Overview of indigo biosynthesis by Flavin-containing Monooxygenases: History, industrialization challenges, and strategies.

Indigo is a natural dye extensively used in the global textile industry. However, the conventional synthesis of indigo using toxic compounds like aniline, formaldehyde, and hydrogen cyanide has led to environmental pollution and health risks for workers. This method also faces growing economic, sustainability, and environmental challenges. To address these issues, the concept of bio-indigo or indigo biosynthesis has been proposed as an alternative to aniline-based indigo synthesis. Among various enzymes, Flavin-containing Monooxygenases (FMOs) have shown promise in achieving a high yield of bio-indigo. However, the industrialization of indigo biosynthesis still encounters several challenges. This review focuses on the historical development of indigo biosynthesis mediated by FMOs. It highlights several factors that have hindered industrialization, including the use of unsuitable chassis (Escherichia coli), the toxicity of indole, the high cost of the substrate L-tryptophan, the water-insolubility of the product indigo, the requirement of reducing reagents such as sodium dithionite, and the relatively low yield and high cost compared to chemical synthesis. Additionally, this paper summarizes various strategies to enhance the yield of indigo synthesized by FMOs, including redundant sequence deletion, semi-rational design, cheap precursor research, NADPH regeneration, large-scale fermentation, and enhancement of water solubility of indigo.

Two new oleanane triterpenes from Maytenus hookeri.

Two new triterpenes mayteneri A (1), mayteneri B (2), and seven known compounds (3-9) were isolated from stems of Maytenus hookeri Loes. The chemical structures of compounds 1 and 2 were established by 1D, 2D NMR, HRESIMS analysis, and calculating electronic circular dichroism (ECD). The structures of known compounds 3-9 were determined by comparison of their spectral with those reported. Compounds 4-7 showed significant inhibitory activity for NLRP3 inflammasome, with the IC50 values of 2.36-3.44 µM.

Functional biomacromolecules-based microneedle patch for the treatment of diabetic wound.

Diabetic wounds are a common complication of diabetes. The prolonged exposure to high glucose and oxidative stress in the wound environment increases the risk of bacterial infection and abnormal angiogenesis, leading to amputation. Microneedle patches have shown promise in promoting the healing of diabetic wounds through transdermal drug delivery. These patches target the four main aspects of diabetic wound treatment: hypoglycemia, antibacterial action, inflammatory regulation, and tissue regeneration. By overcoming the limitations of traditional administration methods, microneedle patches enable targeted therapy for deteriorated tissues. The design of these patches extends beyond the selection of needle tip material and biomacromolecule encapsulated drugs; it can also incorporate near-infrared rays to facilitate cascade reactions and treat diabetic wounds. In this review, we comprehensively summarize the advantages of microneedle patches compared to traditional treatment methods. We focus on the design and mechanism of these patches based on existing experimental articles in the field and discuss the potential for future research on microneedle patches.

Magnetic field filtering of the boundary supercurrent in unconventional metal NiTe2-based Josephson junctions.

Topological materials with boundary (surface/edge/hinge) states have attracted tremendous research interest. Additionally, unconventional (obstructed atomic) materials have recently drawn lots of attention owing to their obstructed boundary states. Experimentally, Josephson junctions (JJs) constructed on materials with boundary states produce the peculiar boundary supercurrent, which was utilized as a powerful diagnostic approach. Here, we report the observations of boundary supercurrent in NiTe2-based JJs. Particularly, applying an in-plane magnetic field along the Josephson current can rapidly suppress the bulk supercurrent and retain the nearly pure boundary supercurrent, namely the magnetic field filtering of supercurrent. Further systematic comparative analysis and theoretical calculations demonstrate the existence of unconventional nature and obstructed hinge states in NiTe2, which could produce hinge supercurrent that accounts for the observation. Our results reveal the probable hinge states in unconventional metal NiTe2, and demonstrate in-plane magnetic field as an efficient method to filter out the bulk contributions and thereby to highlight the hinge states hidden in topological/unconventional materials.

