Search

Polyamines are ubiquitous in almost all biological entities and involved in various crucial physiological processes. They are also closely associated with the onset and progression of many diseases. Polyaminopathies are a group of rare genetic disorders caused by alterations in the function of proteins within the polyamine metabolism network. Although the identified polyaminopathies are all rare diseases at present, they are genetically heritable, rendering high risks not only to the carriers but also to their descendants. Meanwhile, more polyaminopathic patients might be discovered with the increasing accessibility of gene sequencing. This review aims to provide a comprehensive overview of the structural variations of mutated proteins in current polyaminopathies, in addition to their causative genes, types of mutations, clinical symptoms, and therapeutic approaches. We focus on analyzing how alterations in protein structure lead to protein dysfunction, thereby facilitating the onset of diseases. We hope this review will offer valuable insights and references for the future clinical diagnosis and precision treatment of polyaminopathies.

C-type lectins play a crucial role as pathogen-recognition receptors for the dengue virus, which is responsible for causing both dengue fever (DF) and dengue hemorrhagic fever (DHF). DHF is a serious illness caused by the dengue virus, which exists in four different serotypes: DEN-1, DEN-2, DEN-3, and DEN-4. We conducted a genetic association study, during a significant DEN-2 outbreak in southern Taiwan, to explore how variations in the neck-region length of L-SIGN (also known as CD209L, CD299, or CLEC4M) impact the severity of dengue infection. PCR genotyping was utilized to identify polymorphisms in variable-number tandem repeats. We constructed L-SIGN variants containing either 7- or 9-tandem repeats and transfected these constructs into K562 and U937 cells, and cytokine and chemokine levels were evaluated using enzyme-linked immunosorbent assays (ELISAs) following DEN-2 virus infection. The L-SIGN allele 9 was observed to correlate with a heightened risk of developing DHF. Subsequent results revealed that the 9-tandem repeat was linked to elevated viral load alongside predominant T-helper 2 (Th2) cell responses (IL-4 and IL-10) in K562 and U937 cells. Transfecting K562 cells in vitro with L-SIGN variants containing 7- and 9-tandem repeats confirmed that the 9-tandem repeat transfectants facilitated a higher dengue viral load accompanied by increased cytokine production (MCP-1, IL-6, and IL-8). Considering the higher prevalence of DHF and an increased frequency of the L-SIGN neck’s 9-tandem repeat in the Taiwanese population, individuals with the 9-tandem repeat may necessitate more stringent protection against mosquito bites during dengue outbreaks in Taiwan.

Arylalkylamine N-acetyltransferase (AANAT) is a crucial rate-limiting enzyme in the synthesis of melatonin. AANAT has been confirmed to be independently duplicated and inactivated in different animal taxa in order to adapt to the environment. However, the evolutionary forces associated with having a single copy of AANAT remain unclear. The greater horseshoe bat has a single copy of AANAT but exhibits different hibernation rhythms in various populations. We analyzed the adaptive evolution at the gene and protein levels of AANAT from three distinct genetic lineages in China: northeast (NE), central east (CE), and southwest (SW). The results revealed greater genetic diversity in the AANAT loci of the NE and CE lineage populations that have longer hibernation times, and there were two positive selection loci. The catalytic capacity of AANAT in the Liaoning population that underwent positive selection was significantly higher than that of the Yunnan population (p < 0.05). This difference may be related to the lower proportion of α helix and the variation in two interface residues. The adaptive evolution of AANAT was significantly correlated with climate and environment (p < 0.05). After controlling for geographical factors (latitude and altitude), the evolution of AANAT by the negative temperature factor was represented by the monthly mean temperature (r = −0.6, p < 0.05). The results identified the gene level variation, functional adaptation, and evolutionary driving factors of AANAT, provide an important foundation for further understanding the adaptive evolution of the single copy of AANAT in pteropods, and may offer evidence for adaptive hibernation rhythms in bats.

