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The effects of lycopene (LP) on macrophage immune responses were evaluated in this study. Compared with the control treatment, LP treatment significantly increased cell vitality, phagocytic activity, and chemokine production in RAW264.7 cells. Additionally, compared with the control treatment, 4 μM LP treatment significantly activated autophagy, enhanced mitochondrial membrane potential, and upregulated receptor-interacting protein kinase 1 (RIPK1), while necrostatin-1 significantly reversed these effects of LP. Furthermore, compared with that in the control group, RIPK1 was significantly upregulated in the 4 μM LP and 4 μM LP + spautin-1 groups, whereas p-mTOR levels were reduced. More importantly, compared with that in the control group, p62 was significantly downregulated, and Beclin1, LC3-II, and Atg7 were upregulated in the 4 μM LP group, while spautin-1 significantly reversed these effects of LP. These results confirm that LP activates the mTOR/Beclin1/LC3/p62 autophagy signaling pathway through RIPK1, thereby enhancing the immune response of macrophages.

In recent years, the rapid development of remote sensing (RS) technology has led to a drastic increase in the availability of RS images. This calls for the need to develop new methods able to effectively and efficiently retrieve the required instances from a massive amount of RS imagery. In retrieval tasks, finding the nearest-neighbor sample of the retrieval query is a fundamental research topic. Exhaustive comparison is the simplest method to accomplish this task. However, due to the involved computational complexity and memory limitations, this solution is no longer feasible in large data retrieval tasks. As an important branch of approximate nearest-neighbor retrieval (NNR), hash algorithms transform high-dimensional data into low-bit expressions (hash codes) with elements of 0 and 1 to reduce storage and computational costs. Hash algorithms aim to preserve the same nearest-neighbor relationship between the learned hash codes and the original data. Existing hash algorithms are divided into two classes: shallow and deep methods. Furthermore, deep hash algorithms can be divided into (semi-) supervised and unsupervised algorithms. In this article, representative hash-based RS image retrieval (HBRSIR) methods are reviewed, studying the application of hashing in other areas of the RS community and introducing available datasets and evaluation metrics for RS image retrieval (RSIR). The performance of representative and cross-modal hashing methods is validated using two common RSIR datasets (UCMerced and AID) and a cross-modal dataset (DSRSID). Prospects of future work summarizing HBRSIR are also provided.

The widespread availability of remotely sensed datasets establishes a cornerstone for comprehensive image retrieval within the realm of remote sensing (RS). In response, the investigation into hashing-driven retrieval methods garners significance, enabling proficient image acquisition within such extensive data magnitudes. Nevertheless, the used datasets in practical applications are invariably less desirable and with long-tailed distribution. The primary hurdle pertains to the substantial discrepancy in class volumes. Moreover, commonly utilized RS datasets for hashing tasks encompass approximately two–three dozen classes. However, real-world datasets exhibit a randomized number of classes, introducing a challenging variability. This article proposes a new centripetal intensive attention hashing (CIAH) mechanism based on intensive attention features for long-tailed distribution RS image retrieval. Specifically, an intensive attention module (IAM) is adopted to enhance the significant features to facilitate the subsequent generation of representative hash codes. Furthermore, to deal with the inherent imbalance of long-tailed distributed datasets, the utilization of a centripetal loss function is introduced. This endeavor constitutes the inaugural effort toward long-tailed distributed RS image retrieval. In pursuit of this objective, a collection of long-tail datasets is meticulously curated using four widely recognized RS datasets, subsequently disseminated as benchmark datasets. The selected fundamental datasets contain 7, 25, 38, and 45 land-use classes to mimic different real RS datasets. Conducted experiments demonstrate that the proposed methodology attains a performance benchmark that surpasses currently existing methodologies.

Hyperspectral images (HSIs) comprise plenty of information in the spatial and spectral domain, which is highly beneficial for performing classification tasks in a very accurate way. Recently, attention mechanisms have been widely used in the HSI classification due to their ability to extract relevant spatial and spectral features. Notwithstanding their positive results, most of the attentional strategies usually introduce a significant number of parameters to be trained, making the models more complex and increasing the computational load. In this article, we develop a new parameter-free attention network for HSI classification. The main advantage of our model is that it does not add parameters to the original network (as opposed to other state-of-the-art approaches) while providing higher classification accuracies. Extensive experimental validations and quantitative comparisons are conducted—using different benchmark HSIs—to illustrate these advantages. The code is available on https://github.com/mhaut/Free2Resnet.

An alternative method for the synthesis of 2-heteroaryl or alkynyl benzo[b]thiophene or furan derivatives viadirect palladium-catalyzed cross-coupling of 2-benzo[b]thiophene or furan aluminum with heteroaryl or alkynyl bromides, respectively, has been successfully developed. This case is remarkable as the same catalytic system could simultaneously produce either 2-substituted benzo[ b]thiophene or furan derivatives.