Characterization of OsPIN2 Mutants Reveal Novel Roles for Reactive Oxygen Species in Modulating Not Only Root Gravitropism but Also Hypoxia Tolerance in Rice Seedlings.

Tolerance to submergence-induced hypoxia is an important agronomic trait especially for crops in lowland and flooding-affected areas. Although rice (Oryza sativa) is considered a flood-tolerant crop, only limited cultivars display strong tolerance to prolonged submergence and/or hypoxic stress. Therefore, characterization of hypoxic resistant genes and/or germplasms have important theoretical and practical significance for rice breeding and sustained improvements. Previous investigations have demonstrated that loss-of-function of OsPIN2, a gene encoding an auxin efflux transporter, results in the loss of root gravitropism due to disrupted auxin transport in the root tip. In this study, we revealed a novel connection between OsPIN2 and reactive oxygen species (ROS) in modulating root gravitropism and hypoxia tolerance in rice. It is shown that the OsPIN2 mutant had decreased accumulation of ROS in root tip, due to the downregulation of glycolate oxidase encoding gene OsGOX6, one of the main H2O2 sources. The morphological defects of root including waved rooting and agravitropism in OsPIN2 mutant may be rescued partly by exogenous application of H2O2. The OsPIN2 mutant exhibited increased resistance to ROS toxicity in roots due to treatment with H2O2. Furthermore, it is shown that the OsPIN2 mutant had increased tolerance to hypoxic stress accompanied by lower ROS accumulation in roots, because the hypoxia stress led to over production of ROS in the roots of the wild type but not in that of OsPIN2 mutant. Accordingly, the anoxic resistance-related gene SUB1B showed differential expression in the root of the WT and OsPIN2 mutant in response to hypoxic conditions. Notably, compared with the wild type, the OsPIN2 mutant displayed a different pattern of auxin distribution in the root under hypoxia stress. It was shown that hypoxia stress caused a significant increase in auxin distribution in the root tip of the WT but not in that of the war1 mutant. In summary, these results suggested that OsPIN2 may play a role in regulating ROS accumulation probably via mediating auxin transport and distribution in the root tip, affecting root gravitropism and hypoxic tolerance in rice seedlings. These findings may contribute to the genetic improvement and identification of potential hypoxic tolerant lines in rice.

MT-EpiPred: Multitask Learning for Prediction of Small-Molecule Epigenetic Modulators.

Epigenetic modulators play an increasingly crucial role in the treatment of various diseases. In this case, it is imperative to systematically investigate the activity of these agents and understand their influence on the entire epigenetic regulatory network rather than solely concentrate on individual targets. This work introduces MT-EpiPred, a multitask learning method capable of predicting the activity of compounds against 78 epigenetic targets. MT-EpiPred demonstrated outstanding performance, boasting an average auROC of 0.915 and the ability to handle few-shot targets. In comparison to the existing method, MT-EpiPred not only expands the target pool but also achieves superior predictive performance with the same data set. MT-EpiPred was then applied to predict the epigenetic target of a newly synthesized compound (1), where the molecular target was unknown. The method identified KDM4D as a potential target, which was subsequently validated through an in vitro enzyme inhibition assay, revealing an IC50 of 4.8 µM. The MT-EpiPred method has been implemented in the web server MT-EpiPred (http://epipred.com), providing free accessibility. In summary, this work presents a convenient and accurate tool for discovering novel small-molecule epigenetic modulators, particularly in the development of selective inhibitors and evaluating the impact of these inhibitors over a broad epigenetic network.

Spatial distribution and modelling of 239+240Pu in the sediments and seawater columns of the South China Sea and Indian Ocean.

