Discovery of EBI-907: A highly potent and orally active B-Raf(V600E) inhibitor for the treatment of melanoma and associated cancers.

A novel series of pyrazolo[3,4-c]isoquinoline derivatives was discovered as B-Raf(V600E) inhibitors through scaffold hopping based on a literature lead PLX4720. Further SAR exploration and optimization led to the discovery of potent B-Raf(V600E) inhibitors with good oral bioavailability in rats and dogs. One of the compounds EBI-907 (13g) demonstrated excellent in vivo efficacy in B-Raf(V600E) dependent Colo-205 tumor xenograft models in mouse and is under preclinical studies for the treatment of melanoma and B-Raf(V600E) associated cancers.

Broadband optical isolator based on helical metamaterials.

Based on helical metamaterials, a new broadband optical isolator with a triple-helix structure is proposed in this paper. The right-handed circularly polarized light can transmit through the isolator with its polarization unchanged. The reverse propagating light, which is caused by the reflection of the latter optical devices, is converted into left-handed circularly polarized light that is suppressed by the proposed isolator because of absorption. Our design has some unprecedented advantages such as broad frequency ranges and a compact structure; moreover, neither polarizers nor adscititious magnetic fields are required. Properties of the isolator are investigated using the finite-difference time-domain method, and this phenomenon is studied by the mechanism of helical antenna theory.

Differentiating behavioral impact with or without vaccination certification under mass vaccination and non-pharmaceutical interventions on mitigating COVID-19.

As COVID-19 vaccines became widely available worldwide, many countries implemented vaccination certification, also known as a "green pass", to promote and expedite vaccination on containing virus spread from the latter half of 2021. This policy allowed those vaccinated to have more freedom in public activities compared to more constraints on the unvaccinated in addition to existing non-pharmaceutical interventions (NPIs). Accordingly, the vaccination certification also induced heterogeneous behaviors of unvaccinated and vaccinated groups. This makes it essential yet challenging to model the behavioral impact of vaccination certification on the two groups and the transmission dynamics of COVID-19 within and between the groups. Very limited quantitative work is available for addressing these purposes. Here we propose an extended epidemiological model SEIQRD[Formula: see text] to effectively distinguish the behavioral impact of vaccination certification on unvaccinated and vaccinated groups through incorporating two contrastive transmission chains. SEIQRD[Formula: see text] also quantifies the impact of the green pass policy. With the resurgence of COVID-19 in Greece, Austria, and Israel in 2021, our simulation results indicate that their implementation of vaccination certification brought about more than a 14-fold decrease in the total number of infections and deaths as compared to a scenario with no such a policy. Additionally, a green pass policy may offer a reasonable practical solution to strike the balance between public health and individual's freedom during the pandemic.

Polyphenol-hyaluronic acid-based hydrogel remodels the wound microenvironment and eliminates bacterial infection for accelerating wound healing.

The wound microenvironment, often characterized by alkaline pH and severe hypoxia, presents significant challenges to the healing of bacterial-infected wounds. While considerable research has focused on improving wound healing through effective bacterial elimination using advanced therapeutic approaches, the importance of regulating the wound microenvironment has received less emphasis. In this work, we developed a biocompatible hydrogel, HTFC, by incorporating CaO2 nanoparticles (CaO2 NPs) into a gel formed by tannic acid (TA), hyaluronic acid (HA), and Fe3+. The HA and TA in HTFC hydrogel help to create a slightly acidic microenvironment, facilitating the decomposition of CaO2 NPs to release H2O2 for chemodynamic therapy (CDT). The reduction properties of TA promote the recycling of Fe3+/Fe2+, enhancing CDT efficacy and partially converting H2O2 to O2, thereby alleviating hypoxia. Additionally, FeIIITA complexes in HTFC enhance CDT through photothermal therapy (PTT)-induced improvement of the Fenton reaction. This multifunctional hydrogel, with its synergistic effects of PTT and CDT, along with its ability to remodel the wound microenvironment from hypoxic and alkaline to normoxic and acidic, accelerates the bacterial-infected wound healing process.

Transformation Decoupling Strategy based on Screw Theory for Deterministic Point Cloud Registration with Gravity Prior.

