Deciphering cell states and genealogies of human haematopoiesis

The human blood system is maintained through the differentiation and massive amplification of a limited number of long-lived haematopoietic stem cells (HSCs)1. Perturbations to this process underlie diverse diseases, but the clonal contributions to human haematopoiesis and how this changes with age remain incompletely understood. Although recent insights have emerged from barcoding studies in model systems2-5, simultaneous detection of cell states and phylogenies from natural barcodes in humans remains challenging. Here we introduce an improved, single-cell lineage-tracing system based on deep detection of naturally occurring mitochondrial DNA mutations with simultaneous readout of transcriptional states and chromatin accessibility. We use this system to define the clonal architecture of HSCs and map the physiological state and output of clones. We uncover functional heterogeneity in HSC clones, which is stable over months and manifests as both differences in total HSC output and biases towards the production of different mature cell types. We also find that the diversity of HSC clones decreases markedly with age, leading to an oligoclonal structure with multiple distinct clonal expansions. Our study thus provides a clonally resolved and cell-state-aware atlas of human haematopoiesis at single-cell resolution, showing an unappreciated functional diversity of human HSC clones and, more broadly, paving the way for refined studies of clonal dynamics across a range of tissues in human health and disease.

Systematic investigation of mitochondrial transfer between cancer cells and T cells at single-cell resolution

Mitochondria (MT) participate in most metabolic activities of mammalian cells. A near-unidirectional mitochondrial transfer from T cells to cancer cells was recently observed to "metabolically empower" cancer cells while "depleting immune cells," providing new insights into tumor-T cell interaction and immune evasion. Here, we leverage single-cell RNA-seq technology and introduce MERCI, a statistical deconvolution method for tracing and quantifying mitochondrial trafficking between cancer and T cells. Through rigorous benchmarking and validation, MERCI accurately predicts the recipient cells and their relative mitochondrial compositions. Application of MERCI to human cancer samples identifies a reproducible MT transfer phenotype, with its signature genes involved in cytoskeleton remodeling, energy production, and TNF-α signaling pathways. Moreover, MT transfer is associated with increased cell cycle activity and poor clinical outcome across different cancer types. In summary, MERCI enables systematic investigation of an understudied aspect of tumor-T cell interactions that may lead to the development of therapeutic opportunities.

Single cell multiomic analysis reveals diabetes-associated β-cell heterogeneity driven by HNF1A

Broad heterogeneity in pancreatic β-cell function and morphology has been widely reported. However, determining which components of this cellular heterogeneity serve a diabetes-relevant function remains challenging. Here, we integrate single-cell transcriptome, single-nuclei chromatin accessibility, and cell-type specific 3D genome profiles from human islets and identify Type II Diabetes (T2D)-associated β-cell heterogeneity at both transcriptomic and epigenomic levels. We develop a computational method to explicitly dissect the intra-donor and inter-donor heterogeneity between single β-cells, which reflect distinct mechanisms of T2D pathogenesis. Integrative transcriptomic and epigenomic analysis identifies HNF1A as a principal driver of intra-donor heterogeneity between β-cells from the same donors; HNF1A expression is also reduced in β-cells from T2D donors. Interestingly, HNF1A activity in single β-cells is significantly associated with lower Na+ currents and we nominate a HNF1A target, FXYD2, as the primary mitigator. Our study demonstrates the value of investigating disease-associated single-cell heterogeneity and provides new insights into the pathogenesis of T2D.

Massively parallel base editing to map variant effects in human hematopoiesis

Systematic evaluation of the impact of genetic variants is critical for the study and treatment of human physiology and disease. While specific mutations can be introduced by genome engineering, we still lack scalable approaches that are applicable to the important setting of primary cells, such as blood and immune cells. Here, we describe the development of massively parallel base-editing screens in human hematopoietic stem and progenitor cells. Such approaches enable functional screens for variant effects across any hematopoietic differentiation state. Moreover, they allow for rich phenotyping through single-cell RNA sequencing readouts and separately for characterization of editing outcomes through pooled single-cell genotyping. We efficiently design improved leukemia immunotherapy approaches, comprehensively identify non-coding variants modulating fetal hemoglobin expression, define mechanisms regulating hematopoietic differentiation, and probe the pathogenicity of uncharacterized disease-associated variants. These strategies will advance effective and high-throughput variant-to-function mapping in human hematopoiesis to identify the causes of diverse diseases.