In order to investigate the 239+240Pu potential influence in the ocean, and develop a new method for rapidly monitoring radioactive pollution, the 239+240Pu spatial distribution in the South China Sea (SCS) and the Indian Ocean (IND) sediments is analyzed by SF-ICP-MS (ELEMENT 2). The inventory-weighted mean activities of 239+240Pu were 0.413 ± 0.333 mBq/g, 0.128 ± 0.044 mBq/g, and 0.483 ± 0.606 mBq/g in the sediments of the SCS, eastern IND, and Arabian Sea, respectively. The 239+240Pu activity spatial distribution in the SCS sediments was influenced by the current, the vertical distribution of Pu in seawater, and the transport of particulate matter. The 239+240Pu activity spatial distribution in the IND sediments could be impacted by Antarctic Intermediate Water. The average of 240Pu/239Pu atomic ratios were 0.258 ± 0.034, 0.219 ± 0.031, and 0.212 ± 0.028 in the sediments of the SCS, eastern IND, and Arabian Sea, respectively. The 240Pu/239Pu atomic ratios in the SCS and IND indicate that Pu from the Pacific Proving Ground (PPG) is transported to the IND via the SCS internal current and transverse ocean currents within Indonesia. In addition, a seawater advection-dispersion equation (S-ADE) model is established based on the actual physical processes of radionuclides in the seawater column and well fitting results were obtained (R2 = 0.49 to 0.99). The 239+240Pu data and the geographic information from the sample site were used to correct the Pu distribution in the seawater. The calculated 239+240Pu mean concentrations in the surface seawater were 2.465 mBq/m3 and 2.205 mBq/m3 for the SCS and the eastern IND seawater, respectively, and the result is consistent with the previous measurements. Then, the 239+240Pu stored in the study area of SCS and eastern IND was estimated to be approximately 1.0-1.4% of the global ocean based on the model. This study provides a useful model for guiding and designing future monitoring of pollution by anthropogenic Pu and other isotopes.

Layer-by-layer reinforced-mediated sustained-release nanoantioxidants for long-lasting prevention against drug-induced liver injury.

Drug-induced liver injury (DILI) is a commonly encountered and diagnostically complex etiology of acute liver failure, characterized by early indications of hepatic oxidative stress. The most economical approach for DILI treatment is effective and durable oxidative stress prevention. Herein, we propose a long-lasting nanoantioxidant called PDA-Zn-BAI NPs characterized by sustained-release of baicalein (a natural antioxidant) for the long-lasting prevention of DILI. It is constructed using dopamine as an intermediate and layer-by-layer reinforcement strategy based on Zn2+-mediated coordination bonding, π-π stacking, and steric hindrance made of polydopamine network. Optimized PDA-Zn-BAI NPs performed a satisfactory sustained-release effect (36.67% ± 6.67 in normal condition and 60.32% ± 3.19 in acid condition of cumulative release within 5 days). Furthermore, it's been found that PDA-Zn-BAI NPs could continuously be accumulated in the liver with negligible hepatotoxicity and were activated to effectively scavenge reactive oxygen species to break off the damage of acetaminophen to the liver within 5 days (ALT as an indicator, > 70% prevention effect lasts for 5 days), which was vital for the long-lasting prevention of DILI. The long-lasting detoxification by PDA-Zn-BAI NPs in patients with DILI suggested a potential clinical application, especially for those patients who need prolonged administration of hepatotoxic drugs.

Bioactive diterpenoids isolated from the twigs and leaves of Casearia velutina.

Nine previously undescribed clerodane-type diterpenoids (1-9), named caseabalanspenes A-I, along with six know compounds (10-15), were isolated from the twigs and leaves of Casearia velutina. Spectroscopic data (1D and 2D NMR) analysis permitted the definition of their structures and then determination of the molecular formula of the compound by high resolution mass spectrometry (HR-ESI-MS). It is worth noting that compound 7 contains N- heterocycle. Compounds 1-8 were tested the anti-inflammasome activity, and compound 3 exhibited potent activity and decreased LDH level in a dose-dependent manner, with IC50 values of 2.90 µM.

Challenges and opportunities for improving the druggability of natural product: Why need drug delivery system?

