Candidate molecules as alternative nitric oxide donors with better antibacterial property against Escherichia coli and Staphylococcus aureus.

AIMS: Four nitric oxide (NO) donors, S-nitrosoglutathione (GSNO), S-nitrosocysteine (CySNO), S-nitroso-N-acetylcysteine (SNAC), and 2-(2-S-nitroso propionamide) acetic acid (GAS) were prepared and their physicochemical characteristics were analyzed. Besides, the antibacterial properties of NO donors were investigated against Escherichia coli and Staphylococcus aureus. METHODS AND RESULTS: UV-visible absorption spectrum and Fourier transform infrared spectrum verified the successful preparation of RSNOs. All NO donors (10 mmol l-1) could release NO continuously, and the amount of NO release was from 80.22 µmol l-1 to 706.63 µmol l-1, in which the release of NO from SNAC was the highest, and the release of NO from NaNO2 was the least. The inhibition zone indicated that all NO donors showed stronger antibacterial activity against E. coli and S. aureus, and the antibacterial ability was in the order of SNAC > GSNO > CySNO > GAS > NaNO2 for both E. coli and S. aureus (P < 0.05). Scanning electron microscopy(SEM) showed that all NO donors could result in varying degrees of damage to cell wall and membrane of both E. coli and S. aureus and the damage of E. coli was more severe. CONCLUSION: Four alternative NO donors were successfully synthesized. All alternative NO donors showed better antibacterial properties against E. coli and S. aureus than NaNO2.

Trace water in a BF3·OEt2 system: a facile access to sulfinyl alkenylsulfones from alkynes and sodium sulfinates.

A highly efficient and operationally simple method for the synthesis of ß-sulfinyl alkenylsulfones through a BF3·OEt2-promoted reaction of alkynes and sodium sulfinates is developed, successfully avoiding the complicated anhydrous treatment before the reaction and greatly simplifying the reaction conditions. As a facile and selective route to the targets, it features good functional group compatibility, mild conditions, easily available starting materials, and excellent yields. Notably, the trace water in solvent plays a key role in promoting the reaction, which provides a more practical pathway for the utilization of the BF3·OEt2 catalytic system.

Fine-tuning benzazole-based probe for the ultrasensitive detection of Hg2+ in water samples and seaweed samples.

Developing potentially toxic metal ion probes is significant for environment and food safety. Although Hg2+ probes have been extensively studied, small molecule fluorophores that can integrate two applications of visual detection and separation into one unit remain challenging to access. Herein, by incorporating triphenylamine (TPA) into tridentate skeleton with an acetylene bridge, 2,6-bisbenzimidazolpyridine-TPA (4a), 2,6-bisbenzothiazolylpyridine-TPA (4b) and 2,6-bisbenzothiazolylpyridine-TPA (4c) were first constructed, expectably showing distinct solvatochromism and dual-state emission properties. Since the diverse emission properties, the fluorescence detection of 4a-4b can be achieved with an ultrasensitive response (LOD = 10-11 M) and efficient removal of Hg2+. More interestingly, 4a-4b can not only be developed into paper/film sensing platform, but also reliably detect Hg2+ in real water and seaweed samples, with recoveries ranging from 97.3% to 107.8% and a relative standard deviation of less than 5%, indicating that they have excellent application potential in the field of environmental and food chemistry.

PatchNet: Maximize the Exploration of Congeneric Semantics for Weakly Supervised Semantic Segmentation.

With the increase in the number of image data and the lack of corresponding labels, weakly supervised learning has drawn a lot of attention recently in computer vision tasks, especially in the fine-grained semantic segmentation problem. To alleviate human efforts from expensive pixel-by-pixel annotations, our method focuses on weakly supervised semantic segmentation (WSSS) with image-level labels, which are much easier to obtain. As a considerable gap exists between pixel-level segmentation and image-level labels, how to reflect the image-level semantic information on each pixel is an important question. To explore the congeneric semantic regions from the same class to the maximum, we construct the patch-level semantic augmentation network (PatchNet) based on the self-detected patches from different images that contain the same class labels. Patches can frame the objects as much as possible and include as little background as possible. The patch-level semantic augmentation network that is established with patches as the nodes can maximize the mutual learning of similar objects. We regard the embedding vectors of patches as nodes and use a transformer-based complementary learning module to construct weighted edges according to the embedding similarity between different nodes. Moreover, to better supplement semantic information, we propose soft-complementary loss functions matched with the whole network structure. We conduct experiments on the popular PASCAL VOC 2012 and MS COCO 2014 benchmarks, and our model yields the state-of-the-art performance.

