The Differentiation Balance of Bone Marrow Mesenchymal Stem Cells Is Crucial to Hematopoiesis.

Bone marrow mesenchymal stem cells (BMSCs), the important component and regulator of bone marrow microenvironment, give rise to hematopoietic-supporting stromal cells and form hematopoietic niches for hematopoietic stem cells (HSCs). However, how BMSC differentiation affects hematopoiesis is poorly understood. In this review, we focus on the role of BMSC differentiation in hematopoiesis. We discussed the role of BMSCs and their progeny in hematopoiesis. We also examine the mechanisms that cause differentiation bias of BMSCs in stress conditions including aging, irradiation, and chemotherapy. Moreover, the differentiation balance of BMSCs is crucial to hematopoiesis. We highlight the negative effects of differentiation bias of BMSCs on hematopoietic recovery after bone marrow transplantation. Keeping the differentiation balance of BMSCs is critical for hematopoietic recovery. This review summarises current understanding about how BMSC differentiation affects hematopoiesis and its potential application in improving hematopoietic recovery after bone marrow transplantation

Breathing Signature as Vitality Score Index Created by Exercises of Qigong: Implications of Artificial Intelligence Tools Used in Traditional Chinese Medicine.

Rising concerns about the short- and long-term detrimental consequences of administration of conventional pharmacopeia are fueling the search for alternative, complementary, personalized, and comprehensive approaches to human healthcare. Qigong, a form of Traditional Chinese Medicine, represents a viable alternative approach. Here, we started with the practical, philosophical, and psychological background of Ki (in Japanese) or Qi (in Chinese) and their relationship to Qigong theory and clinical application. Noting the drawbacks of the current state of Qigong clinic, herein we propose that to manage the unique aspects of the Eastern 'non-linearity' and 'holistic' approach, it needs to be integrated with the Western "linearity" "one-direction" approach. This is done through developing the concepts of "Qigong breathing signatures," which can define our life breathing patterns associated with diseases using machine learning technology. We predict that this can be achieved by establishing an artificial intelligence (AI)-Medicine training camp of databases, which will integrate Qigong-like breathing patterns with different pathologies unique to individuals. Such an integrated connection will allow the AI-Medicine algorithm to identify breathing patterns and guide medical intervention. This unique view of potentially connecting Eastern Medicine and Western Technology can further add a novel insight to our current understanding of both Western and Eastern medicine, thereby establishing a vitality score index (VSI) that can predict the outcomes of lifestyle behaviors and medical conditions

Zero-Shot Transfer in Imitation Learning

We present an algorithm that learns to imitate expert behavior and can transfer to previously unseen domains without retraining. Such an algorithm is extremely relevant in real-world applications such as robotic learning because 1) reward functions are difficult to design, 2) learned policies from one domain are difficult to deploy in another domain and 3) learning directly in the real world is either expensive or unfeasible due to security concerns. To overcome these constraints, we combine recent advances in Deep RL by using an AnnealedVAE to learn a disentangled state representation and imitate an expert by learning a single Q-function which avoids adversarial training. We demonstrate the effectiveness of our method in 3 environments ranging in difficulty and the type of transfer knowledge required

Multi-Model Data Query Languages and Processing Paradigms

Peer reviewe

Single-cell transcriptomes reveal the mechanism for a breast cancer prognostic gene panel.

The clinical benefits of the MammaPrint® signature for breast cancer is well documented; however, how these genes are related to cell cycle perturbation have not been well determined. Our single-cell transcriptome mapping (algorithm) provides details into the fine perturbation of all individual genes during a cell cycle, providing a view of the cell-cycle-phase specific landscape of any given human genes. Specifically, we identified that 38 out of the 70 (54%) MammaPrint® signature genes are perturbated to a specific phase of the cell cycle. The MammaPrint® signature panel derived its clinical prognosis power from measuring the cell cycle activity of specific breast cancer samples. Such cell cycle phase index of the MammaPrint® signature suggested that measurement of the cell cycle index from tumors could be developed into a prognosis tool for various types of cancer beyond breast cancer, potentially improving therapy through targeting a specific phase of the cell cycle of cancer cells

Collaborative interactions of heterogenous ribonucleoproteins contribute to transcriptional regulation of sterol metabolism in mice.