Autoencoder (AE)-based hyperspectral anomaly detectors have received significant attention. The core of these detectors is to reconstruct backgrounds by optimizing AEs so that anomalies can be detected by reconstruction residuals. Nevertheless, existing methods are flawed in two aspects: 1) most of them reconstruct the background along with the anomalies, resulting in undesired performance for large target detection in complex backgrounds, and 2) they only focus on the encoder optimization part, ignoring the decoder reconstruction quality of the background. Given the above, this article proposes a background-guided deformable convolutional AE (DCAE) network with three mutually supportive parts, including encoder, decoder, and background guidance modules. In the encoder, deformable convolution (DC) is introduced into regular convolution to build the adaptive spatial feature extractor to fit complex spatial structures, while a nonlocal convolution (NLC) is introduced to build an external feature extractor to capture global spatial relationships. Furthermore, a mask is designed to filter potential anomalous information, curbing the representation of high-frequency anomalies to focus on widespread backgrounds. In the decoder, a background guidance module (considering the physical meaning of linear reconstruction) is built, guiding the proposed network learning via two strategies. One is initializing the weight of the decoder, and another is adding a loss term. Notably, both the number of output channels of the encoder and the decoder construction are determined by the background guidance module, which creates a bridge between the network design and practical situations. A profound analysis demonstrates the outstanding performance of the proposed method, which outperforms traditional and deep learning methods, proving that the novel designs introduced in the network architecture are extremely effective.

With the development of the economy, people’s living standards are getting higher and higher. People will look for ways to relax after busy work, and rural tourism is a slow-paced life. The purpose of this paper is to analyse the evaluation system of rural sustainable tourism land based on ecosystem service value. In this paper, an evaluation model based on AHP and association rules is proposed, and the two methods are described in detail. The experimental results of this paper show that the number of tourists has increased from 12 % in 2014 to 24.9 % in 2020, and the growth rate of tourism revenue has increased from 24 % in 2014 to 30 % in 2020. Rural tourism is an important part of tourism and an important force to implement the strategy of rural revitalisation. It plays an important role in accelerating the modernisation of agriculture and rural areas, the integrated development of urban and rural areas, and poverty alleviation in poor areas. The number of farm stays has increased from 1.9 million in 2014 to 3.25 million in 2020. It can be seen that with the growth of time, the rapid development of the economy, and increasing people who love to travel, this has led to changes in the utilisation rate of rural land. Therefore, the research on the evaluation system of rural sustainable tourism land based on ecosystem service value is very meaningful.

Osthole is a coumarin compound extracted from the canopy flower of the umbelliferae. Matrine, whose main components are alkaloids and flavonoids, was extracted from the roots, stems, leaves and fruits of Sophora flavescensby ethanol or other organic solvents. In this study, the efficacy of the combined biological agents matrine and osthole against Sorghum purple spot caused by Cercospora sorghiwas conducted by laboratory, greenhouse and field experiments. The results from petridish assay showed that the inhibitory effect of the mixture of osthole and matrine against C. sorghiwas better than osthole or matrine alone or Zineb, and the best mixing ratio of osthole to matrine was 1:2. In greenhouse experiment, the efficacy of 25 μg/mL of matrine · osthole against Sorghum purple spot was similar to Zineb. Field experiment showed that the efficacy of 25 μg/mL of matrine · osthole on Sorghum purple spot reached 68.4% on the 30th day. These results suggested that the combined matrine and osthole had a good effect and could be used as an alternative fungicide against Sorghum purple spot.

Thiram, as one widely used dithiocarbamate pesticide, has been considered seriously detrimental to food safety and human health because of poor efficiency, nonstandard/superfluous usage, and lack of a targeting effect. Developing high-performance sensors for thirams is strongly needed. With the rapid development of chemistry, biology, and materials science, many sensors have been constructed for thiram with high sensitivity and selectivity. Regarding the energy form of the signal, recognition mode, and detection principle, recent advances in the design and construction of optical and electrochemical sensors for thiram are summarized in this review, including colorimetric, luminescent, chemiluminescent, and electrochemical sensors. The advantages and disadvantages of the sensors for thiram including sensitivity, ability to avoid interference, recognition mechanism, signal output mode, and practicability are clarified in detail. Furthermore, the challenges faced, effective restrictions, and next direction of development are proposed for achieving more sensitive and selective analysis of thiram with less interference. We desire that this review will supply a solid theoretical basis and inspiration to generate innovative thinking for achieving new progress on thiram assays and the commercialization of the developed sensors in the future.

Carabrone is isolated from Carpesium macrocephalumFranch. et Sav, which has good fungicidal activity, especially for Gaeumannomyces graminis(Get). According to previous studies, we speculated that carabrone targets the mitochondrial enzyme complex III of Get. To elucidate the mode of action, we used carabrone to induce oxidative stress and apoptosis in Get. Incubation with carabrone reduced the burst of reactive oxygen species (ROS) and mitochondrial membrane potential, as well as phosphatidylserine release. Carabrone caused ROS accumulation in mycelia by inhibiting the activity of antioxidase enzymes, among which inhibition of glutathione reductase (GR) activity was most obvious. The catalytic center of GR consists of l-cysteine residues that react with the α-methylene-γ-butyrolactone active site of carabrone. Additionally, a positive TUNEL reaction led to diffusion of the DNA electrophoresis band and upregulation of Ggmet1and Ggmet2.We propose that carabrone inhibits antioxidant enzymes and promotes ROS overproduction, which causes membrane hyperpermeability, release of apoptotic factors, activation of the mitochondria-mediated apoptosis pathway, and fungal cell apoptosis.