Abstract Introduction Chronic hepatitis B virus (HBV) infection is associated with significant global morbidity and mortality. Low treatment rates are observed in patients living with HBV; the reasons for this are unclear. This study sought to describe patients’ demographic, clinical and biochemical characteristics across three continents and their associated treatment need. Methods This retrospective cross-sectional post hoc analysis of real-world data used four large electronic databases from the United States, United Kingdom and China (specifically Hong Kong and Fuzhou). Patients were identified by first evidence of chronic HBV infection in a given year (their index date) and characterized. An algorithm was designed and applied, wherein patients were categorized as treated, untreated but indicated for treatment and untreated and not indicated for treatment based on treatment status and demographic, clinical, biochemical and virological characteristics (age; evidence of fibrosis/cirrhosis; alanine aminotransferase [ALT] levels, HCV/HIV coinfection and HBV virology markers). Results In total, 12,614 US patients, 503 UK patients, 34,135 patients from Hong Kong and 21,614 from Fuzhou were included. Adults (99.4%) and males (59.0%) predominated. Overall, 34.5% of patients were treated at index (range 15.9–49.6%), with nucleos(t)ide analogue monotherapy most commonly prescribed. The proportion of untreated-but-indicated patients ranged from 12.9% in Hong Kong to 18.2% in the UK; almost two-thirds of these patients (range 61.3–66.7%) had evidence of fibrosis/cirrhosis. A quarter (25.3%) of untreated-but-indicated patients were aged ≥ 65 years. Conclusion This large real-world dataset demonstrates that chronic hepatitis B infection remains a global health concern; despite the availability of effective suppressive therapy, a considerable proportion of predominantly adult patients apparently indicated for treatment are currently untreated, including many patients with fibrosis/cirrhosis. Causes of disparity in treatment status warrant further investigation.

A new species Rosa funingensis and its variant R. funingensis f. rosea, both collected from Yunnan Province, China, are, for the first time, documented and illustrated in this study. Morphological analysis in comparison with two related species in the wild, R. gigantea and R. rubus, presents distinguishable features through leaf surfaces, inflorescences and the shape of styles. R. funingensis leaf surfaces are abaxially villous, purple-red, pale green when mature, adaxially glabrous, dark green; inflorescences solitary or 2–5(7) in corymbose cyme; and styles connate into a column or not, exserted.

In view of the rapid development and application of blockchain technology, this paper considers a secondary supply chain system consisting of a single upstream supplier and a downstream e-tailer that implements blockchain technology and a traditional e-tailer that does not implement blockchain technology. We establish the demand function of two channels based on consumers' sensitivity to the blockchain and use the Stackelberg game model to compare and analyse the e-tailers' profits from the two channels. For the basic properties, interestingly, we find that there exists a critical threshold on the cost sensitivity to effort that helps each e-tailer decide whether to implement effort. If the cost sensitivity to effort is high, the two-sided e-tailers will reduce their effort as much as possible to obtain greater profits. Conversely, if the cost sensitivity to effort is low, they will increase their effort to obtain more benefits. We also discuss the role of blockchain technology in competition between e-tailers and analyse the impact of the product brand effect brought by the traceability characteristic of blockchain on the competition between e-tailers. To check the robustness of the core results and to investigate different forms of supply chain configurations, this paper further develops the analysis of the supplier entering agency agreements with two-sided e-tailers. Under this scenario, the supplier sells their products directly to consumers through two-sided e-platforms and shares revenue with e-tailers as platform agency fees. These core ideas remain valid in the extended model.

The quality of primary products in a supply chain is determined by the agent and the principal. Simultaneously, there are quota production constraints on the principals. Our discourse centers on the design of incentive contracts for agents within these supply chains. We derived the parameters describing the contract, level of effort, profits for both sides, and the minimum requirements of the principal for the proportion of high-quality primary products. This study compares the decision-making paradigms of agents and principals in various contexts. The results show that decision-making mechanisms are strongly influenced by individual effort costs, various internal and external organizational variables, and the interplay of efforts on both sides. Using numerical experiments, we investigate the effects of different situations between clients and contractors on contracting and effort strategies. The results show that when the agent exerts unilateral effort, reasonable incentive contracts can spur the agent to increase effort and thus increase the proportion of high-quality primary products. In the case of bilateral efforts, a well-calibrated contract design benefits the agent (bearing less risk). For the principal, the expected profit increases in most cases. When considering the quota production, it is necessary to set an appropriate limit on the proportion of high-quality primary products.