Point cloud registration is challenging in the presence of heavy outlier correspondences. This paper focuses on addressing the robust correspondence-based registration problem with gravity prior that often arises in practice. The gravity directions are typically obtained by inertial measurement units (IMUs) and can reduce the degree of freedom (DOF) of rotation from 3 to 1. We propose a novel transformation decoupling strategy by leveraging the screw theory. This strategy decomposes the original 4-DOF problem into three sub-problems with 1-DOF, 2-DOF, and 1-DOF, respectively, enhancing computation efficiency. Specifically, the first 1-DOF represents the translation along the rotation axis, and we propose an interval stabbing-based method to solve it. The second 2-DOF represents the pole which is an auxiliary variable in screw theory, and we utilize a branch-and-bound method to solve it. The last 1-DOF represents the rotation angle, and we propose a global voting method for its estimation. The proposed method solves three consensus maximization sub-problems sequentially, leading to efficient and deterministic registration. In particular, it can even handle the correspondence-free registration problem due to its significant robustness. Extensive experiments on both synthetic and real-world datasets demonstrate that our method is more efficient and robust than state-of-the-art methods, even when dealing with outlier rates exceeding 99%.

EGCG-vanadium nanomedicine with neutral pH Fenton reaction activity inhibits heat shock proteins for enhanced photothermal/chemodynamic therapy.

A burgeoning interest has recently focused on the development of nanomedicine to integrate noninvasive photothermal therapy (PTT) and chemodynamic therapy (CDT) for synergistic tumor treatments, owing to PTT's amplification effect on CDT. However, challenges emerge as hyperthermia often induces an unwarranted overexpression of cytoprotective heat shock proteins (HSPs), thereby curtailing PTT efficacy. Additionally, the nearly neutral tumor intracellular pH (pHi ≈ 7.2) that handicaps the Fenton reaction poses a leading limitation to CDT. Addressing these hurdles, we introduce EVP, a nanomedicine developed through the straightforward assembly of epigallocatechin gallate (EGCG), vanadium sulfate (VOSO4), and Pluronic F-127 (PF127). EVP comprehensively downregulates overexpressed HSPs (HSP 60, 70, 90) through the collaborative action of EGCG and vanadyl (VO2+). Moreover, the tumor intracellular pH-processed Fenton-like reaction by VO2+ ensures highly efficient hydroxyl radicals (OH) production in cytosols, overcoming the stringent acidity requirement for CDT. Additionally, the hyperthermia induced by PTT augments OH production, further enhancing CDT efficacy. In vitro and in vivo experiments validate EVP's excellent biocompatibility and potent tumor inhibition, highlighting its substantial potential in tumor therapy.

Arginine-Functionalized Thin Film Composite Forward Osmosis Membrane Integrating Antifouling and Antibacterial Effects.

Membrane fouling is an inevitable obstacle of polyamide composite forward osmosis (FO) membranes in oily wastewater treatment. In this study, zwitterionic arginine (Arg) is grafted onto nascent self-made FO polyamide poly(ether sulfone) (PA-PES) membrane, imparting superior hydrophilic, antifouling, and antibacterial properties to the membrane. Detailed characterizations revealed that the Arg-modified (Arg-PES) membrane presented obviously surface positively charged and unique morphology. Results showed that our strategy endowed the optimized membrane, the water flux increased by 113.2% compared to the pristine membrane, respectively, meanwhile keeping high NaCl rejection > 93.9% (with DI water as feed solution and 0.5 M NaCl as draw solution, FO mode). The dynamic fouling tests indicated that the Arg-PES membranes exhibited much improved antifouling performance towards oily wastewater treatment. The flux recovery ratios of the membrane were as high as 92.0% for cationic emulsified oil (cetyl pyridinium chloride, CPC), 87.0% for neutral emulsified oil (Tween-80), and 86.0% for anionic emulsified oil (sodium dodecyl sulfate, SDS) after washing, respectively. Meanwhile, the Arg-PES membranes assembled with guanidine cationic groups exhibited an enhanced antibacterial property against E. coli, which exhibited a high antibacterial efficiency of approximately 96%. Consequently, the newly arginine functionalized FO membrane possesses impressive antifouling performance, while simultaneously resisting bacterial invasion, thus rendering it an ideal alternative for oily wastewater treatment in the FO process.

