OD-MVSNet: Omni-dimensional dynamic multi-view stereo network.

Multi-view stereo based on learning is a critical task in three-dimensional reconstruction, enabling the effective inference of depth maps and the reconstruction of fine-grained scene geometry. However, the results obtained by current popular 3D reconstruction methods are not precise, and achieving high-accuracy scene reconstruction remains challenging due to the pervasive impact of feature extraction and the poor correlation between cost and volume. In addressing these issues, we propose a cascade deep residual inference network to enhance the efficiency and accuracy of multi-view stereo depth estimation. This approach builds a cost-volume pyramid from coarse to fine, generating a lightweight, compact network to improve reconstruction results. Specifically, we introduce the omni-dimensional dynamic atrous spatial pyramid pooling (OSPP), a multiscale feature extraction module capable of generating dense feature maps with multiscale contextual information. The feature maps encoded by the OSPP module can generate dense point clouds without consuming significant memory. Furthermore, to alleviate the issue of feature mismatch in cost volume regularization, we propose a normalization-based 3D attention module. The 3D attention module aggregates crucial information within the cost volume across the dimensions of channel, spatial, and depth. Through extensive experiments on benchmark datasets, notably DTU, we found that the OD-MVSNet model outperforms the baseline model by approximately 1.4% in accuracy loss, 0.9% in completeness loss, and 1.2% in overall loss, demonstrating the effectiveness of our module.

Synthesis of Coumarin-Based Photosensitizers for Enhanced Antibacterial Type I/II Photodynamic Therapy.

Photodynamic therapy (PDT) is an effective method for treating microbial infections by leveraging the unique photophysical properties of photosensitizing agents, but issues such as fluorescence quenching and the restricted generation of reactive oxygen species (ROS) under hypoxic conditions still remain. In this study, we successfully synthesized and designed a coumarin-based aggregation-induced emission luminogen (AIEgen), called ICM, that shows a remarkable capacity for type I ROS and type II ROS generation. The 1O2 yield of ICM is 0.839. The ROS it produces include hydroxyl radicals (HO•) and superoxide anions (O2•-), with highly effective antibacterial properties specifically targeting Staphylococcus aureus (a Gram-positive bacterium). Furthermore, ICM enables broad-spectrum fluorescence imaging and exhibits excellent biocompatibility. Consequently, ICM, as a potent type I photosensitizer for eliminating pathogenic microorganisms, represents a promising tool in addressing the threat posed by these pathogens.

Ex Situ Gaseous Reagent for Multicomponent Amine Bioconjugation.

We report a minimalist gaseous sulfonyl-chloride-derived reagent for multicomponent bioconjugation with amine, phenol, or aniline reagents to afford urea or carbamate products. With the utilization of a gas-phase reagent for a reaction mediated by metal ions, a variety of biologically relevant molecules, such as saccharide, poly(ethylene glycol), fluorophore, and affinity tag, can be efficiently cross-linked to the N terminus or lysine side-chain amines on natural polypeptides or proteins.

Theoretical study of transition metal-doped ß12 borophene as a new single-atom catalyst for carbon dioxide electroreduction.

The electrocatalytic carbon dioxide reduction reaction (CO2RR) presents a viable and cost-effective approach for the elimination of CO2 by transforming it into valuable products. Nevertheless, this process is impeded by the absence of exceptionally active and stable catalysts. Herein, a new type of electrocatalyst of transition metal (TM)-doped ß12-borophene (TM@ß12-BM) is investigated via density functional theory (DFT) calculations. Through comprehensive screening, two promising single-atom catalysts (SACs), Sc@ß12-BM and Y@ß12-BM, are successfully identified, exhibiting high stability, catalytic activity and selectivity for the CO2RR. The C1 products methane (CH4) and methanol (CH3OH) are synthesized with limiting potentials (UL) of -0.78 V and -0.56 V on Sc@ß12-BM and Y@ß12-BM, respectively. Meanwhile, CO2 is more favourable for reduction into the C2 product ethanol (CH3CH2OH) compared to ethylene (C2H4) via C-C coupling on these two SACs. More importantly, the dynamic barriers of the key C-C coupling step are 0.53 eV and 0.73 eV for the "slow-growth" sampling approach in the explicit water molecule model. Furthermore, Sc@ß12-BM and Y@ß12-BM exhibit higher selectivity for producing C1 compounds (CH4 and CH3OH) than C2 (CH3CH2OH) in the CO2RR. Compared with Sc@ß12-BM, Y@ß12-BM demonstrates superior inhibition of the competitive hydrogen evolution reaction (HER) in the liquid phase. These results not only demonstrate the great potential of SACs for direct reduction of CO2 to C1 and C2, but also help in rationally designing high-performance SACs.

