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Abstract Background Tongue squamous cell carcinoma (TSCC) is one of the most common malignant tumors with high mortality and poor prognosis. Its incidence rate is increasing gradually. Tumor necrosis factor receptor-associated factor interacting protein (TRAIP), as a factor related to several tumors, reveals that its gene expression is different between normal tissue and primary tumor of head and neck squamous cell carcinoma using bioinformatics analysis. Method In our study, TCGA database, immunohistochemistry, proliferation assay, colony formation, wound healing assay, Transwell, cell cycle analysis and tumor xenografts model were used to determine the expression and functions of TRAIP in TSCC. Result We found that TRAIP may promote the proliferation, migration and invasion of TSCC. Furthermore, the results of bioinformatics analysis, mass spectrometry and co-immunoprecipitation suggested that DDX39A may be a TRAIP interacting protein. DDX39A has been proven to be an oncogene in several tumors, which may have an important effect on cell proliferation and metastasis in multiple tumors. In addition, the high expression of DDX39A implies the poor prognosis of patients. Our study demonstrated that TRAIP probably interact with DDX39A to regulate cell progression through epithelial-mesenchymal transition and Wnt/β-catenin pathway. In addition, we show that the necessary domain of DDX39A for the interaction between DDX39A and TRAIP region. Conclusion These results indicate that TRAIP is important in occurrence and development of TSCC and is expected to become the new promising therapeutic target.

ABSTRACT Semen is one of the common body fluids in sexual crime cases. The current methods of semen identification have certain limitations, so it is necessary to search for other methods. In addition, there are few reports of microbiome changes in body fluids under simulated crime scenes. It is essential to further reveal the changes in semen microbiomes after exposure to various simulated crime scenes. Semen samples from eight volunteers were exposed in closed plastic bags, soil, indoor, cotton, polyester, and wool fabrics. A total of 68 samples (before and after exposure) were collected, detected by 16S rDNA sequencing, and analyzed for the microbiome signature. Finally, a random forest model was constructed for body fluid identification. After exposure, the relative abundance of Pseudomonas and Rhodococcus changed dramatically in almost all groups. In addition, the treatment with the closed plastic bags or soil groups had a greater impact on the semen microbiome. According to the Shannon indices, the alpha diversity of the closed plastic bags and soil groups was much lower than that of the other groups. Attention should be given to the above two scenes in practical work of forensic medicine. In this study, the accuracy of semen recognition was 100%. The exposed semen can still be correctly identified as semen based on its microbiota characteristics. In summary, semen microbiomes exposed to simulated crime scenes still have good application potential for body fluid identification.IMPORTANCEIn this study, the microbiome changes of semen exposed to different environments were observed, and the exposed semen microbiome still has a good application potential in body fluid identification.

Diabetes mellitus induces a pathophysiological disorder known as diabetic cardiomyopathy and may eventually cause heart failure. Diabetic cardiomyopathy is manifested with systolic and diastolic contractile dysfunction along with alterations in unique cardiomyocyte proteins and diminished cardiomyocyte contraction. Multiple mechanisms contribute to the pathology of diabetic cardiomyopathy, mainly including abnormal insulin metabolism, hyperglycemia, glycotoxicity, cardiac lipotoxicity, endoplasmic reticulum stress, oxidative stress, mitochondrial dysfunction, calcium treatment damage, programmed myocardial cell death, improper Renin-Angiotensin-Aldosterone System activation, maladaptive immune modulation, coronary artery endothelial dysfunction, exocrine dysfunction, etc. There is an urgent need to investigate the exact pathogenesis of diabetic cardiomyopathy and improve the diagnosis and treatment of this disease. The nuclear receptor superfamily comprises a group of transcription factors, such as liver X receptor, retinoid X receptor, retinoic acid-related orphan receptor-α, retinoid receptor, vitamin D receptor, mineralocorticoid receptor, estrogen-related receptor, peroxisome proliferatoractivated receptor, nuclear receptor subfamily 4 group A 1(NR4A1), etc. Various studies have reported that nuclear receptors play a crucial role in cardiovascular diseases. A recently conducted work highlighted the function of the nuclear receptor superfamily in the realm of metabolic diseases and their associated complications. This review summarized the available information on several important nuclear receptors in the pathophysiology of diabetic cardiomyopathy and discussed future perspectives on the application of nuclear receptors as targets for diabetic cardiomyopathy treatment.

