Honokiol Exhibits Anti-NLRP3 Inflammasome and Antimicrobial Properties in Neisseria gonorrhoeae-Infected Macrophages.

Purpose: The NOD-like receptor family pyrin domain-containing 3 (NLRP3) inflammasome, crucial in infectious and inflammatory diseases by regulating IL-1ß, presents a target for disease management. Neisseria gonorrhoeae causes gonorrhea in over 87 million people annually, with previous research revealing NLRP3 inflammasome activation in infected macrophages. No natural products have been reported to counteract this activation. Exploring honokiol, a phenolic compound from Chinese herbal medicine, we investigated its impact on NLRP3 inflammasome activation in N. gonorrhoeae-infected macrophages. Methods: Honokiol's impact on the protein expression of pro-inflammatory mediators was analyzed using ELISA and Western blotting. The generation of intracellular H2O2 and mitochondrial reactive oxygen species (ROS) was detected through specific fluorescent probes (CM-H2DCFDA and MitoSOX, respectively) and analyzed by flow cytometry. Mitochondrial membrane integrity was assessed using specific fluorescent probes (MitoTracker and DiOC2(3)) and analyzed by flow cytometry. Additionally, the effect of honokiol on the viability of N. gonorrhoeae was examined through an in vitro colony-forming units assay. Results: Honokiol effectively inhibits caspase-1, caspase-11 and GSDMD activation and reduces the extracellular release of IL-1ß, NLRP3, and apoptosis-associated speck-like protein containing a caspase recruitment domain (ASC) in N. gonorrhoeae-infected macrophages. Detailed investigations have demonstrated that honokiol lowers the production of H2O2 and the phosphorylation of ERK1/2 in N. gonorrhoeae-infected macrophages. Importantly, the phosphorylation of JNK1/2 and p38 and the activation of NF-κB remain unaffected. Moreover, honokiol reduces the N. gonorrhoeae-mediated generation of reactive oxygen species within the mitochondria, preserving their integrity. Additionally, honokiol suppresses the expression of the pro-inflammatory mediator IL-6 and inducible nitric oxide synthase induced by N. gonorrhoeae independently of NLRP3. Impressively, honokiol exhibits in vitro anti-gonococcal activity against N. gonorrhoeae. Conclusion: Honokiol inhibits the NLRP3 inflammasome in N. gonorrhoeae-infected macrophages and holds great promise for further development as an active ingredient in the prevention and treatment of symptoms associated with gonorrhea.

Cinnamaldehyde inhibits the NLRP3 inflammasome by preserving mitochondrial integrity and augmenting autophagy in Shigella sonnei-infected macrophages.

BACKGROUND: Worldwide, more than 125 million people are infected with Shigella each year and develop shigellosis. In our previous study, we provided evidence that Shigella sonnei infection triggers activation of the NACHT, LRR, and PYD domain-containing protein 3 (NLRP3) inflammasome in macrophages. NLRP3 inflammasome is responsible for regulating the release of the proinflammatory cytokines interleukin (IL)-1ß and IL-18 through the protease caspase-1. Researchers and biotech companies have shown great interest in developing inhibitors of the NLRP3 inflammasome, recognizing it as a promising therapeutic target for several diseases. The leaves of Cinnamomum osmophloeum kaneh, an indigenous tree species in Taiwan, are rich in cinnamaldehyde (CA), a compound present in significant amounts. Our aim is to investigate how CA affects the activation of the NLRP3 inflammasome in S. sonnei-infected macrophages. METHODS: Macrophages were infected with S. sonnei, with or without CA. ELISA and Western blotting were employed to detect protein expression or phosphorylation levels. Flow cytometry was utilized to assess H2O2 production and mitochondrial damage. Fluorescent microscopy was used to detect cathepsin B activity and mitochondrial ROS production. Additionally, colony-forming units were employed to measure macrophage phagocytosis and bactericidal activity. RESULTS: CA inhibited the NLRP3 inflammasome in S. sonnei-infected macrophages by suppressing caspase-1 activation and reducing IL-1ß and IL-18 expression. CA also inhibited pyroptosis by decreasing caspase-11 and Gasdermin D activation. Mechanistically, CA reduced lysosomal damage and enhanced autophagy, while leaving mitochondrial damage, mitogen-activated protein kinase phosphorylation, and NF-κB activation unaffected. Furthermore, CA significantly boosted phagocytosis and the bactericidal activity of macrophages against S. sonnei, while reducing secretion of IL-6 and tumour necrosis factor following infection. CONCLUSION: CA shows promise as a nutraceutical for mitigating S. sonnei infection by diminishing inflammation and enhancing phagocytosis and the bactericidal activity of macrophages against S. sonnei.