Primary liver cancer (PLC) is one of the most commonly diagnosed cancers worldwide and a leading cause of cancer-related deaths. However, traditional liver cancer models fail to replicate tumor heterogeneity and the tumor microenvironment, limiting the study and personalized treatment of liver cancer. To overcome these limitations, scientists have introduced three-dimensional (3D) culture models as an emerging research tool. These 3D models, utilizing biofabrication technologies such as 3D bioprinting and microfluidics, enable more accurate simulation of the in vivo tumor microenvironment, replicating cell morphology, tissue stiffness, and cell-cell interactions. Compared to traditional two-dimensional (2D) models, 3D culture models better mimic tumor heterogeneity, revealing differential sensitivity of tumor cell subpopulations to targeted therapies or immunotherapies. Additionally, these models can be used to assess the efficacy of potential treatments, providing guidance for personalized therapy. 3D liver cancer models hold significant value in tumor biology, understanding the mechanisms of disease progression, and drug screening. Researchers can gain deeper insights into the impact of the tumor microenvironment on tumor cells and their interactions with the surrounding milieu. Furthermore, these models allow for the evaluation of treatment responses, offering more accurate guidance for clinical interventions. In summary, 3D models provide a realistic and reliable tool for advancing PLC research. By simulating tumor heterogeneity and the microenvironment, these models contribute to a better understanding of the disease mechanisms and offer new strategies for personalized treatment. Therefore, 3D models hold promising prospects for future PLC research.

IntroductionUnderstanding microbial communities in diverse ecosystems is crucial for unraveling the intricate relationships among microorganisms, their environment, and ecosystem processes. In this study, we investigated differences in the fungal community structure and diversity in soils from two contrasting climatic and vegetation conditions: the Xinjiang western China plateau and the Fujian southeastern coastal province.MethodsA total of 36 soil samples collected from two climatic regions were subjected to high-throughput ITS gene sequencing for fungal community analysis. In conjunction soil physicochemical properties were assessed and compared. Analyses included an examination of the relationship of fungal community structure to environmental factors and functional profiling of the community structure was using the FUNGuild pipeline.ResultsOur data revealed rich fungal diversity, with a total of 11 fungal phyla, 31 classes, 86 orders, 200 families, 388 genera, and 515 species identified in the soil samples. Distinct variations in the physicochemical properties of the soil and fungal community structure were seen in relation to climate and surface vegetation. Notably, despite a colder climate, the rhizosphere soil of Xinjiang exhibited higher fungal (α-)diversity compared to the rhizosphere soil of Fujian. β-diversity analyses indicated that soil heterogeneity and differences in fungal community structure were primarily influenced by spatial distance limitations and vegetation type. Furthermore, we identified dominant fungal phyla with significant roles in energy cycling and organic matter degradation, including members of the Sordariomycetes, Leotiomycetes, Archaeosporomycetes, and Agaricomycetes. Functional analyses of soil fungal communities highlighted distinct microbial ecological functions in Xinjiang and Fujian soils. Xinjiang soil was characterized by a focus on wood and plant saprotrophy, and endophytes, whereas in Fujian soil the fungal community was mainly associated with ectomycorrhizal interactions, fungal parasitism, and wood saprotrophy.DiscussionOur findings suggest fungal communities in different climatic conditions adapt along distinct patterns with, plants to cope with environmental stress and contribute significantly to energy metabolism and material cycling within soil-plant systems. This study provides valuable insights into the ecological diversity of fungal communities driven by geological and environmental factors.

