Key Signature Research Articles

Transdiagnostic connectome signatures from resting-state fMRI predict individual-level intellectual capacity

Medication and other therapies for psychiatric disorders show unsatisfying efficacy, in part due to the significant clinical/ biological heterogeneity within each disorder and our over-reliance on categorical clinical diagnoses. Alternatively, dimensional transdiagnostic studies have provided a promising pathway toward realizing personalized medicine and improved treatment outcomes. One factor that may influence response to psychiatric treatments is cognitive function, which is reflected in one’s intellectual capacity. Intellectual capacity is also reflected in the organization and structure of intrinsic brain networks. Using a large transdiagnostic cohort (n = 1721), we sought to discover neuroimaging biomarkers by developing a resting-state functional connectome-based prediction model for a key intellectual capacity measure, Full-Scale Intelligence Quotient (FSIQ), across the diagnostic spectrum. Our cross-validated model yielded an excellent prediction accuracy (r = 0.5573, p < 0.001). The robustness and generalizability of our model was further validated on three independent cohorts (n = 2641). We identified key transdiagnostic connectome signatures underlying FSIQ capacity involving the dorsal-attention, frontoparietal and default-mode networks. Meanwhile, diagnosis groups showed disorder-specific biomarker patterns. Our findings advance the neurobiological understanding of cognitive functioning across traditional diagnostic categories and provide a new avenue for neuropathological classification of psychiatric disorders.

Identification of drivers of mycobacterial resistance to peptidoglycan synthesis inhibitors.

Beta-lactams have been excluded from tuberculosis therapy due to the intrinsic resistance of Mycobacterium tuberculosis (Mtb) to this antibiotic class, usually attributed to a potent beta-lactamase, BlaC, and to an unusually complex cell wall. In this pathogen, the peptidoglycan is cross-linked by penicillin-binding proteins (PBPs) and L,D-transpeptidases, the latter resistant to inhibition by most beta-lactams. However, recent studies have shown encouraging results of beta-lactam/beta-lactamase inhibitor combinations in clinical strains. Additional research on the mechanisms of action and resistance to these antibiotics and other inhibitors of peptidoglycan synthesis, such as the glycopeptides, is crucial to ascertain their place in alternative regimens against drug-resistant strains. Within this scope, we applied selective pressure to generate mutants resistant to amoxicillin, meropenem or vancomycin in Mtb H37Rv or Mycolicibacterium smegmatis (Msm) mc2-155. These were phenotypically characterized, and whole-genome sequencing was performed. Mutations in promising targets or orthologue genes were inspected in Mtb clinical strains to establish potential associations between altered susceptibility to beta-lactams and the presence of key genomic signatures. The obtained isolates had substantial increases in the minimum inhibitory concentration of the selection antibiotic, and beta-lactam cross-resistance was detected in Mtb. Mutations in L,D-transpeptidases and major PBPs, canonical targets, or BlaC were not found. The transcriptional regulator PhoP (Rv0757) emerged as a common denominator for Mtb resistance to both amoxicillin and meropenem, while Rv2864c, a lipoprotein with PBP activity, appears to be specifically involved in decreased susceptibility to the carbapenem. Nonetheless, the mutational pattern detected in meropenem-resistant mutants was different from the yielded by amoxicillin-or vancomycin-selected isolates, suggesting that distinct pathways may participate in increased resistance to peptidoglycan inhibitors, including at the level of beta-lactam subclasses. Cross-resistance between beta-lactams and antimycobacterials was mostly unnoticed, and Msm meropenem-resistant mutants from parental strains with previous resistance to isoniazid or ethambutol were isolated at a lower frequency. Although cell-associated nitrocefin hydrolysis was increased in some of the isolates, our findings suggest that traditional assumptions of Mtb resistance relying largely in beta-lactamase activity and impaired access of hydrophilic molecules through lipid-rich outer layers should be challenged. Moreover, the therapeutical potential of the identified Mtb targets should be explored.