Environmental damage compensation for illegal solid waste dumping in China

China aims to improve its system for pursuing environmental damage compensation environmental violation cases. To hold violators accountable, China has an effective system for the identification and assessment (I&A) of environmental damage. This study selected a typical case of the illegal dumping of solid waste (IDSW) in China to analyze the causes, the degree, and characteristics of environmental damage, focusing on components such as the physical quantification and valuation of damage. The findings were as follows: (1) Compensation claimants and obligors consider baseline damage confirmation and causality analysis key components of I&A. (2) The I&A process for a specific case needs to focus on key nodes such as the type, location, and duration of IDSW. (3) Restraining IDSW requires accurately quantifying the physical and value-related losses caused by solid waste dumping. (4) In the selected case study, the damage from environmental contamination caused by the IDSW incident amounted to 3938,990 yuan, including an environmental damage value of 3651,990 yuan and a transaction cost of 287,000 yuan. Both parties accepted the I&A calculation process in this case, and the desired punishment effect was achieved. Hence, the case study demonstrated that accurate I&A is the technical basis for environmental damage compensation. Thus, in the future, more attention should be paid to the role of scientific and technological means and knowledge reserves in the I&A of environmental damage.

What Constitutes the High-Quality Soundscape in Human Habitats? Utilizing a Random Forest Model to Explore Soundscape and Its Geospatial Factors Behind

Soundscape is the production of sounds and the acoustic environment, and it emphasizes peoples' perceiving and experiencing process in the context. To this end, this paper focuses on the Pearl River Delta in China, and implements an empirical study based on the soundscape evaluation data from the Participatory Soundscape Sensing (PSS) system, and the geospatial data from multiple sources. The optimal variable set with 24 features are successfully used to establish a random forest model to predict the soundscape comfort of a new site (F1 = 0.61). Results show that the acoustic factors are most important to successfully classify soundscape comfort (averaged relative importance of 17.45), subsequently ranking by built environment elements (11.28), temporal factors (9.59), and demographic factors (9.14), while landscape index (8.60) and land cover type (7.71) seem to have unclear importance. Furthermore, the partial dependence analysis provides the answers about the appropriate threshold or category of various variables to quantitatively or qualitatively specify the necessary management and control metrics for maintaining soundscape quality. These findings suggest that mainstreaming the soundscape in the coupled natural-human systems and clarifying the mechanisms between soundscape perception and geospatial factors can be beneficial to create a high-quality soundscape in human habitats.

Inferring gene regulation from stochastic transcriptional variation across single cells at steady state

Regulatory relationships between transcription factors (TFs) and their target genes lie at the heart of cellular identity and function; however, uncovering these relationships is often labor-intensive and requires perturbations. Here, we propose a principled framework to systematically infer gene regulation for all TFs simultaneously in cells at steady state by leveraging the intrinsic variation in the transcriptional abundance across single cells. Through modeling and simulations, we characterize how transcriptional bursts of a TF gene are propagated to its target genes, including the expected ranges of time delay and magnitude of maximum covariation. We distinguish these temporal trends from the time-invariant covariation arising from cell states, and we delineate the experimental and technical requirements for leveraging these small but meaningful cofluctuations in the presence of measurement noise. While current technology does not yet allow adequate power for definitively detecting regulatory relationships for all TFs simultaneously in cells at steady state, we investigate a small-scale dataset to inform future experimental design. This study supports the potential value of mapping regulatory connections through stochastic variation, and it motivates further technological development to achieve its full potential.

Mapping transcriptomic vector fields of single cells

Single-cell (sc)-RNA-seq, together with RNA-velocity and metabolic labeling, reveals cellular states and transitions at unprecedented resolution. Fully exploiting these data, however, requires kinetic models capable of unveiling governing regulatory functions. Here, we introduce an analytical framework dynamo, that infers absolute RNA velocity, reconstructs continuous vector-field functions that predict cell fates, employs differential geometry to extract underlying regulations, and ultimately predicts optimal reprogramming paths and perturbation outcomes. We highlight dynamo’s power to overcome fundamental limitations of conventional splicing-based RNA velocity analyses to enable accurate velocity estimations on a metabolically-labeled human hematopoiesis scRNA-seq dataset. Furthermore, differential geometry analyses reveal mechanisms driving early megakaryocyte appearance and elucidate asymmetrical regulation within the PU.1–GATA1 circuit. Leveraging the Least-Action-Path method, dynamo accurately predicts drivers of numerous hematopoietic transitions. Finally, in silico perturbations predict cell-fate diversions induced by gene perturbations. Dynamo thus represents an important step in advancing quantitative and predictive theories of cell-state transitions.

Variant to function mapping at single-cell resolution through network propagation.. [PMID: 35118467 PMCID: PMC8811900 DOI: 10.1101/2022.01.23.477426] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

With burgeoning human disease genetic associations and single-cell genomic atlases covering a range of tissues, there are unprecedented opportunities to systematically gain insights into the mechanisms of disease-causal variation. However, sparsity and noise, particularly in the context of single-cell epigenomic data, hamper the identification of disease- or trait-relevant cell types, states, and trajectories. To overcome these challenges, we have developed the SCAVENGE method, which maps causal variants to their relevant cellular context at single-cell resolution by employing the strategy of network propagation. We demonstrate how SCAVENGE can help identify key biological mechanisms underlying human genetic variation including enrichment of blood traits at distinct stages of human hematopoiesis, defining monocyte subsets that increase the risk for severe coronavirus disease 2019 (COVID-19), and identifying intermediate lymphocyte developmental states that are critical for predisposition to acute leukemia. Our approach not only provides a framework for enabling variant-to-function insights at single-cell resolution, but also suggests a more general strategy for maximizing the inferences that can be made using single-cell genomic data.

