PLUNC inhibits invasion and metastasis in nasopharyngeal carcinoma by inhibiting NLRP3 inflammasome activation.

Nasopharyngeal carcinoma (NPC) is a malignant tumor that occurs in the nasopharynx. Palate, lung, and nasal epithelium clone (PLUNC) has been identified as an early secreted protein that is specifically expressed in the nasopharynx. The aim of this study was to determine the role and mechanism of PLUNC in NPC. We used mRNA sequencing (seq) combined with ribosome-nascent chain complex (RNC)-seq to determine the biological role of PLUNC. The expression of epithelial-to-mesenchymal transition (EMT)-related molecules was detected by western blotting. Then, cell migration and invasion were detected by wound healing and Transwell chamber assays. NPC cells were injected into the tail vein of nude mice to explore the biological role of PLUNC in vivo. The sequencing results showed that PLUNC inhibited the progression of NPC and its expression was correlated with that of NOD-like receptors. Experiments confirmed that PLUNC inhibited the invasion and metastasis of NPC cells by promoting the ubiquitination degradation of NLRP3. PLUNC overexpression in combination with the treatment by MCC950, an inhibitor of NLRP3 inflammasome activation, was most effective in inhibiting NPC invasion and metastasis. In vivo experiments also confirmed that the combination of PLUNC overexpression and MCC950 treatment effectively inhibited the lung metastasis of NPC cells. In summary, our research suggested that PLUNC inhibited the invasion and metastasis of NPC by inhibiting NLRP3 inflammasome activation, and targeting the PLUNC-NLRP3 inflammasome axis could provide a new strategy for the diagnosis and treatment of NPC patients.

Adipose-derived stem cell exosomes loaded with icariin alleviates rheumatoid arthritis by modulating macrophage polarization in rats.

Rheumatoid arthritis (RA) is a chronic autoimmune disease marked by synovitis and cartilage destruction. The active compound, icariin (ICA), derived from the herb Epimedium, exhibits potent anti-inflammatory properties. However, its clinical utility is limited by its water insolubility, poor permeability, and low bioavailability. To address these challenges, we developed a multifunctional drug delivery system-adipose-derived stem cells-exosomes (ADSCs-EXO)-ICA to target active macrophages in synovial tissue and modulate macrophage polarization from M1 to M2. High-performance liquid chromatography analysis confirmed a 92.4 ± 0.008% loading efficiency for ADSCs-EXO-ICA. In vitro studies utilizing cellular immunofluorescence (IF) and flow cytometry demonstrated significant inhibition of M1 macrophage proliferation by ADSCs-EXO-ICA. Enzyme-linked immunosorbent assay, cellular transcriptomics, and real-time quantitative PCR indicated that ADSCs-EXO-ICA promotes an M1-to-M2 phenotypic transition by reducing glycolysis through the inhibition of the ERK/HIF-1α/GLUT1 pathway. In vivo, ADSCs-EXO-ICA effectively accumulated in the joints. Pharmacodynamic assessments revealed that ADSCs-EXO-ICA decreased cytokine levels and mitigated arthritis symptoms in collagen-induced arthritis (CIA) rats. Histological analysis and micro computed tomography confirmed that ADSCs-EXO-ICA markedly ameliorated synovitis and preserved cartilage. Further in vivo studies indicated that ADSCs-EXO-ICA suppresses arthritis by promoting an M1-to-M2 switch and suppressing glycolysis. Western blotting supported the therapeutic efficacy of ADSCs-EXO-ICA in RA, confirming its role in modulating macrophage function through energy metabolism regulation. Thus, this study not only introduces a drug delivery system that significantly enhances the anti-RA efficacy of ADSCs-EXO-ICA but also elucidates its mechanism of action in macrophage function inhibition.

Exploring the influence of students' perceptions of face-to-face collaboration on cognitive engagement and learning outcomes in collaborative programming.