Background: In the past, multiple studies have offered incremental evidence that indicates that competitive endogenous RNA (ceRNA) regulatory networks are involved in tumor growth and present novel therapeutic targets. Herein, we investigated the impact of thymidine kinase 1 (TK1)-related ceRNA networks on the prognosis of non-small cell lung cancer (NSCLC). Methods: TK1 expression data in NSCLC and normal tissue samples were retrieved from the Cancer Genome Atlas (TCGA) database and were then compared. Thereafter, the findings of the immunohistochemical staining experiments and clinical follow-up data derived from patients with NSCLC were used for conducting prognostic analysis. The starBase database was searched to determine TK1-targeted microRNAs and long non-coding RNAs, and clinical data from TCGA were used for survival analysis to construct a ceRNA network associated with TK1 expression and prognosis. Finally, the roles played by methylation and immunity in the prognosis and treatment of NSCLC were analyzed. Results: Our findings revealed that the cancer tissues expressed significantly higher TK1 levels than normal tissues, and the follow-up clinical data revealed that the prognosis was generally worse in the high-expression patients than in the low-expression patients. In addition, clinical data collected from the starBase and TCGA databases showed that the LINC00665/has-let-7b-5p/TK1 network could influence the growth and prognosis of NSCLC. It was also noted that the TK1 methylation site was correlated with the prognosis of NSCLC, and immunoprognostic analysis further indicated that patients with higher TK1 expression levels displayed a worse prognosis. Conclusion: When the regulatory network of LINC00665/has-let-7b-5p/TK1 was assessed, it was observed that elevated TK1 levels may affect the prognosis of NSCLC. Therefore, it could be considered a prognostic biomarker and a probable therapeutic target for predicting NSCLC prognosis.

A swarm intelligence optimization algorithm is an effective method to rapidly solve large-scale complex optimization problems. The JAYA algorithm is a new swarm intelligence evolutionary optimization algorithm, which was proposed in 2016. Compared with other active evolutionary algorithms, the JAYA algorithm has several advantages, such as a clear mechanism, concise structure, and ease of implementation. Further, it has guiding characteristics, obtains the best solution, and avoids the worst solution. The JAYA algorithm has an excellent optimization effect on many problems, and it is one of the most influential algorithms in the field of swarm intelligence. However, when dealing with the CEC test suite, which contains and combines shifted, rotation, hybrid, combination, and other composite characteristics, and the complex engineering constrained optimization problems with considerable difficulty and challenges, the JAYA algorithm has some flaws, that is, it easily falls into the local extremum, its optimization accuracy is sometimes low, and its solution is unstable. To better solve complex function optimization and engineering constrained optimization problems and further enhance the optimization capability of the JAYA algorithm, a global optimization-oriented hybrid evolutionary JAYA algorithm is proposed. First, opposition-based learning is introduced to calculate the current best and worst individuals, which improves the possibility of the best and worst individuals jumping out of the local extremum region. Second, the sine–cosine operator and differential disturbance mechanism are introduced and integrated into individual position updating, which not only improves the diversity of the population but also better balances and meets the different requirements of the algorithm for exploration and mining in different iteration periods. Finally, in the algorithm structure, the hybrid evolution strategy with different parity states is adopted and the advantages of different evolution mechanisms are effectively used, which further improves the convergence and accuracy of the algorithm. Then, the pseudocode of the improved algorithm is given, and the theoretical analysis proves that the time complexity of the improved algorithm is consistent with the basic JAYA algorithm. Through the simulation experiment of function extremum optimization of six representative algorithms on multiple dimensions of the CEC2017 test suite, which contains and combines 30 benchmark functions and the optimal solution of six challenging engineering design problems, such as tension/compression spring, corrugated bulkhead, tubular column, reinforced concrete beam, welded beam, and car side impact. The optimal solution of the test results shows that the improved algorithm has significantly improved the optimization accuracy, convergence performance, and solution stability, and it has obvious advantages in solving CEC complex functions and engineering constrained optimization problems.