Variant to function mapping at single-cell resolution through network propagation

Genome-wide association studies in combination with single-cell genomic atlases can provide insights into the mechanisms of disease-causal genetic variation. However, identification of disease-relevant or trait-relevant cell types, states and trajectories is often hampered by sparsity and noise, particularly in the analysis of single-cell epigenomic data. To overcome these challenges, we present SCAVENGE, a computational algorithm that uses network propagation to map causal variants to their relevant cellular context at single-cell resolution. We demonstrate how SCAVENGE can help identify key biological mechanisms underlying human genetic variation, applying the method to blood traits at distinct stages of human hematopoiesis, to monocyte subsets that increase the risk for severe Coronavirus Disease 2019 (COVID-19) and to intermediate lymphocyte developmental states that predispose to acute leukemia. Our approach not only provides a framework for enabling variant-to-function insights at single-cell resolution but also suggests a more general strategy for maximizing the inferences that can be made using single-cell genomic data.

Nutritional composition and proteomic analysis of soft-shelled turtle (Pelodiscus sinensis) egg and identification of oligopeptides with alpha-glucosidase inhibitory activity

This study aimed to explore nutritional compositions and proteomics of soft-shelled turtle (SST) egg, as well as identify potential antidiabetic oligopeptides with α-glucosidase inhibitory property. Results revealed that SST egg is a promising source of highly nutritious proteins and minerals (54.64% and 5.81% of dry matter, respectively). Further proteomic analysis showed SST egg proteins contained at least 9 protein families, such as transferrin/iron binding protein and immunoregulation-related protein. Hydrolysis by different enzymes, especially papain, remarkably increased α-glucosidase inhibitory activity and scavenging activity for ABTS, DPPH, hydroxyl and oxygen radicals of SST egg proteins. Peptides from papain hydrolysate were fractionated using ultrafiltration followed by reverse phase chromatography, and 16 peptides were identified in the most active fraction by LC-QTOF-MS/MS. Molecular docking revealed that 14 of these peptides could easily dock into the substrate-binding pocket and/or inhibitor binding sites of α-glucosidase with the docking score below -150 kcal/mol, indicating their potential α-glucosidase inhibitory properties. The five most abundant oligopeptides with potent interaction with α-glucosidase were further synthesized, and oligopeptides HNKPEVEVR, ARDASVLK and SGTLLHK strongly inhibited the activity of α-glucosidase (IC₅₀ of 56, 195 and 289 µmol/L, respectively). Therefore, oligopeptides from enzymatic hydrolysate of SST egg protein exhibit potential antidiabetic activity, making it a promising functional food ingredient.

Different Influences of trans Fatty Acids on the Phospholipase A2 and Arachidonic Acid Metabolic Pathway in Hepatocytes

This study investigated the effects of 9t18:1 (representing I-TFAs), 9t16:1, and 11t18:1 (representing R-TFAs) and their mixtures on the normal human hepatocyte LO2 cell function, the possible mechanism of lipid metabolism by lipidomics, and the relationship between phospholipase A2 (PLA2) and the arachidonic acid (AA) metabolic pathway. Here, we found that the damaging effect of 9t18:1 on the LO2 cell function was significantly greater than those of 11t18:1 and 9t16:1 (p < 0.05), and the damaging effects of CHB and HSO were significantly greater than those of HHB and CM (p < 0.05). The lipidomic results showed that TFAs and TFA mixtures caused a significant change in the lipid profiles of LO2 cells, in which the TAG, PL, and OL contents increased significantly. Moreover, 9t18:1 regulated only the protein expression of cPLA2 but did not participate in the AA metabolic pathway, while 11t18:1 and 9t16:1 participated in the COX-2 and CYP450 pathways, respectively.

Failure to replicate the association of rare loss-of-function variants in type I IFN immunity genes with severe COVID-19

A recent report found that rare predicted loss-of-function (pLOF) variants across 13 candidate genes in TLR3- and IRF7-dependent type I IFN pathways explain up to 3.5% of severe COVID-19 cases. We performed whole-exome or whole-genome sequencing of 1,934 COVID-19 cases (713 with severe and 1,221 with mild disease) and 15,251 ancestry-matched population controls across four independent COVID-19 biobanks. We then tested if rare pLOF variants in these 13 genes were associated with severe COVID-19. We identified only one rare pLOF mutation across these genes amongst 713 cases with severe COVID-19 and observed no enrichment of pLOFs in severe cases compared to population controls or mild COVID-19 cases. We find no evidence of association of rare loss-of-function variants in the proposed 13 candidate genes with severe COVID-19 outcomes.