OS05.5.A Glioblastoma-instructed microglia transit to heterogeneous phenotypic states with dendritic cell-like features in patient tumors and patient-derived orthotopic xenografts

Abstract Background A major contributing factor to Glioblastoma (GBM) development and progression is its ability to evade the immune system by creating an immune-suppressive tumor microenvironment (TME). GBM-associated myeloid cells, including resident microglia, macrophages and other peripheral immune cells are generally geared towards tumor-supportive roles. It is however unclear whether such recruited myeloid cells are phenotypically and functionally identical. Here, we aim to understand the heterogeneity of the GBM TME, using an unbiased, marker-free approach to systematically characterize cell type identities at the molecular and functional levels. Material and Methods We applied single-cell RNA-sequencing, multicolor flow cytometry, immunohistochemical analyses and functional studies to examine the heterogeneous TME instructed by GBM cells. GBM patient-derived orthotopic xenografts (PDOXs) representing different tumor phenotypes were compared to glioma mouse GL261 model and patient tumors. Results We show that PDOX models recapitulate major components of the TME found in human GBM. Human GBM cells reciprocally interact with mouse cells to create a GBM-specific TME. The most prominent transcriptomic adaptations are found in tumor-associated macrophages (TAMs), which are largely of microglial origin. We reveal inter-patient heterogeneity of TAMs and identify key signatures of distinct phenotypic states within the microglia-derived TAMs across distinct GBM landscapes. GBM-educated microglia adapt expression of genes involved in immunosuppression, migration, phagocytosis and antigen presentation, indicating functional cross-talk with GBM cells. We identify novel phenotypic states with astrocytic and endothelial-like features. Identified gene signatures and phenotypic states are confirmed in GBM patient tumor tissue. Finally we show that temozolomide treatment leads to transcriptomic adaptation of not only the GBM tumor cells but also adjacent TME components. Conclusion Our data provide insights into the phenotypic adaptation of the heterogeneous TME instructed by GBM tumor. We confirm a crucial role of microglia in supporting the immunosuppressive TME and show that PDOXs allow to monitor the highly plastic GBM ecosystem and its phenotypic adaptations upon treatment. This work further confirms the clinical relevance of PDOX avatars for testing novel therapeutics including modalities designed to target the myeloid compartment.

A Survey on Post-Quantum Public-Key Signature Schemes for Secure Vehicular Communications

Basic security requirements such as confidentiality, user authentication and data integrity, are assured by using public-key cryptography (PKC). In particular, public-key signature schemes provide non-repudiation, integrity of transmitted messages and authentication. The presence of a large scale quantum computer would be a real threat to break the most widely used public-key cryptographic algorithms in practice, RSA, DSA, ECDSA signature schemes and Diffie-Hellman key exchange. Thus, all security protocols and applications where these public-key cryptographic algorithms are used are vulnerable to quantum-computer attacks. There are five directions of cryptographic primitives secure against a quantum computer: multivariate quadratic equation-based, hash-based, lattice-based, code-based and supersingular isogeny-based cryptography. These primitives could serve as replacements for current public-key cryptographic algorithms to prepare for post-quantum era. It is important to prioritize the fields to be replaced by post-quantum cryptography (PQC) since it is hard to replace the currently deployed PKC with PQC at the same time. The fields directly connected to human life such as vehicular communications should be the primary targets of PQC applications. This survey is dedicated to providing guidelines for adapting the most suitable post-quantum candidates to the requirements of various devices and suggesting efficient and physically secure implementations that can be built into existing embedded applications as easily as traditional PKC. It focuses on the five types of post-quantum signature schemes and investigates their theoretical backgrounds, structures, state-of-the-art constructions and implementation aspects on various platforms raging from resource constrained IoT devices to powerful servers connected to the devices for secure communications in post-quantum era. It offers appropriate solutions to find tradeoffs between key sizes, signature lengths, performance, and security for practical applications.

A Rosetta Stone for Eccentric Gravitational Waveform Models

Orbital eccentricity is a key signature of dynamical binary black hole formation. The gravitational waves from a coalescing binary contain information about its orbital eccentricity, which may be measured if the binary retains sufficient eccentricity near merger. Dedicated waveforms are required to measure eccentricity. Several models have been put forward, and show good agreement with numerical relativity at the level of a few percent or better. However, there are multiple ways to define eccentricity for inspiralling systems, and different models internally use different definitions of eccentricity, making it difficult to compare eccentricity measurements directly. In this work, we systematically compare two eccentric waveform models, SEOBNRE and TEOBResumS, by developing a framework to translate between different definitions of eccentricity. This mapping is constructed by minimizing the relative mismatch between the two models over eccentricity and reference frequency, before evolving the eccentricity of one model to the same reference frequency as the other model. We show that for a given value of eccentricity passed to SEOBNRE, one must input a 20%–50% smaller value of eccentricity to TEOBResumS in order to obtain a waveform with the same empirical eccentricity. We verify this mapping by repeating our analysis for eccentric numerical relativity simulations, demonstrating that TEOBResumS reports a correspondingly smaller value of eccentricity than SEOBNRE.

