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Single-cell RNA sequencing (scRNA-seq) technologies can generate transcriptomic profiles at a single-cell resolution in large patient cohorts, facilitating discovery of gene and cellular biomarkers for disease. Yet, when the number of biomarker genes is large, the translation to clinical applications is challenging due to prohibitive sequencing costs. Here, we introduce scPanel, a computational framework designed to bridge the gap between biomarker discovery and clinical application by identifying a sparse gene panel for patient classification from the cell population(s) most responsive to perturbations (e.g. diseases/drugs). scPanel incorporates a data-driven way to automatically determine a minimal number of informative biomarker genes. Patient-level classification is achieved by aggregating the prediction probabilities of cells associated with a patient using the area under the curve score. Application of scPanel to scleroderma, colorectal cancer, and COVID-19 datasets resulted in high patient classification accuracy using only a small number of genes (<20), automatically selected from the entire transcriptome. In the COVID-19 case study, we demonstrated cross-dataset generalizability in predicting disease state in an external patient cohort. scPanel outperforms other state-of-the-art gene selection methods for patient classification and can be used to identify parsimonious sets of reliable biomarker candidates for clinical translation., (© The Author(s) 2024. Published by Oxford University Press.)

Background: Hepatocellular carcinoma (HCC) is a deadly cancer with a high global mortality rate, and the downregulation of GATA binding protein 4 (GATA4) has been implicated in HCC progression. In this study, we investigated the role of GATA4 in shaping the immune landscape of HCC., Methods: HCC tumor samples were classified into "low" or "normal/high" based on GATA4 RNA expression relative to adjacent non-tumor liver tissues. The immune landscapes of GATA4-low and GATA4-normal/high tumors were analyzed using cytometry by time-of-flight, bulk/spatial transcriptomic analyses and validated by multiplex immunofluorescence., Results: GATA4-low tumors displayed enrichment in exhausted programmed cell death protein 1+ T cells, immunosuppressive regulatory T cells, myeloid-derived suppressor cells, and macrophages, highlighting the impact of GATA4 downregulation on immunosuppression. Spatial and bulk transcriptomic analyses revealed a negative correlation between GATA4 and C-C Motif Chemokine Ligand 20 (CCL20) expression in HCC. Overexpressing GATA4 confirmed CCL20 as a downstream target, contributing to an immunosuppressive tumor microenvironment, as evidenced by increased regulatory T cells and myeloid-derived suppressor cells in CCL20-high tumors. Lastly, the reduced expression of GATA4 and higher expression of CCL20 were associated with poorer overall survival in patients with HCC, implicating their roles in tumor progression., Conclusions: Our study reveals that GATA4 downregulation contributes to an immunosuppressive microenvironment, driven by CCL20-mediated enrichment of regulatory T cells and myeloid-derived suppressor cells in HCC. These findings underscore the critical role of GATA4 reduction in promoting immunosuppression and HCC progression., (Copyright © 2024 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Association for the Study of Liver Diseases.)

Blood-based gene expression signatures could potentially be used as biomarkers for PD. However, it is unclear whether genetically-regulated transcriptomic signatures can provide novel gene candidates for use as PD biomarkers. We leveraged on the Genotype-Tissue Expression (GTEx) database to impute whole-blood transcriptomic expression using summary statistics of three large-scale PD GWAS. A random forest classifier was used with the consensus whole-blood imputed gene signature (IGS) to discriminate between cases and controls. Outcome measures included Area under the Curve (AUC) of Receiver Operating Characteristic (ROC) Curve. We demonstrated that the IGS (n = 37 genes) is conserved across PD GWAS studies and brain tissues. IGS discriminated between cases and controls in an independent whole-blood RNA-sequencing study (1176 PD, 254 prodromal, and 860 healthy controls) with mean AUC and accuracy of 64.8% and 69.4% for PD cohort, and 78.8% and 74% for prodromal cohort. PATL2 was the top-performing imputed gene in both PD and prodromal PD cohorts, whose classifier performance varied with biological sex (higher performance for males and females in the PD and prodromal PD, respectively). Single-cell RNA-sequencing studies (scRNA-seq) of healthy humans and PD patients found PATL2 to be enriched in terminal effector CD8+ and cytotoxic CD4+ cells, whose proportions are both increased in PD patients. We demonstrated the utility of GWAS transcriptomic imputation in identifying novel whole-blood transcriptomic signatures which could be leveraged upon for PD biomarker derivation. We identified PATL2 as a potential biomarker in both clinical and prodromic PD., (© 2024. The Author(s).)