Bioactive natural products (BNPs) are the marrow of medicinal plants, which are the secondary metabolites of organisms and have been the most famous drug discovery database. Bioactive natural products are famous for their enormous number and great safety in medical applications. However, BNPs are troubled by their poor druggability compared with synthesis drugs and are challenged as medicine (only a few BNPs are applied in clinical settings). In order to find a reasonable solution to improving the druggability of BNPs, this review summarizes their bioactive nature based on the enormous pharmacological research and tries to explain the reasons for the poor druggability of BNPs. And then focused on the boosting research on BNPs loaded drug delivery systems, this review further concludes the advantages of drug delivery systems on the druggability improvement of BNPs from the perspective of their bioactive nature, discusses why BNPs need drug delivery systems, and predicts the next direction.

AlphaTracker: a multi-animal tracking and behavioral analysis tool.

Computer vision has emerged as a powerful tool to elevate behavioral research. This protocol describes a computer vision machine learning pipeline called AlphaTracker, which has minimal hardware requirements and produces reliable tracking of multiple unmarked animals, as well as behavioral clustering. AlphaTracker pairs a top-down pose-estimation software combined with unsupervised clustering to facilitate behavioral motif discovery that will accelerate behavioral research. All steps of the protocol are provided as open-source software with graphic user interfaces or implementable with command-line prompts. Users with a graphical processing unit (GPU) can model and analyze animal behaviors of interest in less than a day. AlphaTracker greatly facilitates the analysis of the mechanism of individual/social behavior and group dynamics.

A new acid isolated from V. negundo L. inhibits NLRP3 inflammasome activation and protects against inflammatory diseases.

The NLRP3 inflammasome plays a critical role in the innate immune response, and its excessive activation will cause pyroptotic cell death and be associated with the onset of inflammatory diseases. However, NLRP3 inflammasome targeting therapies are still to be implemented in the clinic setting. Here, we first isolated, purified and characterized a novel Vitenegu acid from V. negundo L. herb that specifically inhibits NLRP3 inflammasome activation, without affecting NLRC4 or AIM2 inflammasomes. Vitenegu acid blocks the oligomerization of NLRP3, thus inhibiting NLRP3 inflammasome assembly and activation. In vivo data show that Vitenegu acid exerts therapeutic effects on NLRP3 inflammasome-dependent inflammation. Taken together, our results suggest that Vitenegu acid is a candidate therapeutic agent for treating NLRP3 inflammasome related diseases.

Three new lanostane triterpenoids and two new amides from Alternaria sp. with NLRP3 inflammasome inhibitory activity.

Three new lanostane triterpenoids (1-3) along with two new amides fatty compounds (4-5) were isolated from the ethyl acetate extract of a culture of the endophytic fungus Alternaria sp. gx-2. Their structures were identified by 1D and 2D NMR spectral data and HRESIMS. Compounds 1-12 were evaluated for their anti-inflammatory and tyrosinase inhibition activities. The isolated compounds did not show inhibitory activities at a concentration of 100 µM against tyrosinase, while under the concentration of 10 µM, the release of lactate dehydrogenase (LDH) inhibition rate of compound 1 was 54.45%, indicating that compound 1 had moderate anti-inflammatory activity on the activation of NLRP3 inflammasome.

3D Domain Adaptive Instance Segmentation via Cyclic Segmentation GANs.

3D instance segmentation for unlabeled imaging modalities is a challenging but essential task as collecting expert annotation can be expensive and time-consuming. Existing works segment a new modality by either deploying pre-trained models optimized on diverse training data or sequentially conducting image translation and segmentation with two relatively independent networks. In this work, we propose a novel Cyclic Segmentation Generative Adversarial Network (CySGAN) that conducts image translation and instance segmentation simultaneously using a unified network with weight sharing. Since the image translation layer can be removed at inference time, our proposed model does not introduce additional computational cost upon a standard segmentation model. For optimizing CySGAN, besides the CycleGAN losses for image translation and supervised losses for the annotated source domain, we also utilize self-supervised and segmentation-based adversarial objectives to enhance the model performance by leveraging unlabeled target domain images. We benchmark our approach on the task of 3D neuronal nuclei segmentation with annotated electron microscopy (EM) images and unlabeled expansion microscopy (ExM) data. The proposed CySGAN outperforms pre-trained generalist models, feature-level domain adaptation models, and the baselines that conduct image translation and segmentation sequentially. Our implementation and the newly collected, densely annotated ExM zebrafish brain nuclei dataset, named NucExM, are publicly available at https://connectomics-bazaar.github.io/proj/CySGAN/index.html.