Single-cell lineage analysis reveals extensive multimodal transcriptional control during directed beta-cell differentiation

The in vitro differentiation of insulin-producing beta-like cells can model aspects of human pancreatic development. Here, we generate 95,308 single-cell transcriptomes and reconstruct a lineage tree of the entire differentiation process from human embryonic stem cells to beta-like cells to study temporally regulated genes during differentiation. We identify so-called 'switch genes' at the branch point of endocrine/non-endocrine cell fate choice, revealing insights into the mechanisms of differentiation-promoting reagents, such as NOTCH and ROCKII inhibitors, and providing improved differentiation protocols. Over 20% of all detectable genes are activated multiple times during differentiation, even though their enhancer activation is usually unimodal, indicating extensive gene reuse driven by different enhancers. We also identify a stage-specific enhancer at the TCF7L2 locus for diabetes, uncovered by genome-wide association studies, that drives a transient wave of gene expression in pancreatic progenitors. Finally, we develop a web app to visualize gene expression on the lineage tree, providing a comprehensive single-cell data resource for researchers studying islet biology and diabetes.

9t18:1 and 11t18:1 activate the MAPK pathway to regulate the expression of PLA2 and cause inflammation in HUVECs

trans fatty acids (TFAs) have been reported to promote vascular diseases mainly by promoting apoptosis and inflammation of vascular endothelial cells. However, it has been reported in recent years that elaidic acid (9t18:1) and vaccenic acid (11t18:1) may have different effects on vascular health. This study investigated the effects of 9t18:1 and 11t18:1 on human umbilical vein endothelial cell (HUVEC) function and the possible mechanism of inflammation by analyzing the changes in the phospholipid composition and the relationship between phospholipase A2 (PLA2) and MAPK pathway. Here we found that the effect of 11t18:1 on cell viability, membrane damage and cellular inflammation was significantly lower than that of 9t18:1 (p < 0.05). And 9t18:1 and 11t18:1 had different effects on phospholipid composition. Both 9t18:1 and 11t18:1 significantly increased the protein expression of PLA2. Moreover, the MAPK pathway regulated the expression of PLA2, inflammatory cytokines and cyclooxygenase-2 (COX-2) and the secretion of prostaglandin E2 (PGE2) in HUVECs induced by 9t18:1 and 11t18:1. In conclusion, 9t18:1 and 11t18:1 activated the MAPK pathway which regulated the expression of PLA2 to cause inflammation in HUVECs.

TWO-SIGMA: A novel two-component single cell model-based association method for single-cell RNA-seq data

In this paper, we develop TWO-SIGMA, a TWO-component SInGle cell Model-based Association method for differential expression (DE) analyses in single-cell RNA-seq (scRNA-seq) data. The first component models the probability of "drop-out" with a mixed-effects logistic regression model and the second component models the (conditional) mean expression with a mixed-effects negative binomial regression model. TWO-SIGMA is extremely flexible in that it: (i) does not require a log-transformation of the outcome, (ii) allows for overdispersed and zero-inflated counts, (iii) accommodates a correlation structure between cells from the same individual via random effect terms, (iv) can analyze unbalanced designs (in which the number of cells does not need to be identical for all samples), (v) can control for additional sample-level and cell-level covariates including batch effects, (vi) provides interpretable effect size estimates, and (vii) enables general tests of DE beyond two-group comparisons. To our knowledge, TWO-SIGMA is the only method for analyzing scRNA-seq data that can simultaneously accomplish each of these features. Simulations studies show that TWO-SIGMA outperforms alternative regression-based approaches in both type-I error control and power enhancement when the data contains even moderate within-sample correlation. A real data analysis using pancreas islet single-cells exhibits the flexibility of TWO-SIGMA and demonstrates that incorrectly failing to include random effect terms can have dramatic impacts on scientific conclusions. TWO-SIGMA is implemented in the R package twosigma available at https://github.com/edvanburen/twosigma.

Efficacy and safety of duloxetine in osteoarthritis or chronic low back pain: a Systematic review and meta-analysis

OBJECTIVE

To evaluate the efficacy and safety of duloxetine in the treatment of patients with osteoarthritis (OA) or chronic low back pain (CLBP).

METHODS

Relevant randomized controlled trials (RCTs) were searched in PubMed, Embase, Web of Science, Cochrane Central Register of Controlled Trials, and ClinicalTrials.gov. Included RCTs compared the efficacy and safety of duloxetine vs placebo in the treatment of OA or CLBP. Weighted mean difference (WMD) were calculated for continuous outcomes while risk ratio (RR) were calculated for dichotomous outcomes.

RESULTS

Nine RCTs were included in our meta-analysis. Duloxetine had significant improvement over placebo in Brief Pain Inventory 24-h average pain [WMD: -0.67; 95% confidence interval (CI):-0.80, -0.53], weekly mean of the 24-h average pain (WMD: -0.65; 95% CI: -0.79, -0.52), Patient's Global Impression of Improvement (WMD: -0.41; 95% CI: -0.49, -0.32), Clinical Global Impression of Severity (WMD: -0.32; 95% CI: -0.38, -0.25), European Quality of Life Questionnaire-5 Dimension (WMD: 0.04; 95% CI: 0.02, 0.07). In addition, duloxetine is associated with more treatment-emergent adverse events (TEAEs) (RR: 1.25; 95% CI: 1.17, 1.33) and discontinuations for adverse events (AEs) (RR: 2.31; 95% CI: 1.81, 2.94). However, there was no statistically significant difference in serious AEs between duloxetine and placebo.