Regulating donor-acceptor system toward highly efficient dual-state emission for sensitive response of nitroaromatic explosives.

Dual-state emission luminogens (DSEgens) as fluorophores emit efficiently in solution and solid forms have gained increasing concern in the field of chemical sensing. Recent efforts by our group led to the identification of DSEgens as an easy-to-visualize nitroaromatic explosives (NAEs) detection platform. However, none of the previously studied NAEs probes show effective improvement in sensitivity. Here, we designed a series of benzoxazole-based DSEgens through multiple strategies driven by theoretical calculations, revealing their improved detecting performance on NAEs. Compounds 4a-4e exhibit thermal- and photo-stability, large Stokes shift as well as sensitivity solvatochromism (except for 4a and 4b). A subtle balance between rigid conjugation and distorted conformation endows these D-A type fluorophores 4a-4e with DSE properties. Furthermore, 4d and 4e show aggregation-induced emission phenomenon caused by distorted molecular conformation and restricted intramolecular rotation. Interestingly, DSEgen 4e displays anti-interference and sensitivity towards NAEs with a detection limit of 10-8 M. It can be applied for expedient and distinct visual identification of NAEs not only in solution but also on filter paper and film, supporting this new DSEgen as reliable NAEs chemoprobe.

Multivariate models of commodity futures markets: a dynamic copula approach.

We apply flexible multivariate dynamic models to capture the dependence structure of various US commodity futures across different sectors between 2004 and 2022; particular attention is paid to the 2008 financial crisis and the COVID-19 pandemic. Our copula-based models allow for time-varying nonlinear and asymmetric dependence by integrating elliptical and skewed copulas with dynamic conditional correlation (DCC) and block dynamic equicorrelation (Block DECO). Flexible copula models that allow for multivariate asymmetry and tail dependence are found to provide the best performance in characterizing co-movements of commodity returns. We also find that the connectedness between commodities has dramatically increased during the financial distress and the COVID-19 pandemic. The impacts of the financial crisis appear to be more persistent than those of the pandemic. We apply our models to some risk management tasks in the commodity markets. Our results suggest that optimal portfolio weights based on dynamic copulas have persistently outperformed the equal-weighted portfolio, demonstrating the practicality and usefulness of our proposed models.

Adversarial Learning With Cost-Sensitive Classes.

It is necessary to improve the performance of some special classes or to particularly protect them from attacks in adversarial learning. This article proposes a framework combining cost-sensitive classification and adversarial learning together to train a model that can distinguish between the protected and unprotected classes, such that the protected classes are less vulnerable to adversarial examples. We find in this framework an interesting phenomenon during the training of deep neural networks, called the Min-Max property, that is, the absolute values of most parameters in the convolutional layer approach 0 while the absolute values of a few parameters are significantly larger, becoming bigger. Based on this Min-Max property which is formulated and analyzed in a view of random distribution, we further build a new defense model against adversarial examples for adversarial robustness improvement. An advantage of the built model is that it performs better than the standard one and can combine with adversarial training to achieve improved performance. It is experimentally confirmed that, regarding the average accuracy of all classes, our model is almost as same as the existing models when an attack does not occur and is better than the existing models when an attack occurs. Specifically, regarding the accuracy of protected classes, the proposed model is much better than the existing models when an attack occurs.

The emerging therapeutic target of dynamic and reversible N6-methyladenosine modification during cancer development.

As a reversible and dynamic epigenetic modification, N6-methyladenosine (m6A) modification is ubiquitous in eukaryotic cells. m6A methylation is prevalent in almost all RNA metabolism processes that affect the fate of cells, including cancer development. As indicated by the available evidence, targeting m6A regulators may play a crucial role in tumor therapy and multidrug resistance. Currently, many questions remain uncovered. Here, we review recent studies on m6A modification in various aspects of tumor progression, tumor immunity, multidrug resistance, and therapeutic targets to provide new insight into the m6A methylation process.

The Medical Segmentation Decathlon.

