Hierarchical cell-type identifier accurately distinguishes immune-cell subtypes enabling precise profiling of tissue microenvironment with single-cell RNA-sequencing.

Single-cell RNA-seq enabled in-depth study on tissue micro-environment and immune-profiling, where a crucial step is to annotate cell identity. Immune cells play key roles in many diseases, whereas their activities are hard to track due to their diverse and highly variable nature. Existing cell-type identifiers had limited performance for this purpose. We present HiCAT, a hierarchical, marker-based cell-type identifier utilising gene set analysis for statistical scoring for given markers. It features successive identification of major-type, minor-type and subsets utilising subset markers structured in a three-level taxonomy tree. Comparison with manual annotation and pairwise match test showed HiCAT outperforms others in major- and minor-type identification. For subsets, we qualitatively evaluated the marker expression profile demonstrating that HiCAT provide the clearest immune-cell landscape. HiCAT was also used for immune-cell profiling in ulcerative colitis and discovered distinct features of the disease in macrophage and T-cell subsets that could not be identified previously.

Sodium-assisted passivation of grain boundaries and defects in Cu2ZnSnSe4 thin films.

The long stagnation of the photo-conversion efficiency of kesterites below 13% is a source of frustration in the scientific community. In this study, we investigated the effects of sodium on the passivation of grain boundaries and defects in Cu2ZnSnSe4 (CZTSe) grown on a soda-lime glass (SLG) and borosilicate (BS) glass. Because BS glass does not inherently contain sodium, we placed a thin layer of NaF between CZTSe and Mo. The composition of the samples is Cu-poor and Zn-rich. The distribution of sodium and its contributions to phase formation and defects were examined by cross-sectional energy-dispersive X-ray profiling, Raman scattering spectroscopy and imaging, surface potential and photoluminescence. From the experimental results, it can be strongly claimed that sodium ions segregate predominantly near the grain boundaries and reduce CuZn-related defects. These local surface imaging analyses provided the exact locations of the secondary phases. In particular, the photo-assisted scanning probe method enabled us to observe the changes in the optoelectrical properties of the thin films and the carrier behavior within the materials. Further studies with distinct alkali ions and optimal processing conditions will pave a way to improve the performance of kesterite solar cells.

TraRECo: a greedy approach based de novo transcriptome assembler with read error correction using consensus matrix.

BACKGROUND: The challenges when developing a good de novo transcriptome assembler include how to deal with read errors and sequence repeats. Almost all de novo assemblers utilize a de Bruijn graph, with which complexity grows linearly with data size while suffering from errors and repeats. Although one can correct the errors by inspecting the topological structure of the graph, this is not an easy task when there are too many branches. Two research directions are to improve either the graph reliability or the path search precision, and in this study, we focused on the former. RESULTS: We present TraRECo, a greedy approach to de novo assembly employing error-aware graph construction. In the proposed approach, we built contigs by direct read alignment within a distance margin and performed a junction search to construct splicing graphs. While doing so, a contig of length l was represented by a 4 × l matrix (called a consensus matrix), in which each element was the base count of the aligned reads so far. A representative sequence was obtained by taking the majority in each column of the consensus matrix to be used for further read alignment. Once the splicing graphs had been obtained, we used IsoLasso to find paths with a noticeable read depth. The experiments using real and simulated reads show that the method provided considerable improvement in sensitivity and moderately better performance when comparing sensitivity and precision. This was achieved by the error-aware graph construction using the consensus matrix, with which the reads having errors were made usable for the graph construction (otherwise, they might have been eventually discarded). This improved the quality of the coverage depth information used in the subsequent path search step and finally the reliability of the graph. CONCLUSIONS: De novo assembly is mainly used to explore undiscovered isoforms and must be able to represent as many reads as possible in an efficient way. In this sense, TraRECo provides us with a potential alternative for improving graph reliability even though the computational burden is much higher than the single k-mer in the de Bruijn graph approach.

Sulfur-doped graphene as a potential alternative metal-free electrocatalyst and Pt-catalyst supporting material for oxygen reduction reaction.