The Baimai Ointment with the effect of relaxing sinew and activating collaterals demonstrates a definite effect on Baimai disease with pain, spasm, stiffness and other symptoms, while the pharmacodynamic characteristics and mechanism of this agent remain unclear. In this study, a rat model of chronic compression of L4 dorsal root ganglion(CCD) was established by lumbar disc herniation, and the efficacy and mechanism of Baimai Ointment in the treatment of CCD were preliminarily explored by behavioral tests, side effect evaluation, network analysis, antagonist and molecular biology verification. The pharmacodynamic experiment indicated that Baimai Ointment significantly improved the pain thresholds(mechanical pain, thermal pain, and cold pain) and gait behavior of CCD model rats without causing tolerance or obvious toxic and side effects. Baimai Ointment inhibited the second-phase nociceptive response of mice in the formalin test, increased the hot plate threshold of normal mice, and down-regulated the expression of inflammatory cytokines in the spinal cord. Network analysis showed that Baimai Ointment had synergistic effect in the treatment of CCD and was related to descending inhibition/facilitation system and neuroinflammation. Furthermore, behavioral tests, Western blot, and immunofluorescence assay revealed that the pain-relieving effect of Baimai Ointment on CCD may be related to the regulation of the interaction between neuroactive ligand and receptors(neuroligands) such as CHRNA7, ADRA2A, and ADRB2, and the down-regulation of the expression of NOS2/pERK/PI3K, the core regulatory element of HIF-1 signaling pathway in spinal microglia. The findings preliminarily reveal the mechanism of relaxing sinew and activating collaterals of Baimai Ointment in the treatment of Baimai disease, providing a reference for the rational drug use and further research of this agent.

Tissue fibrosis affects multiple organs and involves a master-regulatory role of macrophages which respond to an initial inflammatory insult common in all forms of fibrosis. The recently unravelled multi-organ heterogeneity of macrophages in healthy and fibrotic human disease suggests that macrophages expressing osteopontin (SPP1) associate with lung and liver fibrosis. However, the conservation of this SPP1 + macrophage population across different tissues and its specificity to fibrotic diseases with different etiologies remain unclear. Integrating 15 single-cell RNA-sequencing datasets to profile 235,930 tissue macrophages from healthy and fibrotic heart, lung, liver, kidney, skin, and endometrium, we extended the association of SPP1 + macrophages with fibrosis to all these tissues. We also identified a subpopulation expressing matrisome-associated genes (e.g., matrix metalloproteinases and their tissue inhibitors), functionally enriched for ECM remodelling and cell metabolism, representative of a matrisome-associated macrophage (MAM) polarisation state within SPP1 + macrophages. Importantly, the MAM polarisation state follows a differentiation trajectory from SPP1 + macrophages and is associated with a core set of regulon activity. SPP1 + macrophages without the MAM polarisation state (SPP1 + MAM - ) show a positive association with ageing lung in mice and humans. These results suggest an advanced and conserved polarisation state of SPP1 + macrophages in fibrotic tissues resulting from prolonged inflammatory cues within each tissue microenvironment., Competing Interests: JO, KM, YX, HP, KH, EP, JB No competing interests declared, (© 2023, Ouyang, Mishra et al.)

Cells undergo a major epigenome reconfiguration when reprogrammed to human induced pluripotent stem cells (hiPS cells). However, the epigenomes of hiPS cells and human embryonic stem (hES) cells differ significantly, which affects hiPS cell function 1-8 . These differences include epigenetic memory and aberrations that emerge during reprogramming, for which the mechanisms remain unknown. Here we characterized the persistence and emergence of these epigenetic differences by performing genome-wide DNA methylation profiling throughout primed and naive reprogramming of human somatic cells to hiPS cells. We found that reprogramming-induced epigenetic aberrations emerge midway through primed reprogramming, whereas DNA demethylation begins early in naive reprogramming. Using this knowledge, we developed a transient-naive-treatment (TNT) reprogramming strategy that emulates the embryonic epigenetic reset. We show that the epigenetic memory in hiPS cells is concentrated in cell of origin-dependent repressive chromatin marked by H3K9me3, lamin-B1 and aberrant CpH methylation. TNT reprogramming reconfigures these domains to a hES cell-like state and does not disrupt genomic imprinting. Using an isogenic system, we demonstrate that TNT reprogramming can correct the transposable element overexpression and differential gene expression seen in conventional hiPS cells, and that TNT-reprogrammed hiPS and hES cells show similar differentiation efficiencies. Moreover, TNT reprogramming enhances the differentiation of hiPS cells derived from multiple cell types. Thus, TNT reprogramming corrects epigenetic memory and aberrations, producing hiPS cells that are molecularly and functionally more similar to hES cells than conventional hiPS cells. We foresee TNT reprogramming becoming a new standard for biomedical and therapeutic applications and providing a novel system for studying epigenetic memory., (© 2023. The Author(s).)