Fluorescence immunosensor based on a specific monoclonal antibody for highly sensitive and rapid detection of gizzerosine in feed.

Gizzerosine is a biogenic amine produced in fish meal drying process and posted higher mortality due to gizzard erosion in poultry than histamine. However, it is difficult to obtain gizzerosine and achieve sensitive practical detection due to its simple structure. Herein, a monoclonal antibody (mAb) specific to gizzerosine was generated based on the new structural design and a fluorescence immunosensor for sensitive and on-site detection of gizzerosine in feed was first established. Molecular modeling of the three-dimensional (3D) structure and surface electrostatic potential of gizzerosine indicated that the carbonyl group of gizzerosine hapten might affect the important sites of antigen-antibody interactions. The proposed structure was used to obtain the sensitive and specific mAb with IC50 of 3.88 ng/mL in indirect competitive ELISA which was approximately 100-fold lower than that of direct competitive ELISA. Considering the practical application scenarios, a fluorescence immunosensor based on microporous dry method integrated with independent quality control line was established to improve detection stability. Under the optimum conditions, the proposed immunosensor showed a good linear relationship from 1.10 to 19.78 ng/mL and provided a low detection limit of 50 ng/g which was approximately 80-fold lower than the maximum recommended amount (0.4 mg/kg) of gizzerosine in feed. The recoveries of 6 kinds of feed ranged from 83.1 % to 114.3 %, which was in good consistence with that of UHPLC-MS/MS. Overall, this work provides a fast, cost-effective and reliable on-site tool for rapid screening of gizzerosine residues in feed samples.

Genetically predicted causal effects of gut microbiota on spinal pain: a two-sample Mendelian randomization analysis.

Background: Observational studies have hinted at a correlation between the gut microbiota and spinal pain (SP). However, the impact of the gut microbiota on SP remains inconclusive. Methods: In this study, we employed a two-sample Mendelian randomization (MR) analysis to explore the causal relationship between the gut microbiota and SP, encompassing neck pain (NP), thoracic spine pain (TSP), low back pain (LBP), and back pain (BP). The compiled gut microbiota data originated from a genome-wide association study (GWAS) conducted by the MiBioGen consortium (n = 18,340). Summary data for NP were sourced from the UK Biobank, TSP from the FinnGen Biobank, and LBP from both the UK Biobank and FinnGen Biobank. Summary data for BP were obtained from the UK Biobank. The primary analytical approach for assessing causal relationships was the Inverse Variance Weighted (IVW) method, supplemented by various sensitivity analyses to ensure result robustness. Results: The IVW analysis unveiled 37 bacterial genera with a potential causal relationship to SP. After Benjamini-Hochberg corrected test, four bacterial genera emerged with a strong causal relationship to SP. Specifically, Oxalobacter (OR: 1.143, 95% CI 1.061-1.232, P = 0.0004) and Tyzzerella 3 (OR: 1.145, 95% CI 1.059-1.238, P = 0.0007) were identified as risk factors for LBP, while Ruminococcaceae UCG011 (OR: 0.859, 95% CI 0.791-0.932, P = 0.0003) was marked as a protective factor for LBP, and Olsenella (OR: 0.893, 95% CI 0.839-0.951, P = 0.0004) was recognized as a protective factor for low back pain or/and sciatica. No significant heterogeneity or horizontal pleiotropy was observed through alternative testing methods. Conclusion: This study establishes a causal relationship between the gut microbiota and SP, shedding light on the "gut-spine" axis. These findings offer novel perspectives for understanding the etiology of SP and provide a theoretical foundation for potential interventions targeting the gut microbiota to prevent and treat SP.