Collaborative programming is being increasingly used to overcome the difficulties of the individual programming process. In this study, we investigated the effect of collaborative perception on cognitive engagement and learning outcomes in collaborative programming. We used a quasi-experimental research to determine the differences in cognitive engagement and learning outcomes of three groups with different levels of collaborative perception. The findings highlight several important conclusions. First, there were significant differences in cognitive engagement and learning outcomes across collaborative perception groups. Students with high levels of collaborative perception demonstrate more comprehensive and diverse cognitive engagement, resulting in higher learning outcomes compared to those with lower perception. Second, students in the low collaborative perception group had more Clarification-Elaboration cognitive connections, and students in the high collaborative perception group had stronger Clarification-Positioning and Clarification-Verification cognitive connections. Third, collaborative perception positively moderated the relationship between cognitive engagement and learning outcomes. In particular, three cognitive engagement, Clarification, Elaboration, and Positioning, had a greater impact on performance when moderated by collaborative perceptions. These findings have practical implications for educators and course designers, emphasizing the importance of considering students' collaborative perception when forming groups and promoting effective collaborative programming.

LncRNA AFAP1-AS1 mediates breast cancer cell proliferation and migration through the miR-21/PTEN axis.

LncRNAs play various effects, mostly by sponging with miRNAs. Based on public databases integrating bioinformatics analyses and further validation in breast cancer (BC) tissue and cell lines, the effect of lncRNA AFAP1-AS1 on breast cancer cell proliferation and migration was verified. It might work via the miR-21/PTEN axis. The expression of AFAP1-AS1, which was significantly upregulated in BC tissues and cell lines, was correlated with old age and lymph node metastasis of patients with BC. Knockdown of AFAP1-AS1 inhibited the proliferation and migration of BC cells in vitro and in vivo. And downregulated miR-21 expression and upregulated PTEN expression additionally. Mechanistically, the knockdown of lncRNA AFAP1-AS1 upregulated PTEN expression and consequently attenuated miR-21-mediated enhanced BC cell proliferation and migration. LncRNA AFAP1-AS1 is a potential prognostic biomarker for BC patients.

APLNR inhibited nasopharyngeal carcinoma growth and immune escape by downregulating PD-L1.

BACKGROUND: APLNR is a G protein-coupled receptor and our previous study had revealed that APLNR could inhibit nasopharyngeal carcinoma (NPC) growth and metastasis. However, the role of APLNR in regulating PD-L1 expression and immune escape in NPC is unknown. METHODS: We analyzed the expression and correlation of APLNR and PD-L1 in NPC tissues and cells. We investigated the effect of APLNR on PD-L1 expression and the underlying mechanism in vitro and in vivo. We also evaluated the therapeutic potential of targeting APLNR in combination with PD-L1 antibody in a nude mouse xenograft model. RESULTS: We found that APLNR was negatively correlated with PD-L1 in NPC tissues and cells. APLNR could inhibit PD-L1 expression by binding to the FERM domain of JAK1 and blocking the interaction between JAK1 and IFNGR1, thus suppressing IFN-γ-mediated activation of the JAK1/STAT1 pathway. APLNR could also inhibit NPC immune escape by enhancing IFN-γ secretion and CD8+ T-cell infiltration and reducing CD8+ T-cell apoptosis and dysfunction. Moreover, the best effect was achieved in inhibiting NPC growth in nude mice when APLNR combined with PD-L1 antibody. CONCLUSIONS: Our study revealed a novel mechanism of APLNR regulating PD-L1 expression and immune escape in NPC and suggested that APLNR maybe a potential therapeutic target for NPC immunotherapy.

Dual-Ligand Ruthenium Coordination Polymer-Derived Self-Enhanced Electrochemiluminescent Emitters for Sensitive Detection of Procalcitonin.

