Single-cell RNA-seq reveals the metabolic status of immune cells response to immunotherapy in triple-negative breast cancer.

Immune checkpoint blockade (ICB) therapy offers promise in the treatment of triple-negative breast cancer (TNBC); however, its limited efficacy in certain TNBC patients poses a challenge. In this study, we elucidated the metabolic mechanism at 'sub-subtype' resolution underlying the non-response to ICB therapy in TNBC. Here, an analytic pipeline was developed to reveal the metabolic heterogeneity, which is correlated with the ICB outcomes, within each immune cell subtype. First, we identified metabolic 'sub-subtypes' within certain cell subtypes, predominantly T cell subsets, which are enriched in ICB non-responders and named as non-responder-enriched (NR-E) clusters. Notably, most of NR-E T metabolic cells exhibit globally higher metabolic activities compared to other cells within the same individual subtype. Further, we investigated the extra-cellular signals that trigger the metabolic status of NR-E T cells. In detail, the prediction of cell-to-cell communication indicated that NR-E T cells are regulated by plasmatic dendritic cells (pDCs) through TNFSF9, as well as by macrophages expressing SIGLEC9. In addition, we also validate the communication between TNFSF9+ pDCs and NR-E T cells utilizing deconvolution of spatial transcriptomics analysis. In summary, our research identified specific metabolic 'sub-subtypes' associated with ICB non-response and uncovered the mechanisms of their regulation in TNBC. And the proposed analytical pipeline can be used to examine metabolic heterogeneity within cell types that correlate with diverse phenotypes.

Prediction of lncRNA-disease association based on a Laplace normalized random walk with restart algorithm on heterogeneous networks.

BACKGROUND: More and more evidence showed that long non-coding RNAs (lncRNAs) play important roles in the development and progression of human sophisticated diseases. Therefore, predicting human lncRNA-disease associations is a challenging and urgently task in bioinformatics to research of human sophisticated diseases. RESULTS: In the work, a global network-based computational framework called as LRWRHLDA were proposed which is a universal network-based method. Firstly, four isomorphic networks include lncRNA similarity network, disease similarity network, gene similarity network and miRNA similarity network were constructed. And then, six heterogeneous networks include known lncRNA-disease, lncRNA-gene, lncRNA-miRNA, disease-gene, disease-miRNA, and gene-miRNA associations network were applied to design a multi-layer network. Finally, the Laplace normalized random walk with restart algorithm in this global network is suggested to predict the relationship between lncRNAs and diseases. CONCLUSIONS: The ten-fold cross validation is used to evaluate the performance of LRWRHLDA. As a result, LRWRHLDA achieves an AUC of 0.98402, which is higher than other compared methods. Furthermore, LRWRHLDA can predict isolated disease-related lnRNA (isolated lnRNA related disease). The results for colorectal cancer, lung adenocarcinoma, stomach cancer and breast cancer have been verified by other researches. The case studies indicated that our method is effective.

A time series representation of protein sequences for similarity comparison.

Based on the physicochemical indexes of 20 amino acids and the Hungarian algorithm, each amino acid was mapped into a vector. And, the protein sequence can be represented as time series in eleven-dimensional space. In addition, the DTW algorithm was applied to calculate the distance between two time series to compare the similarities of protein sequences. The validity and accuracy of this method was illustrated by similarity comparison of ND5 proteins of nine species. Furthermore, homology analysis of eleven ACE2 proteins, which included human, Malayan pangolin and six species of bats, confirmed that the human had shorter evolutionary distance from the pangolin than those bats. The phylogenetic tree of spike protein sequences of 36 coronaviruses, which were divided into five groups, Class I, Class II, Class III, SARS-CoVs and COVID-19, was constructed.

A Generalized Iterative Map for Analysis of Protein Sequences.