Heterogeneous nuclear ribonucleoproteins (hnRNPs) are a group of functionally versatile proteins that play critical roles in the biogenesis, cellular localization and transport of RNA. Here, we outline a role for hnRNPs in gene regulatory circuits controlling sterol homeostasis. Specifically, we find that tissue-selective loss of the conserved hnRNP RALY enriches for metabolic pathways. Liver-specific deletion of RALY alters hepatic lipid content and serum cholesterol level. In vivo interrogation of chromatin architecture and genome-wide RALY-binding pattern reveal insights into its cooperative interactions and mode of action in regulating cholesterogenesis. Interestingly, we find that RALY binds the promoter region of the master metabolic regulator Srebp2 and show that it directly interacts with coactivator Nuclear Transcription Factor Y (NFY) to influence cholesterogenic gene expression. Our work offers insights into mechanisms orchestrating selective promoter activation in metabolic control and a model by which hnRNPs can impact health and disease states

Impact of 2009 American Recovery and Reinvestment Act (ARRA) health center investments on disadvantaged neighborhoods after recession

Background: Federally qualified health centers (FQHCs) are integral to the U.S. healthcare safety net and uniquely situated in disadvantaged neighborhoods. The 2009 American Recovery and Reinvestment Act (ARRA) invested $2 billion in FQHC stimulus during the Great Recession; but it remains unknown whether this investment was associated with extended benefits for disadvantaged neighborhoods. Methods: We used a propensity-score matched longitudinal design (2008-2012) to examine whether the 2009 ARRA FQHC investment was associated with local jobs and establishments recovery in FQHC neighborhoods. Job change data were obtained from the Longitudinal Employer-Household Dynamics (LEHD) survey and calculated as an annual rate per 1,000 population. Establishment change data were obtained from the National Neighborhood Data Archive (NaNDA) and calculated as an annual rate per 10,000 population. Establishment data included 4 establishment types: healthcare services, eating/drinking places, retail establishments, and grocery stores. Fixed effects were used to compare annual rates of jobs and establishments recovery between ARRA-funded FQHC census tracts and a matched control group. Results: Of 50,381 tracts, 2,223 contained ≥ 1 FQHC that received ARRA funding. A higher proportion of FQHC tracts had an extreme poverty designation (11.6% vs. 5.4%), high unemployment rate (45.4% vs. 30.3%), and > 50% minority racial/ethnic composition (48.1% vs. 36.3%). On average, jobs grew at an annual rate of 3.84 jobs per 1,000 population (95% CI: 3.62,4.06). In propensity-score weighted models, jobs in ARRA-funded tracts grew at a higher annual rate of 4.34 per 1,000 (95% CI: 2.56,6.12) relative to those with similar social vulnerability. We observed persistent decline in non-healthcare establishments (-1.35 per 10,000; 95% CI: -1.68,-1.02); but did not observe decline in healthcare establishments. Conclusions: Direct funding to HCs may be an effective strategy to support healthcare establishments and some jobs recovery in disadvantaged neighborhoods during recession, reinforcing the important multidimensional roles HCs play in these communities. However, HCs may benefit from additional investments that target upstream determinants of health to mitigate uneven recovery and neighborhood decline.</p

Multimodal Identification of Alzheimer's Disease: A Review

Alzheimer's disease is a progressive neurological disorder characterized by cognitive impairment and memory loss. With the increasing aging population, the incidence of AD is continuously rising, making early diagnosis and intervention an urgent need. In recent years, a considerable number of teams have applied computer-aided diagnostic techniques to early classification research of AD. Most studies have utilized imaging modalities such as magnetic resonance imaging (MRI), positron emission tomography (PET), and electroencephalogram (EEG). However, there have also been studies that attempted to use other modalities as input features for the models, such as sound, posture, biomarkers, cognitive assessment scores, and their fusion. Experimental results have shown that the combination of multiple modalities often leads to better performance compared to a single modality. Therefore, this paper will focus on different modalities and their fusion, thoroughly elucidate the mechanisms of various modalities, explore which methods should be combined to better harness their utility, analyze and summarize the literature in the field of early classification of AD in recent years, in order to explore more possibilities of modality combinations