Ru-based electrochemiluminescence (ECL) coordination polymers are widely employed for bioanalysis and medical diagnosis. However, commonly used Ru-based coordination polymers face the limitation of low efficiency due to the long distance between the ECL reagent and the coreactant dispersed in detecting solution. Herein, we report a dual-ligand self-enhanced ECL coordination polymer, composed of tris(4,4'-dicarboxylic acid-2,2'-bipyridyl) ruthenium(II) dichloride (Ru(dcbpy)32+) as ECL reactant ligand and ethylenediamine (EDA) as corresponding coreactant ligand into Zn2+ metal node, termed Zn-Ru-EDA. Zn-Ru-EDA shows excellent ECL performance which is attributed to the effective intramolecular electron transport between the two ligands. Furthermore, the dual-ligand polymer allows an anodic low excitation potential (+1.09 V) luminescence. The shift in the energy level of the highest occupied molecular orbital (HOMO) upward after the synthesis of the Zn-Ru-EDA has resulted in a reduced excitation potential. The low excitation potential reduced biomolecular damage and the destruction of the modified electrodes. The ECL biosensor has been constructed using Zn-Ru-EDA with high ECL efficiency for the ultrasensitive detection of a bacterial infection and sepsis biomarker, procalcitonin (PCT), in the range from 1.00 × 10-6 to 1.00 × 10 ng·mL-1 with outstanding selectivity, and the detection limit was as low as 0.47 fg·mL-1. Collectively, the dual-ligand-based self-enhanced polymer may provide an ideal strategy for high ECL efficiency improvement as well as designing new self-enhanced multiple-ligand-based coordination in sensitive biomolecular detection for early disease diagnostics.

A Cost-Effective Hemin-Based Artificial Enzyme Allows for Practical Applications.

Nanomaterials excel in mimicking the structure and function of natural enzymes while being far more interesting in terms of structural stability, functional versatility, recyclability, and large-scale preparation. Herein, the story assembles hemin, histidine analogs, and G-quadruplex DNA in a catalytically competent supramolecular assembly referred to as assembly-activated hemin enzyme (AA-heminzyme). The catalytic properties of AA-heminzyme are investigated both in silico (by molecular docking and quantum chemical calculations) and in vitro (notably through a systematic comparison with its natural counterpart horseradish peroxidase, HRP). It is found that this artificial system is not only as efficient as HRP to oxidize various substrates (with a turnover number kcat of 115 s-1) but also more practically convenient (displaying better thermal stability, recoverability, and editability) and more economically viable, with a catalytic cost amounting to <10% of that of HRP. The strategic interest of AA-heminzyme is further demonstrated for both industrial wastewater remediation and biomarker detection (notably glutathione, for which the cost is decreased by 98% as compared to commercial kits).

Simulating chemical reactions promoted by self-assembled peptides with catalytic properties.

Peptides that self-assemble exhibit distinct three-dimensional structures and attributes, positioning them as promising candidates for biocatalysts. Exploring their catalytic processes enhances our comprehension of the catalytic actions inherent to self-assembling peptides, laying a theoretical foundation for creating novel biocatalysts. The investigation into the intricate reaction mechanisms of these entities is rendered challenging due to the vast variability in peptide sequences, their aggregated formations, supportive elements, structures of active sites, types of catalytic reactions, and the interplay between these variables. This complexity hampers the elucidation of the linkage between sequence, structure, and catalytic efficiency in self-assembling peptide catalysts. This chapter delves into the latest progress in understanding the mechanisms behind peptide self-assembly, serving as a catalyst in hydrolysis and oxidation reactions, and employing computational analyses. It discusses the establishment of models, selection of computational strategies, and analysis of computational procedures, emphasizing the application of modeling techniques in probing the catalytic mechanisms of peptide self-assemblies. It also looks ahead to the potential future trajectories within this research domain. Despite facing numerous obstacles, a thorough investigation into the structural and catalytic mechanisms of peptide self-assemblies, combined with the ongoing advancement in computational simulations and experimental methodologies, is set to offer valuable theoretical insights for the development of new biocatalysts, thereby significantly advancing the biocatalysis field.

Computation-Driven Rational Design of Self-Assembled Short Peptides for Catalytic Hydrogen Production.