Association of Lung Cancer Risk With the Presence of Both Lung Nodules and Emphysema in a Lung Cancer Screening Trial.

Background: The coexistence of emphysema and lung nodules could interact with each other and then lead to potential higher lung cancer risk. The study aimed to explore the association between emphysema combined with lung nodules and lung cancer risk. Methods: A total of 21,949 participants from the National Lung Screening Trial (NLST) who underwent low-dose computed tomography (LDCT) examination were included. Participants were categorized into four groups (NENN group (non-emphysema and non-nodules), E group (emphysema without nodules), N group (nodules without emphysema), and E + N group (nodules with emphysema)) according to whether there were lung nodules and emphysema. Multivariable Cox regression and stratified analyses were performed to estimate the association between the four groups and lung cancer risk. Results: Among the 21,949 participants, there were 9,040 (41.2%), 5,819 (26.5%), 4,737 (21.6%), and 2,353 (10.7%) participants in the NENN group, E group, N group, and E + N group. The risk of lung cancer incidence increased in turn in NENN group, E group, N group and E + N group. Compared with NENN group, the age-adjusted hazard ratios (HRs) (95% confidence intervals (CIs)) of lung cancer incidence were 2.07 (1.69 - 2.54) for E group, 4.13 (3.47 - 5.05) for N group, and 6.26 (5.14 - 7.62) for E + N group. The association was robust to adjustment for potential confounders (1.83 (1.47 - 2.27) for E group, 3.97 (3.24 - 4.86) for N group, and 5.23 (4.28 - 6.48) for E + N group). Comparable results as the lung cancer incidence were observed for lung cancer mortality, whether in age-adjusted model (E group: 1.85 (1.39 - 2.46), N group: 2.49 (1.89 - 3.29), E + N group: 4.27 (3.21 - 5.68)) or fully adjusted model (E group: 1.56 (1.15 - 2.11), N group: 2.43 (1.81 - 3.26), E + N group: 3.39 (2.50 - 4.61)). However, the trend of all-cause mortality risk among the four groups was somewhat different from that of lung cancer risk, whether in age-adjusted model (1.37 (1.21 - 1.54) for E group, 1.06 (0.92 - 1.21) for N group, and 1.75 (1.51 - 2.02) for E + N group) or fully adjusted model (1.26 (1.10 - 1.44) for E group, 1.09 (0.94 - 1.27) for N group, and 1.52 (1.30 - 1.79) for E + N group). Conclusion: Based on a large-scale lung cancer screening trial in the United States, this study demonstrated that either emphysema or lung nodules can increase lung cancer risk, and lung nodules combined with emphysema can further increase the lung cancer risk and all-cause mortality. The significance of these findings for lung cancer screening should be evaluated.

Insights into drought stress response mechanism of tobacco during seed germination by integrated analysis of transcriptome and metabolome.

Drought stress inhibits seed germination, plant growth and development of tobacco, and seriously affects the yield and quality of tobacco leaves. However, the molecular mechanism underlying tobacco drought stress response remains largely unknown. In this study, integrated analysis of transcriptome and metabolome was performed on the germinated seeds of a cultivated variety K326 and its EMS mutagenic mutant M28 with great drought tolerance. The result showed that drought stress inhibited seed germination of the both varieties, while the germination rate of M28 was faster than that of K326 under drought stress. Besides, the levels of phytohormone ABA, GA19, and zeatin were increased by drought stress in M28. Five vital pathways were identified through integrated transcriptomic and metabolomic analysis, including zeatin biosynthesis, aspartate and glutamate synthesis, phenylamine metabolism, glutathione metabolism, and phenylpropanoid synthesis. Furthermore, 20 key metabolites in the above pathways were selected for further analysis of gene modular-trait relationship, and then four highly correlated modules were found. Then analysis of gene expression network was carried out of Top30 hub gene of these four modules, and 9 key candidate genes were identified, including HSP70s, XTH16s, APX, PHI-1, 14-3-3, SCP, PPO. In conclusion, our study uncovered some key drought-responsive pathways and genes of tobacco during seeds germination, providing new insights into the regulatory mechanisms of tobacco drought stress response.

