Distinctive and Complementary Roles of Default Mode Network Subsystems in Semantic Cognition.

The default mode network (DMN) typically deactivates to external tasks, yet supports semantic cognition. It comprises medial temporal (MT), core, and frontotemporal (FT) subsystems, but its functional organization is unclear: the requirement for perceptual coupling versus decoupling, input modality (visual/verbal), type of information (social/spatial), and control demands all potentially affect its recruitment. We examined the effect of these factors on activation and deactivation of DMN subsystems during semantic cognition, across four task-based human functional magnetic resonance imaging (fMRI) datasets, and localized these responses in whole-brain state space defined by gradients of intrinsic connectivity. FT showed activation consistent with a central role across domains, tasks, and modalities, although it was most responsive to abstract, verbal tasks; this subsystem uniquely showed more "tuned" states characterized by increases in both activation and deactivation when semantic retrieval demands were higher. MT also activated to both perceptually coupled (scenes) and decoupled (autobiographical memory) tasks and showed stronger responses to picture associations, consistent with a role in scene construction. Core DMN consistently showed deactivation, especially to externally oriented tasks. These diverse contributions of DMN subsystems to semantic cognition were related to their location on intrinsic connectivity gradients: activation was closer to the sensory-motor cortex than deactivation, particularly for FT and MT, while activation for core DMN was distant from both visual cortex and cognitive control. These results reveal distinctive yet complementary DMN responses: MT and FT support different memory-based representations that are accessed externally and internally, while deactivation in core DMN is associated with demanding, external semantic tasks.

Default mode network shows distinct emotional and contextual responses yet common effects of retrieval demands across tasks.

The default mode network (DMN) lies towards the heteromodal end of the principal gradient of intrinsic connectivity, maximally separated from the sensory-motor cortex. It supports memory-based cognition, including the capacity to retrieve conceptual and evaluative information from sensory inputs, and to generate meaningful states internally; however, the functional organisation of DMN that can support these distinct modes of retrieval remains unclear. We used fMRI to examine whether activation within subsystems of DMN differed as a function of retrieval demands, or the type of association to be retrieved, or both. In a picture association task, participants retrieved semantic associations that were either contextual or emotional in nature. Participants were asked to avoid generating episodic associations. In the generate phase, these associations were retrieved from a novel picture, while in the switch phase, participants retrieved a new association for the same image. Semantic context and emotion trials were associated with dissociable DMN subnetworks, indicating that a key dimension of DMN organisation relates to the type of association being accessed. The frontotemporal and medial temporal DMN showed a preference for emotional and semantic contextual associations, respectively. Relative to the generate phase, the switch phase recruited clusters closer to the heteromodal apex of the principal gradient-a cortical hierarchy separating unimodal and heteromodal regions. There were no differences in this effect between association types. Instead, memory switching was associated with a distinct subnetwork associated with controlled internal cognition. These findings delineate distinct patterns of DMN recruitment for different kinds of associations yet common responses across tasks that reflect retrieval demands.

The Neural Basis of Semantic Prediction in Sentence Comprehension.

Although prediction plays an important role in language comprehension, its precise neural basis remains unclear. This fMRI study investigated whether and how semantic-category-specific and common cerebral areas are recruited in predictive semantic processing during sentence comprehension. We manipulated the semantic constraint of sentence contexts, upon which a tool-related, a building-related, or no specific category of noun is highly predictable. This noun-predictability effect was measured not only over the target nouns but also over their preceding transitive verbs. Both before and after the appearance of target nouns, left anterior supramarginal gyrus was specifically activated for tool-related nouns and left parahippocampal place area was activated specifically for building-related nouns. The semantic-category common areas included a subset of left inferior frontal gyrus during the anticipation of incoming target nouns (activity enhancement for high predictability) and included a wide spread of areas (bilateral inferior frontal gyrus, left superior/middle temporal gyrus, left medial pFC, and left TPJ) during the integration of actually perceived nouns (activity reduction for high predictability). These results indicated that the human brain recruits fine divisions of cortical areas to distinguish different semantic categories of predicted words, and anticipatory semantic processing relies, at least partially, on top-down prediction conducted in higher-level cortical areas.

Bifunctional Compounds as Molecular Degraders for Integrin-Facilitated Targeted Protein Degradation.