Self-assembling peptides represent a captivating area of study in nanotechnology and biomaterials. This interest is largely driven by their unique properties and the vast application potential across various fields such as catalytic functions. However, design complexities, including high-dimensional sequence space and structural diversity, pose significant challenges in the study of such systems. In this work, we explored the possibility of self-assembled peptides to catalyze the hydrolysis of hydrosilane for hydrogen production using ab initio calculations and carried out wet-lab experiments to confirm the feasibility of these catalytic reactions under ambient conditions. Further, we delved into the nuanced interplay between sequence, structural conformation, and catalytic activity by combining modeling with experimental techniques such as transmission electron microscopy and nuclear magnetic resonance and proposed a dual mode of the microstructure of the catalytic center. Our results reveal that although research in this area is still at an early stage, the development of self-assembled peptide catalysts for hydrogen production has the potential to provide a more sustainable and efficient alternative to conventional hydrogen production methods. In addition, this work also demonstrates that a computation-driven rational design supplemented by experimental validation is an effective protocol for conducting research on functional self-assembled peptides.

A Three-Dimensional Non-Fullerene Acceptor with Contorted Hexabenzocoronene and Perylenediimide for Organic Solar Cells.

Although fullerene derivatives such as [6,6]-phenyl-C61/C71-butyric acid methyl ester (PC61BM/PC71BM) have dominated the the photoactive acceptor materials in bulk heterojunction organic solar cells (OSCs) for decades, they have several drawbacks such as weak absorption, limited structural tunability, prone to aggregation, and high costs of production. Constructing non-fullerene small molecules with three-dimensional (3D) molecular geometry is one of the strategies to replace fullerenes in OSCs. In this study, a 3D molecule, contorted hexa-cata-hexabenzocoronene tetra perylenediimide (HBC-4-PDI), was designed and synthesized. HBC-4-PDI shows a wide and strong light absorption in the whole UV-vis region as well as suitable energy levels as an acceptor for OSCs. More importantly, the 3D construction effectively reduced the self-aggregation of c-HBC, leading to an appropriate scale phase separation of the blend film morphology in OSCs. A preliminary power conversion efficiency of 2.70 % with a champion open-circuit voltage of 1.06 V was obtained in OSCs with HBC-4-PDI as the acceptor, which was the highest among the previously reported OSCs based on c-HBC derivatives. The results indicated that HBC-4-PDI may serve as a good non-fullerene acceptor for OSCs.

Tin-doped NiFe2O4 nanoblocks grown on an iron foil for efficient and stable water splitting at large current densities.

Developing low-cost and self-supported bifunctional catalysts for highly efficient water splitting devices is of great significance. Herein, different from previously reported NiFe2O4-based electrocatalysts, we have grown nano-NiFe2O4 directly onto the iron foil (IF) surface and in situ introduced Sn4+ into NiFe2O4. The resulting experimental phenomena confirmed that the as-synthesized Sn-NiFe2O4/IF can deliver large-current densities (>1000 mA cm-2) during oxygen evolution reaction (OER) and hydrogen evolution reaction (HER) processes at a low overpotential. The needed overpotentials at the current density of 10 and 1000 mA cm-2 are 231 and 368 mV for OER and 57 and 439 mV for HER, respectively. Additionally, when applied for the two-electrode water splitting, the corresponding needed voltage for Sn-NiFe2O4/IF at the current density of 10 mA cm-2 was only 1.56 V, which was comparable to the commercial Pt/C-RuO2/IF electrode. Thus, the introduced Sn4+ greatly enhanced the electrocatalytic property of Sn-NiFe2O4/IF, resulting in a superior bifunctional catalyst that can be applied for large-scale hydrogen production.

Circular mRNA-based TCR-T offers a safe and effective therapeutic strategy for treatment of cytomegalovirus infection.