Supplemental Digital Content is available in the text.Eicosapentaenoic acid (EPA), a typical kind of n-3 polyunsaturated fatty acids, has been considered to be a potent antitumor adjuvant. However, the mechanism related to EPA-induced SKOV-3 cell apoptosis has not been investigated. In this study, we elucidated the anticancer effect of EPA on SKOV-3 cells and its molecular mechanisms. The results of fluorescence microscopy showed that EPA induced typical apoptotic morphological features in SKOV-3 cells. Flow cytometric analysis indicated that EPA induced apoptosis of SKOV-3 cells through cells arrested at the S phase. Western blotting results showed that EPA could inhibit the phosphorylation of ERK1/2 and Akt, which restrained mammalian target of rapamycin (mTOR) phosphorylated. Simultaneously, EPA downregulated the phosphorylation status of mTOR, which may act as an upstream regulator of EPA-blocked nuclear factor κB (NF-κB) p65 translocation from the cytoplasm into the nucleus; the apoptotic mechanism of SKOV-3 cells induced by EPA was associated with the release of cytochrome c, Bax-to-Bcl-2 expression ratio, and activation of caspase-3 and caspase-9. The results suggested that EPA induced SKOV-3 cell apoptosis through ERK1/2, Akt–mTOR–NF-κB pathways.

Purpose:To evaluate the advantages and disadvantages of the retention and removal of silicone oil in the treatment of complicated retinal detachments. Methods:The records of 344 patients (348 eyes) that underwent vitrectomy and silicone oil injection for complicated retinal detachments were abstracted and analysed. The anatomical and functional results, complications and influencing factors are discussed. The outcome in eyes after removal of the silicone oil was compared with the outcome in a comparable group of eyes in which the silicone oil was retained. Results:The overall retinal reattachment rate was 63% (220/348). The final vision of 5/300 or better was 52% (115/220) in those eyes with totally attached retinas. The silicone oil-related complications included keratopathy (23%) and secondary glaucoma (11%). Comparing removal of silicone oil with retention of silicone oil, we found: (i) there was no statistical difference in the redetachment rate (19 vs 17%); (ii) Oil-removed eyes had a better final vision (P< 0.05); and (iii) keratopathy (13 vs 23%), secondary glaucoma (11 vs 25%) and optic nerve atrophy (4 vs 18%) were significantly lower in oil-removed eyes. Conclusion:Silicone oil injection is useful in the treatment of complicated retinal detachments. For reducing the incidence of complications, early removal of silicone oil is recommended in those cases in which the retina is attached, all breaks adequately closed and traction relieved.

The preventive effect and molecular mechanism of lycopene (LP) in dextran sulfate sodium (DSS)-induced ulcerative colitis (UC) in mice were evaluated. Compared to the DSS group, the LP prevention groups not only significantly inhibited the DSS-induced weight loss, decreased the disease activity index (DAI) score, increased the colon length, and improved inflammation in the colon but also significantly increased the levels of superoxide dismutase (SOD),catalase (CAT), glutathione peroxidase (GSH-Px), and glutathione (GSH) in the colon and reduced inflammatory cytokine, myeloperoxidase (MPO), and malondialdehyde (MDA) levels. Notably, when compared to the DSS group, the protein expression levels of TLR4, TRIF, and p-NF-κB p65 in the mice colon tissue were downregulated and those of tight junction-related proteins were upregulated in the LP + DSS group, with the most significant effect observed in the 10 mg/kg LP + DSS group. These results confirmed that the upregulation of tight junction-related protein expression after blocking the TLR4/TRIF/NF-κB signaling pathway may be one of the mechanisms through which LP prevents UC.

Purpose:To report a typical case of nanophthalmos with uveal effusion and local serous retinal detachment followed for 1 year. Methods:Clinical ocular examinations included vision, refraction, corneal diameter; anterior chamber depth, intraocular pressure, fundoscopy, A/B scan ultrasonography and gonioscopy. Results:Both eyes were hypermetropic with small corneas and shallow anterior chambers. Decreased axial length and thickened sclera were also found. There were peripheral choroidal effusions and local serous retinal detachments as well. The patient declined any surgery that was offered. No significant change in either eye was found after I year follow-up. Conclusion:This case illustrates that the progress of choroidal effusion and retinal detachment in nanophthalmos may be very slow and even non-progressive for at least 1 year. In these cases sclerectomy and or sclerotomy may be delayed without undue immediate risk to the vision.