As effective ways to regulate protein levels, targeted protein degradation technologies have attracted great attention in recent years. Here, we established a novel integrin-facilitated lysosomal degradation (IFLD) strategy to degrade extracellular and cell membrane proteins using bifunctional compounds as molecular degraders. By conjugation of a target protein-binding ligand with an integrin-recognition ligand, the resulting molecular degrader proved to be highly efficient to induce the internalization and subsequent degradation of extracellular or cell membrane proteins in an integrin- and lysosome-dependent manner. As demonstrated in the development of BMS-L1-RGD, which is an efficient programmed death-ligand 1 (PD-L1) degrader validated both in vitro and in vivo, the IFLD strategy expands the toolbox for regulation of secreted and membrane-associated proteins and thus has great potential to be applied in chemical biology and drug discovery.

A novel pyrrole-imidazole polyamide targets Aurora kinase A and suppresses tumor growth in vivo.

Aurora kinase A (Aurora A) plays a critical role in regulating cell mitotic progression and has been considered as a promising drug target for cancer therapy. To develop a novel molecule targeting Aurora A with high selectivity and efficacy, we designed and synthesized a pyrrole-imidazole polyamide (PIP) Hoechst conjugate, PIP-Ht, targeting to a cell-cycle regulated DNA sequence locating at the promoter of human Aurora A gene (AURKA). PIP-Ht potently suppressed AURKA promoter activities, mRNA expression and protein level, induced tumor cell cycle delay and inhibited tumor cell proliferation in vitro. Furthermore, subcutaneous injection of PIP-Ht into mice bearing human cancer xenografts induced significant tumor growth suppression and cell apoptosis. Collectively, PIP-Ht exhibits the potential as an effective therapeutic candidate for the tumor treatment.

Coibamide A kills cancer cells through inhibiting autophagy.

Natural products are useful tools for biological mechanism research and drug discovery. Due to the excellent tumor cell growth inhibitory profile and sub-nanomolar potency, Coibamide A (CA), an N-methyl-stabilized depsipeptide isolated from marine cyanobacterium, has been considered as a promising lead compound for cancer treatment. However, the molecular anti-cancer mechanism of the action of CA remains unclear. Here, we showed that CA treatment induced caspase-independent cell death in breast cancer cells. CA treatment also led to severe lysosome defects, which was ascribed to the impaired glycosylation of lysosome membrane protein LAMP1 and LAMP2. As a consequence, the autophagosome-lysosome fusion was blocked upon CA treatment. In addition, we presented evidence that this autophagy defect partially contributed to the CA treatment-induced tumor cell death. Together, our work uncovers a novel mechanism underlying the anti-cancer action of CA, which will promote its further application for cancer therapy.

A novel machine learning based approach for iPS progenitor cell identification.

Identification of induced pluripotent stem (iPS) progenitor cells, the iPS forming cells in early stage of reprogramming, could provide valuable information for studying the origin and underlying mechanism of iPS cells. However, it is very difficult to identify experimentally since there are no biomarkers known for early progenitor cells, and only about 6 days after reprogramming initiation, iPS cells can be experimentally determined via fluorescent probes. What is more, the ratio of progenitor cells during early reprograming period is below 5%, which is too low to capture experimentally in the early stage. In this paper, we propose a novel computational approach for the identification of iPS progenitor cells based on machine learning and microscopic image analysis. Firstly, we record the reprogramming process using a live cell imaging system after 48 hours of infection with retroviruses expressing Oct4, Sox2 and Klf4, later iPS progenitor cells and normal murine embryonic fibroblasts (MEFs) within 3 to 5 days after infection are labeled by retrospectively tracing the time-lapse microscopic image. We then calculate 11 types of cell morphological and motion features such as area, speed, etc., and select best time windows for modeling and perform feature selection. Finally, a prediction model using XGBoost is built based on the selected six types of features and best time windows. Our model allows several missing values/frames in the sample datasets, thus it is applicable to a wide range of scenarios. Cross-validation, holdout validation and independent test experiments show that the minimum precision is above 52%, that is, the ratio of predicted progenitor cells within 3 to 5 days after viral infection is above 52%. The results also confirm that the morphology and motion pattern of iPS progenitor cells is different from that of normal MEFs, which helps with the machine learning methods for iPS progenitor cell identification.

Bio-Orthogonal T Cell Targeting Strategy for Robustly Enhancing Cytotoxicity against Tumor Cells.