Excitonic Tonks-Girardeau and charge density wave phases in monolayer semiconductors

Excitons in two-dimensional semiconductors provide a novel platform for fundamental studies of many-body interactions. In particular, dipolar interactions between spatially indirect excitons may give rise to strongly correlated phases of matter that so far have been out of reach of experiments. Here, we show that excitonic few-body systems in atomically thin transition-metal dichalcogenides undergo a crossover from a Tonks-Girardeau to a charge-density-wave regime. To this end, we take into account realistic system parameters and predict the effective exciton-exciton interaction potential. We find that the pair correlation function contains key signatures of the many-body crossover already at small exciton numbers and show that photoluminescence spectra provide readily accessible experimental fingerprints of these strongly correlated quantum many-body states.

Blockchain-based decentralized security using Crypto-Proof of Stake for securing sensitive personal health care records

The blockchain is tremendous technology for securing data transmission over a decentralized cloud environment. A PHR can offer easy data exchange and storage. However, unauthorised individuals may steal sensitive users' data from cloud devices, leading to significant privacy leakage risks. The main problem is that the non-authentication policy leads to key leakages due to unauthorised entries through intruders. To resolve this problem, we propose Blockchain-Based Decentralized Security (BCDS) using Crypto-Proof of Stake (CPoS) for securing sensitive Personal health care records. First, to process the security, the lattice construction phase is used based on blockchain decentralized. The Random shuffle block padding is intended to rehash the block to score with padding bits to block-level encryption. Then the sensitive terms are marginalized by threshold labels being highly encrypted by Optimized Starvation Point Link Encryption (OSPLE) to protect the data. By integrating Master Node Key Aggregation Policy (MNKAP) to verify the contact proof of staking authentication to the peer end to authenticate the security. The Delegate proof of stack provides higher security to protect the sensitive terms by accessing PHR records transactions to improve the integrity proofing to the admittance of the key to deliver the data. The key signature verification then validates the key for authentication to decrypt the protected data. This proves a higher security protocol and authentication principle than any other method as well as security proofing.

Kardar–Parisi–Zhang universality in a one-dimensional polariton condensate

Revealing universal behaviours is a hallmark of statistical physics. Phenomena such as the stochastic growth of crystalline surfaces1 and of interfaces in bacterial colonies2, and spin transport in quantum magnets3-6 all belong to the same universality class, despite the great plurality of physical mechanisms they involve at the microscopic level. More specifically, in all these systems, space-time correlations show power-law scalings characterized by universal critical exponents. This universality stems from a common underlying effective dynamics governed by the nonlinear stochastic Kardar-Parisi-Zhang (KPZ) equation7. Recent theoretical works have suggested that this dynamics also emerges in the phase of out-of-equilibrium systems showing macroscopic spontaneous coherence8-17. Here we experimentally demonstrate that the evolution of the phase in a driven-dissipative one-dimensional polariton condensate falls in the KPZ universality class. Our demonstration relies on a direct measurement of KPZ space-time scaling laws18,19, combined with a theoretical analysis that reveals other key signatures of this universality class. Our results highlight fundamental physical differences between out-of-equilibrium condensates and their equilibrium counterparts, and open a paradigm for exploring universal behaviours in driven open quantumsystems.