Profiling tumors at single-cell resolution provides an opportunity to understand complexities underpinning lymph-node metastases in head and neck squamous-cell carcinoma. Single-cell RNAseq (scRNAseq) analysis of cancer-cell trajectories identifies a subpopulation of pre-metastatic cells, driven by actionable pathways including AXL and AURK. Blocking these two proteins blunts tumor invasion in patient-derived cultures. Furthermore, scRNAseq analyses of tumor-infiltrating CD8 + T-lymphocytes show two distinct trajectories to T-cell dysfunction, corroborated by their clonal architecture based on single-cell T-cell receptor sequencing. By determining key modulators of these trajectories, followed by validation using external datasets and functional experiments, we uncover a role for SOX4 in mediating T-cell exhaustion. Finally, interactome analyses between pre-metastatic tumor cells and CD8 + T-lymphocytes uncover a putative role for the Midkine pathway in immune-modulation and this is confirmed by scRNAseq of tumors from humanized mice. Aside from specific findings, this study demonstrates the importance of tumor heterogeneity analyses in identifying key vulnerabilities during early metastasis., (© 2023. The Author(s).)

Our ability to understand and control stem cell biology is being augmented by developments on two fronts, our ability to collect more data describing cell state and our capability to comprehend these data using deep learning models. Here we consider the impact deep learning will have in the future of stem cell research. We explore the importance of generating data suitable for these methods, the requirement for close collaboration between experimental and computational researchers, and the challenges we face to do this fairly and effectively. Achieving this will ensure that the resulting deep learning models are biologically meaningful and computationally tractable., Competing Interests: Conflict of interests O.J.L.R. is an SAB member and shareholder of Mogrify Ltd., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

Background and Purpose: Cerebral small vessel disease (CSVD) is a clinically commonly-seen slow-progressing cerebral vascular disease. As a classic Chinese formula for the treatment of stroke, Daqinjiao Decoction (DQJD) is now used to treat CSVD with desirable effect. Since the mechanism of action is still unclear, this article will explore the therapeutic effect and mechanism of action of the formula using network pharmacology technology., Methods: The major chemical components and potential target genes of DQJD were screened by bioinformatics. The key targets in CSVD were identified based on network modules. Gene Ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed. Pharmacodynamics of the decoction was evaluated by establishing a rat model with bilateral common carotid artery occlusion in the brain. Molecular docking, Western blot analysis and quantitative real-time polymerase chain reaction (QRT-PCR) were performed to confirm the effectiveness of targets in related pathways., Results: Network pharmacology showed that 16 targets and 30 pathways were involved in the DQJD-targeted pathway network. Results revealed that DQJD might play a role by targeting the key targets including Caspse3 and P53 and regulating the P53 signaling pathway. Cognitive function and neuronal cell changes of rats were evaluated using Morris water maze, open field test and HE staining. It was indicated that DQJD could keep the nerve cells intact and neatly arranged. The decoction could improve the memory and learning ability of rats compared with the model group. It decreased the protein and mRNA expression levels of Caspse3 and P53 significantly (p<0.01)., Conclusion: The study shows that baicalein, quercetin and wogonin, the effective components of DQJD, may regulate multiple signaling pathways by targeting the targets like Caspse3 and P53 and treat CSVD by reducing the damage to brain nerve cells., Competing Interests: Declaration of Competing Interest The authors declare that they have no conflicts of interest., (Copyright © 2022. Published by Elsevier GmbH.)