Robust Face Alignment via Inherent Relation Learning and Uncertainty Estimation.

Human tends to locate the facial landmarks with heavy occlusion by their relative position to the easily identified landmarks. The clue is defined as the landmark inherent relation while it is ignored by most existing methods. In this paper, we present Dynamic Sparse Local Patch Transformer (DSLPT), a novel face alignment framework for the inherent relation learning and uncertainty estimation. Unlike most existing methods that regress facial landmarks directly from global features, the DSLPT first generates a rough representation of each landmark from a local patch cropped from the feature map and then adaptively aggregates them by a case dependent inherent relation. Finally, the DSLPT predicts the coordinate and uncertainty of each landmark by regressing their probability distribution from the output features. Moreover, we introduce a coarse-to-fine framework to incorporate with DSLPT for an improved result. In the framework, the position and size of each patch are determined by the probability distribution of the corresponding landmark predicted in the previous stage. The dynamic patches will ensure a fine-grained landmark representation for inherent relation learning so that a rough prediction result can gradually converge to the target facial landmarks. We integrate the coarse-to-fine model into an end-to-end training pipeline and carry out experiments on the mainstream benchmarks. The results demonstrate that the DSLPT achieves state-of-the-art performance with much less computational complexity. The codes and models are available at https://github.com/Jiahao-UTS/DSLPT.

A Metal-Polyphenol-Based Oxygen Economizer and Fenton Reaction Amplifier for Self-Enhanced Synergistic Photothermal/Chemodynamic/Chemotherapy.

To overcome the limitations of doxorubicin (DOX) chemotherapy, nanomedicines that integrate additional photothermal therapy (PTT) and chemodynamic therapy (CDT) strategies are highlighted as promising alternatives for the treatment of malignant tumors. However, time-consuming preparation processes, biosafety concerns, and the bottlenecks of individual therapeutic modalities often limit the practical applications of this strategy. To address these issues, this work designs an oxygen economizer that additionally serves as a Fenton reaction amplifier through the simple assembly of epigallocatechin gallate (EGCG), pluronic F-127 (PF127), iron (III) ions, and doxorubicin (DOX) for the enhancement of synergistic PTT/CDT/chemotherapy. The resulting nanoformulation, EFPD, can target mitochondria and inhibit cell respiration to reduce O2 consumption, thus boosting DOX-mediated H2 O2 generation for enhanced CDT and simultaneously improving hypoxia-limited DOX chemotherapy efficacy. Moreover, the coordination between EGCG and Fe3+ provides EFPD with excellent photothermal conversion efficiencies (η = 34.7%) for PTT and photothermal-accelerated drug release. Experimental results indicate that EFPD-mediated synergistic enhancement of PTT/CDT/chemotherapy can achieve excellent therapeutic outcomes, including enhanced ablation of solid tumors, reduced metastasis and cardiotoxicity, and extended life spans.

Light-Triggered Nitric Oxide Nanogenerator with High l-Arginine Loading for Synergistic Photodynamic/Gas/Photothermal Therapy.

The development of nanomedicines that combine photothermal therapy (PTT) with photodynamic therapy (PDT) is considered promising for cancer treatment, but still faces the challenge of enhancing tumoricidal efficiency. Fortunately, apart from the well-acknowledged effect on direct tumor cell-killing, nitric oxide (NO) is also considered to be effective for the enhancement of both PTT and PDT. However, both the low loading efficiency of NO precursor and the short half-life time and diffusion distance of NO hamper the synergistic therapeutic efficacy of NO. Taking the aforementioned factors into account, a mitochondria-targeted nitric oxide nanogenerator, EArgFe@Ce6, is constructed to achieve high loading of the NO donor l-Arginine (l-Arg) for synergistic photodynamic/gas/photothermal therapy upon single 660 nm light irradiation. The coordination of epigallocatechin gallate (EGCG) and ferric ions (Fe3+ ) provides EArgFe@Ce6 supreme photothermal capability to perform low-temperature PTT (mPTT). EGCG endows EArgFe@Ce6 with mitochondria-targeting capability and meanwhile favors hypoxia alleviation for enhanced PDT. The PDT-produced massive reactive oxygen species (ROS) further catalyzes l-Arg to generate a considerable amount of NO to perform gas therapy and sensitize both mPTT and PDT. In vitro and in vivo studies demonstrate that the synergistic photodynamic/gas/photothermal therapy triggered by single 660 nm light irradiation is highly effective for tumor treatments.