Selective Macrocyclization of Unprotected Peptides with an Ex Situ Gaseous Linchpin Reagent.

Peptide cyclization has dramatic effects on a variety of important properties, enhancing metabolic stability, limiting conformational flexibility, and altering cellular entry and intracellular localization. The hydrophilic, polyfunctional nature of peptides creates chemoselectivity challenges in macrocyclization, especially for natural sequences without biorthogonal handles. Herein, we describe a gaseous sulfonyl chloride derived reagent that achieves amine-amine, amine-phenol, and amine-aniline crosslinking through a minimalist linchpin strategy that affords macrocyclic urea or carbamate products. The cyclization reaction is metal-mediated and involves a novel application of sulfine species that remains unexplored in aqueous or biological contexts. The aqueous method delivers unique cyclic or bicyclic topologies directly from a variety of natural bioactive peptides without the need for protecting-group strategies.

Synthetic steroid of 5α-Androst-3ß,5α,6ß-Triol alleviates acute lung injury via inhibiting inflammation and oxidative stress.

Acute lung injury (ALI) is a severe and potentially fatal respiratory condition with limited treatment options. The pathological evolution of ALI is driven by persistent inflammation, destruction of the pulmonary vascular barrier and oxidative stress. Evidence from prior investigations has identified 5α-androst-3ß,5α,6ß-Triol (TRIOL), a synthetic analogue of the naturally occurring neuroprotective compound cholestane-3ß,5α,6ß-triol, possesses notable anti-inflammatory and antioxidative properties. However, the precise effects of TRIOL on alleviating lung injury along with the mechanisms, have remained largely unexplored. Here, TRIOL exhibited pronounced inhibitory actions on lipopolysaccharide (LPS)-induced inflammation and oxidative stress damage in both lung epithelial and endothelial cells. This protective effect is achieved by its ability to mitigate oxidative stress and restrain the inflammatory cascade orchestrated by nuclear factor-kappa B (NF-κB), thereby preserving the integrity of the pulmonary epithelial barrier. We further validated that TRIOL can attenuate LPS-induced lung injury in rats and mice by reducing inflammatory cell infiltration and improving pulmonary edema. Furthermore, TRIOL decreased the pro-inflammatory factors and increased of anti-inflammatory factors induced by LPS. In conclusion, our study presents TRIOL as a promising novel candidate for the treatment of ALI.

Preparation and research of new black zirconia ceramics.

The existing black zirconia has problems such as uneven color development, poor stability, expensive raw materials, and harm to the human body and the environment. In order to solve the above problems, this paper intends to use NiAl2O4, NiTiO3, Fe2O3 as chromophore, zirconia as a matrix, and a solid-phase method is used to prepare high-performance black zirconia ceramics. The method avoids the introduction of toxic elements, and at the same time, it is more economical in the selection of color-developing pigments. The experimental results show that black zirconia ceramics with uniform color, continuous adjustment and high temperature stability can be obtained. When the sintering temperature is lower than 1450 °C and the color material mixing ratio is 10 wt.%, the mechanical properties and optical properties of the obtained samples optimum, the overall reflectance of the sample is less than 10 wt.%, which meets the conditions for market application. These black ceramics can be widely used in high-tech fields such as mobile phone backplanes, photovoltaic industry and high-end decorative materials, and have broad application prospects.