Translated small open reading frames (smORFs) can have important regulatory roles and encode microproteins, yet their genome-wide identification has been challenging. We determined the ribosome locations across six primary human cell types and five tissues and detected 7,767 smORFs with translational profiles matching those of known proteins. The human genome was found to contain highly cell-type- and tissue-specific smORFs and a subset that encodes highly conserved amino acid sequences. Changes in the translational efficiency of upstream-encoded smORFs (uORFs) and the corresponding main ORFs predominantly occur in the same direction. Integration with 456 mass-spectrometry datasets confirms the presence of 603 small peptides at the protein level in humans and provides insights into the subcellular localization of these small proteins. This study provides a comprehensive atlas of high-confidence translated smORFs derived from primary human cells and tissues in order to provide a more complete understanding of the translated human genome., Competing Interests: Declaration of interests S.S. and S.A.C. are co-founders and shareholders of Enleofen Bio Pte Ltd. O.J.L.R. and J.M.P. are SAB members and shareholders of Mogrify Ltd. All other authors declare no competing interests., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Motivation: As the generation of complex single-cell RNA sequencing datasets becomes more commonplace it is the responsibility of researchers to provide access to these data in a way that can be easily explored and shared. Whilst it is often the case that data is deposited for future bioinformatic analysis many studies do not release their data in a way that is easy to explore by non-computational researchers., Results: In order to help address this we have developed ShinyCell, an R package that converts single-cell RNA sequencing datasets into explorable and shareable interactive interfaces. These interfaces can be easily customized in order to maximize their usability and can be easily uploaded to online platforms to facilitate wider access to published data., Availability and Implementation: ShinyCell is available at https://github.com/SGDDNB/ShinyCell and https://figshare.com/projects/ShinyCell/100439., Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author(s) 2021. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Preclinical testing is a crucial step in evaluating cancer therapeutics. We aimed to establish a significant resource of patient-derived xenografts (PDXs) of prostate cancer for rapid and systematic evaluation of candidate therapies. The PDX collection comprises 59 tumors collected from 30 patients between 2012-2020, coinciding with availability of abiraterone and enzalutamide. The PDXs represent the clinico-pathological and genomic spectrum of prostate cancer, from treatment-naïve primary tumors to castration-resistant metastases. Inter- and intra-tumor heterogeneity in adenocarcinoma and neuroendocrine phenotypes is evident from bulk and single-cell RNA sequencing data. Organoids can be cultured from PDXs, providing further capabilities for preclinical studies. Using a 1 x 1 x 1 design, we rapidly identify tumors with exceptional responses to combination treatments. To govern the distribution of PDXs, we formed the Melbourne Urological Research Alliance (MURAL). This PDX collection is a substantial resource, expanding the capacity to test and prioritize effective treatments for prospective clinical trials in prostate cancer., (© 2021. The Author(s).)

The role of microglia cells in Alzheimer's disease (AD) is well recognized, however their molecular and functional diversity remain unclear. Here, we isolated amyloid plaque-containing (using labelling with methoxy-XO4, XO4 + ) and non-containing (XO4 - ) microglia from an AD mouse model. Transcriptomics analysis identified different transcriptional trajectories in ageing and AD mice. XO4 + microglial transcriptomes demonstrated dysregulated expression of genes associated with late onset AD. We further showed that the transcriptional program associated with XO4 + microglia from mice is present in a subset of human microglia isolated from brains of individuals with AD. XO4 - microglia displayed transcriptional signatures associated with accelerated ageing and contained more intracellular post-synaptic material than XO4 + microglia, despite reduced active synaptosome phagocytosis. We identified HIF1α as potentially regulating synaptosome phagocytosis in vitro using primary human microglia, and BV2 mouse microglial cells. Together, these findings provide insight into molecular mechanisms underpinning the functional diversity of microglia in AD.

The combination of single-cell RNA sequencing with CRISPR inhibition/activation provides a high-throughput approach to simultaneously study the effects of hundreds if not thousands of gene perturbations in a single experiment. One recent development in CRISPR-based single-cell techniques introduces a feature barcoding technology that allows for the simultaneous capture of mRNA and guide RNA (gRNA) from the same cell. This is achieved by introducing a capture sequence, whose complement can be incorporated into each gRNA and that can be used to amplify these features prior to sequencing. However, because the technology is in its infancy, there is little information available on how such experimental parameters can be optimized. To overcome this, we varied the capture sequence, capture sequence position, and gRNA backbone to identify an optimal gRNA scaffold for CRISPR activation gene perturbation studies. We provide a report on our screening approach along with our observations and recommendations for future use.