CONCLUSION

Duloxetine had modest to moderate effects on pain relief, function improvement, mood regulation and improvement in quality of life with mild AEs in the treatment of OA or CLBP. Future RCTs should focus on comparing duloxetine with other oral drugs and assessing the long-term safety of duloxetine.

Identification and functional characterization of a hemizygous novel intronic variant in OCRL gene causes Lowe syndrome

BACKGROUND

Lowe syndrome is an X-linked multisystem disorder affecting eyes, nervous system, and kidney. The main causes are mutations in the OCRL gene that encodes a member of the inositol polyphosphate-5-phosphatase protein family. In this study, we aimed to gain new insights into the consequences of a novel OCRL intronic variant on pre-mRNA splicing as a main cause of Lowe syndrome in a boy.

METHODS

After clinical diagnosis of the patient with Lowe syndrome, genetic testing was used to detect the presence of the OCRL variants. In silico analysis, human splicing finder and PyMol were used to predict this variant effect. Then, we analyzed the variant transcript by using a minigene construct in addition to in silico analysis.

RESULTS

A hemizygous novel splicing variant in the intron 10 splice donor site of OCRL (c.939 + 3A > C) was identified in a boy with Lowe syndrome. We detected that the splice junction variant leads to aberrant OCRL mRNA splicing which results in the formation of an alternative transcript in which 29 nucleotides of exon 10 were skipped. The findings obtained from the exon-trapping assay were identical to those of in silico analysis. Hence, the truncated OCRL protein may lacked the last 597 native amino acids.

CONCLUSIONS

The minigene assays detected the same transcript abnormality to in silico assay and were reliable in revealing the pathogenicity of the intronic variant we have used previously. Overall, this study provides new insights about Lowe syndrome and further reveals the molecular pathogenicity mechanism of the intronic variant disease.

Myt Transcription Factors Prevent Stress-Response Gene Overactivation to Enable Postnatal Pancreatic β Cell Proliferation, Function, and Survival

Although cellular stress response is important for maintaining function and survival, overactivation of late-stage stress effectors cause dysfunction and death. We show that the myelin transcription factors (TFs) Myt1 (Nzf2), Myt2 (Myt1l, Nztf1, and Png-1), and Myt3 (St18 and Nzf3) prevent such overactivation in islet β cells. Thus, we found that co-inactivating the Myt TFs in mouse pancreatic progenitors compromised postnatal β cell function, proliferation, and survival, preceded by upregulation of late-stage stress-response genes activating transcription factors (e.g., Atf4) and heat-shock proteins (Hsps). Myt1 binds putative enhancers of Atf4 and Hsps, whose overexpression largely recapitulated the Myt-mutant phenotypes. Moreover, Myt(MYT)-TF levels were upregulated in mouse and human β cells during metabolic stress-induced compensation but downregulated in dysfunctional type 2 diabetic (T2D) human β cells. Lastly, MYT knockdown caused stress-gene overactivation and death in human EndoC-βH1 cells. These findings suggest that Myt TFs are essential restrictors of stress-response overactivity.

Single-Cell Heterogeneity Analysis and CRISPR Screen Identify Key β-Cell-Specific Disease Genes

Identification of human disease signature genes typically requires samples from many donors to achieve statistical significance. Here, we show that single-cell heterogeneity analysis may overcome this hurdle by significantly improving the test sensitivity. We analyzed the transcriptome of 39,905 single islets cells from 9 donors and observed distinct β cell heterogeneity trajectories associated with obesity or type 2 diabetes (T2D). We therefore developed RePACT, a sensitive single-cell analysis algorithm to identify both common and specific signature genes for obesity and T2D. We mapped both β-cell-specific genes and disease signature genes to the insulin regulatory network identified from a genome-wide CRISPR screen. Our integrative analysis discovered the previously unrecognized roles of the cohesin loading complex and the NuA4/Tip60 histone acetyltransferase complex in regulating insulin transcription and release. Our study demonstrated the power of combining single-cell heterogeneity analysis and functional genomics to dissect the etiology of complex diseases.

Zinc Deficiency and Long-Term Outcome in Cases After Isolated Intestinal Transplantation in Taiwan

OBJECTIVES

The small intestine is the primary site for absorption of dietary zinc. Intestinal transplant recipients are at high risk for zinc deficiency because of the long process of posttransplant adaptation. We initiated an intestinal transplant program in Taiwan in 2007. In this study, we aimed to retrospectively investigate the incidence of zinc deficiency in recipients after intestinal transplantation.