In this study, sulfur-doped graphene (S-graphene) was synthesized by thermal treatment of exfoliated graphene under CS2 gas flow. Its electrocatalytic activity as a metal-free catalyst was evaluated and compared with other doped-graphenes and commercial platinum nanoparticles loaded on carbon black (Pt/C) catalysts for oxygen reduction reaction (ORR) in fuel cell cathodes. The resultant S-graphene was shown to act as a viable catalyst for ORR and its limiting current density and durability were improved compared to those of the commercial Pt/C catalyst. The current density at -1.0 V for the commercial Pt/C catalyst, pristine graphene, nitrogen-doped graphene (N-graphene) and S-graphene was 4.7, 0.15, 6.26 and 6.99 mA cm(-2), respectively. The durability of S-graphene (70.3%) was much better compared to commercial Pt/C (37.2%) and N-graphene (67.9%). When S-graphene was used as a supporting material for Pt nanoparticles, its catalytic performance was significantly higher than other Pt catalysts supported on different doped graphenes. Here, we demonstrate that S-graphene can be used as a novel graphene-based efficient metal-free ORR catalyst in fuel cells.

A Retrospective View of the Triple-Negative Breast Cancer Microenvironment: Novel Markers, Interactions, and Mechanisms of Tumor-Associated Components Using Public Single-Cell RNA-Seq Datasets.

Triple-negative breast cancer (TNBC) is a significant clinical challenge due to its aggressive nature and limited treatment options. In search of new treatment targets, not only single genes but also gene pairs involved in protein interactions, we explored the tumor microenvironment (TME) of TNBC from a retrospective point of view, using public single-cell RNA sequencing datasets. A High-resolution Cell type Annotation Tool, HiCAT, was used first to identify the cell type in 3-level taxonomies. Tumor cells were then identified based on the estimates of copy number variation. With the annotation results, differentially expressed genes were analyzed to find subtype-specific markers for each cell type, including tumor cells, fibroblast, and macrophage. Cell-cell interactions were also inferred for each cell type pair. Through integrative analysis, we could find unique TNBC markers not only for tumor cells but also for various TME components, including fibroblasts and macrophages. Specifically, twelve marker genes, including DSC2 and CDKN2A, were identified for TNBC tumor cells. Another key finding of our study was the interaction between the DSC2 and DSG2 genes among TNBC tumor cells, suggesting that they are more tightly aggregated with each other than those of other subtypes, including normal epithelial cells. The overexpression of DSC2 in TNBC and its prognostic power were verified by using METABRIC, a large bulk RNA-seq dataset with clinical information. These findings not only corroborate previous hypotheses but also lay the foundation for a new structural understanding of TNBC, as revealed through our single-cell analysis workflow.

Thermal activation energy on electrical degradation process in BaTiO3 based multilayer ceramic capacitors for lifetime reliability.

For a high capacitance and high lifetime reliability of multilayer ceramic capacitors for automotive applications, the activation energy on thermal activation process can typically be calculated by using Arrhenius based Prokopowicz-Vaskas equation as a method for lifetime prediction. In this study, it is clearly observed that the activation energy shows to be constant in the range of ~ 1.5 eV for the prototype MLCCs, higher than the activation energy values of ~ 1.0 eV related to the motion or diffusion of oxygen vacancies reported in the previous literature. The activation energy value of ~ 1.5 eV for three prototype MLCCs is close to a half the energy band gap (Eg/2 ≈ 1.6 eV) of BaTiO3 obtained from specific environment, where oxygen vacancies are stabilized by external containment such as the effect of rare earth oxide additives. Due to an obvious difference in activation energy values, it difficult to explain the conduction mechanism for failure by only oxygen vacancy migration. Therefore, the concepts of electronic processes and oxygen vacancy should be considered together to understand conduction mechanism for failure of BaTiO3-based MLCCs in thermal activation processes. It can be useful as an indicator for future MLCC development with high lifetime reliability.

Integrative analysis of single-cell RNA-seq and gut microbiome metabarcoding data elucidates macrophage dysfunction in mice with DSS-induced ulcerative colitis.