Human pluripotent and trophoblast stem cells have been essential alternatives to blastocysts for understanding early human development 1-4 . However, these simple culture systems lack the complexity to adequately model the spatiotemporal cellular and molecular dynamics that occur during early embryonic development. Here we describe the reprogramming of fibroblasts into in vitro three-dimensional models of the human blastocyst, termed iBlastoids. Characterization of iBlastoids shows that they model the overall architecture of blastocysts, presenting an inner cell mass-like structure, with epiblast- and primitive endoderm-like cells, a blastocoel-like cavity and a trophectoderm-like outer layer of cells. Single-cell transcriptomics further confirmed the presence of epiblast-, primitive endoderm-, and trophectoderm-like cells. Moreover, iBlastoids can give rise to pluripotent and trophoblast stem cells and are capable of modelling, in vitro, several aspects of the early stage of implantation. In summary, we have developed a scalable and tractable system to model human blastocyst biology; we envision that this will facilitate the study of early human development and the effects of gene mutations and toxins during early embryogenesis, as well as aiding in the development of new therapies associated with in vitro fertilization.

The need to derive and culture diverse cell or tissue types in vitro has prompted investigations on how changes in culture conditions affect cell states. However, the identification of the optimal conditions (e.g., signaling molecules and growth factors) required to maintain cell types or convert between cell types remains a time-consuming task. Here, we developed EpiMogrify, an approach that leverages data from ∼100 human cell/tissue types available from ENCODE and Roadmap Epigenomics consortia to predict signaling molecules and factors that can either maintain cell identity or enhance directed differentiation (or cell conversion). EpiMogrify integrates protein-protein interaction network information with a model of the cell's epigenetic landscape based on H3K4me3 histone modifications. Using EpiMogrify-predicted factors for maintenance conditions, we were able to better potentiate the maintenance of astrocytes and cardiomyocytes in vitro. We report a significant increase in the efficiency of astrocyte and cardiomyocyte differentiation using EpiMogrify-predicted factors for conversion conditions., Competing Interests: Declaration of Interests O.J.L.R., E.P., U.S.K., J.M.P., and J.C. have filed a patent (PCT application no: PCT/AU, 2020/050656 titled “Cell Culture Methods and Compositions” filed on June 26, 2020). There are restrictions to the availability of some predicted culture conditions and EpiMogrify code, as they are subject to the patent application and are under commercial investigation. O.J.L.R. and J.M.P. are also co-inventors of the patent (WO/2017/106932) and are co-founders, scientific advisory board members, and shareholders of Mogrify Ltd, a cell therapy company. All other authors declare no competing interests., (Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.)

The reprogramming of human somatic cells to primed or naive induced pluripotent stem cells recapitulates the stages of early embryonic development 1-6 . The molecular mechanism that underpins these reprogramming processes remains largely unexplored, which impedes our understanding and limits rational improvements to reprogramming protocols. Here, to address these issues, we reconstruct molecular reprogramming trajectories of human dermal fibroblasts using single-cell transcriptomics. This revealed that reprogramming into primed and naive pluripotency follows diverging and distinct trajectories. Moreover, genome-wide analyses of accessible chromatin showed key changes in the regulatory elements of core pluripotency genes, and orchestrated global changes in chromatin accessibility over time. Integrated analysis of these datasets revealed a role for transcription factors associated with the trophectoderm lineage, and the existence of a subpopulation of cells that enter a trophectoderm-like state during reprogramming. Furthermore, this trophectoderm-like state could be captured, which enabled the derivation of induced trophoblast stem cells. Induced trophoblast stem cells are molecularly and functionally similar to trophoblast stem cells derived from human blastocysts or first-trimester placentas 7 . Our results provide a high-resolution roadmap for the transcription-factor-mediated reprogramming of human somatic cells, indicate a role for the trophectoderm-lineage-specific regulatory program during this process, and facilitate the direct reprogramming of somatic cells into induced trophoblast stem cells.

Long noncoding RNAs (lncRNAs) constitute the majority of transcripts in the mammalian genomes, and yet, their functions remain largely unknown. As part of the FANTOM6 project, we systematically knocked down the expression of 285 lncRNAs in human dermal fibroblasts and quantified cellular growth, morphological changes, and transcriptomic responses using Capped Analysis of Gene Expression (CAGE). Antisense oligonucleotides targeting the same lncRNAs exhibited global concordance, and the molecular phenotype, measured by CAGE, recapitulated the observed cellular phenotypes while providing additional insights on the affected genes and pathways. Here, we disseminate the largest-to-date lncRNA knockdown data set with molecular phenotyping (over 1000 CAGE deep-sequencing libraries) for further exploration and highlight functional roles for ZNF213-AS1 and lnc-KHDC3L-2 ., (© 2020 Ramilowski et al.; Published by Cold Spring Harbor Laboratory Press.)