International challenges have become the de facto standard for comparative assessment of image analysis algorithms. Although segmentation is the most widely investigated medical image processing task, the various challenges have been organized to focus only on specific clinical tasks. We organized the Medical Segmentation Decathlon (MSD)-a biomedical image analysis challenge, in which algorithms compete in a multitude of both tasks and modalities to investigate the hypothesis that a method capable of performing well on multiple tasks will generalize well to a previously unseen task and potentially outperform a custom-designed solution. MSD results confirmed this hypothesis, moreover, MSD winner continued generalizing well to a wide range of other clinical problems for the next two years. Three main conclusions can be drawn from this study: (1) state-of-the-art image segmentation algorithms generalize well when retrained on unseen tasks; (2) consistent algorithmic performance across multiple tasks is a strong surrogate of algorithmic generalizability; (3) the training of accurate AI segmentation models is now commoditized to scientists that are not versed in AI model training.

An investigation on catalytic nitrite reduction reaction by bioinspired CuII complexes.

Catalytic nitrite reductions by CuII complexes containing anionic Me2Tp, neutral Me2Tpm, or neutral iPrTIC ligands in the presence of L-ascorbic acid, which served as an electron donor and proton source, were investigated. The results showed that auxiliary ligands are important for copper-mediated catalytic nitrite reduction. Furthermore, the electronic effects of the ligand govern the nitrite reduction efficiency, which should be considered at two control points: one is the susceptibility of the LCuI-nitrite species to protonation and the other is the susceptibility of LCuII to reduction giving LCuI. In addition, an external strong acid leads to the production of nitrous acid, which may suggest that the reactivity of nitrous acid toward the LCuI species is a third control point.

Towards improving fast adversarial training in multi-exit network.

Adversarial examples are usually generated by adding adversarial perturbations on clean samples, designed to deceive the model to make wrong classifications. Adversarial robustness refers to the ability of a model to resist adversarial attacks. And currently, a mainstream method to enhance adversarial robustness is the Projected Gradient Descent (PGD). However, PGD is often criticized for being time-consuming during constructing adversarial examples. Fast adversarial training can improve the adversarial robustness in shorter time, but it only can train for a limited number of epochs, leading to sub-optimal performance. This paper demonstrates that the multi-exit network can reduce the impact of adversarial perturbations by outputting easily identified samples at early exits. Therefore, we can improve the adversarial robustness. Further, we find that the multi-exit network can prevent catastrophic overfitting existing in single-step adversarial training. Specifically, we find that, in the multi-exit network, (1) the norm of weights at a fully connected layer in a non-overfitted exit is much smaller than that in an overfitted exit; and (2) catastrophic overfitting occurs when the late exits have weight norms larger than the early exits. Based on these findings, we propose an approach to alleviating the catastrophic overfitting of the multi-exit network. Compared to PGD adversarial training, our approach can train a model with decreased time complexity and increased empirical robustness. Extensive experiments have been conducted to evaluate our approach against various adversarial attacks, and the experimental results demonstrate superior robustness accuracies on CIFAR-10, CIFAR-100 and SVHN.

Epigenetic enzyme mutations as mediators of anti-cancer drug resistance.

Despite the rapid advancement in the introduction of new drugs for cancer therapy, the frequent emergence of drug resistance leads to disease progression or tumor recurrence resulting in dismal prognosis. Given that genetic mutations are thought to be important drivers of anti-cancer drug resistance, it is of paramount importance to pin-point mutant genes that mediate drug resistance and elucidate the underlying molecular mechanisms in order to develop novel modalities to surmount chemoresistance and achieve more efficacious and durable cancer therapies. Cumulative evidence suggests that epigenetic alterations, especially those mediated by epigenetic enzymes with high mutation rates in cancer patients, can be a crucial factor in the development of chemoresistance. Mutant epigenetic enzymes have altered enzymatic activity which may directly or indirectly affect the level of histone modifications. This can change chromatin structure and function hence altering the expression of target genes and eventually lead to chemoresistance. In the current review, we summarize epigenetic enzyme mutations and the consequent mechanisms of drug resistance in pre-clinical drug-resistance models and relapsed cancer patient specimens. We also introduce previously unreported mutation sites in the DOT1 domain of DOT1L, which are related to lung cancer drug resistance. It is worth noting that mutations occur not only in domains with enzymatic activity but also in non-catalytic regions. Each protein domain is an evolutionarily conserved region with independent functional properties. This may provide a rationale for the potential development of small molecule inhibitors which target various functional domains of epigenetic enzymes. Finally, based on the multitude of mechanisms of drug resistance, we propose several therapeutic strategies to reverse or overcome drug-resistance phenotypes, with the aim to provide cancer patients with novel efficacious combination therapeutic regimens and strategies to improve patient prognosis.

A programmable and skin temperature-activated electromechanical synergistic dressing for effective wound healing.