Immunothrombosis and vascular heterogeneity in cerebral cavernous malformation

AbstractCerebral cavernous malformation (CCM) is a neurovascular disease that results in various neurological symptoms. Thrombi have been reported in surgically resected CCM patient biopsies, but the molecular signatures of these thrombi remain elusive. Here, we investigated the kinetics of thrombi formation in CCM and how thrombi affect the vasculature and contribute to cerebral hypoxia. We used RNA sequencing to investigate the transcriptome of mouse brain endothelial cells with an inducible endothelial-specific Ccm3 knock-out (Ccm3-iECKO). We found that Ccm3-deficient brain endothelial cells had a higher expression of genes related to the coagulation cascade and hypoxia when compared with wild-type brain endothelial cells. Immunofluorescent assays identified key molecular signatures of thrombi such as fibrin, von Willebrand factor, and activated platelets in Ccm3-iECKO mice and human CCM biopsies. Notably, we identified polyhedrocytes in Ccm3-iECKO mice and human CCM biopsies and report it for the first time. We also found that the parenchyma surrounding CCM lesions is hypoxic and that more thrombi correlate with higher levels of hypoxia. We created an in vitro model to study CCM pathology and found that human brain endothelial cells deficient for CCM3 expressed elevated levels of plasminogen activator inhibitor-1 and had a redistribution of von Willebrand factor. With transcriptomics, comprehensive imaging, and an in vitro CCM preclinical model, this study provides experimental evidence that genes and proteins related to the coagulation cascade affect the brain vasculature and promote neurological side effects such as hypoxia in CCMs. This study supports the concept that antithrombotic therapy may be beneficial for patients with CCM.

Metastatic triple negative breast cancer adapts its metabolism to destination tissues while retaining key metabolic signatures

Triple negative breast cancer (TNBC) metastases are assumed to exhibit similar functions in different organs as in the original primary tumor. However, studies of metastasis are often limited to a comparison of metastatic tumors with primary tumors of their origin, and little is known about the adaptation to the local environment of the metastatic sites. We therefore used transcriptomic data and metabolic network analyses to investigate whether metastatic tumors adapt their metabolism to the metastatic site and found that metastatic tumors adopt a metabolic signature with some similarity to primary tumors of their destinations. The extent of adaptation, however, varies across different organs, and metastatic tumors retain metabolic signatures associated with TNBC. Our findings suggest that a combination of anti-metastatic approaches and metabolic inhibitors selected specifically for different metastatic sites, rather than solely targeting TNBC primary tumors, may constitute a more effective treatment approach.

A morphological classification of coastal forelands, with examples from South Africa

Alongshore variations in the cross-shore width, and therefore volume, of sandy beaches are important because these reflect spatial variability in the operation of wave- and wind-driven processes taking place both at the shoreface and in the supratidal zone. One key geomorphic signature of variations in cross-shore beach width is the development of coastal forelands. Different foreland types have been described in the literature from very specific geomorphic contexts, but hitherto there has been no overarching classification scheme that genetically links these different foreland types, or considers them in the wider context of sandy beach dynamics. In order to achieve this aim, this study maps and inventorises 87 forelands from the South African coast (~2600 km long), and classifies these into four morphological types: salients, tombolos, cuspate forelands, and ramp forelands. These foreland types have different morphological properties, reflecting the interplay of coastal erosional and depositional processes and any antecedent conditions; and a varying balance of morphodynamic controls on their development and behaviour. These include variations in wave (and to a lesser extent wind) energy, sediment supply, and the presence of bedrock outcrops of different sizes, shapes and positions along the shoreline. Analysis of foreland morphology and dynamic behaviour, based on examples from South Africa, enables a better understanding of coastal forelands globally as integrated sediment systems and responsive to the range of forcings driving coastal change.

HER2-enriched subtype and novel molecular subgroups drive aromatase inhibitor resistance and an increased risk of relapse in early ER+/HER2+ breast cancer.