Identification of candidate genes for salinity tolerance in Japonica rice at the seedling stage based on genome-wide association study and linkage mapping.

Background: Salinity tolerance plays a vital role in rice cultivation because the strength of salinity tolerance at the seedling stage directly affects seedling survival and final crop yield in saline soils. Here, we combined a genome-wide association study (GWAS) and linkage mapping to analyze the candidate intervals for salinity tolerance in Japonica rice at the seedling stage. Results: We used the Na+ concentration in shoots (SNC), K+ concentration in shoots (SKC), Na+/K+ ratio in shoots (SNK), and seedling survival rate (SSR) as indices to assess the salinity tolerance at the seedling stage in rice. The GWAS identified the lead SNP (Chr12_20864157), associated with an SNK, which the linkage mapping detected as being in qSK12. A 195-kb region on chromosome 12 was selected based on the overlapping regions in the GWAS and the linkage mapping. Based on haplotype analysis, qRT-PCR, and sequence analysis, we obtained LOC_Os12g34450 as a candidate gene. Conclusion: Based on these results, LOC_Os12g34450 was identified as a candidate gene contributing to salinity tolerance in Japonica rice. This study provides valuable guidance for plant breeders to improve the response of Japonica rice to salt stress.

Shape and size of highly concentrated micelles in CTAB/NaSal solutions by Small Angle Neutron Scattering (SANS).

Highly concentrated micelles in CTAB/NaSal solutions with a fixed salt/surfactant ratio of 0.6 have been studied using Small Angle Neutron Scattering (SANS) as a function of temperature and concentration. A worm-like chain model analysis of the SANS data using a combination of a cylindrical form factors for the polydisperse micellar length, circular cross-sectional radius with Gaussian polydispersity, and the structure factor based on a random phase approximation (RPA) suggests that these micelle solutions have a worm-like micellar structure that is independent of the concentration and temperature. The size of the micelle decreases monotonically with increasing temperature and increases with concentration. These observations indicate that large micelles are formed at low temperature and begin to break up to form smaller micelles with increasing temperature.

Analysis of Marine Microplastic Pollution of Disposable Masks under COVID-19 Epidemic-A DPSIR Framework.

Marine microplastic pollution (MMP) is becoming one of the most pressing environmental problems facing humanity today. The novel coronavirus epidemic has raised the issue of environmental contamination caused by large-scale improper disposal of medical waste such as disposable masks (DMs). To assess the impact of MMP caused by DMs and to seek solutions for the prevention and control of MMP, this study uses the Driving force-Pressure-State-Impact-Response (DPSIR) framework to establish a causal chain of MMP caused by DMs. The conclusion shows that the novel coronavirus epidemic has led to a surge in the use of DMs, which has brought pressure on resource constraints and environmental pollution at the same time. Improperly DMs enter the environment and eventually transform into MMP, which not only endangers the marine ecological system but also poses potential human health risks as well as economic and social hazards. In addition, further research on environmentally friendly masks (cloth masks and biodegradable masks) is essential to mitigate the environmental damage caused by the large-scale global use of DMs. This study provides a scientific and theoretical basis for the assessment of MMP from discarded DMs, and the findings of this study will provide a reference for the formulation of relevant policies.

Event-Based Robotic Grasping Detection With Neuromorphic Vision Sensor and Event-Grasping Dataset.