CO2 electrocatalytic reduction to ethylene and its application outlook in food science.

The efficient conversion of CO2 is considered to be an important step toward carbon emissions peak and carbon neutrality. Presently, great efforts have been devoted to the study of efficient nanocatalysts, electrolytic cell, and electrolytes to achieve high reactivity and selectivity in the electrochemical reduction of CO2 to mono- and multi-carbon (C2+) compounds. However, there are very few reviews focusing on highly reactive and selective ethylene production and application in the field of electrochemical carbon dioxide reduction reaction (CO2RR). Ethylene is a class of multi-carbon compounds that are widely applied in industrial, ecological, and agricultural fields. This review focuses especially on the convertibility of CO2 reduction to generate ethylene technology in practical applications and provides a detailed summary of the latest technologies for the efficient production of ethylene by CO2RR and suggests the potential application of CO2RR systems in food science to further expand the application market of CO2RR for ethylene production.

Polyol recognition in catalysis: toward selective modification of glycosylated polypeptides with boronic acid-rhodium(II) catalysts.

Proximity-induced methodologies for peptide and protein modification have been developed using recognition elements like inhibitors, antibodies, or affinity tags on amino acids. However, the recognition of saccharides for chemical modification remains widely unexplored. Studies exploring boronic acids and their derivatives have shown their alluring capabilities as selective molecular recognition elements for saccharides, and in this study we describe the application of these ideas to the discovery of a catalytic proximity-induced methodology for covalent modification of glycopeptides using boronic acids as a saccharide recognition element.

Femtosecond Laser Direct Writing of Gecko-Inspired Switchable Adhesion Interfaces on a Flexible Substrate.

Biomimetic switchable adhesion interfaces (BSAIs) with dynamic adhesion states have demonstrated significant advantages in micro-manipulation and bio-detection. Among them, gecko-inspired adhesives have garnered considerable attention due to their exceptional adaptability to extreme environments. However, their high adhesion strength poses challenges in achieving flexible control. Herein, we propose an elegant and efficient approach by fabricating three-dimensional mushroom-shaped polydimethylsiloxane (PDMS) micropillars on a flexible PDMS substrate to mimic the bending and stretching of gecko footpads. The fabrication process that employs two-photon polymerization ensures high spatial resolution, resulting in micropillars with exquisite structures and ultra-smooth surfaces, even for tip/stem ratios exceeding 2 (a critical factor for maintaining adhesion strength). Furthermore, these adhesive structures display outstanding resilience, enduring 175% deformation and severe bending without collapse, ascribing to the excellent compatibility of the micropillar's composition and physical properties with the substrate. Our BSAIs can achieve highly controllable adhesion force and rapid manipulation of liquid droplets through mechanical bending and stretching of the PDMS substrate. By adjusting the spacing between the micropillars, precise control of adhesion strength is achieved. These intriguing properties make them promising candidates for various applications in the fields of microfluidics, micro-assembly, flexible electronics, and beyond.

Advances in biomimetic hydrogels for organoid culture.

An organoid is a 3-dimensional (3D) cell culture system that mimics the structural and functional characteristics of organs, and it has promising applications in regenerative medicine, precision drug screening and personalised therapy. However, current culture techniques of organoids usually use mouse tumour-derived scaffolds (Matrigel) or other animal-derived decellularised extracellular matrices as culture systems with poorly defined components and undefined chemical and physical properties, which limit the growth of organoids and the reproducibility of culture conditions. In contrast, some synthetic culture materials have emerged in recent years with well-defined compositions, and flexible adjustment and optimisation of physical and chemical properties, which can effectively support organoid growth and development and prolong survival time of organoid in vitro. In this review, we will introduce the challenge of animal-derived decellularised extracellular matrices in organoid culture, and summarise the categories of biomimetic hydrogels currently used for organoid culture, and then discuss the future opportunities and perspectives in the development of advanced hydrogels in organoids. We hope that this review can promote academic communication in the field of organoid research and provide some assistance in advancing the development of organoid cultivation technology.