Summary: Emerging single-cell RNA-sequencing data technologies has made it possible to capture and assess the gene expression of individual cells. Based on the similarity of gene expression profiles, many tools have been developed to generate an in silico ordering of cells in the form of pseudo-time trajectories. However, these tools do not provide a means to find the ordering of critical gene expression changes over pseudo-time. We present GeneSwitches, a tool that takes any single-cell pseudo-time trajectory and determines the precise order of gene expression and functional-event changes over time. GeneSwitches uses a statistical framework based on logistic regression to identify the order in which genes are either switched on or off along pseudo-time. With this information, users can identify the order in which surface markers appear, investigate how functional ontologies are gained or lost over time and compare the ordering of switching genes from two related pseudo-temporal processes., Availability: GeneSwitches is available at https://geneswitches.ddnetbio.com., Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author(s) 2020. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Ribosome profiling quantifies the genome-wide ribosome occupancy of transcripts. With the integration of matched RNA sequencing data, the translation efficiency (TE) of genes can be calculated to reveal translational regulation. This layer of gene-expression regulation is otherwise difficult to assess on a global scale and generally not well understood in the context of human disease. Current statistical methods to calculate differences in TE have low accuracy, cannot accommodate complex experimental designs or confounding factors, and do not categorize genes into buffered, intensified, or exclusively translationally regulated genes. This article outlines a method [referred to as deltaTE (ΔTE), standing for change in TE] to identify translationally regulated genes, which addresses the shortcomings of previous methods. In an extensive benchmarking analysis, ΔTE outperforms all methods tested. Furthermore, applying ΔTE on data from human primary cells allows detection of substantially more translationally regulated genes, providing a clearer understanding of translational regulation in pathogenic processes. In this article, we describe protocols for data preparation, normalization, analysis, and visualization, starting from raw sequencing files. © 2019 The Authors. Basic Protocol: One-step detection and classification of differential translation efficiency genes using DTEG.R Alternate Protocol: Step-wise detection and classification of differential translation efficiency genes using R Support Protocol: Workflow from raw data to read counts., (© 2019 The Authors.)

There is currently little information available about how individual cell types contribute to Alzheimer's disease. Here we applied single-nucleus RNA sequencing to entorhinal cortex samples from control and Alzheimer's disease brains (n = 6 per group), yielding a total of 13,214 high-quality nuclei. We detail cell-type-specific gene expression patterns, unveiling how transcriptional changes in specific cell subpopulations are associated with Alzheimer's disease. We report that the Alzheimer's disease risk gene APOE is specifically repressed in Alzheimer's disease oligodendrocyte progenitor cells and astrocyte subpopulations and upregulated in an Alzheimer's disease-specific microglial subopulation. Integrating transcription factor regulatory modules with Alzheimer's disease risk loci revealed drivers of cell-type-specific state transitions towards Alzheimer's disease. For example, transcription factor EB, a master regulator of lysosomal function, regulates multiple disease genes in a specific Alzheimer's disease astrocyte subpopulation. These results provide insights into the coordinated control of Alzheimer's disease risk genes and their cell-type-specific contribution to disease susceptibility. These results are available at http://adsn.ddnetbio.com.

This chapter was published without including the "Conflict of Interest" section given by the author along with the corrected proof.

The process of identifying sets of transcription factors that can induce a cell conversion can be time-consuming and expensive. To help alleviate this, a number of computational tools have been developed which integrate gene expression data with molecular interaction networks in order to predict these factors. One such approach is Mogrify, an algorithm which ranks transcriptions factors based on their regulatory influence in different cell types and tissues. These ranks are then used to identify a nonredundant set of transcription factors to promote cell conversion between any two cell types/tissues. Here we summarize the important concepts and data sources that were used in the implementation of this approach. Furthermore, we describe how the associated web resource ( www.mogrify.net ) can be used to tailor predictions to specific experimental scenarios, for instance, limiting the set of possible transcription factors and including domain knowledge. Finally, we describe important considerations for the effective selection of reprogramming factors. We envision that such data-driven approaches will become commonplace in the field, rapidly accelerating the progress in stem cell biology.