Ulcerative colitis (UC) is a significant inflammatory bowel disease caused by an abnormal immune response to gut microbes. However, there are still gaps in our understanding of how immune and metabolic changes specifically contribute to this disease. Our research aims to address this gap by examining mouse colons after inducing ulcerative colitis-like symptoms. Employing single-cell RNA-seq and 16 s rRNA amplicon sequencing to analyze distinct cell clusters and microbiomes in the mouse colon at different time points after induction with dextran sodium sulfate. We observe a significant reduction in epithelial populations during acute colitis, indicating tissue damage, with a partial recovery observed in chronic inflammation. Analyses of cell-cell interactions demonstrate shifts in networking patterns among different cell types during disease progression. Notably, macrophage phenotypes exhibit diversity, with a pronounced polarization towards the pro-inflammatory M1 phenotype in chronic conditions, suggesting the role of macrophage heterogeneity in disease severity. Increased expression of Nampt and NOX2 complex subunits in chronic UC macrophages contributes to the inflammatory processes. The chronic UC microbiome exhibits reduced taxonomic diversity compared to healthy conditions and acute UC. The study also highlights the role of T cell differentiation in the context of dysbiosis and its implications in colitis progression, emphasizing the need for targeted interventions to modulate the inflammatory response and immune balance in colitis.

Controlling Surface Structure and Primary Particle Size to Enhance Performance and Reduce Gas Evolution in Lithium- and Manganese-Rich Layered Oxide Cathodes.

Practical application of lithium- and manganese-rich layered oxide cathodes has been hindered despite their high performance and low cost owing to high gas evolution accompanying capacity loss even in a conservative voltage window. Here, we control the surface structure and primary particle size of lithium- and manganese-rich layered oxide cathodes not only to enhance the electrochemical performance but also to reduce gas evolution. Sulfur-coated Fm3̅m/R3̅m double reduced surface layers and Mo doping dramatically reduce gas evolution, which entails the improvement of electrochemical performance. With the optimization, we prove that it is competitive enough to conventional high-nickel cathodes in the aspects of gas evolution as well as electrochemical performance in the conservative voltage window of 2.5-4.4 V. Our findings provide invaluable insights on the improvement of electrochemical performance and gas evolution properties in lithium- and manganese-rich layered oxide cathodes.

StringFix: an annotation-guided transcriptome assembler improves the recovery of amino acid sequences from RNA-Seq reads.

BACKGROUND: Reconstruction of amino acid sequences from assembled transcriptome is of interest in personalized medicine, for example, to predict drug-target (or protein-protein) interaction considering individual's genomic variations. Most of the existing transcriptome assemblers, however, seems not well suited for this purpose. METHODS: In this work, we present StringFix, an annotation guided transcriptome assembly and protein sequence reconstruction software tool that takes genome-aligned reads and the annotations associated to the reference genome as input. The tool 'fixes' the pre-annotated transcript sequence by taking small variations into account, finally to produce possible amino acid sequences that are likely to exist in the test tissue. RESULTS: The results show that, using outputs from existing reference-based assemblers as the input GTF-guide, StringFix could reconstruct amino acid sequences more precisely with higher sensitivity than direct generation using the recovered transcripts from all the assemblers we tested. CONCLUSION: By using StringFix with the existing reference-based assemblers, one can recover not only a novel transcripts and isoforms but also the possible amino acid sequence stemming from them.

Role of lymphoid lineage cells aberrantly expressing alarmins S100A8/A9 in determining the severity of COVID-19.

BACKGROUND: Alarmins S100A8 and S100A9 are recognized as hallmarks of severe COVID-19 and are primarily produced in myeloid cells, such as monocytes and neutrophils. As single-cell RNA-sequencing (scRNA-seq) data from patients with COVID-19 revealed the expression of S100A8/A9 in lymphoid cells in patients with severe COVID-19. OBJECTIVE: We investigated the characteristics of lymphoid cells expressing S100A8/A9 in COVID-19 patients. METHODS: Publicly available scRNA-seq data from patients with mild (N = 12) or severe (N = 7) COVID-19 were reanalyzed. The data were further divided into the following two groups based on the time of sample collection (from infection-onset): within 6 days (early phase) and after 6 days (late phase). Differential expression and gene set enrichment analyses were performed between S100A8/A9High and S100A8/A9Low lymphoid cells. Finally, cell-cell interaction analysis was performed to investigate the role of lymphoid cells expressing high levels of S100A8/A9 in COVID-19. RESULTS: S100A8/A9 overexpression was observed in lymphoid cells, including B cells, T cells, and NK cells, in patients with severe COVID-19 (compared to patients with mild COVID-19). Cells exhibiting strong interferon/cytokine responses were found to be associated with the severity of COVID-19. Furthermore, differences in S100A8/A9-TLR4/RAGE interactions were confirmed between patients with severe and mild disease. CONCLUSIONS: Lymphoid cells overexpressing S100A8/A9 contribute to the dysregulation of the innate immune response in patients with severe COVID-19, specifically during the early phase of infection. This study fosters a better understanding of the hyper-induction of pro-inflammatory cytokine expression and the generation of a cytokine storm in response to COVID-19 infection.