T cells can kill tumor cells by cell surface immunological recognition, but low affinity for tumor-associated antigens could lead to T cell off-target effects. Herein, a universal T cell targeting strategy based on bio-orthogonal chemistry and glycol-metabolic engineering is introduced to enhance recognition and cytotoxicity of T cells in tumor immunotherapy. Three kinds of bicycle [6.1.0] nonyne (BCN)-modified sugars are designed and synthesized, in which Ac4 ManN-BCN shows efficient incorporation into wide tumor cells with a BCN motif on surface glycans. Meanwhile, activated T cells are treated with Ac4 GalNAz to introduce azide (N3 ) on the cell surface, initiating specific tumor targeting through a bio-orthogonal click reaction between N3 and BCN. This artificial targeting strategy remarkably enhances recognition and migration of T cells to tumor cells, and increases the cytotoxicity 2 to 4 times for T cells against different kinds of tumor cells. Surprisingly, based on this strategy, the T cells even exhibit similar cytotoxicity with the chimeric antigen receptor T-cell against Raji cells in vitro at the effector: target cell ratios (E:T) of 1:1. Such a universal bio-orthogonal T cell-targeting strategy might further broaden applications of T cell therapy against tumors and provide a new strategy for T cell modification.

Mammalian Numb protein antagonizes Notch by controlling postendocytic trafficking of the Notch ligand Delta-like 4.

The biological antagonism between the signaling proteins Numb and Notch has been implicated in the regulation of many developmental processes, especially in asymmetric cell division. Mechanistic studies show that Numb inactivates Notch via endocytosis and proteasomal degradation that directly reduce Notch protein levels at the cell surface. However, some aspects of how Numb antagonizes Notch remain unclear. Here, we report a novel mechanism in which Numb acts as a Notch antagonist by controlling the intracellular destination and stability of the Notch ligand Delta-like 4 (Dll4) through a postendocytic-sorting process. We observed that Numb/Numblike knockdown increases the stability and cell-surface accumulation of Dll4. Further study indicated that Numb acts as a sorting switch to control the postendocytic trafficking of Dll4. Of note, the Numb/Numblike knockdown decreased Dll4 delivery to the lysosome, while increasing the recycling of Dll4 to the plasma membrane. Moreover, we demonstrate that this enrichment of Dll4 at the cell surface within Numb/Numblike knockdown cells could activate Notch signaling in neighboring cells. We also provide evidence that Numb negatively controls the Dll4 plasma membrane recycling through a well-documented recycling regulator protein AP1. In conclusion, our study has uncovered a molecular mechanism whereby Numb regulates the endocytic trafficking of the Notch ligand Dll4. Our findings provide a new perspective on how Numb counteracts Notch signaling and sheds additional critical insights into the antagonistic relationship between Numb and Notch signaling.

Numb positively regulates autophagic flux via regulating lysosomal function.

Autophagy is a lysosome-dependent catabolic process involving in the degradation and recycling of unnecessary or damaged proteins and organelles. Emerging evidence indicates that autophagy dysfunction is closely related to various human diseases including cancer, aging, myopathies and neurodegenerative disorders. Here, using genetic knockdown, we uncover the role of Numb, an endocytic adaptor protein, in regulating the late steps of autophagy. We found that Numb depletion led to the accumulation of autophagic vacuole, as verified by RFP-LC3 staining combined with transmission electron microscopy. Further investigation indicated that Numb depletion impaired autophagic degradation through inhibiting the activities of lysosomal enzymes (Cathepsin D, ß-glucuronidase and ß-glucosidase). Moreover, Numb depletion induced elevation of lysosomal pH values and decrease of glycosylated lysosome-associated membrane proteins. We further observed that Rab7 activity was inhibited in Numb-depleted cells. Together, our findings revealed a novel function of Numb and its likely mechanism in regulation of autophagy events.

[The mechanism of NUMB regulate tumor proliferation].