Abstract The original Harris hawks optimization (HHO) algorithm has the problems of unstable optimization effect and easy to fall into stagnation. However, most of the improved HHO algorithms can not effectively improve the ability of the algorithm to jump out of the local optimum. In this regard, an integrated improved HHO (IIHHO) algorithm is proposed. Firstly, the linear transformation escape energy used by the original HHO algorithm is relatively simple and lacks the escape law of the prey in the actual nature. Therefore, intermittent energy regulator is introduced to adjust the energy of Harris hawks, which is conducive to improving the local search ability of the algorithm while restoring the prey's rest mechanism; Secondly, to adjust the uncertainty of random vector, a more regular vector change mechanism is used instead, and the attenuation vector is obtained by modifying the composite function. Finally, the search scope of Levy flight is further clarified, which is conducive to the algorithm jumping out of the local optimum. Finally, in order to modify the calculation limitations caused by the fixed step size, Cardano formula function is introduced to adjust the step size setting and improve the accuracy of the algorithm. First, the performance of IIHHO algorithm is analyzed on the Computational Experimental Competition 2013 (CEC 2013) function test set and compared with seven improved evolutionary algorithms, and the convergence value of the iterative curve obtained is better than most of the improved algorithms, verifying the effectiveness of the proposed IIHHO algorithm. Second, the IIHHO is compared with another three state of the art (SOTA) algorithms with the Computational Experimental Competition 2022 (CEC 2022) function test set, the experiments show that the proposed IIHHO algorithm still has a strong ability to search for the optimal value. Third, IIHHO algorithm is applied in two different engineering experiments. The calculation results of minimum cost prove that IIHHO algorithm has certain advantages in dealing with the problem of search space. All these demonstrate that the proposed IIHHO is promising for numeric optimization and engineering applications.

Farmers’ cooperatives, as one of the new types of agricultural businesses, are an effective carrier for the digital transformation of agriculture, yet existing studies have paid less attention to how farmers’ cooperatives realize digital transformation. As agricultural economic organizations embedded in social networks, the digital transformation of farmers’ cooperatives requires the joint efforts of governments and companies. Based on the evolutionary game theory, this paper constructs a tripartite evolutionary game model of the government, digital technology companies and farmers’ cooperatives, and simulates and analyzes the behavioral decisions of different participants in the digital transformation of farmers’ cooperatives from the perspective of government policy. The results show: Medium government subsidies can effectively promote the digital transformation of farmers’ cooperatives, and strong subsidy policies increase the government’s financial burden, which is not conducive to policy sustainability. Strong government regulation facilitates digital technology companies to actively provide high-quality services for the digital transformation of farmers’ cooperatives, but government regulation does not have a significant impact on the strategic choices of the government and farmers’ cooperatives. When farmer cooperatives and digital technology companies are in a medium or high level of cooperative trust or when the number of labors saved by digital transformation reaches a certain level, farmers’ cooperatives opt for digital transformation even if the government withdraws from policy intervention.

