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Cancer stem-like cells (CSCs) contribute to cancer metastasis, drug resistance and tumor relapse, yet how amino acid metabolism promotes CSC maintenance remains exclusive. Here, we identify that proline synthetase PYCR1 is critical for breast cancer stemness and tumor growth. Mechanistically, PYCR1-synthesized proline activates cGMP-PKG signaling to enhance cancer stem-like traits. Importantly, cGMP-PKG signaling mediates psychological stress-induced cancer stem-like phenotypes and tumorigenesis. Ablation of PYCR1 markedly reverses psychological stress-induced proline synthesis, cGMP-PKG signaling activation and cancer progression. Clinically, PYCR1 and cGMP-PKG signaling components are highly expressed in breast tumor specimens, conferring poor survival in breast cancer patients. Targeting proline metabolism or cGMP-PKG signaling pathway provides a potential therapeutic strategy for breast patients undergoing psychological stress. Collectively, our findings unveil that PYCR1-enhanced proline synthesis displays a critical role in maintaining breast cancer stemness.

β-Lactam antibiotics are the most important and widely used antibacterial agents across the world. However, the widespread dissemination of β-lactamases among pathogenic bacteria limits the efficacy of β-lactam antibiotics. This has created a major public health crisis. The use of β-lactamase inhibitors has proven useful in restoring the activity of β-lactam antibiotics, yet, effective clinically approved inhibitors against class B metallo-β-lactamases are not available. L1, a class B3 enzyme expressed by Stenotrophomonas maltophilia , is a significant contributor to the β-lactam resistance displayed by this opportunistic pathogen. Structurally, L1 is a tetramer with two elongated loops, α3-β7 and β12-α5, present around the active site of each monomer. Residues in these two loops influence substrate/inhibitor binding. To study how the conformational changes of the elongated loops affect the active site in each monomer, enhanced sampling molecular dynamics simulations were performed, Markov State Models were built, and convolutional variational autoencoder-based deep learning was applied. The key identified residues (D150a, H151, P225, Y227, and R236) were mutated and the activity of the generated L1 variants was evaluated in cell-based experiments. The results demonstrate that there are extremely significant gating interactions between α3-β7 and β12-α5 loops. Taken together, the gating interactions with the conformational changes of the key residues play an important role in the structural remodeling of the active site. These observations offer insights into the potential for novel drug development exploiting these gating interactions.

Background Olanzapine (OLZ) reverses chronic stress-induced anxiety. Chronic stress promotes cancer development via abnormal neuro-endocrine activation. However, how intervention of brain-body interaction reverses chronic stress-induced tumorigenesis remains elusive. Methods Kras LSL−G12D/WT lung cancer model and LLC1 syngeneic tumor model were used to study the effect of OLZ on cancer stemness and anxiety-like behaviors. Cancer stemness was evaluated by qPCR, western-blotting, immunohistology staining and flow-cytometry analysis of stemness markers, and cancer stem-like function was assessed by serial dilution tumorigenesis in mice and extreme limiting dilution analysis in primary tumor cells. Anxiety-like behaviors in mice were detected by elevated plus maze and open field test. Depression-like behaviors in mice were detected by tail suspension test. Anxiety and depression states in human were assessed by Hospital Anxiety and Depression Scale (HADS). Chemo-sensitivity of lung cancer was assessed by in vivo syngeneic tumor model and in vitro CCK-8 assay in lung cancer cell lines. Results In this study, we found that OLZ reversed chronic stress-enhanced lung tumorigenesis in both Kras LSL−G12D/WT lung cancer model and LLC1 syngeneic tumor model. OLZ relieved anxiety and depression-like behaviors by suppressing neuro-activity in the mPFC and reducing norepinephrine (NE) releasing under chronic stress. NE activated ADRB2-cAMP-PKA-CREB pathway to promote CLOCK transcription, leading to cancer stem-like traits. As such, CLOCK-deficiency or OLZ reverses NE/chronic stress-induced gemcitabine (GEM) resistance in lung cancer. Of note, tumoral CLOCK expression is positively associated with stress status, serum NE level and poor prognosis in lung cancer patients. Conclusion We identify a new mechanism by which OLZ ameliorates chronic stress-enhanced tumorigenesis and chemoresistance. OLZ suppresses mPFC-NE-CLOCK axis to reverse chronic stress-induced anxiety-like behaviors and lung cancer stemness. Decreased NE-releasing prevents activation of ADRB2-cAMP-PKA-CREB pathway to inhibit CLOCK transcription, thus reversing lung cancer stem-like traits and chemoresistance under chronic stress.