OBJECTIVE: To study the specific mechanism of NUMB regulate tumor proliferation. METHODS: A stable cell line by knocking down NUMB in Hela was eatablished and the Western blot and qRT-PCR was applied to confirm the knocking out of NUMB. The effect on tumor proliferation in the absence of NUMB was investigated by observing tumor growth in nude mice. The effect on the cell cycle in the absence of NUMB was detected by flow cytometry and Brdu assay. Finally, differential expression profiles of various cell cycle regulatory proteins was detected by using Western blot analysis. RESULTS: Western blot and qRT-PCR results indicated that NUMB was specifically and efficiently knocked down in the Hela stable cell line. Tumor growth experiments demonstrated that NUMB depletion significantly promoted the tumor proliferation. Flow cytometry and Brdu assay indicated that NUMB depletion significantly promoted the G1/S transition and enhanced the cell proliferation. Western blot results demonstrated that Cyclin-E protein level was increased in NUMB depletion cell, whereas expression of P27 protein was decreased. CONCLUSION: NUMB might be involved in cell cycle process by regulating Cyclin-E and P27 protein level and thereby has an effect on tumor proliferation.

Polyethylenimine Triggers Dll4 Degradation to Regulate Angiogenesis In Vitro.

The Dll4-Notch signaling pathway plays a crucial role in the regulation of angiogenesis and is a promising therapeutic target for diseases associated with abnormal angiogenesis, such as cancer and ophthalmic diseases. Here, we find that polyethylenimine (PEI), a cationic polymer widely used as nucleic acid transfection reagents, can target the Notch ligand Dll4. By immunostaining and immunoblotting, we demonstrate that PEI significantly induces the clearance of cell-surface Dll4 and facilitates its degradation through the lysosomal pathway. As a result, the activation of Notch signaling in endothelial cells is effectively inhibited by PEI, as evidenced by the observed decrease in the generation of the activated form of Notch and expression of Notch target genes Hes1 and Hey1. Furthermore, through blocking Dll4-mediated Notch signaling, PEI treatment enhances angiogenesis in vitro. Together, our study reveals a novel biological effect of PEI and establishes a foundation for the development of a Dll4-targeted biomaterial for the treatment of angiogenesis-related disease.

Individual differences in gradients of intrinsic connectivity within the semantic network relate to distinct aspects of semantic cognition.

Semantic cognition allows us to make sense of our varied experiences, including the words we hear and the objects we see. Contemporary accounts identify multiple interacting components that underpin semantic cognition, including diverse unimodal "spoke" systems that are integrated by a heteromodal "hub", and control processes that allow us to access weakly-encoded as well as dominant aspects of knowledge to suit the circumstances. The current study examined how these dimensions of semantic cognition might be related to whole-brain-derived components (or gradients) of connectivity. A nonlinear dimensionality reduction technique was applied to resting-state functional magnetic resonance imaging from 176 participants to characterise the strength of two key connectivity gradients in each individual: the principal gradient captured the separation between unimodal and heteromodal cortex, while the second gradient corresponded to the distinction between motor and visual cortex. We then examined whether the magnitude of these gradients within the semantic network was related to specific aspects of semantic cognition by examining individual differences in semantic and non-semantic tasks. Participants whose intrinsic connectivity showed a better fit with Gradient 1 had faster identification of weak semantic associations. Furthermore, a better fit with Gradient 2 was linked to faster performance on picture semantic judgements. These findings show that individual differences in aspects of semantic cognition can be related to components of connectivity within the semantic network.

A nanomaterial targeting the spike protein captures SARS-CoV-2 variants and promotes viral elimination.

The global emergency caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic can only be solved with effective and widespread preventive and therapeutic strategies, and both are still insufficient. Here, we describe an ultrathin two-dimensional CuInP2S6 (CIPS) nanosheet as a new agent against SARS-CoV-2 infection. CIPS exhibits an extremely high and selective binding capacity (dissociation constant (KD) < 1 pM) for the receptor binding domain of the spike protein of wild-type SARS-CoV-2 and its variants of concern, including Delta and Omicron, inhibiting virus entry and infection in angiotensin converting enzyme 2 (ACE2)-bearing cells, human airway epithelial organoids and human ACE2-transgenic mice. On association with CIPS, the virus is quickly phagocytosed and eliminated by macrophages, suggesting that CIPS could be successfully used to capture and facilitate virus elimination by the host. Thus, we propose CIPS as a promising nanodrug for future safe and effective anti-SARS-CoV-2 therapy, and as a decontamination agent and surface-coating material to reduce SARS-CoV-2 infectivity.

Novel N-Methylated Cyclodepsipeptide Prodrugs for Targeted Cancer Therapy.