Abstract Gastric cancer is a high molecular heterogeneous disease with a poor prognosis. Although gastric cancer is a hot area of medical research, the mechanism of gastric cancer occurrence and development is still unclear. New strategies for treating gastric cancer need to be further explored. Protein tyrosine phosphatases play vital roles in cancer. A growing stream of studies shows that strategies or inhibitors targeting protein tyrosine phosphatases have been developed. PTPN14 belongs to the protein tyrosine phosphatase subfamily. As an inert phosphatase, PTPN14 has very poor activity and mainly functions as a binding protein through its FERM (four-point-one, ezrin, radixin, and moesin) domain or PPxY motif. The online database indicated that PTPN14 may be a poor prognostic factor for gastric cancer. However, the function and underlying mechanism of PTPN14 in gastric cancer remain unclear. We collected gastric cancer tissues and detected the expression of PTPN14. We found that PTPN14 was elevated in gastric cancer. Further correlation analysis indicated that PTPN14 was relevant with the T stage and cTNM (clinical tumor node metastasis classification) stage. The survival curve analysis showed that gastric cancer patients with higher PTPN14 expression had a shorter survival time. In addition, we illustrated that CEBP/β (CCAAT enhanced binding protein beta) could transcriptionally activate PTPN14 expression in gastric cancer. The highly expressed PTPN14 combined with NFkB (nuclear factor Kappa B) through its FERM domain and accelerated NFkB nucleus translocation. Then, NFkB promoted the transcription of PI3KA and initiated the PI3KA/AKT/mTOR pathway to promote gastric cancer cell proliferation, migration, and invasion. Finally, we established mice models to validate the function and the molecular mechanism of PTPN14 in gastric cancer. In summary, our results illustrated the function of PTPN14 in gastric cancer and demonstrated the potential mechanisms. Our findings provide a theoretical basis to better understand the occurrence and development of gastric cancer.

Lithium–sulfur batteries (LSBs) are recognized as among the best potential alternative battery systems to lithium-ion batteries and have been widely investigated. However, the shuttle effect has severely restricted the advancement in their practical applications. Here, we prepare vanadium nitride (VN) nanoparticles grown in situ on a nitrogen-doped carbon skeleton (denoted as VN@NC) derived from the MAX phase and use it as separator modification materials for LSBs to suppress the shuttle effect and optimize electrochemical performance. Thanks to the outstanding catalytic performance of VN and the superior electrical conductivity of carbon skeleton derived from MAX, the synergistic effect between the two accelerates the kinetics of both lithium polysulfides (LiPSs) to Li2S and the reverse reaction, effectively suppresses the shuttle effect, and increases cathode sulfur availability, significantly enhancing the electrochemical performance of LSBs. LSBs constructed with VN@NC-modified separators achieve outstanding rate performance and cycle stability. With a capacity of 560 mAh g−1 at 4 C, it exhibits enhanced structural and chemical stability. At 1 C, the device has an incipient capacity of 1052.4 mAh g−1, and the degradation rate averaged only 0.085% over 400cycles. Meanwhile, the LSBs also show larger capacities and good cycling stability at a low electrolyte/sulfur ratio and high surface-loaded sulfur conditions. Thus, a facile and efficient way of preparing modified materials for separators is provided to realize high-performance LSBs.

This research delves into the impact of climate change on the wood traits of Cunninghamia lanceolata across various altitudinal gradients, aiming to understand the influence of altitude and climatic factors like temperature and precipitation on key wood characteristics. Employing a comprehensive approach, samples were collected from different altitudes for detailed phenotypic analysis. Methods included Pearson correlation, principal component analysis, cluster analysis, and random forest analysis. Results revealed significant variations in wood traits such as heartwood ratio, tracheid length, and width across altitudes. Notably, wood traits in lower- and middle-elevation populations exhibited higher variability compared to higher elevations, indicating greater environmental diversity and genetic adaptability at these altitudes. Climatic factors, particularly temperature and precipitation, were found to increasingly influence wood trait variation with altitude. The research concludes that the adaptation of Cunninghamia lanceolata to climate change is significantly influenced by both altitudinal and climatic factors, highlighting their importance in forest genetic breeding and conservation strategies amidst global climate change.