Robotic grasping plays an important role in the field of robotics. The current state-of-the-art robotic grasping detection systems are usually built on the conventional vision, such as the RGB-D camera. Compared to traditional frame-based computer vision, neuromorphic vision is a small and young community of research. Currently, there are limited event-based datasets due to the troublesome annotation of the asynchronous event stream. Annotating large scale vision datasets often takes lots of computation resources, especially when it comes to troublesome data for video-level annotation. In this work, we consider the problem of detecting robotic grasps in a moving camera view of a scene containing objects. To obtain more agile robotic perception, a neuromorphic vision sensor (Dynamic and Active-pixel Vision Sensor, DAVIS) attaching to the robot gripper is introduced to explore the potential usage in grasping detection. We construct a robotic grasping dataset named Event-Grasping dataset with 91 objects. A spatial-temporal mixed particle filter (SMP Filter) is proposed to track the LED-based grasp rectangles, which enables video-level annotation of a single grasp rectangle per object. As LEDs blink at high frequency, the Event-Grasping dataset is annotated at a high frequency of 1 kHz. Based on the Event-Grasping dataset, we develop a deep neural network for grasping detection that considers the angle learning problem as classification instead of regression. The method performs high detection accuracy on our Event-Grasping dataset with 93% precision at an object-wise level split. This work provides a large-scale and well-annotated dataset and promotes the neuromorphic vision applications in agile robot.

Parking Slot Detection on Around-View Images Using DCNN.

Due to the complex visual environment and incomplete display of parking slots on around-view images, vision-based parking slot detection is a major challenge. Previous studies in this field mostly use the existing models to solve the problem, the steps of which are cumbersome. In this paper, we propose a parking slot detection method that uses directional entrance line regression and classification based on a deep convolutional neural network (DCNN) to make it robust and simple. For parking slots with different shapes and observed from different angles, we represent the parking slot as a directional entrance line. Subsequently, we design a DCNN detector to simultaneously obtain the type, position, length, and direction of the entrance line. After that, the complete parking slot can be easily inferred using the detection results and prior geometric information. To verify our method, we conduct experiments on the public ps2.0 dataset and self-annotated parking slot dataset with 2,135 images. The results show that our method not only outperforms state-of-the-art competitors with a precision rate of 99.68% and a recall rate of 99.41% on the ps2.0 dataset but also performs a satisfying generalization on the self-annotated dataset. Moreover, it achieves a real-time detection speed of 13 ms per frame on Titan Xp. By converting the parking slot into a directional entrance line, the specially designed DCNN detector can quickly and effectively detect various types of parking slots.

Multi-Cue Event Information Fusion for Pedestrian Detection With Neuromorphic Vision Sensors.

Neuromorphic vision sensors are bio-inspired cameras that naturally capture the dynamics of a scene with ultra-low latency, filtering out redundant information with low power consumption. Few works are addressing the object detection with this sensor. In this work, we propose to develop pedestrian detectors that unlock the potential of the event data by leveraging multi-cue information and different fusion strategies. To make the best out of the event data, we introduce three different event-stream encoding methods based on Frequency, Surface of Active Event (SAE) and Leaky Integrate-and-Fire (LIF). We further integrate them into the state-of-the-art neural network architectures with two fusion approaches: the channel-level fusion of the raw feature space and decision-level fusion with the probability assignments. We present a qualitative and quantitative explanation why different encoding methods are chosen to evaluate the pedestrian detection and which method performs the best. We demonstrate the advantages of the decision-level fusion via leveraging multi-cue event information and show that our approach performs well on a self-annotated event-based pedestrian dataset with 8,736 event frames. This work paves the way of more fascinating perception applications with neuromorphic vision sensors.

Knockdown of PHGDH potentiates 5-FU cytotoxicity in gastric cancer cells via the Bcl-2/Bax/caspase-3 signaling pathway.

Gastric cancer (GC) is one of the most common malignancies in the world. Fluorouracil (5-FU) is widely used in the treatment of cancers, but resistance to 5-FU results in the failure of chemotherapy. Phosphoglycerate dehydrogenase (PHGDH) has been reported to play a vital role in the development of 5-FU resistance in cancer cells. However, the exact role of PHGDH and the underlying mechanisms for 5-FU resistance in GC cells remain elusive. In this study, PHGDH expression was much higher in the GC tissues of 5-FU-resistant patients than that in the GC tissues of 5-FU-sensitive patients. Moreover, the expression of PHGDH was obviously increased in BGC823/5-FU cells compared with that in BGC823 cells. 5-FU treatment significantly reduced the viability of BGC823/5-FU cells, in a dose- and time-dependent manner. Furthermore, 5-FU treatment inhibited the proliferation of BGC823/5-FU cells, as evidenced by decreased cell viability and reduced colony-forming ability. The knockdown of PHGDH made possible the inhibitory effect of 5-FU on the proliferation of BGC823/5-FU cells. Furthermore, 5-FU treatment promoted apoptosis of BGC823/5-FU cells, as indicated by increased numbers of TUNEL-positive cells and increased rates of apoptosis. Notably, the promoting effect of 5-FU on the apoptosis of BGC823/5-FU cells was markedly enhanced by PHGDH knockdown. Additionally, 5-FU treatment downregulated Bcl-2 expression and upregulated the expression of Bax and caspase-3, and this effect was remarkably enhanced by PHGDH knockdown. In conclusion, knockdown of PHGDH potentiates 5-FU cytotoxicity in GC cells via the Bcl-2/Bax/caspase-3 signaling pathway.