AIM AND OBJECTIVE: The similarities comparison of biological sequences is an important task in bioinformatics. The methods of the similarities comparison for biological sequences are divided into two classes: sequence alignment method and alignment-free method. The graphical representation of biological sequences is a kind of alignment-free method, which constitutes a tool for analyzing and visualizing the biological sequences. In this article, a generalized iterative map of protein sequences was suggested to analyze the similarities of biological sequences. MATERIALS AND METHODS: Based on the normalized physicochemical indexes of 20 amino acids, each amino acid can be mapped into a point in 5D space. A generalized iterative function system was introduced to outline a generalized iterative map of protein sequences, which can not only reflect various physicochemical properties of amino acids but also incorporate with different compression ratios of the component of a generalized iterative map. Several properties were proved to illustrate the advantage of the generalized iterative map. The mathematical description of the generalized iterative map was suggested to compare the similarities and dissimilarities of protein sequences. Based on this method, similarities/dissimilarities were compared among ND5 protein sequences, as well as ND6 protein sequences of ten different species. RESULTS: By correlation analysis, the ClustalW results were compared with our similarity/dissimilarity results and other graphical representation results to show the utility of our approach. The comparison results show that our approach has better correlations with ClustalW for all species than other approaches and illustrate the effectiveness of our approach. CONCLUSION: Two examples show that our method not only has good performances and effects in the similarity/dissimilarity analysis of protein sequences but also does not require complex computation.

Aeromonas hydrophila bloodstream infection in patients with hematologic diseases: a report of 4 cases / 中国热带医学

@#Abstract: To report the diagnosis, treatment and outcome of 4 patients with hematological diseases complicated with Aeromonas hydrophila bloodstream infection in the Second Affiliated Hospital of Kunming Medical University, further clarify the importance of blood culture and deepen the clinical understanding of the disease. Four patients with hematological diseases complicated with Aeromonas hydrophila bloodstream infection treated in the Second Affiliated Hospital of Kunming Medical University from 2017 to 2021 were recruited as the study objects. The clinical manifestations, blood culture collection, detection time of Aeromonas hydrophila, laboratory examination, treatment and prognosis of the patients were retrospectively analyzed. In this study, 4 cases were male patients with hematological diseases, who were in myelosuppression after chemotherapy. After fever, blood culture was collected and Aeromonas hydrophila was detected. The positive time of blood culture in 4 cases ranged from 4 to 11 hours. The results of antibiotic sensitivity showed that it was highly sensitive to the second, third and fourth generation cephalosporins, quinolones and carbapenems. Four patients were treated with imipenem cilastatin sodium in the early stage, and one patient recovered after active anti infection and leukocyte raising treatment. One patient did not complete chemotherapy due to a request for discharged, and the follow-up was unknown. Two patients developed rapidly into necrotizing fasciitis and died later. Hematological diseases complicated with Aeromonas hydrophila bloodstream infection are rare, but the mortality rate is high. For patients with repeated fever and considering infection, blood culture should be carried out as soon as possible to confirm the pathogen and drug sensitivity test. During clinical treatment, the treatment should be adjusted in time in combination with the patient's situation. In addition to anti-infection treatment, the patient's immunity should be improved and the development of necrotizing fasciitis should be vigilant. Keywords: Aeromonas hydrophila; hematologic diseases; leukemia; bloodstream infection; blood culture; necrotizing fasciitis

Understanding the unimodal distributions of cancer occurrence rates: it takes two factors for a cancer to occur.

Data from the SEER reports reveal that the occurrence rate of a cancer type generally follows a unimodal distribution over age, peaking at an age that is cancer-type specific and ranges from 30+ through 70+. Previous studies attribute such bell-shaped distributions to the reduced proliferative potential in senior years but fail to explain why some cancers have their occurrence peak at 30+ or 40+. We present a computational model to offer a new explanation to such distributions. The model uses two factors to explain the observed age-dependent cancer occurrence rates: cancer risk of an organ and the availability level of the growth signals in circulation needed by a cancer type, with the former increasing and the latter decreasing with age. Regression analyses were conducted of known occurrence rates against such factors for triple negative breast cancer, testicular cancer and cervical cancer; and all achieved highly tight fitting results, which were also consistent with clinical, gene-expression and cancer-drug data. These reveal a fundamentally important relationship: while cancer is driven by endogenous stressors, it requires sufficient levels of exogenous growth signals to happen, hence suggesting the realistic possibility for treating cancer via cleaning out the growth signals in circulation needed by a cancer.