This study aimed to analyze the analgesic effect and related central mechanisms of CQ prescription on cancer invasion induced mirror image pain (CIIMIP)in model mice.In the study, male BALB/c mice were randomly divided into normal group, operation control group (injected with 0.2 mL inactivated S180 sarcoma cell sap), model group (injected with 0.2 mL S180 sarcoma cell sap on the right leg near the greater trochanter of femur) and CQ prescription low dose group (intraperitoneally injected with CQ prescription 100 mg•kg⁻¹ on the basis of model mice), CQ prescription middle dose group (intraperitoneally injected with CQ prescription 150 mg•kg⁻¹ on the basis of model mice), and CQ prescription high dose group (intraperitoneally injected with CQ prescription 200 mg•kg⁻¹ on the basis of model mice). Mechanical withdraw threshold (MWT) of the mirror image lateral hind paws were evaluated by Von Frey hairs before modeling and after surgery. The levels of glutamate (Glu), gamma aminobutyric acid (GABA), glycine (Gly), and taurine (Tau) in the L3-L5 spinal cord were measured by the high performance liquid chromatography-fluorescence detector (HPLC-FLD); AimPlex detection technology with multiple factors was used to detect the levels of regulated on activation in normal T-cell expressed and secreted (RANTES), monocyte chemoattractant protein (MCP-3) in the L3-L5 spinal cord. Then we observed the influence of GABAa receptor antagonist (Bicuculline) on analgesic effect of CQ prescription.The results indicated that CQ prescription could remarkably increase MWT of model mice(P<0.01, P<0.05), decrease the level of Glu(P<0.01, P<0.05), improve the levels of GABA, Gly, Tau(P<0.01, P<0.05), lower the ratio of Glu/GABA(P<0.01, P<0.05), and reduce the levels of RANTES, MCP-3(P<0.05) in the L3-L5 spinal cord, and GABAa receptor antagonist significantly blocked the analgesic effect of CQ prescription at two time points(P<0.05).This study showed that CQ prescription had significant analgesic effect on CIIMIP model mice, and its mechanism was associated with regulating the balance between excitability amino acid(EAA) and inhibitory amino acid (IAA) transmitters in central nervous system, partially activating GABAa receptor, and reducing the release of RANTES and MCP-3 in the spinal cord., Competing Interests: The authors of this article and the planning committee members and staff have no relevant financial relationships with commercial interests to disclose., (Copyright© by the Chinese Pharmaceutical Association.)

Many-body effects are required for an accurate description of both structure and dynamics of large chemical systems. However, there are numerous such interactions to consider, and it is not obvious which ones are significant. We provide a general and fast method for establishing which small set of three- and four-body interactions are important. This is achieved by estimating the maximum many-body effects, ϵ max , that can arise in a given arrangement of bodies. Through careful analysis of ϵ max , we find two overall causes for significant many-body interactions. First, many-body induction propagates in nonbranching paths, that is, in a chain-like manner. Second, linear arrangements of bodies promote the alignment of the dipoles to reinforce the many-body interaction. Consequently, compact and extended linear arrangements are favored. The latter result is not intuitive as these linear arrangements can lead to significant many-body effects extending over large distances. For the first time, this study provides a rigorous explanation as to how cooperative effects provide enhanced stability in helices making them one of the most common structures in biomolecules. Not only do these helices promote linear dipole alignment, but their chain-like structure is consistent with the way many-body induction propagates. Finally, using ϵ max to screen for significant many-body interactions, we are able to reproduce the total three- and four-body interaction energies using a small number of individual many-body interactions.