Two-dimensional MXene Nanomaterials: Preparation, Structure Modulation and the Applications in Electrochemical Energy Storage.

BACKGROUND: MXenes have attracted intensive attention owing to their unique twodimensional (2D) layered structure, high specific surface area, excellent conductivity, superior surface hydrophilicity, and chemical stability. In recent years, selective etching of the A element layers from MAX phases by fluorine-containing etchants (HF, LiF-HCl, etc) is a common method to prepare multilayered MXene nanomaterials (NMs) with plentiful surface terminations. At present, many studies have been reported on the use of fluorine-free etchants (NaOH, ZnCl2, etc) to etch MAX phases. The properties of MXene NMs are dependent on their structures. OBJECTIVE: The purpose of this review is to focus on a comprehensive and systematical survey on the preparation, structure modulation, and applications of MXene NMs in electrochemical energy storage devices, including supercapacitors, lithium-ion battery, sodium-ion battery, potassium-ion battery, and aluminum-ion battery. METHODS: Extensive information related to the preparation and applications of 2D MXene NMs for electrochemical energy storage and their associated patents were collected. This review highlights the recently reported 2D MXene NMs which are used in supercapacitor and various metal ion. RESULTS: It is found that the preparation methods have great impacts on the layer spacing and surface terminations of MXenes, consequently affecting their performance. Hence, this paper summarizes the research progress of the preparation strategies, layer spacing and surface termination modulation of MXene NMs. CONCLUSION: The applications of 2D MXene NMs in electrochemical energy storage are outlined. The forward-looking challenges and prospects for the development of MXenes are also proposed.

PFENet++: Boosting Few-Shot Semantic Segmentation With the Noise-Filtered Context-Aware Prior Mask.

In this work, we revisit the prior mask guidance proposed in "Prior Guided Feature Enrichment Network for Few-Shot Segmentation". The prior mask serves as an indicator that highlights the region of interests of unseen categories, and it is effective in achieving better performance on different frameworks of recent studies. However, the current method directly takes the maximum element-to-element correspondence between the query and support features to indicate the probability of belonging to the target class, thus the broader contextual information is seldom exploited during the prior mask generation. To address this issue, first, we propose the Context-aware Prior Mask (CAPM) that leverages additional nearby semantic cues for better locating the objects in query images. Second, since the maximum correlation value is vulnerable to noisy features, we take one step further by incorporating a lightweight Noise Suppression Module (NSM) to screen out the unnecessary responses, yielding high-quality masks for providing the prior knowledge. Both two contributions are experimentally shown to have substantial practical merit, and the new model named PFENet++ significantly outperforms the baseline PFENet as well as all other competitors on three challenging benchmarks PASCAL-5 i, COCO-20 i and FSS-1000. The new state-of-the-art performance is achieved without compromising the efficiency, manifesting the potential for being a new strong baseline in few-shot semantic segmentation.

Specific gastrointestinal microbiota profiles in Chinese Tan sheep are associated with lauric acid content in muscle.

The biological mechanisms underlying meat quality remain unclear. Currently, many studies report that the gastrointestinal microbiota is essential for animal growth and performance. However, it is uncertain which bacterial species are specifically associated with the meat quality traits. In this study, 16S rDNA and metagenomic sequencing were performed to explore the composition and function of microbes in various gastrointestinal segments of Tan sheep and Dorper sheep, as well as the relationship between microbiota and meat quality (specifically, the fatty acid content of the muscle). In the ruminal, duodenal, and colonic microbiome, several bacteria were uniquely identified in respective breeds, including Agrobacterium tumefaciens, Bacteroidales bacterium CF, and several members of the family Oscillospiraceae. The annotation of GO, KEGG, and CAZYme revealed that these different bacterial species were linked to the metabolism of glucose, lipids, and amino acids. Additionally, our findings suggested that 16 microbial species may be essential to the content of fatty acids in the muscle, especially C12:0 (lauric acid). 4 bacterial species, including Achromobacter xylosoxidans, Mageeibacillus indolicus, and Mycobacterium dioxanotrophicus, were positively correlated with C12:0, while 13 bacteria, including Methanobrevibacter millerae, Bacteroidales bacterium CF, and Bacteroides coprosuis were negatively correlated with C12:0. In a word, this study provides a basic data for better understanding the interaction between ruminant gastrointestinal microorganisms and the meat quality traits of hosts.