Mechanical Grinding Preparation and Characterization of TiO2-Coated Wollastonite Composite Pigments.

TiO2-coated wollastonite composite pigments were prepared by the mechano-chemical grinding of wollastonite and TiO2 powder together in a wet ultrafine stirred mill. X-ray diffraction, scanning electron microscopy, X-ray photoelectron spectroscopy and infrared spectra were used to investigate the microstructures and morphologies of the composite and the reaction mechanism. The results indicate that the TiO2-coated wollastonite composite pigments have similar properties to titanium dioxide pigment, showing much better properties than dry and wet mixing of wollastonite and TiO2. The hiding power of TiO2-coated wollastonite composite pigments (45% TiO2) is 17.97 g/m², reaching 81.08% of titanium dioxide. A firm combination between wollastonite and TiO2 is obtained through a surface dehydroxylation reaction during the mechano-chemical method.

Phase coexistence in [111] electric-field-cooled 0.7Pb (Mg(1/3)Nb(2/3))O(3)-0.3PbTiO(3) crystals.

Features of phase coexistence in polydomain 0.7Pb(Mg(1/3)Nb(2/3))O(3)-0.3PbTiO(3) crystals cooled under an applied [111] electric field E have been investigated. A sequence of ferroelectric phases as well as the elastic matching between coexisting phases in heterophase states has been analysed for cases where the angle between the spontaneous polarization vector of each domain type and the applied E vector remains equal in each ferroelectric phase. This analysis is based on a method that involves distortion matrices of the polydomain phases and invariants of interfaces regarded as quadric surfaces separating the phases. Results are represented in a system of diagrams linking domain states and interfaces at first-order phase transitions observed in [111] field-cooled 0.7Pb(Mg(1/3)Nb(2/3))O(3)-0.3PbTiO(3) crystals. A 'fine' structure of the domain state-interface diagrams related to tetragonal-orthorhombic phase coexistence has been revealed. It has been shown that conditions for complete stress relaxation in different heterophase states are achieved for a phase sequence of [Formula: see text] tetragonal [Formula: see text] near single-domain orthorhombic [Formula: see text] single-domain monoclinic of the B type.

Using Variable-Length Aligned Fragment Pairs and an Improved Transition Function for Flexible Protein Structure Alignment.

With the rapid growth of known protein 3D structures in number, how to efficiently compare protein structures becomes an essential and challenging problem in computational structural biology. At present, many protein structure alignment methods have been developed. Among all these methods, flexible structure alignment methods are shown to be superior to rigid structure alignment methods in identifying structure similarities between proteins, which have gone through conformational changes. It is also found that the methods based on aligned fragment pairs (AFPs) have a special advantage over other approaches in balancing global structure similarities and local structure similarities. Accordingly, we propose a new flexible protein structure alignment method based on variable-length AFPs. Compared with other methods, the proposed method possesses three main advantages. First, it is based on variable-length AFPs. The length of each AFP is separately determined to maximally represent a local similar structure fragment, which reduces the number of AFPs. Second, it uses local coordinate systems, which simplify the computation at each step of the expansion of AFPs during the AFP identification. Third, it decreases the number of twists by rewarding the situation where nonconsecutive AFPs share the same transformation in the alignment, which is realized by dynamic programming with an improved transition function. The experimental data show that compared with FlexProt, FATCAT, and FlexSnap, the proposed method can achieve comparable results by introducing fewer twists. Meanwhile, it can generate results similar to those of the FATCAT method in much less running time due to the reduced number of AFPs.