Coibamide A (1) is a highly N-methylated cyclodepsipeptide with low nanomolar antiproliferative activities against various cancer cell lines. In previous work, we discovered a simplified analogue, [MeAla3-MeAla6]-coibamide (1a), which exhibited the same inhibitory abilities as coibamide A. Herein, to reduce the whole-body toxicity and improve the solubility of 1a, two novel peptide-drug conjugates RGD-SS-CA (2) and RGD-VC-CA (3) were designed, synthesized, and evaluated. Composed of cyclodepsipeptide 1a, a tumor-homing RGD motif, and a conditionally labile linker, the conjugates are expected to release 1a tracelessly in specific tumor microenvironments. Compared with RGD-VC-CA (3), RGD-SS-CA (2) proved to be superior in in vitro drug release and cytotoxicity tests. Notably, intravenous injection of RGD-SS-CA (2) into mice-bearing human tumor xenografts induced significant tumor growth suppression with negligible toxicity. Therefore, as a novel prodrug of the coibamide A analogue, conjugate 2 has great potential for further exploration in cancer drug discovery.

Intrinsic bioactivity of black phosphorus nanomaterials on mitotic centrosome destabilization through suppression of PLK1 kinase.

Although nanomaterials have shown promising biomedical application potential, incomplete understanding of their molecular interactions with biological systems prevents their inclusion into mainstream clinical applications. Here we show that black phosphorus (BP) nanomaterials directly affect the cell cycle's centrosome machinery. BP destabilizes mitotic centrosomes by attenuating the cohesion of pericentriolar material and consequently leads to centrosome fragmentation within mitosis. As a result, BP-treated cells exhibit multipolar spindles and mitotic delay, and ultimately undergo apoptosis. Mechanistically, BP compromises centrosome integrity by deactivating the centrosome kinase polo-like kinase 1 (PLK1). BP directly binds to PLK1, inducing its aggregation, decreasing its cytosolic mobility and eventually restricting its recruitment to centrosomes for activation. With this mechanism, BP nanomaterials show great anticancer potential in tumour xenografted mice. Together, our study reveals a molecular mechanism for the tumoricidal properties of BP and proposes a direction for biomedical application of nanomaterials by exploring their intrinsic bioactivities.

Anticancer mechanism of peptide P18 in human leukemia K562 cells.

Studies on the anticancer mechanism of peptide P18 in human leukemia K562 cells revealed that P18 causes the death of most K562 cells by depolarizing plasma membrane potential and enhancing membrane permeability, rather than activating the classical apoptosis pathway. The mechanistic studies indicate that disrupting plasma membrane is an effective approach to kill cancer cells and help design more effective peptide analogues in future cancer therapies.

Anti-melanoma activity of hybrid peptide P18 and its mechanism of action.

The anticancer properties and mechanism of action of a hybrid peptide -P18 were investigated. It had significant cytotoxic activity against human melanoma cells and low toxicity to normal NIH-3T3 cells. It also induced cell death via necrosis rather than classical apoptosis. The peptide targets the cells membrane, causing a sustained depolarization of transmembrane potential resulting in the cells swelling and bursting, thereby triggering cytolysis. P18 peptide initially binds to the melanoma cell membrane via electrostatic interaction, causing the cell membrane to rupture. The effect may be mediated by the amphiphilic alpha-helical structure of P18 peptide, coupled with changes in ion channels and an increase in plasma membrane permeability that eventually leads to melanoma cell death.

Chlorotoxin-derived bicyclic peptides for targeted imaging of glioblastomas.

A convenient and efficient strategy was developed for accessing chlorotoxin-derived bicyclic peptide-biomolecule conjugates by cyclizing fully-unprotected linear peptides with a designed tetrafunctional chemical linker. Among these peptides, bicycle-P3 bearing the N-terminal sequence of chlorotoxin shows high tumor selectivity and penetration ability, which is promising for treatment of gliomas.

Clinical HDAC Inhibitors Are Effective Drugs to Prevent the Entry of SARS-CoV2.

The outbreak of COVID-19 by the end of 2019 has posed serious health threats to humanity and jeopardized the global economy. However, no effective drugs are available to treat COVID-19 currently and there is a great demand to fight against it. Here, we combined computational screening and an efficient cellular pseudotyped virus system, confirming that clinical HDAC inhibitors can efficiently prevent SARS-CoV-2 and potentially be used to fight against COVID-19.