Psychological stress causes gut microbial dysbiosis and cancer progression, yet how gut microbiota determines psychological stress-induced tumor development remains unclear. Here we showed that psychological stress promotes breast tumor growth and cancer stemness, an outcome that depends on gut microbiota in germ-free and antibiotic-treated mice. Metagenomic and metabolomic analyses revealed that psychological stress markedly alters the composition and abundance of gut microbiota, especially Akkermansia muciniphila ( A. muciniphila ), and decreases short-chain fatty acid butyrate. Supplement of active A. muciniphila , butyrate or a butyrate-producing high fiber diet dramatically reversed the oncogenic property and anxiety-like behavior of psychological stress in a murine spontaneous tumor model or an orthotopic tumor model. Mechanistically, RNA sequencing analysis screened out that butyrate decreases LRP5 expression to block the activation of Wnt/β-catenin signaling pathway, dampening breast cancer stemness. Moreover, butyrate as a HDAC inhibitor elevated histone H3K9 acetylation level to transcriptionally activate ZFP36, which further accelerates LRP5 mRNA decay by binding adenine uridine-rich (AU-rich) elements of LRP5 transcript. Clinically, fecal A. muciniphila and serum butyrate were inversely correlated with tumoral LRP5/β-catenin expression, poor prognosis and negative mood in breast cancer patients. Altogether, our findings uncover a microbiota-dependent mechanism of psychological stress-triggered cancer stemness, and provide both clinical biomarkers and potential therapeutic avenues for cancer patients undergoing psychological stress.

Marrow stromal cells (MSCs) have the potential to differentiate into multiple mesenchymal cell types. To harness the power of MSCs for bone regeneration, methods must be developed to direct their differentiation selectively to the osteoblast lineage. The objective of this study was to examine the feasibility of using ex vivo Runx2 gene transfer to enhance the osteogenic activity of MSCs. Primary MSCs isolated from C57BL6 mice were transduced with adenoviral vectors encoding beta-galactosidase or Runx2. Cells transduced with Ad-Runx2 expressed Runx2 protein and underwent osteoblast differentiation as measured by increases in alkaline phosphatase activity and mineralization. Time-course studies revealed that Runx2 protein was highest 1 day after transduction and declined below the limits of detection by 15 days. Osteoblast marker mRNA expression paralleled Runx2 levels. In contrast, Runx2-dependent mineralization persisted for the duration of the experiment. To assess in vivo osteogenic activity, Ad-Runx2-transduced and control MSCs were adsorbed to two different carrier scaffolds and subcutaneously implanted into C57BL6 mice. In both cases, MSCs expressing Runx2 formed substantially more bone than cells transduced with control virus. Taken together, these studies indicate that Runx2 gene transfer may be an effective route to enhance the osteogenic potential of MSCs.

Gene therapy using constitutively active viral promoters to drive expression of bone morphogenetic proteins (BMPs) has been extensively evaluated as a strategy for inducing bone regeneration. However, this approach offers little control over the concentration, timing, or duration of BMP synthesis. To gain greater control over BMP kinetics, we developed a new inducible system for the controlled expression of BMP2 using a two-component transcription factor that is dimerized with rapamycin (Rap). This approach provided stringent control over BMP2 synthesis with no BMP expression detected in the uninduced state. Rapamycin or the less immunosuppressive analogue, AP21967, rapidly and reversibly induced BMP2 in a dose-dependent manner (range 0.1-10 nM). Subcutaneous implants of fibroblasts containing the Rap-inducible system in syngeneic C57BL/6 mice were highly responsive to ip Rap injection (0.1-1 mg/kg). Peak BMP2 levels were detected within 24 h of a single Rap injection and declined to undetectable levels after 8-10 days. Alternate-day Rap injections (1 mg/kg) for 6 weeks induced subcutaneous ectopic bone formation. Rap-dependent healing of a critical-sized cranial defect was also achieved using this system. This regulated BMP2 expression system will be extremely useful for examining the role of timing and sequence of BMP delivery on bone regeneration.