TTFields Prolonged the PFS of Epithelioid Glioblastoma Patient: A Case Report.

Epithelioid glioblastoma (EGBM, classified as glioblastoma, IDH wild type, grade 4 according to the fifth edition of the World Health Organization (WHO) Classification of Tumors of the Central Nervous System (CNS) (WHO CNS5)) is a highly aggressive malignancy, with a median progression-free survival (mPFS) of about 6 months in adults. The application of tumor-treating fields (TTFields, possessing anti-cancer capabilities via anti-mitotic effects) in the maintenance of temozolomide (TMZ) chemotherapy showed a benefit for prolonging the mPFS of newly diagnosed glioblastoma (GBM) for patients for up to 6.9 months in the EF-14 clinical trial (NCT00916409). However, studies focusing on the effect of TTFields in EGBM treatment are very limited due to the rarity of EGBM. Here, we have reported a case of a 28-year-old male (recurrent left-sided limb twitching for 1 month and dizziness for 1 week) diagnosed with EGBM. A right frontal lobe occupancy was detected by magnetic resonance imaging (MRI), and a total tumor resection was performed. Meanwhile, a postoperative histopathology test, including immunohistochemistry and molecular characterization, was conducted, and the results revealed a BRAF V600E mutation, no co-deletion of 1p and 19q, and negative O-6-methylguanine DNA methyltransferase (MGMT) promoter methylation. Then, chemoradiotherapy was conducted, and TTFields and TMZ were performed sequentially. Notably, a long-term PFS of 34 months and a Karnofsky Performance Scale (KPS) of 90 were achieved by the patient on TTFields combined with TMZ, whose average daily usage of TTFields was higher than 90%.

Position-Aware Relation Learning for RGB-Thermal Salient Object Detection.

Salient object detection (SOD) is an important task in computer vision that aims to identify visually conspicuous regions in images. RGB-Thermal SOD combines two spectra to achieve better segmentation results. However, most existing methods for RGB-T SOD use boundary maps to learn sharp boundaries, which lead to sub-optimal performance as they ignore the interactions between isolated boundary pixels and other confident pixels. To address this issue, we propose a novel position-aware relation learning network (PRLNet) for RGB-T SOD. PRLNet explores the distance and direction relationships between pixels by designing an auxiliary task and optimizing the feature structure to strengthen intra-class compactness and inter-class separation. Our method consists of two main components: A signed distance map auxiliary module (SDMAM), and a feature refinement approach with direction field (FRDF). SDMAM improves the encoder feature representation by considering the distance relationship between foreground-background pixels and boundaries, which increases the inter-class separation between foreground and background features. FRDF rectifies the features of boundary neighborhoods by exploiting the features inside salient objects. It utilizes the direction relationship of object pixels to enhance the intra-class compactness of salient features. In addition, we constitute a transformer-based decoder to decode multispectral feature representation. Experimental results on three public RGB-T SOD datasets demonstrate that our proposed method not only outperforms the state-of-the-art methods, but also can be integrated with different backbone networks in a plug-and-play manner. Ablation study and visualizations further prove the validity and interpretability of our method.

Directly targeting ASC by lonidamine alleviates inflammasome-driven diseases.