Chinese herbal injections in combination with radiotherapy for advanced pancreatic cancer: A systematic review and network meta-analysis.

Background: Advanced pancreatic cancer (APC) is a fatal disease with limited treatment options. This study aims to evaluate the effectiveness and safety of different Chinese herbal injections (CHIs) as adjuvants for radiotherapy (RT) in APC and compare their treatment potentials using network meta-analysis. Methods: We systematically searched three English and four Chinese databases for randomized controlled trials (RCTs) from inception to July 25, 2023. The primary outcome was the objective response rate (ORR). Secondary outcomes included Karnofsky performance status (KPS) score, overall survival (OS), and adverse events (AEs). The treatment potentials of different CHIs were ranked using the surface under the cumulative ranking curve (SUCRA). The Cochrane RoB 2 tool and CINeMA were used for quality assessment and evidence grading. Results: Eighteen RCTs involving 1199 patients were included. Five CHIs were evaluated. Compound Kushen injection (CKI) combined with RT significantly improved ORR compared to RT alone (RR 1.49, 95 % CrI 1.21-1.86). Kanglaite (KLT) plus RT (RR 1.58, 95 % CrI 1.20-2.16) and CKI plus RT (RR 1.49, 95 % CrI 1.16-1.95) were associated with improved KPS score compared to radiation monotherapy, with KLT+RT being the highest rank (SUCRA 72.28 %). Regarding AEs, CKI plus RT was the most favorable in reducing the incidence of leukopenia (SUCRA 90.37 %) and nausea/vomiting (SUCRA 85.79 %). Conclusions: CKI may be the optimal choice of CHIs to combine with RT for APC as it may improve clinical response, quality of life, and reduce AEs. High-quality trials are necessary to establish a robust body of evidence. Protocol registration: PROSPERO, CRD42023396828.

Functional characterization of alkaline phosphatases involved alarm pheromone in the vetch aphid Megoura viciae.

The alkaline phosphatases (ALPs) are highly promiscuous enzymes and have been extensively investigated in mammals for their medical significance, but their functional promiscuity is relatively poorly understood in insects. Here, we first identified four ALP genes (designated as MvALP1-4) in the vetch aphid Megoura viciae that contained one alkaline phosphatase site, three metal-binding sites, and varied other functional sites. Phylogenetic analysis, molecular docking and the spatiotemporal expression profiling of MvALP1-4 were very different, indicating a promiscuous functionality. We also found that MvALP4 involved the biosynthesis of aphid alarm pheromones (EßF) in vitro and in vivo. Finally, transcriptome analysis in the stimulated and unstimulated aphids supported the involvement of MvALPs in the biosynthesis of aphid alarm pheromones. Our study identified a multifunctional ALP involved terpene synthase enzyme activity in the aphid, which contributes to the understanding of the functional plasticity of ALPs in insects.

Integrating single-cell and bulk RNA sequencing to predict prognosis and immunotherapy response in prostate cancer.