Driven by recent advances in networking and computing technologies, distributed application scenarios are increasingly deployed on resource-constrained processing platforms. This includes networked embedded and cyber-physical systems as well as edge computing in mobile applications and the Internet of Things (IoT). In such resource-constrained Networks-of-Systems (NoS), computation and communication workloads need to be carefully co-optimized yet are tightly coupled. How to optimally partition and schedule application tasks among an appropriately designed NoS architecture requires a simultaneous consideration of design parameters from applications and processing platforms all the way to network configurations. Traditionally, however, systems and networks are designed in isolation and combined in an ad-hoc manner, which ignores joint effects and optimization opportunities. To systematically explore and optimize NoS design spaces, a higher level of design abstraction on top of traditional system and network design is required.In this thesis, we propose a novel network-level design methodology for resource-constrained NoS optimization and design space exploration. A key component in such a design flow is fast yet accurate network/system co-simulation to rapidly evaluate NoS parameters with high fidelity. We first introduce a novel NoS simulator (NoSSim) that integrates source-level simulation models of applications supporting a wide range of estimation metrics with a host-compiled system simulation platform and a reconfigurable network simulation backplane to accurately capture system and network interactions. In order to consider dynamic NoS application scenarios, we further introduce a novel lightweight middleware aimed at making task mapping and load balancing decisions dynamically at runtime. Our middleware employs a distributed, peer-to-peer work stealing approach and a novel work scheduling method to minimize data synchronization overhead and better exploit available parallelism and computation/communication overlap in the presence of dynamic data sources and task dependencies. Finally, to explore design-time decisions, our co-simulation platform is combined with model generation tools and a multi-objective genetic search algorithm to provide a comprehensive and fully automated NoS design space exploration framework.We evaluate our proposed network-level design flow on a case study of distributed deep learning inference on IoT edge clusters. We developed DeepThings, a framework for adaptively distributed execution of Convolutional Neural Network inference applications on tightly resource-constrained IoT edge clusters. DeepThings employs a novel scalable Fused Tile Partitioning (FTP) for convolutional layers to minimize memory footprint while producing independent distributable tasks.Comprehensive evaluations of our network-level design flow are performed. Results show that our source-level application models can achieve more than 90% accuracy with simulation speeds ranging from 180 MIPS to 5740 MIPS at different abstraction levels. When integrated with system and network models, our NoSSim co-simulator can achieve more than 86% simulation accuracy on average as compared to a real world edge device cluster, where sensitivities to various design parameters are faithfully captured with high fidelity. Compared to existing work sharing methods, our distributed work stealing and work scheduling middleware can improve throughput by 1.7-2.2x under dynamic application scenarios with multiple dynamic data sources. Finally, when applying our network-level design space exploration methodology to the DeepThings application, design-time and runtime decisions are automatically optimized, where non-obvious NoS configurations are discovered outperforming manually-designed solutions by more than 45%. Comparing with a single device execution, more than 90% per-device energy consumption reduction and a 3.6x inference speedup can be achieved on a resource-constrained edge device cluster.

In the 25 years since Hong Kong’s return to Chinese sovereignty, the mainland’s economy has risen rapidly, and Hong Kong, China, is no longer a standout. Nonetheless, the Anti-Extradition Law Amendment Bill Movement in 2019 and the COVID pandemic have forced Hong Kong’s economy to experience a severe recession, particularly as the continued development of the COVID triggered a global financial crisis and a contraction of the national economy. Hong Kong will experience a more severe macroeconomic recession than the 2009 global financial crisis, with the unemployment rate expected to rise to 5.5% or even higher. Consequently, all sectors of society have voiced concerns about Hong Kong’s “uselessness” and “marginalization,” casting doubt on the city’s role as a global financial center. With its unique advantages, Hong Kong’s financial industry has basically completed its repositioning in today’s complex social background and seized the opportunities that can promote its own development in a timely manner so that the functions of an international financial center can continue to be played, and the international financial status is safe and stable.

The conventional mesh-based Level of Detail (LoD) technique, exemplified by applications such as Google Earth and many game engines, exhibits the capability to holistically represent a large scene even the Earth, and achieves rendering with a space complexity of O(log n). This constrained data requirement not only enhances rendering efficiency but also facilitates dynamic data fetching, thereby enabling a seamless 3D navigation experience for users. In this work, we extend this proven LoD technique to Neural Radiance Fields (NeRF) by introducing an octree structure to represent the scenes in different scales. This innovative approach provides a mathematically simple and elegant representation with a rendering space complexity of O(log n), aligned with the efficiency of mesh-based LoD techniques. We also present a novel training strategy that maintains a complexity of O(n). This strategy allows for parallel training with minimal overhead, ensuring the scalability and efficiency of our proposed method. Our contribution is not only in extending the capabilities of existing techniques but also in establishing a foundation for scalable and efficient large-scale scene representation using NeRF and octree structures.

Tetrahymena is a well-established ciliate model organism, known for its nuclear dualism and unique mechanism for transposon defense, wherein transposons are kept within the highly heterochromatinized micronucleus (MIC), which is transcriptionally inert except during meiosis. The discovery of preferential transcription in the meiotic MIC at regions enriched with transposons, and the identification of MIC transcription regulatory proteins, emphasizes the necessity to elucidate the underlying mechanisms driving this process. In this study, we demonstrate that G/C-rich tracts are overrepresented in meiotic non-coding RNA (ncRNA) transcription regions and that RNA polymerase II (Pol II) is highly enriched at and around these tracts. Further analysis revealed that Pol II’s association with G/C-rich tracts is not abolished in cells lacking Rib1, a Mediator complex-associated protein essential for MIC ncRNA biogenesis. Nevertheless, in the absence of Rib1, Pol II showed abnormal association with the meiotic MIC chromatin, suggesting that Rib1 is critical for maintaining Pol II’s binding specificity. Through Rib1 truncation analysis, we found that the intrinsically disordered region, which contains putative phase-separating peptides, is crucial for its function. Disruption of phase-separation, either by deleting these peptides or by treating cells with a phase-separation disruption reagent, leads to aberrant localization of both Rib1 and Pol II on the MIC chromatin, implicating that Rib1 likely facilitates the MIC ncRNA transcription via phase-separation.