BACKGROUND: Dysregulated activation of the inflammasome is involved in various human diseases including acute cerebral ischemia, multiple sclerosis and sepsis. Though many inflammasome inhibitors targeting NOD-like receptor protein 3 (NLRP3) have been designed and developed, none of the inhibitors are clinically available. Growing evidence suggests that targeting apoptosis-associated speck-like protein containing a CARD (ASC), the oligomerization of which is the key event for the assembly of inflammasome, may be another promising therapeutic strategy. Lonidamine (LND), a small-molecule inhibitor of glycolysis used as an antineoplastic drug, has been evidenced to have anti-inflammation effects. However, its anti-inflammatory mechanism is still largely unknown. METHODS: Middle cerebral artery occlusion (MCAO), experimental autoimmune encephalomyelitis (EAE) and LPS-induced sepsis mice models were constructed to investigate the therapeutic and anti-inflammasome effects of LND. The inhibition of inflammasome activation and ASC oligomerization by LND was evaluated using western blot (WB), immunofluorescence (IF), quantitative polymerase chain reaction (qPCR) and enzyme-linked immunosorbent assay (ELISA) in murine bone marrow-derived macrophages (BMDMs). Direct binding of LND with ASC was assessed using molecular mock docking, surface plasmon resonance (SPR), and drug affinity responsive target stability (DARTS). RESULTS: Here, we find that LND strongly attenuates the inflammatory injury in experimental models of inflammasome-associated diseases including autoimmune disease-multiple sclerosis (MS), ischemic stroke and sepsis. Moreover, LND blocks diverse types of inflammasome activation independent of its known targets including hexokinase 2 (HK2). We further reveal that LND directly binds to the inflammasome ligand ASC and inhibits its oligomerization. CONCLUSIONS: Taken together, our results identify LND as a broad-spectrum inflammasome inhibitor by directly targeting ASC, providing a novel candidate drug for the treatment of inflammasome-driven diseases in clinic.

Direct formation and site-selective elaboration of methionine sulfoximine in polypeptides.

Sulfoximines are emerging moieties for medicinal and biological chemistry, due in part to their efficacy in selective inhibition of amide-forming enzymes such as γ-glutamylcysteine synthetase. While small-molecule sulfoximines such as methionine sulfoximine (MSO) and its derivatives are well studied, structures with methionine sulfoximine residues within complex polypeptides have been generally inaccessible. This paper describes a straightforward means of late-stage one-step oxidation of methionine residues within polypeptides to afford NH-sulfoximines. We also present chemoselective subsequent elaboration, most notably by copper(ii)-mediated N-H cross-coupling at methionine sulfoximine residues with arylboronic acid reagents. This development serves as a strategy to incorporate diverse sulfoximine structures within natural polypeptides, and also identifies the methionine sulfoximine residue as a new site for bioorthogonal, chemoselective bioconjugation.

Dual-Boronic Acid Reagents That Combine Dynamic and Covalent Bioconjugation.

Boronic acids and boronate esters find appreciable use in chemical biology. Molecules containing orthogonal boronic acid pairs can be utilized for sequential metal-catalyzed cross-couplings for facile preparation of complex bioconjugates including protein-protein conjugates. In this paper, we expand bis-boronic acid reagents for tandem covalent and dynamic bioconjugation. Sequential cross-coupling of 2-nitroarylboronic acid with cysteine residues and condensation of phenylboronic acid with salicylhydroxamic acids (SHA) readily afforded bioconjugates under physiological conditions with dual covalent and dynamic linkages. Both small molecule- and macromolecule-protein conjugates were amenable with this approach and reversible upon addition of excess unfunctionalized SHA or reactive oxygen species. These investigations provide new insights into the kinetic stability of SHA adducts.

Seeking Subjectivity in Visual Emotion Distribution Learning.