Identification of ulcerative colitis-specific immune cell signatures from public single-cell RNA-seq data.

BACKGROUND: Single-cell RNA-seq enabled microscopic studies on tissue microenvironment of many diseases. Inflammatory bowel disease, an autoimmune disease, is involved with various dysfunction of immune cells, for which single-cell RNA-seq may provide us a deeper insight into the causes and mechanism of this complex disease. OBJECTIVE: In this work, we used public single-cell RNA-seq data to study tissue microenvironment around ulcerative colitis, an inflammatory bowel disease causing chronic inflammation and ulcers in large intestine. METHODS: Since not all the datasets provide cell-type annotations, we first identified cell identities to select cell populations of our interest. Differentially expressed genes and gene set enrichment analysis was then performed to infer the polarization/activation state of macrophages and T cells. Cell-to-cell interaction analysis was also performed to discover distinct interactions in ulcerative colitis. RESULTS: Differentially expressed genes analysis of the two datasets confirmed the regulation of CTLA4, IL2RA, and CCL5 genes in the T cell subset and regulation of S100A8/A9, CLEC10A genes in macrophages. Cell-to-cell interaction analysis showed CD4+ T cells and macrophages interact actively to each other. We also identified IL-18 pathway activation in inflammatory macrophages, evidence that CD4+ T cells induce Th1 and Th2 differentiation, and also found that macrophages regulate T cell activation through different ligand-receptor pairs, viz. CD86-CTL4, LGALS9-CD47, SIRPA-CD47, and GRN-TNFRSF1B. CONCLUSION: Analysis of these immune cell subsets may suggest novel strategies for the treatment of inflammatory bowel disease.

Inhibition of CD82 improves colitis by increasing NLRP3 deubiquitination by BRCC3.

CD82 is a transmembrane protein that is involved in cancer suppression and activates immune cells; however, information on the NLRP3 inflammasome is limited. Herein, we show that although CD82 suppressed the activation of the NLRP3 inflammasome in vivo and in vitro, CD82 deficiency decreased the severity of colitis in mice. Furthermore, two binding partners of CD82, NLRP3 and BRCC3, were identified. CD82 binding to these partners increased the degradation of NLRP3 by blocking BRCC3-dependent K63-specific deubiquitination. Previous studies have shown that CD82-specific bacteria in the colon microbiota called Bacteroides vulgatus (B. vulgatus) regulated the expression of CD82 and promoted the activation of the NLRP3 inflammasome. Accordingly, we observed that B. vulgatus administration increased mouse survival by mediating CD82 expression and activating NLRP3 in mice with colitis. Overall, this study showed that CD82 suppression reduced the pathogenesis of colitis by elevating the activation of the NLRP3 inflammasome through BRCC3-dependent K63 deubiquitination. Based on our findings, we propose that B. vulgatus is a novel therapeutic candidate for colitis.

MarkerCount: A stable, count-based cell type identifier for single-cell RNA-seq experiments.

Cell type identification is a key step toward downstream analysis of single cell RNA-seq experiments. Although the primary objective is to identify known cell populations, good identifiers should also recognize unknown clusters which may represent a previously unidentified subpopulation of a known cell type or tumor cells of an unknown phenotype. Herein, we present MarkerCount, which utilizes the number of expressed markers, regardless of their expression level. MarkerCount works in both reference- and marker-based mode, where the latter utilizes existing lists of markers, while the former uses a pre-annotated dataset to find markers to be used for cell type identification. In both modes, MarkerCount first utilizes the "marker count" to identify cell populations and, after rejecting uncertain cells, reassigns cell type and/or makes corrections in cluster-basis. The performance of MarkerCount was evaluated and compared with existing identifiers, both marker- and reference-based, that can be customized using publicly available datasets and marker databases. The results show that MarkerCount performs better in the identification of known populations as well as of unknown ones, when compared to other reference- and marker-based cell type identifiers for most of the datasets analyzed.