SummaryBackgroundOestrogen receptor positive/ human epidermal growth factor receptor positive (ER+/HER2+) breast cancers (BCs) are less responsive to endocrine therapy than ER+/HER2- tumours. Mechanisms underpinning the differential behaviour of ER+HER2+ tumours are poorly characterised. Our aim was to identify biomarkers of response to 2 weeks’ presurgical AI treatment in ER+/HER2+ BCs.MethodsAll available ER+/HER2+ BC baseline tumours (n=342) in the POETIC trial were gene expression profiled using BC360™ (NanoString) covering intrinsic subtypes and 46 key biological signatures. Early response to AI was assessed by changes in Ki67 expression and residual Ki67 at 2 weeks (Ki672wk). Time-To-Recurrence (TTR) was estimated using Kaplan-Meier methods and Cox models adjusted for standard clinicopathological variables. New molecular subgroups (MS) were identified using consensus clustering.FindingsHER2-enriched (HER2-E) subtype BCs (44.7% of the total) showed poorer Ki67 response and higher Ki672wk (p<0.0001) than non-HER2-E BCs. High expression of ERBB2 expression, homologous recombination deficiency (HRD) and TP53 mutational score were associated with poor response and immune-related signatures with High Ki672wk. Five new MS that were associated with differential response to AI were identified. HER2-E had significantly poorer TTR compared to Luminal BCs (HR 2.55, 95% CI 1.14–5.69; p=0.0222). The new MS were independent predictors of TTR, adding significant value beyond intrinsic subtypes.InterpretationOur results show HER2-E as a standardised biomarker associated with poor response to AI and worse outcome in ER+/HER2+. HRD, TP53 mutational score and immune-tumour tolerance are predictive biomarkers for poor response to AI. Lastly, novel MS identify additional non-HER2-E tumours not responding to AI with an increased risk of relapse.FundingCancer Research UK (CRUK/07/015).

Lattice dynamics and spin–phonon coupling in the noncollinear antiferromagnetic antiperovskite Mn[formula omitted]NiN

Antiferromagnetic antiperovskites, of the form Mn3BN (B= Ni, Cu, Zn, Sn, Ir, and Pt), have shown an outstanding behavior in which, giant negative thermal expansion and chiral magnetic structures are intertwined. As such, aiming to shed light on the magnetostructural behavior, related to the magnetic ordering and crystalline structure of this type of materials, we studied theoretically, based-on first-principles calculations, the lattice dynamics and spin–phonon coupling in the Manganese-based antiperovskite Mn3NiN, as a prototype in the Mn3BN family. We found a strong spin–lattice coupling by means of the understanding of the phonon-dispersion curves obtained when including the chiral noncollinear magnetic structures. To do so, we highlight the importance of the exchange–correlation scheme selected and its influence on the structural, electronic, magnetic, and vibrational degrees of freedom. Finally, we found two unstable vibrational modes at the M- and R-points when the magnetic ordering is switched to ferromagnetic from the chiral Γ4g and Γ5g. These octahedral-associated modes with spin–phonon coupling parameters, λ, as large as 10.74 cm−1 and −2.53 cm−1 for the R5−, and M2+, respectively. The latter coupling is observed as a key signature of the strong spin–lattice interaction.

A Signature of Genes Featuring FGF11 Revealed Aberrant Fibroblast Activation and Immune Infiltration Properties in Keloid Tissue.

Keloid is a fibroproliferative disorder in the skin, which manifested with extensive deposition of collagen and extracellular matrix. Its etiology remains a mystery and its recurrence rate remains high despite combinative treatment regimens. Current hypotheses of its pathogenesis centered on the role of inflammatory processes as well as immune infiltration in the microenvironment. However, there are a lot of discrepancies when it comes to the verification of certain well-recognized pathways involved in the dysfunctional fibroblast. Further exploration and characterization are required to reveal the driving force and even leading genes responsible for keloid formation. In this study, we provided supportive evidence of the immunologic nature of keloids distinct from normal fibroblasts and physiological scars by incorporating multiple available expressional profiles in the Gene Expression Omnibus (GEO). Through differential analyses and functional analyses, we identified a set of genes that successfully captures the dissimilarities between keloid lesions and nonlesions. They were differentially regulated in keloid samples and had opposite behavior in exposure to hydrocortisone. A key signature of six genes featuring FGF11 not only was highly correlated with significantly dysregulated fibroblast activation but also reflected various levels of immune cell infiltration. FGF11, in particular, revealed the heterogenous immunologic nature of keloid lesions. This study further supported that aberrant fibroblast was one of the main contributing factors and shed some light on investigating immune properties in future studies.

Multiple optical fiber sensing with a single data channel of optical frequency-domain reflectometry

Fully distributed strain sensing of multiple optical fibers normally requires assigning each fiber a dedicated data channel. However, in this Letter, we show that using a single data channel of optical frequency-domain reflectometry, simultaneous measurement along multiple fibers combined with optical couplers can be realized by taking the advantage that each fiber has its unique Rayleigh backscattering pattern which can be used as a key signature for identifying sensing information, even though the individual pattern is buried in the signals contributed from all the fibers. Preliminary results show that four single-mode fibers, with the feasibility to be extended to six, can be demodulated simultaneously with spatial resolutions of the order of millimeter, offering great system simplicity and cost reduction for fully distributed strain sensing of multiple optical fibers or multiple cores in a specialty fiber.