Prostate cancer (PCa) stands as a prominent contributor to morbidity and mortality among males on a global scale. Cancer-associated fibroblasts (CAFs) are considered to be closely connected to tumour growth, invasion, and metastasis. We explored the role and characteristics of CAFs in PCa through bioinformatics analysis and built a CAFs-based risk model to predict prognostic treatment and treatment response in PCa patients. First, we downloaded the scRNA-seq data for PCa from the GEO. We extracted bulk RNA-seq data for PCa from the TCGA and GEO and adopted "ComBat" to remove batch effects. Then, we created a Seurat object for the scRNA-seq data using the package "Seurat" in R and identified CAF clusters based on the CAF-related genes (CAFRGs). Based on CAFRGs, a prognostic model was constructed by univariate Cox, LASSO, and multivariate Cox analyses. And the model was validated internally and externally by Kaplan-Meier analysis, respectively. We further performed GO and KEGG analyses of DEGs between risk groups. Besides, we investigated differences in somatic mutations between different risk groups. We explored differences in the immune microenvironment landscape and ICG expression levels in the different groups. Finally, we predicted the response to immunotherapy and the sensitivity of antitumour drugs between the different groups. We screened 4 CAF clusters and identified 463 CAFRGs in PCa scRNA-seq. We constructed a model containing 10 prognostic CAFRGs by univariate Cox, LASSO, and multivariate Cox analysis. Somatic mutation analysis revealed that TTN and TP53 were significantly more mutated in the high-risk group. Finally, we screened 31 chemotherapeutic drugs and targeted therapeutic drugs for PCa. In conclusion, we identified four clusters based on CAFs and constructed a new CAFs-based prognostic signature that could predict PCa patient prognosis and response to immunotherapy and might suggest meaningful clinical options for the treatment of PCa.

Quantization via Distillation and Contrastive Learning.

Quantization is a critical technique employed across various research fields for compressing deep neural networks (DNNs) to facilitate deployment within resource-limited environments. This process necessitates a delicate balance between model size and performance. In this work, we explore knowledge distillation (KD) as a promising approach for improving quantization performance by transferring knowledge from high-precision networks to low-precision counterparts. We specifically investigate feature-level information loss during distillation and emphasize the importance of feature-level network quantization perception. We propose a novel quantization method that combines feature-level distillation and contrastive learning to extract and preserve more valuable information during the quantization process. Furthermore, we utilize the hyperbolic tangent function to estimate gradients with respect to the rounding function, which smoothens the training procedure. Our extensive experimental results demonstrate that the proposed approach achieves competitive model performance with the quantized network compared to its full-precision counterpart, thus validating its efficacy and potential for real-world applications.

Ultrasonic visualization technique for anatomical and functional analyses of the sciatic nerve in rats.

Background and objective: Ultrasound has been widely used in the diagnosis and minimally invasive treatment of peripheral nerve diseases in the clinic, but there is still a lack of feasibility analysis in rodent models of neurological disease. The purpose of this study was to investigate the changes in the cross-sectional area of the sciatic nerve of different genders and body weights and to explore the effectiveness and reliability of an ultrasound-guided block around the sciatic nerve in living rats. Methods: Using ultrasound imaging anatomy of the sciatic nerve of rats, the cross-sectional area of the sciatic nerve in rats of different genders from 6 to 10 weeks old was calculated, and then analyzed its correlation with body weight. Further analyses were conducted through behavioral and cadaveric studies to evaluate the feasibility of ultrasound-guided perineural injection of the sciatic nerve in rats. Results: We first reported that the sciatic nerve cross-sectional area of rats was increased with age (F = 89.169, P < 0.001), males had a higher sciatic nerve cross-sectional area than females (F = 60.770, P < 0.001), and there was a positive correlation with body weight (rMale = 0.8976, P < 0.001; rFemale = 0.7733, P < 0.001). Behavioral observation of rats showed that the lower extremity complete block rate was 80% following the administration of drugs around the sciatic nerve under ultrasound guidance and staining with methylene blue occurred in all sciatic nerves and surrounding muscles and fascia using 20 ultrasound-guided injections. Conclusions: Ultrasound visualization technology can be used as a new auxiliary evaluation and intervention therapy for animal models of peripheral nerve injury, and will provide overwhelming new references for the basic research of neurological diseases.

Generalized Parametric Contrastive Learning.

