Otilonium bromide ameliorates pulmonary fibrosis in mice through activating phosphatase PPM1A.

Pulmonary fibrosis (PF) is a chronic, progressive and irreversible interstitial lung disease characterized by unremitting pulmonary myofibroblasts activation, extracellular matrix (ECM) deposition and inflammatory recruitment. PF has no curable medication yet. In this study we investigated the molecular pathogenesis and potential therapeutic targets of PF and discovered drug lead compounds for PF therapy. A murine PF model was established in mice by intratracheal instillation of bleomycin (BLM, 5 mg/kg). We showed that the protein level of pulmonary protein phosphatase magnesium-dependent 1A (PPM1A, also known as PP2Cα) was significantly downregulated in PF patients and BLM-induced PF mice. We demonstrated that TRIM47 promoted ubiquitination and decreased PPM1A protein in PF progression. By screening the lab in-house compound library, we discovered otilonium bromide (OB, clinically used for treating irritable bowel syndrome) as a PPM1A enzymatic activator with an EC50 value of 4.23 µM. Treatment with OB (2.5, 5 mg·kg-1·d-1, i.p., for 20 days) significantly ameliorated PF-like pathology in mice. We constructed PF mice with PPM1A-specific knockdown in the lung tissues, and determined that by targeting PPM1A, OB treatment suppressed ECM deposition through TGF-ß/SMAD3 pathway in fibroblasts, repressed inflammatory responses through NF-κB/NLRP3 pathway in alveolar epithelial cells, and blunted the crosstalk between inflammation in alveolar epithelial cells and ECM deposition in fibroblasts. Together, our results demonstrate that pulmonary PPM1A activation is a promising therapeutic strategy for PF and highlighted the potential of OB in the treatment of the disease.

Rational Design of Mono-Substituted Gd-DOTA as Highly Stable and Efficient MRI Contrast Agents for Hepatobiliary and Inflammation Imaging.

Hepatobiliary-specific magnetic resonance imaging contrast agents (MRI CAs) play a crucial role in the early diagnosis of hepatocellular carcinoma (HCC). However, only two acyclic CAs, Gd-BOPTA and Gd-EOB-DTPA, exhibit unfavorable kinetic inertness. Our study focused on the development of superior stable innovative macrocyclic CAs. By introducing a lipophilic benzyloxy group (OBn) into the H4DOTA ring (Gd-L1), we achieved significant enhancement in kinetic inertness. In vivo experiments in mice demonstrated that 40% of the dosage was distributed to the liver at 5 min, providing sustained hepatic enhancement for over 35 min. We also developed an MPO-responsive MRI CA (Gd-L3), which can participate in the "peroxidase cycle" as the substrate, generating oligomers with a 3.8-fold increase in relaxivity, and selectively enhance the lesion in an acute gout mouse model. Overall, our work represents a significant advancement in the field of hepatic and inflammatory MRI, offering promising avenues for early diagnosis and improved imaging outcomes.

Antiferromagnetic phase transition in a 3D fermionic Hubbard model.

The fermionic Hubbard model (FHM)1 describes a wide range of physical phenomena resulting from strong electron-electron correlations, including conjectured mechanisms for unconventional superconductivity. Resolving its low-temperature physics is, however, challenging theoretically or numerically. Ultracold fermions in optical lattices2,3 provide a clean and well-controlled platform offering a path to simulate the FHM. Doping the antiferromagnetic ground state of a FHM simulator at half-filling is expected to yield various exotic phases, including stripe order4, pseudogap5, and d-wave superfluid6, offering valuable insights into high-temperature superconductivity7-9. Although the observation of antiferromagnetic correlations over short10 and extended distances11 has been obtained, the antiferromagnetic phase has yet to be realized as it requires sufficiently low temperatures in a large and uniform quantum simulator. Here we report the observation of the antiferromagnetic phase transition in a three-dimensional fermionic Hubbard system comprising lithium-6 atoms in a uniform optical lattice with approximately 800,000 sites. When the interaction strength, temperature and doping concentration are finely tuned to approach their respective critical values, a sharp increase in the spin structure factor is observed. These observations can be well described by a power-law divergence, with a critical exponent of 1.396 from the Heisenberg universality class12. At half-filling and with optimal interaction strength, the measured spin structure factor reaches 123(8), signifying the establishment of an antiferromagnetic phase. Our results provide opportunities for exploring the low-temperature phase diagram of the FHM.