Depth perception based 3D holograms enabled with polarization-independent metasurfaces.

Metasurfaces consist of dielectric nanobrick arrays with different dimensions in the long and short axes can be used to generate different phase delays, predicting a new way to manipulate an incident beam in the two orthogonal directions separately. Here we demonstrate the concept of depth perception based three-dimensional (3D) holograms with polarization-independent metasurfaces. 4-step dielectric metasurfaces-based fan-out optical elements and holograms operating at 658 nm were designed and simulated. Two different holographic images with high fidelity were generated at the same plane in the far field for different polarization states. One can observe the 3D effect of target objects with polarized glasses. With the advantages of ultracompactness, flexibility and replicability, the polarization-independent metasurfaces open up depth perception based stereoscopic imaging in a holographic way.

Theoretical study of polarization dependence of carrier-induced refractive index change of quantum dot.

The influences of dot material component, barrier material component, aspect ratio and carrier density on the refractive index changes of TE mode and TM mode of columnar quantum dot are analyzed, and a multiparameter adjustment method is proposed to realize low polarization dependence of refractive index change. Then the quantum dots with low polarization dependence of refractive index change (<1.5%) within C-band (1530 nm - 1565 nm) are designed, and it shows that quantum dots with different material parameters are anticipated to have similar characteristics of low polarization dependence.

Dual field-of-view step-zoom metalens.

A conventional optical zoom system is bulky, expensive, and complicated for real-time adjustment. Recent progress in metasurface research has provided a new solution to achieve innovative compact optical systems. In this Letter, we propose a highly integrated step-zoom lens with dual field of view (FOV) based on double-sided metasurfaces. With silicon nanobrick arrays of spatially varying orientations sitting on both sides of a transparent substrate, this ultrathin step-zoom metalens can be designed to focus an incident circular polarized beam with handedness-dependent FOVs without varying the focal plane, which is important for practical applications. The proposed dual FOV step-zoom metalens, with advantages such as ultracompactness, flexibility, and replicability, can find applications in fields that require ultracompact zoom imaging and beam focusing.

Comparative transcriptome analysis of the different tissues between the cultivated and wild tomato.

Although domesticated tomato is cultivated by wild tomato, there are a lot of differences between cultivated tomato and wild tomato, such as shape, physiological function and life history. Many studies show that wild tomato has better salt resistance and drought resistance. In addition to, domesticated tomato's fruit is bigger and has more nutritious than wild tomato. The different features are closely related to differentially expressed genes. We identified 126 up-regulated differentially expressed genes and 87 down-regulated differentially expressed genes in cultivated tomato and wild tomato by RNA-Seq. These differentially expressed genes may be associated with salt resistance, drought resistance and fruit nutrition. These differentially expressed genes also further highlight the large-scale reconstruction between wild and cultivated species. In this paper, we mainly study GO enrichment analysis and pathway analysis of the differentially expressed genes. After GO and pathway enrichment analysis, a set of significantly enriched GO annotations and pathways were identified for the differentially expressed genes. What's more, we also identified long non-coding RNAs and mRNAs in the two species and analyzed its essential features. In addition to, we construct a co-expression network of long non-coding RNAs and mRNAs, and annotate mRNAs associated with long non-coding RNAs as target genes, and speculate the regulation function of long non-coding RNAs. In total, our results reveal the effects of artificial and natural selection on tomato's transcript, providing scientific basis for tomato's research in the future.