The Asian water plantain, Alisma orientale (Sam.) Juzep, is a traditional Chinese medicinal plant. The dried tubers of the Alisma orientale, commonly referred to as Alismatis rhizome (AR), have long been used in traditional Chinese medicine to treat a variety of diseases. Soil properties and the soil microbial composition are known to affect the quality and bioactivity of plants. Here, we sought to identify variations in soil fungal communities and soil properties to determine which would be optimal for cultivation of A. orietale. Soil properties, heavy metal content, and pesticide residues were determined from soils derived from four different agricultural regions around Shaowu City, Fujian, China, that had previously been cultivated with various crops, namely, Shui Dao Tu (SDT, rice), Guo Shu Tu (GST, pecan), Cha Shu Tu (CST, tea trees), and Sang Shen Tu (SST, mulberry). As fungi can either positively or negatively impact plant growth, the fungal communities in the different soils were characterized using long-read PacBio sequencing. Finally, we examined the quality of A. orientale grown in the different soils. Our results show that fungal community diversity of the GST soil was the highest with saprotrophs the main functional modes in these and SDT soils. Our data show that GST and SDT soils were most suitable for A. orientale growth, with the quality of the AR tubers harvested from GST soil being the highest. These data provide a systematic approach at soil properties of agricultural lands in need of replacement and/or rotating crops. Based on our findings, GST was identified as the optimal soil for planting A. orientale, providing a new resource for local farmers.

ABSTRACT Variations in ambient temperature (Ta) may significantly influence the gut microbiotas of ectothermic and endothermic animals, affecting fitness. It remains unclear, however, whether temperature fluctuations affect the gut microbial communities of hibernating animals during torpor. To investigate temperature-induced changes in the gut microbiota during hibernation under entirely natural conditions, we took advantage of two adjacent but distinct populations of the least horseshoe bat (Rhinolophus pusillus), which inhabit sites with a similar summer Ta but a different winter Ta. Using 16S rRNA gene high-throughput sequencing, we estimated differences in gut microbial diversity and composition between the hibernating (winter) and active (summer) R. pusillus populations at both sites. During the active period, gut microbiotas did not differ significantly between the two populations, probably due to the similar Tas. However, during hibernation, a higher Ta was associated with decreased α-diversity in the gut microbiome. During hibernation, temperature variation did not significantly affect the relative abundance of Proteobacteria, the dominant phylum at both sites, but marked site-specific differences were detected in the relative abundances of Firmicutes, Actinobacteria, and Tenericutes. In total, 74 amplicon sequence variants (ASVs) were significantly differentially abundant between the hibernating and active bat guts across the two sites; most of these ASVs were associated with the cooler site, and many belonged to pathogenic genera, suggesting that lower ambient temperatures during hibernation may increase the risk of pathogen proliferation in the host gut. Our findings help to clarify the mechanisms underlying the gut microbiota-driven adaptation of hibernating mammals to temperature changes. IMPORTANCE Temperature variations affect gut microbiome diversity and structure in both ectothermic and endothermic animals. Here, we aimed to characterize temperature-induced changes in the gut microbiotas of adjacent natural populations of the least horseshoe bat (Rhinolophus pusillus) which hibernate at different ambient temperatures. We found that the ambient temperature significantly affected the α-diversity, but not the β-diversity, of the gut microbiota. Bats hibernating at cooler temperatures experienced more drastic shifts in gut microbiome structure, with consequent effects on energy-related metabolic pathways. Our results provide novel insights into the effects of ambient temperature on the gut microbiotas of hibernating animals.

GluN2A and GluN2B, two predominant Glu2N subunits of NMDARs in hippocampus and cortex, display distinct organization and mobility in the neuronal surface. Here, authors show Rph3A, a GluN2A-specific binding protein, undergoes liquid-liquid phase separation, which regulate mobility, synaptic and extrasynaptic surface clustering, synaptic localization and synaptic response of GluN2A.

Visual question answering(VQA) is a multi-modal task that combines computer vision and natural language proces-sing,which is extremely challenging.However,the current VQA model is often misled by the apparent correlation in the data,and the output of the model is directly guided by language bias.Many previous researches focus on solving language bias and assisting the model via counterfactual sample methods.These studies,however,ignore the prediction information and the difference between key features and non-key features in counterfactual samples.The proposed model can distinguish the difference between the original sample,the factual sample and the counterfactual sample.In view of this,this paper proposes a paradigm of contrastive learning based on counterfactual samples.By comparing these three samples in terms of feature gaps and prediction gaps,the VQA model has been significantly improved in its robustness.Compared with CL-VQA method,the overall precision,average precision and Num index of this method improves by 0.19%,0.89% and 2.6% respectively.Compared with the CSSVQA method,the Gap of the proposed method decrease to 0.45 from 0.96.