Exciton Transfer at Heterointerfaces of MoS2 Monolayers and Fluorescent Molecular Aggregates.

Integration of distinct materials to form heterostructures enables the proposal of new functional devices based on emergent physical phenomena beyond the properties of the constituent materials. The optical responses and electrical transport characteristics of heterostructures depend on the charge and exciton transfer (CT and ET) at the interfaces, determined by the interfacial energy level alignment. In this work, heterostructures consisting of aggregates of fluorescent molecules (DY1) and 2D semiconductor MoS2 monolayers are fabricated. Photoluminescence spectra of DY1/MoS2 show quenching of the DY1 emission and enhancement of the MoS2 emission, indicating a strong electronic interaction between these two materials. Nanoscopic mappings of the light-induced contact potential difference changes rule out the CT process at the interface. Using femtosecond transient absorption spectroscopy, the rapid interfacial ET process from DY1 aggregates to MoS2 and a fourfold extension of the exciton lifetime in MoS2 are elucidated. These results suggest that the integration of 2D inorganic semiconductors with fluorescent molecules can provide versatile approaches to engineer the physical characteristics of materials for both fundamental studies and novel optoelectronic device applications.

Colon-Targeted eNAMPT-Specific Peptide Systems for Treatment of DSS-Induced Acute and Chronic Colitis in Mouse.

Nicotinamide phosphoribosyl transferase (NAMPT) is required to maintain the NAD+ pool, among which extracellular (e) NAMPT is associated with inflammation, mainly mediated by macrophages. However, the role of (e) NAMPT in inflammatory macrophages in ulcerative colitis is insufficiently understood. Here our analyses of single-cell RNA-seq data revealed that the levels of NAMPT and CYBB/NOX2 in macrophages were elevated in patients with colitis and in mouse models of acute and chronic colitis. These findings indicate the clinical significance of NAMPT and CYBB in colitis. Further, we found that eNAMPT directly binds the extracellular domains of CYBB and TLR4 in activated NLRP3 inflammasomes. Moreover, we developed a recombinant 12-residue TK peptide designated colon-targeted (CT)-conjugated multifunctional NAMPT (rCT-NAMPT), comprising CT as the colon-targeting moiety, which harbors the minimal essential residues required for CYBB/TLR4 binding. rCT-NAMPT effectively suppressed the severity of disease in DSS-induced acute and chronic colitis models through targeting the colon and inhibiting the interaction of NAMPT with CYBB or TLR4. Together, our data show that rCT-NAMPT may serve as an effective novel candidate therapeutic for colitis by modulating the NLRP3 inflammasome-mediated immune signaling system.

Machine learning based anti-cancer drug response prediction and search for predictor genes using cancer cell line gene expression.

Although many models have been proposed to accurately predict the response of drugs in cell lines recent years, understanding the genome related to drug response is also the key for completing oncology precision medicine. In this paper, based on the cancer cell line gene expression and the drug response data, we established a reliable and accurate drug response prediction model and found predictor genes for some drugs of interest. To this end, we first performed pre-selection of genes based on the Pearson correlation coefficient and then used ElasticNet regression model for drug response prediction and fine gene selection. To find more reliable set of predictor genes, we performed regression twice for each drug, one with IC50 and the other with area under the curve (AUC) (or activity area). For the 12 drugs we tested, the predictive performance in terms of Pearson correlation coefficient exceeded 0.6 and the highest one was 17-AAG for which Pearson correlation coefficient was 0.811 for IC50 and 0.81 for AUC. We identify common predictor genes for IC50 and AUC, with which the performance was similar to those with genes separately found for IC50 and AUC, but with much smaller number of predictor genes. By using only common predictor genes, the highest performance was AZD6244 (0.8016 for IC50, 0.7945 for AUC) with 321 predictor genes.

High speed growth of MAPbBr3 single crystals via low-temperature inverting solubility: enhancement of mobility and trap density for photodetector applications.