Abietane diterpenoids from Orthosiphon wulfenioides with NLRP3 inflammasome inhibitory activity.

Wulfenioidones A - K (1-11) were abietane diterpenoids with highly oxidized 6/6/6 aromatic tricyclic skeleton isolated from the whole plant of Orthosiphon wulfenioides, and their planar structures and absolute configurations were elucidated by spectroscopic data interpretation, electronic circular dichroism calculation as well as X-ray crystallography analysis. Bioactivity screening indicated that compounds 1-4, 6 and 8 exhibited lactate dehydrogenase (LDH) inhibition effect with IC50 values ranging from 0.23 to 3.43 µM by preventing the mononuclear macrophage cell pyroptosis induced by double signal stimulation of LPS and nigericin. Western Blot analyses of Caspase-1 and IL-1ß down-regulation exhibited that compound 1 could selectively inhibit NLRP3 inflammasome, and the cell morphological observation further supported that compound 1 prevented macrophage cell pyroptosis.

Nudifloids A-N, structurally diverse 3,4-seco-labdane diterpenoids from Callicarpa nudiflora with inflammatory inhibitory activity.

Fourteen undescribed seco-type diterpenoids, named nudifloids A-N, together with ten known analogs, were isolated from the leaves of Callicarpa nudiflora. Nudifloids A-N had a characteristic 3,4-seco-labdane-type diterpenoid skeleton, whereas nudifloids A-C and K-N were 3,4-seco-norditerpenoids. Nudifloid A was the first example of a 3,4-seco-12,13,14,15,16-quartnor-labdane diterpenoid, with a seven-membered lactone ring formed through esterification between C-3 and C-11. Nudifloids B and C were a pair of highly modified 3,4-seco-labdane nor-diterpenoid epimers, of which C-2 and C-18 were cyclized together to form a cyclohexene fragment. The structures of these undescribed diterpenoids were established by spectroscopic analysis and reference data. The anti-inflammatory activity of diterpenoids in rich yield was evaluated by analyzing the inhibition of lipopolysaccharide plus nigericin-induced pyroptosis in J774A.1 cells. Nudifloids D and E exhibited prominent anti-NLRP3 inflammasome activity, with IC50 values of 1.80 and 1.59 µM, respectively. Cell permeability assays revealed that nudifloid D inhibited pyroptosis, which could ameliorate inflammation by blocking the activation of the NLRP3 inflammasome.

An ATG4B inhibitor blocks autophagy and sensitizes Sorafenib inhibition activities in HCC tumor cells.

Autophagy related 4B (ATG4B) which regulates autophagy by promoting the formation of autophagosome through reversible modification of LC3, is closely related to cancer cell growth and drug resistance, and therefore is an attractive therapeutic target. Recently, ATG4B inhibitors have been reported, yet with drawbacks including weak potency. To discover more promising ATG4B inhibitors, we developed a high-throughput screening (HTS) assay and identified a new ATG4B inhibitor named DC-ATG4in. DC-ATG4in directly binds to ATG4B and inhibits its enzyme activity with an IC50 of 3.08 ± 0.47 µM. We further confirmed that DC-ATG4in is an autophagy inhibitor and blocks autophagy induced by Sorafenib in Hepatocellular Carcinoma (HCC) cells. More importantly, combination of DC-ATG4in with Sorafenib synergized the cancer cell killing effect and proliferation inhibition activities on HCC cells. Our data suggested that inactivation of autophagy via ATG4B inhibition may be a viable strategy to sensitize existing targeted therapy such as Sorafenib in the future.

16,17-dinor-abietane diterpenoids from Casearia kurzii.