Mechanical regulation and electric stimulation hold great promise in skin tissue engineering for manipulating wound healing. However, the complexity of equipment operation and stimulation implementation remains an ongoing challenge in clinical applications. Here, we propose a programmable and skin temperature-activated electromechanical synergistic wound dressing composed of a shape memory alloy-based mechanical metamaterial for wound contraction and an antibacterial electret thin film for electric field generation. This strategy is successfully demonstrated on rats to achieve effective wound healing in as short as 4 and 8 days for linear and circular wounds, respectively, with a statistically significant over 50% improvement in wound closure rate versus the blank control group. The optimally designed electromechanical synergistic stimulation could regulate the wound microenvironment to accelerate healing metabolism, promote wound closure, and inhibit infection. This work provided an effective wound healing strategy in the context of a programmable temperature-responsive, battery-free electromechanical synergistic biomedical device.

Rational Design and Facile Synthesis of Dual-State Emission Fluorophores: Expanding Functionality for the Sensitive Detection of Nitroaromatic Compounds.

Six novel benzimidazole-based D-π-A compounds 4 a-4 f were concisely synthesized by attaching different donor/acceptor units to the skeleton of 1,3-bis(1H-benzimidazol-2-yl)benzene on its 5-position through an ethynyl link. Due to the twisted conformation and effective conjugation structure, these dual-state emission (DSE) molecules show intense and multifarious photoluminescence, and their fluorescence quantum yields in solution and solid state can be up to 96.16 and 69.82 %, respectively. Especially, for excellent photostability, obvious solvatofluorochromic and extraordinary wide range of solvent compatibility, DSE molecule 4 a is a multifunctional fluorescent probe for the visual detection of nitroaromatic compounds (NACs) with the limit of detection as low as 10-7 M. The quenching mechanism has been proved as the results of photoinduced electron transfer and fluorescence resonance energy transfer processes. Importantly, probe 4 a can sensitively detect NACs not only in real water samples, but also on 4 a-coated strips and 4 a@PBAT thin films.

Simple inorganic base promoted C-N and C-C formation: synthesis of benzo[4,5]imidazo[1,2-a]pyridines as functional AIEgens used for detecting picric acid.

Metal-free catalyzed intermolecular tandem Michael addition/cyclization has been developed for the synthesis of benzo[4,5]imidazo[1,2-a]pyridines from α-bromocinnamaldehyde and 2-substituted benzimidazoles. The reaction promoted by a simple inorganic base displays moderate to good yields and good functional group tolerance. The optical properties of some typical products have been investigated. We found that, due to the presence of the benzene ring at the C1-position of benzo[4,5]imidazo[1,2-a]pyridines which restricts intramolecular motion, as a new type of aggregation-induced emission (AIE) luminogen (AIEgen), they show very good solid-state fluorescence with quantum yields up to 88.80%. Importantly, the AIE performance of compound 3b can be useful to detect the nitroaromatic explosive picric acid (PA) with a detection limit and quenching constant of 42.5 nM and 7.27 × 104 M-M, respectively.

A self-powered implantable and bioresorbable electrostimulation device for biofeedback bone fracture healing.

Electrostimulation has been recognized as a promising nonpharmacological treatment in orthopedics to promote bone fracture healing. However, clinical applications have been largely limited by the complexity of equipment operation and stimulation implementation. Here, we present a self-powered implantable and bioresorbable bone fracture electrostimulation device, which consists of a triboelectric nanogenerator for electricity generation and a pair of dressing electrodes for applying electrostimulations directly toward the fracture. The device can be attached to irregular tissue surfaces and provide biphasic electric pulses in response to nearby body movements. We demonstrated the operation of this device on rats and achieved effective bone fracture healing in as short as 6 wk versus the controls for more than 10 wk to reach the same healing result. The optimized electrical field could activate relevant growth factors to regulate bone microenvironment for promoting bone formation and bone remodeling to accelerate bone regeneration and maturation, with statistically significant 27% and 83% improvement over the control groups in mineral density and flexural strength, respectively. This work provided an effective implantable fracture therapy device that is self-responsive, battery free, and requires no surgical removal after fulfilling the biomedical intervention.

High-Affinity Sulfate Transporter Sultr1;2 Is a Major Transporter for Cr(VI) Uptake in Plants.