METHODS

Twenty-one isolated intestinal transplants were performed in 20 patients with 1 retransplantation. The level of serum zinc was monitored periodically, and zinc supplements were administered when zinc level was below 700 ng/mL. Twelve patients with graft above 1-year survival and with available related data were enrolled for the analysis of zinc deficiency. The levels of serum zinc were tracked, and the protocol of zinc supplementation is discussed herein.

RESULTS

The survival rates of 20 transplant recipients for 1 year, 3 years, and 5 years were 85%, 75%, and 65%, respectively. In the 12 grafts that survived longer than 1 year, we found that zinc deficiency was highest during the third (41.7%) to sixth (50%) month after transplantation. Sustained supplementation of zinc was required for over 70% of patients throughout the 3-year period to maintain their zinc level around the lower normal limit.

CONCLUSION

The outcome of isolated small bowel transplantation is promising. Periodical monitoring and sufficient dosing of zinc supplements should be considered into the posttransplant protocol to prevent zinc deficiency after intestinal transplantation.

Chemical Screening Identifies Enhancers of Mutant Oligodendrocyte Survival and Unmasks a Distinct Pathological Phase in Pelizaeus-Merzbacher Disease

Pelizaeus-Merzbacher disease (PMD) is a fatal X-linked disorder caused by loss of myelinating oligodendrocytes and consequent hypomyelination. The underlying cellular and molecular dysfunctions are not fully defined, but therapeutic enhancement of oligodendrocyte survival could restore functional myelination in patients. Here we generated pure, scalable quantities of induced pluripotent stem cell-derived oligodendrocyte progenitor cells (OPCs) from a severe mouse model of PMD, Plp1jimpy. Temporal phenotypic and transcriptomic studies defined an early pathological window characterized by endoplasmic reticulum (ER) stress and cell death as OPCs exit their progenitor state. High-throughput phenotypic screening identified a compound, Ro 25-6981, which modulates the ER stress response and rescues mutant oligodendrocyte survival in jimpy, in vitro and in vivo, and in human PMD oligocortical spheroids. Surprisingly, increasing oligodendrocyte survival did not restore subsequent myelination, revealing a second pathological phase. Collectively, our work shows that PMD oligodendrocyte loss can be rescued pharmacologically and defines a need for multifactorial intervention to restore myelination.

Enhancing bioethanol production from water hyacinth by new combined pretreatment methods

This study investigated the possibility of enhancing bioethanol production by combined pretreatment methods for water hyacinth. Three different kinds of pretreatment methods, including microbial pretreatment, microbial combined dilute acid pretreatment, and microbial combined dilute alkaline pretreatment, were investigated for water hyacinth degradation. The results showed that microbial combined dilute acid pretreatment is the most effective method, resulting in the highest cellulose content (39.4 ± 2.8%) and reducing sugars production (430.66 mg·g^-1). Scanning Electron Microscopy and Fourier Transform Infrared Spectrometer analysis indicated that the basic tissue of water hyacinth was significantly destroyed. Compared to the other previously reported pretreatment methods for water hyacinth, which did not append additional cellulase and microbes for hydrolysis process, the microbial combined dilute acid pretreatment of our research could achieve the highest reducing sugars. Moreover, the production of bioethanol could achieve 1.40 g·L^-1 after fermentation, which could provide an extremely promising way for utilization of water hyacinth.

Study on Permeability of Porous Ultra-High Molecular Weight Polyethylene (UHMWPE)

In recent years, porous materials are gaining in popularity for engineering applications, due to their special characteristics, such as low density, large specific surface area, and excellent permeability. In this study, powder processing technique was used to prepare ultra-high molecular weight polyethylene UHMWPE porous materials. Sintering temperature was obtained by combining differential scanning calorimetry (DSC) analysis and tensile tests. The surface morphology of sintering necks and tensile fracture were observed by scanning electron microscopy (SEM). Finally, single factor tests and orthogonal experiments were conducted to optimize three main processing parameters for a better permeability. It is found that the proper sintering temperature range would be from 143 to 153.1°C. According to the significance of influence, processing factors come in the sequence of the particle size, the compaction strength and the sintering temperature. Porous materials were successfully prepared, under the optimized parameters as the particle size >250 μm, the compaction strength of 2.5 MPa and the sintering temperature of 152°C.

Clinical Research Informatics for Big Data and Precision Medicine

OBJECTIVES

To reflect on the notable events and significant developments in Clinical Research Informatics (CRI) in the year of 2015 and discuss near-term trends impacting CRI.

METHODS

We selected key publications that highlight not only important recent advances in CRI but also notable events likely to have significant impact on CRI activities over the next few years or longer, and consulted the discussions in relevant scientific communities and an online living textbook for modern clinical trials. We also related the new concepts with old problems to improve the continuity of CRI research.

RESULTS

The highlights in CRI in 2015 include the growing adoption of electronic health records (EHR), the rapid development of regional, national, and global clinical data research networks for using EHR data to integrate scalable clinical research with clinical care and generate robust medical evidence. Data quality, integration, and fusion, data access by researchers, study transparency, results reproducibility, and infrastructure sustainability are persistent challenges.