In this paper, we propose the Generalized Parametric Contrastive Learning (GPaCo/PaCo) which works well on both imbalanced and balanced data. Based on theoretical analysis, we observe supervised contrastive loss tends to bias on high-frequency classes and thus increases the difficulty of imbalanced learning. We introduce a set of parametric class-wise learnable centers to rebalance from an optimization perspective. Further, we analyze our GPaCo/PaCo loss under a balanced setting. Our analysis demonstrates that GPaCo/PaCo can adaptively enhance the intensity of pushing samples of the same class close as more samples are pulled together with their corresponding centers and benefit hard example learning. Experiments on long-tailed benchmarks manifest the new state-of-the-art for long-tailed recognition. On full ImageNet, models from CNNs to vision transformers trained with GPaCo loss show better generalization performance and stronger robustness compared with MAE models. Moreover, GPaCo can be applied to semantic segmentation task and obvious improvements are observed on 4 most popular benchmarks. Our code is available at https://github.com/dvlab-research/Parametric-Contrastive-Learning.

Effective Active Learning Method for Spiking Neural Networks.

A large quantity of labeled data is required to train high-performance deep spiking neural networks (SNNs), but obtaining labeled data is expensive. Active learning is proposed to reduce the quantity of labeled data required by deep learning models. However, conventional active learning methods in SNNs are not as effective as that in conventional artificial neural networks (ANNs) because of the difference in feature representation and information transmission. To address this issue, we propose an effective active learning method for a deep SNN model in this article. Specifically, a loss prediction module ActiveLossNet is proposed to extract features and select valuable samples for deep SNNs. Then, we derive the corresponding active learning algorithm for deep SNN models. Comprehensive experiments are conducted on CIFAR-10, MNIST, Fashion-MNIST, and SVHN on different SNN frameworks, including seven-layer CIFARNet and 20-layer ResNet-18. The comparison results demonstrate that the proposed active learning algorithm outperforms random selection and conventional ANN active learning methods. In addition, our method converges faster than conventional active learning methods.

The role of Rho GTPase family in cochlear hair cells and hearing.

Rho GTPases are essential regulators of the actin cytoskeleton. They are involved in various physiological and biochemical processes such as the regulation of cytoskeleton dynamics, development, proliferation, survival, and regeneration. During the development of cochlear hair cells, Rho GTPases are activated by various extracellular signals through membrane receptors to further stimulate multiple downstream effectors. Specifically, RhoA, Cdc42, and Rac1, members of the classical subfamily of the Rho GTPase family, regulate the development and maintenance of cilia by inducing the polymerization of actin monomers and stabilizing actin filaments. In addition, they also regulate the normal morphology orientation of ciliary bundles in auditory hair cells, which is an important element of cell polarity regulation. Moreover, the actin-related pathways mediated by RhoA, Cdc42, and Rac1 also play a role in the motility of outer hair cells, indicating that the function of Rho GTPases is crucial in the highly polar auditory sensory system. In this review, we focus on the expression of RhoA, Cdc42, and Rac1 in cochlear hair cells and how these small molecules participate in ciliary bundle morphogenesis and cochlear hair cell movement. We also discuss the progress of current research investigating the use of these small molecules as drug targets for deafness treatment.

Diagnosis and treatment of gastric hamartomatous inverted polyp (GHIP) by endoscopic submucosal dissection: A case report.