Circular mRNA (cmRNA) is particular useful due to its high resistance to degradation by exonucleases, resulting in greater stability and protein expression compared to linear mRNA. T cell receptor (TCR)-engineered T cells (TCR-T) represent a promising means of treating viral infections and cancer. This study aimed to evaluate the feasibility and efficacy of cmRNA in antigen-specific-TCR discovery and TCR-T therapy. Using human cytomegalovirus (CMV) pp65 antigen as a model, we found that the expansion of pp65-responsive T cells was induced more effectively by monocyte-derived dendritic cells transfected with pp65-encoding cmRNA compared with linear mRNA. Subsequently, we developed cmRNA-transduced pp65-TCR-T (cm-pp65-TCR-T) that specifically targets the CMV-pp65 epitope. Our results showed that pp65-TCR could be expressed on primary T cells for more than 7 days. Moreover, both in vitro killing and in vivo CDX models demonstrated that cm-pp65-TCR-T cells specifically and persistently kill pp65-and HLA-expressing tumor cells, significantly prolonging the survival of mice. Collectively, our results demonstrated that cmRNA can be used as a more effective technical approach for antigen-specific TCR isolation and identification, and cm-pp65-TCR-T may provide a safe, non-viral, non-integrated therapeutic approach for controlling CMV infection, particularly in patients who have undergone allogeneic hematopoietic stem cell transplantation.

MGA-seq: robust identification of extrachromosomal DNA and genetic variants using multiple genetic abnormality sequencing.

Genomic abnormalities are strongly associated with cancer and infertility. In this study, we develop a simple and efficient method - multiple genetic abnormality sequencing (MGA-Seq) - to simultaneously detect structural variation, copy number variation, single-nucleotide polymorphism, homogeneously staining regions, and extrachromosomal DNA (ecDNA) from a single tube. MGA-Seq directly sequences proximity-ligated genomic fragments, yielding a dataset with concurrent genome three-dimensional and whole-genome sequencing information, enabling approximate localization of genomic structural variations and facilitating breakpoint identification. Additionally, by utilizing MGA-Seq, we map focal amplification and oncogene coamplification, thus facilitating the exploration of ecDNA's transcriptional regulatory function.

Sequencing, Functional Annotation, and Interaction Prediction of mRNAs and Candidate Long Noncoding RNAs Originating from Tea Leaves During Infection by the Fungal Pathogen Causing Tea Leaf Spot, Didymella bellidis.

Tea leaf spot caused by Didymella bellidis can seriously reduce the productivity and quality of tea (Camellia sinensis var. sinensis) leaves in Guizhou Province, southwest China. Analysis of the relationship between messenger RNAs (mRNAs) and long non-coding RNAs (lncRNAs) of tea could provide insights into the plant-pathogen interaction. In this study, high-throughput sequencing of mRNAs and lncRNAs from tea leaves during infection by D. bellidis was conducted using the Illumina Novaseq 6000 platform. Infection by D. bellidis hyphae resulted in up- or downregulation of 553 and 191 of the differentially expressed mRNAs (DEmRNAs), respectively. As the S gene number (total number of genes with significantly differential expression annotated in the specified Gene Ontology [GO] database), three were enriched with respect to the defense response to the fungus at the biological process level. Expression of the DEmRNAs peroxidase 21 (TEA000222.1) and mcht-2 (TEA013240.1) originating from tea leaves were upregulated during challenge by D. bellidis hyphae, whereas expression of the LRR receptor-like serine/threonine-protein kinase ERECTA (TEA016781.1) gene was downregulated. The infection of D. bellidis hyphae resulted in up- or downregulation of 227 and 958 of the differentially expressed lncRNAs (DElncRNAs). The DEmRNAs associated with uncharacterized LOC101499401 (TEA015626.1), uncharacterized protein (TEA014125.1), structural maintenance of chromosomes protein 1 (TEA001660.1), and uncharacterized protein (TEA017727.1) occurred as a result of cis regulation by DElncRNAs MSTRG.20036, MSTRG.3843, MSTRG.26132, and MSTRG.56701, respectively. The expression profiling and lncRNA/mRNA association prediction in the tea leaves infected by D. bellidis will provide a valuable resource for further research into disease resistance.

A new polymodal gating model of the proton-activated chloride channel.