A new quantum-safe multivariate polynomial public key digital signature algorithm

We propose a new quantum-safe digital signature algorithm called Multivariate Polynomial Public Key Digital Signature (MPPK/DS). The core of the algorithm is based on the modular arithmetic property that for a given element g, greater than equal to two, in a prime Galois field GF(p) and two multivariate polynomials P and Q, if P is equal to Q modulo p-1, then g to the power of P is equal to g to the power of Q modulo p. MPPK/DS is designed to withstand the key-only, chosen-message, and known-message attacks. Most importantly, making secret the element g disfavors quantum computers’ capability to solve the discrete logarithm problem. The security of the MPPK/DS algorithm stems from choosing a prime p associated with the field GF(p), such that p is a sum of a product of an odd prime number q multiplied with a power x of two and one. Given such a choice of a prime, choosing even coefficients of the publicly available polynomials makes it hard to find any private information modulo p-1. Moreover, it makes it exponentially hard to lift the solutions found modulo q to the ring of integers modulo p-1 by properly arranging x and q. However, finding private information modulo the components q and power x of two is an NP-hard problem since it involves solving multivariate equations over the chosen finite field. The time complexity of searching a private key from a public key or signatures is exponential over GF(p). The time complexity of perpetrating a spoofing attack is also exponential for a field GF(p). MPPK/DS can achieve all three NIST security levels with optimized choices of multivariate polynomials and the generalized safe prime p.

Innovative signature establishment using lymphangiogenesis-related lncRNA pairs to predict prognosis of hepatocellular carcinoma

AimsHepatocellular carcinoma (HCC) remains a major tumoral burden globally, and its heterogeneity encumbers prognostic prediction. The lymphangiogenesis-related long non-coding RNAs (lrlncRNAs) reported to be implicated in immune response regulation show potential importance in predicting the prognostic and therapeutic outcome. Hence, this study aims to establish a lrlncRNA pairs-based signature not requiring specific expression levels of transcripts, which displays promising clinical practicality and satisfactory predictive capability. Main methodsTranscriptomic and clinical information of the Liver Hepatocellular Carcinoma (LIHC) project retrieved from the TCGA portal were used to find differently expressed lrlncRNA (DElrlncRNA) via analysis performed between lymphangiogenesis-related genes (lr-genes) and lncRNAs(lrlncRNA), and to ultimately construct the signature based on lrlncRNA pairs screened out via Lasso and Cox regression analyses. Akaike information criterion (AIC) values were computed to find the cut-off point optimum for high-risk and low-risk group allocation. The signature then underwent trials in terms of its predictive value for survival, clinicopathological features, immune cells infiltration in tumoral microenvironment, selected checkpoint biomarkers and chemosensitivity. Key findingsA novel lymphangiogenesis-related lncRNA pair signature was established using nine lrlncRNA pairs identified and significantly related to overall survival, clinicopathological features, immune cells infiltration and susceptibility to chemotherapy. Moreover, the signature efficacy was verified in acknowledged clinicopathological subgroups and partially validated by qRT-PCR assay in various human HCC cell lines. SignificanceThe novel lrlncRNA-pairs based signature was shown to effectively and independently estimate HCC prognosis and help screen patients suitable for anti-tumor immunotherapy and chemotherapy.

A reference single-cell regulomic and transcriptomic map of cynomolgus monkeys

Non-human primates are attractive laboratory animal models that accurately reflect both developmental and pathological features of humans. Here we present a compendium of cell types across multiple organs in cynomolgus monkeys (Macaca fascicularis) using both single-cell chromatin accessibility and RNA sequencing data. The integrated cell map enables in-depth dissection and comparison of molecular dynamics, cell-type compositions and cellular heterogeneity across multiple tissues and organs. Using single-cell transcriptomic data, we infer pseudotime cell trajectories and cell-cell communications to uncover key molecular signatures underlying their cellular processes. Furthermore, we identify various cell-specific cis-regulatory elements and construct organ-specific gene regulatory networks at the single-cell level. Finally, we perform comparative analyses of single-cell landscapes among mouse, monkey and human. We show that cynomolgus monkey has strikingly higher degree of similarities in terms of immune-associated gene expression patterns and cellular communications to human than mouse. Taken together, our study provides a valuable resource for non-human primate cell biology.