Learning obstacle avoidance and predation in complex reef environments with deep reinforcement learning.

The reef ecosystem plays a vital role as a habitat for fish species with limited swimming capabilities, serving not only as a sanctuary and food source but also influencing their behavioral tendencies. Understanding the intricate mechanism through which fish adeptly navigate the moving targets within reef environments within complex water flow, all while evading obstacles and maintaining stable postures, has remained a challenging and prominent subject in the realms of fish behavior, ecology, and biomimetics alike. An integrated simulation framework is used to investigate fish predation problems within intricate environments, combining deep reinforcement learning algorithms (DRL) with high-precision fluid-structure interaction numerical methods-immersed boundary lattice Boltzmann method (lB-LBM). The Soft Actor-Critic (SAC) algorithm is used to improve the intelligent fish's capacity for random exploration, tackling the multi-objective sparse reward challenge inherent in real-world scenarios. Additionally, a reward shaping method tailored to its action purposes has been developed, capable of capturing outcomes and trend characteristics effectively. The convergence and robustness advantages of the method elucidated in this paper are showcased through two case studies: one addressing fish capturing randomly moving targets in hydrostatic flow field, and the other focusing on fish counter-current foraging in reef environments to capture drifting food. A comprehensive analysis was conducted of the influence and significance of various reward types on the decision-making processes of intelligent fish within intricate environments.

Polarity-Driven Fluorescence Monitoring of Lipid Droplet Dynamics in Dry Eye Disease.

The emergence of lipid droplets (LDs) has been recognized as cellular markers of ocular surface hyperosmosis, which is recognized as a fundamental mechanism driving dry eye disease (DED), while their dynamics during DED progression and therapy remains unlocked. For this purpose, an LD-specific fluorescent probe P1 is presented in this work that exhibits highly selective and sensitive emission enhancement in response to a decreased ambient polarity (Δf) from 0.209 to 0.021. The hydrophobic nature of P1 enables specific staining of LDs, facilitating visualization of changes in polarity within these cellular structures. Utilizing P1, we observe a decrease in polarity accompanied by an increase in the size and number of LDs in hyperosmotic human corneal epithelial cells (HCECs). Furthermore, interplays between LDs and cellular organelles such as mitochondria and the Golgi apparatus are visualized, suggesting the underlying pathogenesis in DED. Notably, the variations of LDs are observed after the inhibition of ferroptosis or activation of autophagy in hyperosmotic HCECs, implying the great potential of LDs as indicators for the design and efficacy evaluation of DED drugs regarding ferroptosis or autophagy as targets. Finally, LDs are confirmed to be overproduced in corneal tissues from DED mice, and the application of clinical eye drops effectively impedes these changes. This detailed exploration underscores the significant roles of LDs as an indicator for the deep insight into DED advancement and therapy.

Visible Light-Induced 1,2-Diphenyldisulfane-Mediated Defluoroborylation of Polyfluoroarenes.

A green and practical protocol of defluoroborylation of polyfluoroarenes with stable and readily accessible NHC-borane was developed, using 1,2-diphenyldisulfane as a hydrogen atom transfer (HAT) and single electron transfer (SET) reagent precursor under visible-light irradiation, leading to the concise formation of value-added fluorinated organoboron scaffolds. Mechanism studies revealed the method underwent a boryl radical addition reaction with polyfluoroarene, followed by successive single electron transfer pathways and defluorination of the C-F bond to offer the targeted product. This unprecedented platform relies on 1,2-diphenyldisulfane and base without using expensive photocatalysts, highlighting the methodology has promising application value to prepare borylated polyfluoroarene compounds.

RIGA: Rotation-Invariant and Globally-Aware Descriptors for Point Cloud Registration.