The proton-activated chloride (PAC) channel plays critical roles in ischemic neuron death, but its activation mechanisms remain elusive. Here, we investigated the gating of PAC channels using its novel bifunctional modulator C77304. C77304 acted as a weak activator of the PAC channel, causing moderate activation by acting on its proton gating. However, at higher concentrations, C77304 acted as a weak inhibitor, suppressing channel activity. This dual function was achieved by interacting with 2 modulatory sites of the channel, each with different affinities and dependencies on the channel's state. Moreover, we discovered a protonation-independent voltage activation of the PAC channel that appears to operate through an ion-flux gating mechanism. Through scanning-mutagenesis and molecular dynamics simulation, we confirmed that E181, E257, and E261 in the human PAC channel serve as primary proton sensors, as their alanine mutations eliminated the channel's proton gating while sparing the voltage-dependent gating. This proton-sensing mechanism was conserved among orthologous PAC channels from different species. Collectively, our data unveils the polymodal gating and proton-sensing mechanisms in the PAC channel that may inspire potential drug development.

Machine Learning-Guided Adaptive Parametrization for Coupling Terms in a Mixed United-Atom/Coarse-Grained Model for Diphenylalanine Self-Assembly in Aqueous Ionic Liquids.

Precise regulation of the peptide self-assembly into ordered nanostructures with intriguing properties has attracted intense attention. However, predicting peptide assembly at atomic resolution is a challenge due to both the structural flexibility of peptides and the associated huge computational costs. A machine learning-guided adaptive parametrization method was proposed for developing a mixed atomic and coarse-grained (CG) model through a multiobjective optimization strategy. Our model incorporates the united-atom (UA) model for diphenylalanine (P) and the polarizable electrostatic-variable coarse-grained (VaCG) model for aqueous ionic liquid [BMIM]+[BF4]- solution. In this mixed model, the coupling van der Waals (vdW) interaction is addressed by introducing virtual sites (VS) in the UA model to interact with solvent CG beads. The coupling parameters, including the electrostatic parameter and vdW parameters, are automatically optimized through ML-guided adaptive parametrization. The performance of this model was tested by some microstructural properties, e.g., the average number of P-P intermolecular hydrogen bonds (HBs) and radius distribution functions (RDFs) between P and different fragments of IL, in comparison with all-atom (AA) simulations. The computational cost is significantly reduced using such a parametrization scheme, which could search tens of thousands of force-field parameter sets, while needing only a small fraction of them to be assessed with molecular dynamics (MD) simulations. We used such a mixed resolution model to investigate the self-assembly in IL-water mixtures with variants of IL concentration (X). The long-range-ordered fibril structure is formed in a pure water system (X = 0). With an increase of IL concentrations, the formation of an ordered self-assembly nanostructure is prohibited, instead forming branched fibril at X = 2 mol % or amorphous aggregates when X > 10 mol %, resulting from the interplay between π-stacking and HB interactions between P and IL. The qualitative agreement between the simulated structures and the observed morphologies in experiments indicates the applicability of ML-guided parametrization strategy in the study of complex systems, such as polymers, lipid bilayers, and polysaccharides.

Ultrasensitive MicroRNA Photoelectric Assay Based on a Mimosa-like CdS-NiS/Au Schottky Junction.

Seeking and constructing superior photoactive materials have the potential to improve the performance of photoelectrochemical (PEC) biosensors. In this work, we proposed a novel mimosa-like ternary inorganic composite with a significantly enhanced light-harvesting ability and photogenerated carrier separation rate. This ternary photoactive material was obtained via electrodeposition of gold nanoparticles (Au) on the surface of transition metal sulfide composite of CdS and NiS (CdS-NiS/Au). The experimental results showed that the high initial photocurrent was acquired on CdS-NiS/Au (68-fold higher than that of individual CdS) with the synergistic effect of p-n heterojunction, Schottky junction, and the eminent optical properties of gold nanoparticles. Meanwhile, using silver nanoclusters prepared by link DNA protection as an effective quencher, integrating the duplex-specific nuclease-assisted rolling circle amplification strategy, a "Signal ON" PEC biosensor was fabricated for the detection of microRNA 21 (miRNA 21). With the release of the quencher, the recovered photocurrent is able to achieve determination of miRNA 21 within the range from 10 aM to 1 pM with a detection limit down to 4.6 aM (3σ). Importantly, this work not only provides a superb idea for designing ternary inorganic heteromaterials with exceptional photoactive ability but also allows the detection of other biomarkers by selecting appropriate recognition units.