Chromate (Cr[VI]) is a highly phytotoxic contaminant that is ubiquitous in soils. However, how Cr(VI) is taken up by plant roots remains largely unknown. Here, we show that the high-affinity sulfate transporter Sultr1;2 is responsible for Cr(VI) uptake by the roots of Arabidopsis thaliana. Sultr1;2 showed a much higher transport activity for Cr(VI) than Sultr1;1 when expressed in yeast cells. Knockdown of Sultr1;2 expression in Arabidopsis markedly reduced the Cr(VI) uptake rate, whereas knockout of Sultr1;1 had no or little effect. A double-knockout mutant (DKO) of the two genes lost the ability of Cr(VI) uptake almost completely. The Sultr1;2 knockdown mutant or DKO plants displayed higher resistance to Cr(VI) under normal sulfate conditions as a consequence of the lower tissue Cr accumulation. Overexpression of Sultr1;2 substantially increased Cr(VI) uptake with shoot Cr concentration being 1.6-2.0 times higher than that in the wild-type. These results indicate that Sultr1;2 is a major transporter responsible for Cr(VI) uptake in Arabidopsis, while Sultr1;1 plays a negligible role. Taken together, our study has identified a major transporter for Cr(VI) uptake in plants, providing potential strategies for engineering plants with low Cr accumulation and consequently enhanced Cr(VI) resistance and also plants with enhanced accumulation of Cr for the purpose of phytoremediation.

Mechanical Terahertz Modulation by Skin-Like Ultrathin Stretchable Metasurface.

The modulation of terahertz plays a key role in realizing the tunable terahertz devices. The concept of flexible and stretchable electronics provides the possibility to dynamically modulate the terahertz with mechanical strain rather than additional electrical components. Here, the mechanical modulation of the terahertz transmission with a freestanding, skin-like, and highly stretchable metasurface is experimentally illustrated. The stretchable metasurface is fabricated by merely constructing an Al/PI mesh film consisting of serpentine-like unit cells, with total thickness of only 7 µm. With the flexibility realized by the extremely small thickness, the metasurface can be stretched, bended, and twisted, which provides the possibility to modulate terahertz transmission properties by the mechanical deformation of the metasurface. The terahertz time domain spectroscopy results indicate that the stretchable metasurface shows the band-stop frequency selective effect and the transmission of the terahertz wave can be modulated from 0.15 to 0.5 with applied external tensile strains up to 28%, while only 3.4% of the shift of the resonance frequency is observed. The mechanisms of the metasurface and the relation between the modulation effect and the structural mesh parameters are also discussed with the electromagnetic simulations and the LC equivalent circuit model.

Self-Activated Electrical Stimulation for Effective Hair Regeneration via a Wearable Omnidirectional Pulse Generator.

Hair loss, a common and distressing symptom, has been plaguing humans. Various pharmacological and nonpharmacological treatments have been widely studied to achieve the desired effect for hair regeneration. As a nonpharmacological physical approach, physiologically appropriate alternating electric field plays a key role in the field of regenerative tissue engineering. Here, a universal motion-activated and wearable electric stimulation device that can effectively promote hair regeneration via random body motions was designed. Significantly facilitated hair regeneration results were obtained from Sprague-Dawley rats and nude mice. Higher hair follicle density and longer hair shaft length were observed on Sprague-Dawley rats when the device was employed compared to conventional pharmacological treatments. The device can also improve the secretion of vascular endothelial growth factor and keratinocyte growth factor and thereby alleviate hair keratin disorder, increase the number of hair follicles, and promote hair regeneration on genetically defective nude mice. This work provides an effective hair regeneration strategy in the context of a nonpharmacological self-powered wearable electronic device.

Tailoring the energy band in flexible photodetector based on transferred ITO/Si heterojunction via interface engineering.

Interface engineering is an important method to modulate electronic structures for improving the physical properties of semiconductors as well as designing novel devices. Recently, development of flexible electronic devices based on inorganic thin films on flexible substrates, which provides solutions to meet the emerging technological demands, may also expend the methodology of interface engineering. Herein, a semitransparent photodetector based on an indium-tin oxide (ITO)-on-silicon (Si) heterojunction was fabricated on a flexible substrate and investigated under mechanical bending strains. It is found that the barrier height of the heterojunction can be tailored continuously and reversibly from 0.23 eV to 0 eV, corresponding to the Schottky and Ohmic junctions respectively. Meanwhile, the turn-on voltage and the response time of the as-prepared photodetector can be obviously reduced under bending strain, which can be attributed to the modulation of the Si bandgap and hole mobility. Our experimental studies not only shed new light on the strain modulation mechanism of the heterojunction interface, but also pave a prominent way to integrated high-performance flexible photodetectors.