Hsa_Circ_0066351 Acts as a Prognostic and Immunotherapeutic Biomarker in Colorectal Cancer.

Circular RNA (circRNA), a novel class of non-coding RNA, has been reported in various diseases, especially in tumors. However, the key signatures of circRNA-competitive endogenous RNA (ceRNA) network are largely unclear in colorectal cancer (CRC). We first characterized circRNAs profile by using circRNA-seq analysis from real-word dataset. The expression level of hsa_circ_0066351 in CRC tissues and cell lines was detected by quantitative real-time PCR. Then, cell proliferation assay was used to confirm the proliferation function of hsa_circ_0066351. Next, Cytoscape was used to construct circRNA-miRNA-mRNA networks. Last but not least, the landscape of hsa_circ_0066351-miRNA-mRNA in CRC had been investigated in the bulk tissue RNA-Seq level and single-cell Seq level. We proved that hsa_circ_0066351 was significantly downregulated in CRC cell lines and tissues (P < 0.001), and was negatively associated with distant metastasis (P < 0.01). Significantly, the expression of hsa_circ_0066351 was associated with better survival in patients with CRC. Function assays showed that hsa_circ_0066351 could inhibit CRC cells proliferation. In addition, a ceRNA network, including hsa_circ_0066351, two miRNAs, and ten mRNAs, was constructed. Our analyses showed that these ten mRNAs were consistently downregulated in pan-cancer and enriched in tumor suppressive function. A risk score model constructed by these ten downstream genes also indicated that they were related to the prognosis and immune response in CRC. In conclusion, we demonstrated that a novel circRNA (hsa_circ_0066351) inhibited CRC proliferation, and revealed a potential prognostic and immunotherapeutic biomarker in CRC.

Identification of key genes related to immune cells in patients with gram-negative sepsis based on weighted gene co-expression network analysis.

BackgroundGram-negative sepsis is closely related to the immune response, involving collaborative efforts of different immune cells. However, the mechanisms underlying immune cell regulation in gram-negative sepsis remain unclear. Therefore, this study investigated the potential regulatory mechanisms and identified the key genes related to immune cells in gram-negative sepsis.MethodsThe RNA-sequencing data for gram-negative sepsis samples and normal samples were collected from the Gene Expression Omnibus (GEO) dataset GSE9960. CIBERSORT was performed to analyze the proportion of 22 types of immune cells in gram-negative sepsis and normal samples. Weighted gene co-expression network analysis (WGCNA) was used to determine the networks that are associated with the differentially distributed immune cells in the two groups. Differentially expressed genes were identified using the limma package. The least absolute shrinkage and selection operator (LASSO) and support vector machine-recursive feature elimination (SVM-RFE) algorithms were applied to ascertain hub gene signatures. The gene interaction network of hub gene signatures was determined by ingenuity pathway analysis. Furthermore, the expression levels of the key genes were verified using quantitative real-time polymerase chain reaction (qRT-PCR).ResultsCIBERSORT analysis showed that the proportions of plasma cells, resting CD4+ memory T cells, M1 macrophages, and eosinophils were significantly different between gram-negative sepsis and normal samples. WGCNA identified 1,100 genes in the most relevant modules associated with these immune cells. In addition, 87 differentially expressed genes were identified. By overlapping the genes found in the WGCNA and the differentially expressed genes, a total of 46 genes related to immune cells were identified. Integrative analysis of LASSO and SVM-RFE identified NLR family CARD domain-containing 4 (NLRC4) and ral guanine nucleotide dissociation stimulator like 4 (RGL4) as key gene signatures related to immune cells in gram-negative sepsis. The qRT-PCR results demonstrated that both NLRC4 and RGL4 were upregulated in peripheral blood mononuclear cells (PBMCs) from patients with sepsis.ConclusionsThis investigation provides novel insights into the molecular mechanisms of immune cells involved in the pathogenesis of gram-negative sepsis. NLRC4 and RGL4 were identified as key gene signatures related to immune cells and may act as potential diagnostic biomarkers for gram-negative sepsis.