Eleven undescribed 16,17-dinor-abietane diterpenoids, caseazins A-K (1-11), and ten known diterpenoids (12-21) were isolated from the twigs and leaves of Casearia kurzii (Flacourtiaceae). Caseazins A-K were the first abietane -type dinorditerpenoids to have been isolated from the plant of Casearia kurzii. Their chemical structures were elucidated using a combination of 1D and 2D NMR spectroscopy and mass spectrometry. The absolute configurations of 5 and 10 were established by electronic circular dichroism calculations. Moreover, compounds 2, 3, 13, 14, and 18 exhibited anti-inflammatory activity with IC50 values of 0.17, 0.36, 6.55, 1.30, and 4.53 µM, respectively. IL-1ß and caspase-1 analyses suggested that compound 14 inhibited NLRP3 inflammasome activation and blocked macrophage pyroptosis.

Large Spin Hall Conductivity and Excellent Hydrogen Evolution Reaction Activity in Unconventional PtTe1.75 Monolayer.

Two-dimensional (2D) materials have gained lots of attention due to the potential applications. In this work, we propose that based on first-principles calculations, the (2 × 2) patterned PtTe2 monolayer with kagome lattice formed by the well-ordered Te vacancy (PtTe1.75) hosts large and tunable spin Hall conductivity (SHC) and excellent hydrogen evolution reaction (HER) activity. The unconventional nature relies on the A1 @ 1b band representation of the highest valence band without spin-orbit coupling (SOC). The large SHC comes from the Rashba SOC in the noncentrosymmetric structure induced by the Te vacancy. Even though it has a metallic SOC band structure, the ℤ2 invariant is well defined because of the existence of the direct bandgap and is computed to be nontrivial. The calculated SHC is as large as 1.25 × 103 ℏ e (Ω cm)-1 at the Fermi level (EF ). By tuning the chemical potential from EF - 0.3 to EF + 0.3 eV, it varies rapidly and monotonically from -1.2 × 103 to 3.1 × 1 0 3 ℏ e Ω   cm - 1 . In addition, we also find that the Te vacancy in the patterned monolayer can induce excellent HER activity. Our results not only offer a new idea to search 2D materials with large SHC, i.e., by introducing inversion-symmetry breaking vacancies in large SOC systems, but also provide a feasible system with tunable SHC (by applying gate voltage) and excellent HER activity.

MetaHMEI: meta-learning for prediction of few-shot histone modifying enzyme inhibitors.

MOTIVATION: Histones are the chief protein components of chromatin, and the chemical modifications on histones crucially influence the transcriptional state of related genes. Histone modifying enzyme (HME), responsible for adding or removing the chemical labels, has emerged as a very important class of drug target, with a few HME inhibitors launched as anti-cancerous drugs and tens of molecules under clinical trials. To accelerate the drug discovery process of HME inhibitors, machine learning-based predictive models have been developed to enrich the active molecules from vast chemical space. However, the number of compounds with known activity distributed largely unbalanced among different HMEs, particularly with many targets of less than a hundred active samples. In this case, it is difficult to build effective virtual screening models directly based on machine learning. RESULTS: To this end, we propose a new Meta-learning-based Histone Modifying Enzymes Inhibitor prediction method (MetaHMEI). Our proposed MetaHMEI first uses a self-supervised pre-training approach to obtain high-quality molecular substructure embeddings from a large unlabeled chemical dataset. Then, MetaHMEI exploits a Transformer-based encoder and meta-learning framework to build a prediction model. MetaHMEI allows the effective transfer of the prior knowledge learned from HMEs with sufficient samples to HMEs with a small number of samples, so the proposed model can produce accurate predictions for HMEs with limited data. Extensive experimental results on our collected and curated HMEs datasets show that MetaHMEI is better than other methods in the case of few-shot learning. Furthermore, we applied MetaHMEI in the virtual screening process of histone JMJD3 inhibitors and successfully obtained three small molecule inhibitors, further supporting the validity of our model.