Abstract Breast cancer (BC) is the most common malignant tumor in women worldwide. Metastasis is the main cause of BC-related death. The specific mechanism underlying BC metastasis remains obscure. Recently, PRSS22 was discovered to be involved in tumor development, however, its detailed biological function and regulatory mechanism in BC are unclear. Here, we characterized that PRSS22 expression is upregulated in BC tissues compared with non-tumorous breast tissues. Dual luciferase assays, bioinformatics analyses and chromatin immunoprecipitation (ChIP) assays indicated that transcription factor E2F1 directly binds to the PRSS22 promoter region and activates its transcription. Functionally, upregulation of PRSS22 promoted invasion and metastasis of BC cells in vitro and in vivo, whereas knockdown of PRSS22 inhibited its function. Mechanistically, the combination of PRSS22 and ANXA1 protein in BC cells was first screened by protein mass spectrometry analysis, and then confirmed by co-immunoprecipitation (Co-IP) and western blot assays. Co-overexpression of PRSS22 and ANXA1 could promote BC cell migration and invasion. We further demonstrated that PRSS22 promotes the cleavage of ANXA1 and in turn generates an N-terminal peptide, which initiates the FPR2/ERK signaling axis to increase BC aggressiveness.

Abstract Background The long chain non-coding RNA HOXA11-OS was recently identified. Increasing studies have shown that HOXA11-OS has regulatory effects on genes in gastric cancer, prostate cancer, and various kidney diseases, but research on its role in systemic lupus erythematosus is still lacking. The present study aimed to investigate the role of HOXA11-OS in the regulation of podocyte autophagy in the development of lupus nephritis (LN) and its potential molecular mechanism. Methods mRNA and protein expression of the target gene (i.e., Cyr61) was detected by quantitative real-time polymerase chain reaction, western blotting, and immunofluorescence. Mouse podocytes were induced using serum immunoglobulin G (IgG) from patients with lupus and their viability was detected using the cell counting kit-8 assay. The interaction of miR-124-3p with HOXA11-OS and Cyr61 was analyzed by double luciferase reporter gene assay. Serum autoantibody levels were detected by enzyme-linked immunosorbent assay. Pathological lesions in the kidney tissue were detected by hematoxylin–eosin and periodate-Schiff staining. The independent samples t-test was used for comparing two groups, and one-way analysis of variance for comparing multiple groups. Results HOXA11-OS was highly expressed in LN tissues, serum, and cells, and the expression of some key autophagy factors and Cyr61 was significantly increased, while miR-124-3p expression was significantly decreased. In vitro, LN-IgG inhibited podocyte activity, increased autophagy and Cyr61 expression, and aggravated podocyte injury in a time- and dose-dependent manner. As a competitive endogenous RNA of miR-124-3p, HOXA11-OS promoted the expression of Cyr61, thus enhancing the autophagy increase induced by LN-IgG and aggravating podocyte injury. Knockdown of HOXA11-OS had the opposite effect. miR-124-3p mimic or Cyr61 knockdown restored the high expression of autophagy factors and Cyr61 induced by HOXA11-OS overexpression and alleviated podocyte injury. Further in vivo experiments showed that injection of sh-HOXA11-OS adeno-associated virus downregulated HOXA11-OS and significantly alleviated renal damage in lupus mice. Conclusions HOXA11-OS is involved in the occurrence and development of LN by regulating podocyte autophagy through miR-124-3p/Cyr61 sponging, which may provide a good potential therapeutic target for LN.

The scalability of neuromorphic devices depends on the dismissal of capacitors and additional circuits. Here Liu et al. report an artificial neuron based on the polarization and depolarization of an anti-ferroelectric film, avoiding additional elements and reaching 37 fJ/spike of power consumption.