CONCLUSION

The advances in Big Data Analytics and Internet technologies together with the engagement of citizens in sciences are shaping the global clinical research enterprise, which is getting more open and increasingly stakeholder-centered, where stakeholders include patients, clinicians, researchers, and sponsors.

UBE2S, a novel substrate of Akt1, associates with Ku70 and regulates DNA repair and glioblastoma multiforme resistance to chemotherapy

Glioblastoma multiforme (GBM) is the most common primary malignant brain cancer in adults. However, the molecular events underlying carcinogenesis and their interplay remain elusive. Here, we report that the stability of Ubiquitin-conjugating enzyme E2S (UBE2S) is regulated by the PTEN/Akt pathway and that its degradation depends on the ubiquitin-proteasome system. Mechanistically, Akt1 physically interacted with and phosphorylated UBE2S at Thr 152, enhancing its stability by inhibiting proteasomal degradation. Additionally, accumulated UBE2S was found to be associated with the components of the non-homologous end-joining (NHEJ) complex and participated in the NHEJ-mediated DNA repair process. The association of Ku70 with UBE2S was enhanced, and the complex was recruited to double-stranded break (DSB) sites in response to etoposide treatment. Furthermore, knockdown of UBE2S expression inhibited NHEJ-mediated DSB repair and rendered glioblastoma cells more sensitive to chemotherapy. Overall, our findings provide a novel drug target that may serve as the rationale for the development of a new therapeutic approach.

Optimization of Bioethanol Production Using Whole Plant of Water Hyacinth as Substrate in Simultaneous Saccharification and Fermentation Process

Water hyacinth was used as substrate for bioethanol production in the present study. Combination of acid pretreatment and enzymatic hydrolysis was the most effective process for sugar production that resulted in the production of 402.93 mg reducing sugar at optimal condition. A regression model was built to optimize the fermentation factors according to response surface method in saccharification and fermentation (SSF) process. The optimized condition for ethanol production by SSF process was fermented at 38.87°C in 81.87 h when inoculated with 6.11 ml yeast, where 1.291 g/L bioethanol was produced. Meanwhile, 1.289 g/L ethanol was produced during experimentation, which showed reliability of presented regression model in this research. The optimization method discussed in the present study leading to relatively high bioethanol production could provide a promising way for Alien Invasive Species with high cellulose content.

Mechanisms mediating renal sympathetic nerve activation in obesity-related hypertension

Excessive renal sympathetic nerve activation may be one of the mechanisms underlying obesity-related hypertension. Impaired baroreflex sensitivity, adipokine disorders-such as leptin, adiponectin, and resistin-activation of the renin-angiotensin system, hyperinsulinemia, insulin resistance, and renal sodium retention present in obesity increase renal sympathetic nerve activity, thus contributing to the development of hypertension. Renal sympathetic denervation reduces both renal sympathetic activity and blood pressure in patients with obesity-related hypertension.

A de novo mosaic mutation of PHEX in a boy with hypophosphatemic rickets

X-linked dominant hypophosphatemic rickets (XLHR), is characterized mainly by renal phosphate wasting with hypophosphatemia, short stature and abnormal bone mineralization. PHEX, located at Xp22.1-p22.2, is the gene causing XLHR. We aim to characterize the pathogenesis of a Chinese boy who is apparently 'heterozygous' in PHEX gene. Direct sequencing showed two peaks: one was a wild-type 'G' and the other was one base substitution to 'A', though the patient was a male. TA clone assay clearly showed each sequences and the ratios. The mutation effect was predicted via bioinformatics and validated by exon-trapping assay. Real-time PCR was applied to determine the copy number of PHEX. TA clone assay showed the frequency of normal (G) to mutant allele (A) as 19:13. Normal karyotype and real-time PCR results indicate the normal copy number of PHEX. This splice site mutation leads to 4 bp of exon 18 skipping out causing frame shift p.Gly590Glufs*28 that ends up with a loss of active site and Zn(2+)-binding site of PHEX, which probably interfere with renal phosphate reabsorption and bone mineralization. In conclusion, mutation at conserved splice acceptor site resulted in aberrant splicing, ending up with a damaged protein product. This novel mutation is de novo in mosaic pattern that may be induced during early postzygotic period. Taking mosaic somatic mutation of PHEX into consideration is strongly suggested in genetic counseling and etiology research for XLHR.

Adaptive semantic tag mining from heterogeneous clinical research texts

OBJECTIVES

To develop an adaptive approach to mine frequent semantic tags (FSTs) from heterogeneous clinical research texts.

METHODS

We develop a "plug-n-play" framework that integrates replaceable unsupervised kernel algorithms with formatting, functional, and utility wrappers for FST mining. Temporal information identification and semantic equivalence detection were two example functional wrappers. We first compared this approach's recall and efficiency for mining FSTs from ClinicalTrials.gov to that of a recently published tag-mining algorithm. Then we assessed this approach's adaptability to two other types of clinical research texts: clinical data requests and clinical trial protocols, by comparing the prevalence trends of FSTs across three texts.