Exosomes-transferred LINC00668 Contributes to Thrombosis by Promoting NETs Formation in Inflammatory Bowel Disease.

Epidemiological studies show an association between inflammatory bowel disease (IBD) and increased risk of thrombosis. However, how IBD influences thrombosis remains unknown. The current study shows that formation of neutrophil extracellular traps (NETs) significantly increased in the dextran sulfate sodium (DSS)-induced IBD mice, which in turn, contributes to thrombus formation in a NETs-dependent fashion. Furthermore, the exosomes isolated from the plasma of the IBD mice induce arterial and venous thrombosis in vivo. Importantly, proinflammatory factors-exposed intestinal epithelial cells (inflamed IECs) promote neutrophils to release NETs through their secreted exosomes. RNA sequencing revealed that LINC00668 is highly enriched in the inflamed IECs-derived exosomes. Mechanistically, LINC00668 facilitates the translocation of neutrophil elastase (NE) from the cytoplasmic granules to the nucleus via its interaction with NE in a sequence-specific manner, thereby inducing NETs release and thrombus formation. Importantly, berberine (BBR) suppresses the nuclear translocation of NE and subsequent NETs formation by inhibiting the interaction of LINC00668 with NE, thus exerting its antithrombotic effects. This study provides a novel pathobiological mechanism linking IBD and thrombosis by exosome-mediated NETs formation. Targeting LINC00668 can serve as a novel molecular treatment strategy to treat IBD-related thrombosis.

Discovering the Mechanisms of Oleodaphnone as a Potential HIV Latency-Reversing Agent by Transcriptome Profiling.

Latent HIV is a key factor that makes AIDS difficult to cure. Highly effective and specific latent HIV activators can effectively activate latent HIV, and then combined with antiretroviral therapy to achieve a functional cure of AIDS. Here, four sesquiterpenes (1-4) including a new one (1), five flavonoids (5-9) including three biflavonoid structures, and two lignans (10 and 11) were obtained from the roots of Wikstroemia chamaedaphne. Their structures were elucidated through comprehensive spectroscopic analyses. The absolute configuration of 1 was determined by experimental electronic circular dichroism. NH2 cell model was used to test the activity of these 11 compounds in activating latent HIV. Oleodaphnone (2) showed the latent HIV activation effect as well as the positive drug prostratin, and the activation effect was time- and concentration-dependent. Based on transcriptome analysis, the underlying mechanism was that oleodaphnone regulated the TNF, C-type lectin receptor, NF-κB, IL-17, MAPK, NOD-like receptor, JAK-Stat, FoxO, and Toll-like receptor signaling pathways. This study provides the basis for the potential development of oleodaphnone as an effective HIV latency-reversing agent.

Collective motions of fish originate from balanced local perceptual interactions and individual stochastics.

The movement of a group of biological individuals, such as fish schools, can evolve from disordered motions to synergistic movements or even ordered patterns. However, the physical origins behind such emergent phenomena of complex systems remain elusive. Here, we established a high-precision protocol for studying the collective behavior of biological groups in quasi-two-dimensional systems. Based on our video recording of ∼600h of fish movements, we extracted a force map of the interactions between fish from their trajectories using the convolution neural network. Presumably, this force implies the fish's perception of the surrounding individuals, the environment, and their response to social information. Interestingly, the fish in our experiments were predominantly in a seemingly disordered swarm state, but their local interactions were clearly specific. Combining such local interactions with the inherent stochasticity of the fish movements, we reproduced the collective motions of the fish through simulations. We demonstrated that a delicate balance between the specific local force and the intrinsic stochasticity is essential for ordered movements. This study presents implications for self-organized systems that use basic physical characterization to produce higher-level sophistication.