A Novel Protein Characterization Based on Pseudo Amino Acids Composition and Star-Like Graph Topological Indices.

BACKGROUND AND OBJECTIVE: The rapidly growing number of protein data available creates necessity of computational methods with low complexity to infer accurate protein structure, function, and evolution. METHOD: A new description of proteins based on five topological indices of star-like graph representation and the occurrence frequency of 20 amino acids was proposed to compare the similarities of proteins. RESULTS: A phylogenetic tree of eight ND6 proteins was constructed to demonstrate the effectiveness and rationality of our approach. Analogously, we applied this method to RNA polymerase proteins of some subtypes of influenza virus to infer their phylogenetic relationship. The results showed that the phylogenetic relationship among RNA polymerase of influenza virus is closely related to distributions of species virus host and geographical distribution. CONCLUSION: This novel approach is based on a mapping which can be recaptured mathematically without loss of information.

Ultracompact high-efficiency polarising beam splitter based on silicon nanobrick arrays.

Since the transmission of anisotropic nano-structures is sensitive to the polarisation of an incident beam, a novel polarising beam splitter (PBS) based on silicon nanobrick arrays is proposed. With careful design of such structures, an incident beam with polarisation direction aligned with the long axis of the nanobrick is almost totally reflected (~98.5%), whilst that along the short axis is nearly totally transmitted (~94.3%). More importantly, by simply changing the width of the nanobrick we can shift the peak response wavelength from 1460 nm to 1625 nm, covering S, C and L bands of the fiber telecommunications windows. The silicon nanobrick-based PBS can find applications in many fields which require ultracompactness, high efficiency, and compatibility with semiconductor industry technologies.

A multiple information fusion method for predicting subcellular locations of two different types of bacterial protein simultaneously.

Subcellular localization prediction of bacterial protein is an important component of bioinformatics, which has great importance for drug design and other applications. For the prediction of protein subcellular localization, as we all know, lots of computational tools have been developed in the recent decades. In this study, we firstly introduce three kinds of protein sequences encoding schemes: physicochemical-based, evolutionary-based, and GO-based. The original and consensus sequences were combined with physicochemical properties. And elements information of different rows and columns in position-specific scoring matrix were taken into consideration simultaneously for more core and essence information. Computational methods based on gene ontology (GO) have been demonstrated to be superior to methods based on other features. Then principal component analysis (PCA) is applied for feature selection and reduced vectors are input to a support vector machine (SVM) to predict protein subcellular localization. The proposed method can achieve a prediction accuracy of 98.28% and 97.87% on a stringent Gram-positive (Gpos) and Gram-negative (Gneg) dataset with Jackknife test, respectively. At last, we calculate "absolute true overall accuracy (ATOA)", which is stricter than overall accuracy. The ATOA obtained from the proposed method is also up to 97.32% and 93.06% for Gpos and Gneg. From both the rationality of testing procedure and the success rates of test results, the current method can improve the prediction quality of protein subcellular localization.

All-silicon nanorod-based Dammann gratings.

Established diffractive optical elements (DOEs), such as Dammann gratings, whose phase profile is controlled by etching different depths into a transparent dielectric substrate, suffer from a contradiction between the complexity of fabrication procedures and the performance of such gratings. In this Letter, we combine the concept of geometric phase and phase modulation in depth, and prove by theoretical analysis and numerical simulation that nanorod arrays etched on a silicon substrate have a characteristic of strong polarization conversion between two circularly polarized states and can act as a highly efficient half-wave plate. More importantly, only by changing the orientation angles of each nanorod can the arrays control the phase of a circularly polarized light, cell by cell. With the above principle, we report the realization of nanorod-based Dammann gratings reaching diffraction efficiencies of 50%-52% in the C-band fiber telecommunications window (1530-1565 nm). In this design, uniform 4×4 spot arrays with an extending angle of 59°×59° can be obtained in the far field. Because of these advantages of the single-step fabrication procedure, accurate phase controlling, and strong polarization conversion, nanorod-based Dammann gratings could be utilized for various practical applications in a range of fields.