RESULTS

Our approach increased the average recall and speed by 12.8% and 47.02% respectively upon the baseline when mining FSTs from ClinicalTrials.gov, and maintained an overlap in relevant FSTs with the base- line ranging between 76.9% and 100% for varying FST frequency thresholds. The FSTs saturated when the data size reached 200 documents. Consistent trends in the prevalence of FST were observed across the three texts as the data size or frequency threshold changed.

CONCLUSIONS

This paper contributes an adaptive tag-mining framework that is scalable and adaptable without sacrificing its recall. This component-based architectural design can be potentially generalizable to improve the adaptability of other clinical text mining methods.

A distribution-based method for assessing the differences between clinical trial target populations and patient populations in electronic health records

OBJECTIVE

To improve the transparency of clinical trial generalizability and to illustrate the method using Type 2 diabetes as an example.

METHODS

Our data included 1,761 diabetes clinical trials and the electronic health records (EHR) of 26,120 patients with Type 2 diabetes who visited Columbia University Medical Center of New-York Presbyterian Hospital. The two populations were compared using the Generalizability Index for Study Traits (GIST) on the earliest diagnosis age and the mean hemoglobin A1c (HbA1c) values.

RESULTS

Greater than 70% of Type 2 diabetes studies allow patients with HbA1c measures between 7 and 10.5, but less than 40% of studies allow HbA1c<7 and fewer than 45% of studies allow HbA1c>10.5. In the real-world population, only 38% of patients had HbA1c between 7 and 10.5, with 12% having values above the range and 52% having HbA1c<7. The GIST for HbA1c was 0.51. Most studies adopted broad age value ranges, with the most common restrictions excluding patients >80 or <18 years. Most of the real-world population fell within this range, but 2% of patients were <18 at time of first diagnosis and 8% were >80. The GIST for age was 0.75.

CONCLUSIONS

We contribute a scalable method to profile and compare aggregated clinical trial target populations with EHR patient populations. We demonstrate that Type 2 diabetes studies are more generalizable with regard to age than they are with regard to HbA1c. We found that the generalizability of age increased from Phase 1 to Phase 3 while the generalizability of HbA1c decreased during those same phases. This method can generalize to other medical conditions and other continuous or binary variables. We envision the potential use of EHR data for examining the generalizability of clinical trials and for defining population-representative clinical trial eligibility criteria.

Microchannel Deformation of Polymer Chip in In-Mold Bonding

Microchannel deformation is a problem which often occurs in the thermal bonding of polymer microfluidic chip, and which is significantly determined by bonding parameters. In this paper, numerical analysis of the microchannel deformation in the process of in-mold bonding polymer chip was conducted, using Young's modulus and shear relaxation modulus of polymethylmethacrylate (PMMA) obtained in creep tests. Adhesion between the top and two lateral walls of microchannel was observed in the results, which can be attributed mainly to the viscoelastic deformation of PMMA. It was also revealed that the maximum percent deformation of microchannel is in height, and that bonding temperature had greater effect on the deformation of microchannel than bonding pressure and bonding time. The deformation of microchannel in simulation were consistent with those of experiment under the optimized parameters of 105 °C, 2 MPa and 240 s.

Feasibility of feature-based indexing, clustering, and search of clinical trials. A case study of breast cancer trials from ClinicalTrials.gov

BACKGROUND

When standard therapies fail, clinical trials provide experimental treatment opportunities for patients with drug-resistant illnesses or terminal diseases. Clinical Trials can also provide free treatment and education for individuals who otherwise may not have access to such care. To find relevant clinical trials, patients often search online; however, they often encounter a significant barrier due to the large number of trials and in-effective indexing methods for reducing the trial search space.

OBJECTIVES

This study explores the feasibility of feature-based indexing, clustering, and search of clinical trials and informs designs to automate these processes.

METHODS

We decomposed 80 randomly selected stage III breast cancer clinical trials into a vector of eligibility features, which were organized into a hierarchy. We clustered trials based on their eligibility feature similarities. In a simulated search process, manually selected features were used to generate specific eligibility questions to filter trials iteratively.

RESULTS

We extracted 1,437 distinct eligibility features and achieved an inter-rater agreement of 0.73 for feature extraction for 37 frequent features occurring in more than 20 trials. Using all the 1,437 features we stratified the 80 trials into six clusters containing trials recruiting similar patients by patient-characteristic features, five clusters by disease-characteristic features, and two clusters by mixed features. Most of the features were mapped to one or more Unified Medical Language System (UMLS) concepts, demonstrating the utility of named entity recognition prior to mapping with the UMLS for automatic feature extraction.

CONCLUSIONS

It is feasible to develop feature-based indexing and clustering methods for clinical trials to identify trials with similar target populations and to improve trial search efficiency.