scale samples for effectively training CedNet. This stands in contrast to traditional ESI methods where the prior information is often enforced via constraints primarily aimed for mathematical convenience. Extensive numerical experiments as well as analysis of a real MEG and Epilepsy EEG dataset demonstrate that DST-CedNet outperforms several state-of-the-art ESI methods in robustly estimating source signals under a variety of source configurations.Comment: 15 pages, 14 figures, and journa

A Systematic Review and Meta-Analysis on the Efficacy of Repeated Transcranial Direct Current Stimulation for Migraine

Purpose: Transcranial direct current stimulation (tDCS) may have therapeutic potential in the management of migraine. However, studies to date have yielded conflicting results. We reviewed studies using repeated tDCS for longer than 4 weeks in migraine treatment, and performed meta-analysis on the efficacy of tDCS in migraine. Methods: In this meta-analysis, we included the common outcome measurements reported across randomized controlled trials (RCTs). Subgroup analysis was performed at different post-treatment endpoints, and with different stimulation intensities and polarities. Results: Five RCTs were included in the quantitative meta-analysis with a total of 104 migraine patients. We found a significant reduction of migraine pain intensity (MD: − 1.44; CI: [− 2.13, − 0.76]) in active vs sham tDCS treated patients. Within active treatment groups, pain intensity and duration were significantly improved from baseline after tDCS treatment (intensity MD: − 1.86; CI: [− 3.30, − 0.43]; duration MD: − 4.42; CI: [− 8.11, − 0.74]) and during a follow-up period (intensity MD: − 1.52; CI: [− 1.84, − 1.20]; duration MD: − 1.94; CI: [− 3.10, − 0.77]). There was a significant reduction of pain intensity by both anodal (MD: − 1.74; CI: [− 2.80, − 0.68]) and cathodal (MD: − 1.49; CI: [− 1.89, − 1.09]) stimulation conditions. Conclusion: tDCS treatment repeated over days for a period of 4 weeks or more is effective in reducing migraine pain intensity and duration of migraine episode. The benefit of tDCS can persist for at least 4 weeks after the completion of last tDCS session. Both anodal and cathodal stimulation are effective for reducing migraine pain intensity

Coupled evolution of nitrogen cycling and redoxcline dynamics on the Yangtze Block across the Ediacaran-Cambrian transition

The authors acknowledge funding support from the NSF FESD and Earth-Life Transitions programs (T.L.), the NASA Astrobiology Institute under Cooperative Agreement No. NNA15BB03A issued through the Science Mission Directorate (T.L.), the key project of the Natural Science Foundation of China (C.-F.C.) (No. 41730424), and the program of China Scholarships Council (Y.C.) (No. 201504910582). Nitrogen and carbon isotope analyses were funded by startup funds from Virginia Tech to B.C.G.The Ediacaran-Cambrian transition is characterized by the evolution of complex eukaryotes and rapid diversification of metazoans. However, linkages between environmental triggers and evolutionary patterns remain unclear. Here, we present high-resolution records of carbon and nitrogen isotopic data (δ13C, δ15N) for a drill core extending from the early Ediacaran Doushantuo Formation to the early Cambrian Jiumenchong Formation, located on the slope of the Yangtze Block. Our data show that sedimentary bulk nitrogen isotope values (δ15Nbulk) decrease progressively from the early Ediacaran to the early Cambrian, broadly concurrent with nitrogen isotope data from other sections throughout the Yangtze Block. During the early Ediacaran, however, δ15Nbulk values from our study are higher (maximum 11.2‰) compared to those from more restricted coeval sections, suggesting a higher degree of denitrification in our slope section. The early Ediacaran δ15Nbulk data from the Yangtze Block may thus provide indirect evidence for an upwelling system that led to a shallower redoxcline in slope environments of the Upper Yangtze region. Widespread light δ15Nbulk values from the early Cambrian (minimum −7.5‰) paired with excess silicate-bound nitrogen throughout much of the Yangtze Block are most parsimoniously interpreted as non-quantitative assimilation of ammonium (NH4+) with relatively high concentrations of NH4+ accumulating in the deep basin. Overall, the spatial and temporal trends in nitrogen cycling across the Yangtze Block suggest that fixed nitrogen was more bioavailable in the Ediacaran-Cambrian Yangtze Basin compared to previously studied Mesoproterozoic sections, although nitrogen speciation in the photic zone may have varied with time. Environmental factors such as oxygen levels and nitrogen bioavailability may have shaped the evolutionary trajectory of life on the Yangtze Block and potentially elsewhere across the Ediacaran-Cambrian transition.PostprintPeer reviewe