Successful point cloud registration relies on accurate correspondences established upon powerful descriptors. However, existing neural descriptors either leverage a rotation-variant backbone whose performance declines under large rotations, or encode local geometry that is less distinctive. To address this issue, we introduce RIGA to learn descriptors that are Rotation-Invariant by design and Globally-Aware. From the Point Pair Features (PPFs) of sparse local regions, rotation-invariant local geometry is encoded into geometric descriptors. Global awareness of 3D structures and geometric context is subsequently incorporated, both in a rotation-invariant fashion. More specifically, 3D structures of the whole frame are first represented by our global PPF signatures, from which structural descriptors are learned to help geometric descriptors sense the 3D world beyond local regions. Geometric context from the whole scene is then globally aggregated into descriptors. Finally, the description of sparse regions is interpolated to dense point descriptors, from which correspondences are extracted for registration. To validate our approach, we conduct extensive experiments on both object- and scene-level data. With large rotations, RIGA surpasses the state-of-the-art methods by a margin of 8 ° in terms of the Relative Rotation Error on ModelNet40 and improves the Feature Matching Recall by at least 5 percentage points on 3DLoMatch.

Self-Rectifying Memristors for Three-Dimensional In-Memory Computing.

Costly data movement in terms of time and energy in traditional von Neumann systems is exacerbated by emerging information technologies related to artificial intelligence. In-memory computing (IMC) architecture aims to address this problem. Although the IMC hardware prototype represented by a memristor is developed rapidly and performs well, the sneak path issue is a critical and unavoidable challenge prevalent in large-scale and high-density crossbar arrays, particularly in three-dimensional (3D) integration. As a perfect solution to the sneak-path issue, a self-rectifying memristor (SRM) is proposed for 3D integration because of its superior integration density. To date, SRMs have performed well in terms of power consumption (aJ level) and scalability (>102  Mbit). Moreover, SRM-configured 3D integration is considered an ideal hardware platform for 3D IMC. This review focuses on the progress in SRMs and their applications in 3D memory, IMC, neuromorphic computing, and hardware security. The advantages, disadvantages, and optimization strategies of SRMs in diverse application scenarios are illustrated. Challenges posed by physical mechanisms, fabrication processes, and peripheral circuits, as well as potential solutions at the device and system levels, are also discussed.

Analysis of the Influencing Factors on the Extraction of Residual Oil through the Gel Foam Flooding of Underground Reservoirs in the Tahe Oilfield.

Fractured-vuggy reservoirs are mainly composed of three types: underground rivers, vugs, and fractured-vuggy structures. Based on the similarity criterion, a 3D model can truly reflect the characteristics of the multi-scale space of a fractured-vuggy reservoir, and it can reflect fluid flow laws in the formation. Water flooding, gas flooding, and gel foam flooding were carried out in the model sequentially. Based on gas flooding, the enhanced recovery ratio of gel foam flooding in the underground river was approximately 12%. By changing the injection rate, the average recovery ratio of nitrogen flooding was 6.84% higher than that of other injection rates at 5 mL/min, and that of gel foam flooding was 1.88% higher than that of other injection rates at 5 mL/min. The experimental results showed that the gel foam induced four oil displacement mechanisms, which selectively plugged high-permeability channels, controlled the mobility ratio, reduced oil-water interfacial tension, and changed the wettability of rock surfaces. With different injection-production methods, gel foam flooding can spread across two underground river channels. Two cases of nitrogen flooding affected one underground river channel and two underground river channels. By adjusting the injection rate, it was found that after nitrogen flooding, there were mainly four types of residual oil, and gel foam flooding mainly yielded three types of remaining oil. This study verified the influencing factors of extracting residual oil from an underground river and provides theoretical support for the subsequent application of gel foam flooding in underground rivers.

Molecular engineering and bioimaging applications of C2-alkenyl indole dyes with tunable emission wavelengths covering visible to NIR light.

As an important member of dyes, small-molecule fluorescent dyes show indispensable value in biomedical fields. Although various molecular dyes have been developed, full-color dyes covering blue to red region derived from a single chromophore are still in urgent demand. In this work, a series of dyes based on C2-alkenyl indole skeleton were synthesized, namely AI dyes, and their photophysical properties, cytotoxicity, and imaging capacity were verified to be satisfactory. Particularly, the maximal emission wavelengths of these dyes could cover a wide range from visible to NIR light with large Stokes shifts. Besides, the optical and structural discrepancies between the C2- and C3- alkenyl AI dyes were discussed in detail, and the theoretical calculations were conducted to provide insights on such structure-activity relationship. Finally, as a proof-of-concept, a fluorescent probe AI-Py-B capable of imaging endogenous ONOO- was presented, demonstrating the bioimaging potentials of these alkenyl indole dyes. This work is anticipated to open up new possibilities for developing dye engineering and bio-applications of natural indole framework.