The basis set superposition effect (BSSE) arises in electronic structure calculations of molecular clusters when questions relating to interactions between monomers within the larger cluster are asked. The binding energy, or total energy, of the cluster may be broken down into many smaller subcluster calculations and the energies of these subsystems linearly combined to, hopefully, produce the desired quantity of interest. Unfortunately, BSSE can plague these smaller fragment calculations. In this work, we carefully examine the major sources of error associated with reproducing the binding energy and total energy of a molecular cluster. In order to do so, we decompose these energies in terms of a many-body expansion (MBE), where a "body" here refers to the monomers that make up the cluster. In our analysis, we found it necessary to introduce something we designate here as a many-ghost many-body expansion (MGMBE). The work presented here produces some surprising results, but perhaps the most significant of all is that BSSE effects up to the order of truncation in a MBE of the total energy cancel exactly. In the case of the binding energy, the only BSSE correction terms remaining arise from the removal of the one-body monomer total energies. Nevertheless, our earlier work indicated that BSSE effects continued to remain in the total energy of the cluster up to very high truncation order in the MBE. We show in this work that the vast majority of these high-order many-body effects arise from BSSE associated with the one-body monomer total energies. Also, we found that, remarkably, the complete basis set limit values for the three-body and four-body interactions differed very little from that at the MP2/aug-cc-pVDZ level for the respective subclusters embedded within a larger cluster.

The first attempt to describe water dates back to 1933 with the Bernal-Fowler model and it would take another forty years before the first computer simulation of liquid water by Barker and Watts in 1969. Since then, over a hundred different water models have been proposed. Despite being widely studied, water remains poorly understood. Examining the evolution of water models, we identified three distinct philosophies in water modelling, namely the employment of effective point charges in pioneering empirical models, the incorporation of polarization to describe many-body inductive effects and the extensive use of ab initio calculations to describe short-range effects. In doing so, we can appraise the current understanding of water and identify attributes that a water model should possess to capture the intricate interactions between water molecules.

Longstanding conventional wisdom dictates that the widely used Many-Body Expansion (MBE) converges rapidly by the four-body term when applied to large chemical systems. We have found, however, that this is not true for calculations using many common, moderate-sized basis sets such as 6-311++G** and aug-cc-pVDZ. Energy calculations performed on water clusters using these basis sets showed a deceptively small error when the MBE was truncated at the three-body level, while inclusion of four- and five-body contributions drastically increased the error. Moreover, the error per monomer increases with system size, showing that the MBE is unsuitable to apply to large chemical systems when using these basis sets. Through a systematic study, we identified the cause of the poor MBE convergence to be a many-body basis set superposition effect exacerbated by diffuse functions. This was verified by analysis of MO coefficients and the behavior of the MBE with increasing monomer-monomer separation. We also found poor convergence of the MBE when applied to valence-bonded systems, which has implications for molecular fragmentation methods. The findings in this work suggest that calculations involving the MBE must be performed using the full-cluster basis set, using basis sets without diffuse functions, or using a basis set of at least aug-cc-pVTZ quality.

Here we present a new energy-based fragmentation method that is based on our previous work and combines the best elements of other energy-based fragmentation methods. Our new approach, termed "combined fragmentation method", is foremost simple to implement, robust, accurate, and produces small fragments, which are independent of conformation and size of the target molecule. Essentially small collections of bonded atoms in the target molecule are assigned to groups. Fragment molecules are formed by taking all bonded pairs of these groups. These fragments are then interacted with one another, and the interaction energy is simply added to the initial fragmentation energy. The method has been tested on numerous molecules of biological interest both in vacuum and in a continuum solvent.

Objectives: The present study aimed to investigate whether salidroside can induce differentiation of rat mesenchymal stem cells (rMSCs) towards hepatocytes in vitro and the mechanism of hepatic differentiation of rMSCs., Methods: rMSCs were subject to hepatic differentiation. One, two and three weeks later, the expression of alpha fetoprotein (AFP) and albumin (ALB), cytochrome P450 (CYP450)-dependent activity and inducibility, cellular uptake of low density lipoprotein (LDL) and urea synthesis were assessed and the hepatic differentiation of rMSCs was evaluated. In order to unravel the mechanism of hepatic differentiation of rMSCs in vitro, inhibitors of extracellular regulated kinase1/2 (ERK1/2), phosphatidylinositol 3-kinase (PI3K) and p38 were applied. When the process of hepatic differentiation was completed, special proteins of hepatic differentiation were detected and blocking of inhibitors was evaluated., Key Findings: Salidroside significantly induce differentiation of rMSCs towards hepatocytes. Differentiated rMSCs have typical functional hepatic characteristics. The results also showed that the ERK1/2 and PI3K signalling pathways play important roles in the regulatory effects of salidroside on hepatic differentiation of rMSCs and are involved in cell fate determinations, while the p38 signalling pathway does not., Conclusions: Salidroside can induce differentiation of rMSCs towards hepatocytes in vivo, and the ERK1/2 or PI3K signalling pathway underlie the process of hepatic differentiation.