There has been growing interest in organic-inorganic hybrid perovskites as a promising candidate for optoelectronic applications due to their superior physical properties. Despite this, most of the reported perovskite devices based on polycrystalline thin films suffer immensely from poor stability and high trap density owing to grain boundaries limiting their performance. Perovskite single crystal structures have been recently explored to construct stable devices and reduce the trap density compared to their thin-film counterparts. We present a novel method of growing sizable CH3NH3PbBr3 single crystals based on the high solubility characteristic of hybrid perovskites at low temperatures within inverse temperature crystallization. We compared both the crystallinity of perovskite single crystal structures and optoelectronic charge transport of single crystal photodetectors as a function of dissolution temperature. The performance of the photodetector fabricated with our large-scaled single crystal with high quality demonstrated low trap density, high mobility, and high photoresponse.

Enhanced optical absorption in conformally grown MoS2 layers on SiO2/Si substrates with SiO2 nanopillars with a height of 50 nm.

The integration of transition metal dichalcogenide (TMDC) layers on nanostructures has attracted growing attention as a means to improve the physical properties of the ultrathin TMDC materials. In this work, the influence of SiO2 nanopillars (NPs) with a height of 50 nm on the optical characteristics of MoS2 layers is investigated. Using a metal organic chemical vapor deposition technique, a few layers of MoS2 were conformally grown on the NP-patterned SiO2/Si substrates without notable strain. The photoluminescence and Raman intensities of the MoS2 layers on the SiO2 NPs were larger than those observed from a flat SiO2 surface. For 100 nm-SiO2/Si wafers, the 50 nm-NP patterning enabled improved absorption in the MoS2 layers over the whole visible wavelength range. Optical simulations showed that a strong electric-field could be formed at the NP surface, which led to the enhanced absorption in the MoS2 layers. These results suggest a versatile strategy to realize high-efficiency TMDC-based optoelectronic devices.

Vertically-Oriented WS2 Nanosheets with a Few Layers and Its Raman Enhancements.

Vertically-oriented two-dimensional (2D) tungsten disulfide (WS2) nanosheets were successfully grown on a Si substrate at a temperature range between and 550 °C via the direct chemical reaction between WCl6 and S in the gas phase. The growth process was carefully optimized by adjusting temperature, the locations of reactants and substrate, and carrier gas flow. Additionally, vertically-oriented 2D WS2 nanosheets with a few layers were tested as a surface-enhanced Raman scattering substrate for detecting rhodamine 6G (R6G) molecules where enhancement occurs from chemical enhancement by charge transfer transition from semiconductor). Raman spectra of R6G molecules adsorbed on vertically-oriented 2D WS2 nanosheets exhibited strong Raman enhancement effects up to 9.2 times greater than that on the exfoliated WS2 monolayer flake sample. From our results, we suggest that the WS2 nanosheets can be an effective surface-enhanced Raman scattering substrate for detecting target molecules.

Hormone Receptor-Status Prediction in Breast Cancer Using Gene Expression Profiles and Their Macroscopic Landscape.

The cost of next-generation sequencing technologies is rapidly declining, making RNA-seq-based gene expression profiling (GEP) an affordable technique for predicting receptor expression status and intrinsic subtypes in breast cancer patients. Based on the expression levels of co-expressed genes, GEP-based receptor-status prediction can classify clinical subtypes more accurately than can immunohistochemistry (IHC). Using data from The Cancer Genome Atlas Breast Invasive Carcinoma (TCGA BRCA) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) datasets, we identified common predictor genes found in both datasets and performed receptor-status prediction based on these genes. By assessing the survival outcomes of patients classified using GEP- or IHC-based receptor status, we compared the prognostic value of the two methods. We found that GEP-based HR prediction provided higher concordance with the intrinsic subtypes and a stronger association with treatment outcomes than did IHC-based hormone receptor (HR) status. GEP-based prediction improved the identification of patients who could benefit from hormone therapy, even in patients with non-luminal breast cancer. We also confirmed that non-matching subgroup classification affected the survival of breast cancer patients and that this could be largely overcome by GEP-based receptor-status prediction. In conclusion, GEP-based prediction provides more reliable classification of HR status, improving therapeutic decision making for breast cancer patients.