Visual Emotion Analysis (VEA), which aims to predict people's emotions towards different visual stimuli, has become an attractive research topic recently. Rather than a single label classification task, it is more rational to regard VEA as a Label Distribution Learning (LDL) problem by voting from different individuals. Existing methods often predict visual emotion distribution in a unified network, neglecting the inherent subjectivity in its crowd voting process. In psychology, the Object-Appraisal-Emotion model has demonstrated that each individual's emotion is affected by his/her subjective appraisal, which is further formed by the affective memory. Inspired by this, we propose a novel Subjectivity Appraise-and-Match Network (SAMNet) to investigate the subjectivity in visual emotion distribution. To depict the diversity in crowd voting process, we first propose the Subjectivity Appraising with multiple branches, where each branch simulates the emotion evocation process of a specific individual. Specifically, we construct the affective memory with an attention-based mechanism to preserve each individual's unique emotional experience. A subjectivity loss is further proposed to guarantee the divergence between different individuals. Moreover, we propose the Subjectivity Matching with a matching loss, aiming at assigning unordered emotion labels to ordered individual predictions in a one-to-one correspondence with the Hungarian algorithm. Extensive experiments and comparisons are conducted on public visual emotion distribution datasets, and the results demonstrate that the proposed SAMNet consistently outperforms the state-of-the-art methods. Ablation study verifies the effectiveness of our method and visualization proves its interpretability.

Storage Quality Variation of Mushrooms (Flammulina velutipes) after Cold Plasma Treatment.

Flammulina velutipes is susceptible to mechanical damage, water loss, microbial growth, and other factors that lead to postharvest deterioration, thereby shortening the storage period. The purpose of this study was to analyze the effects of cold plasma treatment on the physicochemical properties and antioxidant capacity of F. velutipes during storage at 4 °C for 21 days. Compared to the control group, cold plasma cold sterilization (CPCS) treatment (150 Hz, 95 kV for 150 s) effectively inhibited the growth and multiplication of microorganisms on the surface of F. velutipes, with no significant effect on the fresh weight change and the superoxide anion generation rate, but with a higher postharvest 1,1-dephenyl-2-picrylhydrzyl (DPPH) clearance rate. Moreover, CPCS increased antioxidant enzyme activities, delayed both malondialdehyde (MDA) accumulation and vitamin C loss, inhibited the browning reaction and polyphenol oxidases (PPO) activity and protected F. velutipes cell membrane from disruption. In general, CPCS not only achieved bacteriostatic effects on F. velutipes during storage, but also reduced cell damage from free radical oxidation, resulting in better postharvest quality and longer shelf life.

Tandem H/D Exchange-SET Reductive Deuteration Strategy for the Synthesis of α,ß-Deuterated Amines Using D2O.

α,ß-Deuterated amines are crucial for the development of deuterated drugs. We intend to introduce the novel tandem H/D exchange-single electron transfer (SET) reductive deuteration strategy with high pot- and reagent-economy by the synthesis of α,ß-deuterated amine using nitrile as the precursor. The H/D exchange of the -CH2CN group was achieved by D2O/Et3N, which were also the required reagents in the tandem SmI2-mediated SET reductive deuteration of the α-deuterated nitrile. The potential application of this method was further showcased by the synthesis of bevantolol-d4.

Stimuli-Aware Visual Emotion Analysis.

Visual emotion analysis (VEA) has attracted great attention recently, due to the increasing tendency of expressing and understanding emotions through images on social networks. Different from traditional vision tasks, VEA is inherently more challenging since it involves a much higher level of complexity and ambiguity in human cognitive process. Most of the existing methods adopt deep learning techniques to extract general features from the whole image, disregarding the specific features evoked by various emotional stimuli. Inspired by the Stimuli-Organism-Response (S-O-R) emotion model in psychological theory, we proposed a stimuli-aware VEA method consisting of three stages, namely stimuli selection (S), feature extraction (O) and emotion prediction (R). First, specific emotional stimuli (i. e., color, object, face) are selected from images by employing the off-the-shelf tools. To the best of our knowledge, it is the first time to introduce stimuli selection process into VEA in an end-to-end network. Then, we design three specific networks, i. e., Global-Net, Semantic-Net and Expression-Net, to extract distinct emotional features from different stimuli simultaneously. Finally, benefiting from the inherent structure of Mikel's wheel, we design a novel hierarchical cross-entropy loss to distinguish hard false examples from easy ones in an emotion-specific manner. Experiments demonstrate that the proposed method consistently outperforms the state-of-the-art approaches on four public visual emotion datasets. Ablation study and visualizations further prove the validity and interpretability of our method.