Prediction of success for polymerase chain reactions using the Markov maximal order model and support vector machine.

Polymerase chain reaction (PCR) is hailed as one of the monumental scientific techniques of the twentieth century, and has become a common and often indispensable technique in many areas. However, researchers still frequently find some DNA templates very hard to amplify with PCR, although many kinds of endeavors were introduced to optimize the amplification. In fact, during the past decades, the experimental procedure of PCR was always the focus of attention, while the analysis of a DNA template, the PCR experimental subject itself, was almost neglected. Up to now, nobody can certainly identify whether a fragment of DNA can be simply amplified using conventional Taq DNA polymerase-based PCR protocol. Characterizing a DNA template and then developing a reliable and efficient method to predict the success of PCR reactions is thus urgently needed. In this study, by means of the Markov maximal order model, we construct a 48-D feature vector to represent a DNA template. Support vector machine (SVM) is then employed to help evaluate PCR result. To examine the anticipated success rates of our predictor, jackknife cross-validation test is adopted. The overall accuracy of our approach arrives at 93.12%, with the sensitivity, specificity, and MCC of 94.68%, 91.58%, and 0.863%, respectively.

Novel numerical characterization of protein sequences based on individual amino acid and its application.

The hydrophobicity and hydrophilicity of amino acids play a very important role in protein folding and its interaction with the environment and other molecules, as well as its catalytic mechanism. Based on the two physicochemical indexes, a 2D graphical representation of protein sequences is introduced; meanwhile, a new numerical characteristic has been proposed to compute the distance of different sequences for analysis of sequence similarity/dissimilarity on the basis of this graphical representation. Furthermore, we apply the new distance in the similarities/dissimilarities of ND5 proteins of nine species and predict the four major classes based on the dataset containing 639 domains. The results show that the method is simple and effective.

Phylogenetic analysis of H7N9 avian influenza virus based on a novel mathematical descriptor.

A new mathematical descriptor was proposed based on 3D graphical representation. Using the method, we construct the phylogenetic trees of nine proteins of H7N9 influenza virus to analyze the originated source of H7N9. The results show that the evolution route of H7N9 avian influenza is from America through Europe to Asia. Furthermore, two samples collected from environment in Nanjing and Zhejiang and one sample collected from chicken are the sources of H7N9 influenza virus that infected human in China.

Similarity/Dissimilarity analysis of protein sequences based on a new spectrum-like graphical representation.

Sequence comparison is one of the foundations in bioinformatics, which can be used to study evolutionary relations among the sequences. In this study, a 2D spectrum-like graphical representation of protein sequences is presented based on the hydrophobicity scale of amino acids. The frequencies of amplitudes of 4-subsequences are adopted to characterize a spectrum-like graph, and a 17D vector is used as the descriptor of protein sequence. The χ(2) value of compatibility test is performed. New similarity analysis approach is illustrated on the all protein sequences, which are encoded by the mitochondrion genome of 20 different species. Finally, comparison with the ClustalW method shows the utility of our method.

A novel descriptor of protein sequences and its application.

In this paper, a dynamic 3-D graphical representation of protein sequences is introduced based on three physical-chemical properties of amino acids. The coordinates of the graph have direct biological significance, which could reflect the innate structure of the proteins. The information of principal moments of inertia and range of axis coordinate are extracted as a novel mixed descriptor and proposed for the comparison of protein primary sequences. Meanwhile, the Euclidean distance of the normalized descriptor vectors which avoid the influence of the difference in length of protein sequences under consideration is employed as a quantitative measurement of the similarity of proteins. Finally, we take the nine ND5 (NADH dehydrogenase subunit 5) proteins for example and illustrate the effectiveness of our approach.