A Novel Signal Transduction Pathway that Modulates <i>rhl</i> Quorum Sensing and Bacterial Virulence in <i>Pseudomonas aeruginosa</i>

The rhl quorum-sensing (QS) system plays critical roles in the pathogenesis of P. aeruginosa. However, the regulatory effects that occur directly upstream of the rhl QS system are poorly understood. Here, we show that deletion of gene encoding for the two-component sensor BfmS leads to the activation of its cognate response regulator BfmR, which in turn directly binds to the promoter and decreases the expression of the rhlR gene that encodes the QS regulator RhlR, causing the inhibition of the rhl QS system. In the absence of bfmS, the Acka-Pta pathway can modulate the regulatory activity of BfmR. In addition, BfmS tunes the expression of 202 genes that comprise 3.6% of the P. aeruginosa genome. We further demonstrate that deletion of bfmS causes substantially reduced virulence in lettuce leaf, reduced cytotoxicity, enhanced invasion, and reduced bacterial survival during acute mouse lung infection. Intriguingly, specific missense mutations, which occur naturally in the bfmS gene in P. aeruginosa cystic fibrosis (CF) isolates such as DK2 strains and RP73 strain, can produce BfmS variants (BfmSL181P, BfmSL181P/E376Q, and BfmSR393H) that no longer repress, but instead activate BfmR. As a result, BfmS variants, but not the wild-type BfmS, inhibit the rhl QS system. This study thus uncovers a previously unexplored signal transduction pathway, BfmS/BfmR/RhlR, for the regulation of rhl QS in P. aeruginosa. We propose that BfmRS TCS may have an important role in the regulation and evolution of P. aeruginosa virulence during chronic infection in CF lungs.</p

Robust Nuclear Spin Polarization via Ground-State Level Anti-Crossing of Boron Vacancy Defects in Hexagonal Boron Nitride

Nuclear spin polarization plays a crucial role in quantum information processing and quantum sensing. In this work, we demonstrate a robust and efficient method for nuclear spin polarization with boron vacancy ($\mathrm{V_B^-}$) defects in hexagonal boron nitride (h-BN) using ground-state level anti-crossing (GSLAC). We show that GSLAC-assisted nuclear polarization can be achieved with significantly lower laser power than excited-state level anti-crossing, making the process experimentally more viable. Furthermore, we have demonstrated direct optical readout of nuclear spins for $\mathrm{V_B^-}$ in h-BN. Our findings suggest that GSLAC is a promising technique for the precise control and manipulation of nuclear spins in $\mathrm{V_B^-}$ defects in h-BN.Comment: 6 pages, 4 figure

Mutation-induced remodeling of the BfmRS two-component system in Pseudomonas aeruginosa clinical isolates

Genetic mutations are a primary driving force behind the adaptive evolution of bacterial pathogens. Multiple clinical isolates of Pseudomonas aeruginosa, an important human pathogen, have naturally evolved one or more missense mutations in bfmS, which encodes the sensor histidine kinase of the BfmRS two-component system (TCS). A mutant BfmS protein containing both the L181P and E376Q substitutions increased the phosphorylation and thus the transcriptional regulatory activity of its cognate downstream response regulator, BfmR. This reduced acute virulence and enhanced biofilm formation, both of which are phenotypic changes associated with a chronic infection state. The increased phosphorylation of BfmR was due, at least in part, to the cross-phosphorylation of BfmR by GtrS, a noncognate sensor kinase. Other spontaneous missense mutations in bfmS, such as A42E/G347D, T242R, and R393H, also caused a similar remodeling of the BfmRS TCS in P. aeruginosa. This study highlights the plasticity of TCSs mediated by spontaneous mutations and suggests that mutation-induced activation of BfmRS may contribute to host adaptation by P. aeruginosa during chronic infections