RATIONALE: Gastric hamartomatous inverted polyps (GHIP) is not a common disease, and it has rarely been reported in the literature. Preoperative diagnosis is difficult due to the deep position and surface covered with normal gastric mucosa. However, with the progress of endoscopic technology, endoscopic submucosal dissection (ESD) can play a crucial role in the diagnosis and treatment of GHIP. PATIENT CONCERNS: A 61-year-old Chinese man underwent gastroscopy due to abdominal pain 2 months prior that revealed chronic superficial nonatrophic gastritis with erosion and a submucosal tumor in the gastric body (an ultrasound gastroscopy was recommended). Therefore, he was admitted to our hospital for further diagnosis and treatment. DIAGNOSES: A hemispherical submucosal tumor was found in the middle segment of the stomach, with a size of approximately 30 mm × 35 mm and a smooth surface without central ulceration or mucosal bridge formation. Ultrasound gastroscopy showed that the lesion was a hypoechoic mass with uniform internal echo originating from the muscularis propria. INTERVENTIONS: The tumor was completely removed by using ESD. The postoperative pathological results indicated a monocystic structure in the submucosa that was not connected with the surface mucosa. The surface of the cyst was covered with foveolar cells and mucous-neck cells (part of which had low-grade intraepithelial neoplasia), and GHIP was considered to be diagnosed. OUTCOMES: According to the abovementioned endoscopic and pathological features, the patient was finally diagnosed with GHIP. The patient was successfully discharged after surgery and received regular follow-up observations. LESSONS: GHIP is located in the submucosa layer and has the potential risk of malignant transformation. However, it is not easy to diagnose by using gastroscopy and ultrasound gastroscopy. ESD can obtain complete specimens, which contributes to the diagnosis and treatment of GHIP.

Adaptive Perspective Distillation for Semantic Segmentation.

Strong semantic segmentation models require large backbones to achieve promising performance, making it hard to adapt to real applications where effective real-time algorithms are needed. Knowledge distillation tackles this issue by letting the smaller model (student) produce similar pixel-wise predictions to that of a larger model (teacher). However, the classifier, which can be deemed as the perspective by which models perceive the encoded features for yielding observations (i.e., predictions), is shared by all training samples, fitting a universal feature distribution. Since good generalization to the entire distribution may bring the inferior specification to individual samples with a certain capacity, the shared universal perspective often overlooks details existing in each sample, causing degradation of knowledge distillation. In this paper, we propose Adaptive Perspective Distillation (APD) that creates an adaptive local perspective for each individual training sample. It extracts detailed contextual information from each training sample specifically, mining more details from the teacher and thus achieving better knowledge distillation results on the student. APD has no structural constraints to both teacher and student models, thus generalizing well to different semantic segmentation models. Extensive experiments on Cityscapes, ADE20K, and PASCAL-Context manifest the effectiveness of our proposed APD. Besides, APD can yield favorable performance gain to the models in both object detection and instance segmentation without bells and whistles.

Farnesyl/geranylgeranyl diphosphate synthases regulate the biosynthesis of alarm pheromone in a unique manner in the vetch aphid Megoura viciae.

Farnesyl/geranylgeranyl diphosphate synthases (FPPS/GGPPS) as the short-chain prenyltransferases catalyse the formation of the acyclic precursors (E)-FPP and (E)-GGPP for isoprenoid biosynthesis. Here, we first cloned the cDNAs encoding FPPS and GGPPS in the vetch aphid Megoura viciae (designated as MvFPPS and MvGGPPS). They had an open reading frame of 1185 and 930 bp in length, encoding 395 and 309 amino acids, with a theoretical isoelectric point of 6.52 and 6.21, respectively. Sequence alignment and phylogenetic analysis showed that MvFPPS and MvGGPPS shared the conserved aspartate-rich motifs characterized by all prenyltransferases identified to date and were clustered with their homologues in two large clades. RNA interference (RNAi) combined with gas chromatography/mass spectrometry (GC-MS) analysis showed that both MvFPPS and MvGGPPS were involved in the biosynthesis of alarm pheromone. Spatiotemporal expression profiling showed that the expression of MvFPPS and MvGGPPS was significantly higher in embryos than in other tissues. RNAi and GC-MS performed specifically in embryos corroborated the function of MvFPPS and MvGGPPS. In vitro, enzymatic activity assay and product analysis demonstrated that MvFPPS could catalysed the formation of (E)-FPP using DMAPP or (E)-GPP as the allylic cosubstrates in the presence of IPP, while MvGGPPS could only use (E)-GPP or (E)-FPP as cosubstrates. Functional interaction analysis using RNAi revealed that MvGGPPS exerts unidirectional functional compensation for MvFPPS. Moreover, it can regulate the biosynthesis of alarm pheromone by imposing a negative feedback regulation on MvFPPS. Our study helps to understand the molecular regulatory mechanism of terpenoid biosynthesis in the aphid.