Background: Previously, our investigations have underscored the potential of hyperthermia to improve the therapeutic efficacy of gemcitabine (GEM) in pancreatic cancer (PC). Nonetheless, the precise underlying mechanisms remain elusive. Methods: We engineered two GEM-resistant PC cell lines (BxPC-3/GEM and PANC-1/GEM) and treated them with GEM alongside hyperthermia. The impact of hyperthermia on the therapeutic potency of GEM was ascertained through MTT assay, assessment of the concentration of its active metabolite dFdCTP, and evaluation of deoxycytidine kinase (dCK) activity. Lentivirus-mediated dCK silencing was further employed to validate its involvement in mediating the GEM-sensitizing effect of hyperthermia. The mechanism underlying hyperthermia-mediated dCK activation was explored using bioinformatics analyses. The interplay between hyperthermia and the ephrin A4 (EFNA4)/β-catenin/dCK axis was investigated, and their roles in GEM resistance was further explored via the establishment of xenograft tumor models in nude mice. Results: Hyperthermia restored dCK expression in GEM-resistant cell lines, concurrently enhancing GEM sensitivity and fostering DNA damage and cell death. These observed effects were negated by dCK silencing. Regarding the mechanism, hyperthermia activated dCK by downregulating EFNA4 expression and mitigating β-catenin activation. Overexpression of EFNA4 activated the β-catenin while suppressing dCK, thus diminishing cellular GEM sensitivity—a phenomenon remediated by the β-catenin antagonist MSAB. Consistently, in vivo, hyperthermia augmented the therapeutic efficacy of GEM on xenograft tumors through modulation of the ephrin A4/β-catenin/dCK axis. Conclusion: This study delineates the role of hyperthermia in enhancing GEM sensitivity of PC cells, primarily mediated through the suppression of the EFNA4/β-catenin axis and activation of dCK.

The emergence of COVID-19 has broken the silence of humanity and people are gradually becoming concerned about pneumonia-related diseases; thus, improving the recognition rate of pneumonia-related diseases is an important task. Neural networks have a remarkable effectiveness in medical diagnoses, though the internal parameters need to be set in accordance to different data sets; therefore, an important challenge is how to further improve the efficiency of neural network models. In this paper, we proposed a learning exponential distribution optimizer based on chaotic evolution, and we optimized Resnet50 for COVID classification, in which the model is abbreviated as IEDO-net. The algorithm introduces a criterion for judging the distance of the signal-to-noise ratio, a chaotic evolution mechanism is designed according to this criterion to effectively improve the search efficiency of the algorithm, and a rotating flight mechanism is introduced to improve the search capability of the algorithm. In the computed tomography (CT) image data of COVID-19, the accuracy, sensitivity, specificity, precision, and F1 score of the optimized Resnet50 were 94.42%, 93.40%, 94.92%, 94.29% and 93.84%, respectively. The proposed network model is compared with other algorithms and models, and ablation experiments and convergence and statistical analyses are performed. The results show that the diagnostic performance of IEDO-net is competitive, which validates the feasibility and effectiveness of the proposed network.

AbstractCanine individual identification and parentage testing are essential in various fields, including forensics and breeding programs. This study aimed to develop and validate the Canine 25 A kit, a multiplex polymerase chain reaction (PCR) system designed to address these critical requirements. This novel system enables the simultaneous amplification of 24 canine autosomal short tandem repeat (STR) loci and one sex-determining marker. Validation of the Canine 25 A kit was conducted following the Scientific Working Group on DNA Analysis Methods (SWGDAM) guidelines, demonstrating significant sensitivity, high inhibitor tolerance, canine specificity within a mixture, species specificity, and precision in genotype determination. The Canine 25 A kit was crucial in resolving several forensic cases, such as casework samples from a dog attack incident and parentage determination. Its effectiveness in genotyping these samples highlights its significance in forensic applications. Population genetic parameter analysis revealed a high discriminatory power, as indicated by the calculated combined discrimination power (CDP) values for each breed exceeding 0.999 999 999 999, while the combined power of exclusion (CPE) surpassed 0.9999. Overall, the Canine 25 A kit offers a precise and dependable tool for canine individual identification and parentage determination.

Abstract Background Nerve compression symptoms and spinal instability, resulting from spinal metastases, significantly impact the quality of life for patients. A 3D-printed vertebral body is considered an effective approach to reconstruct bone defects following en bloc resection of spinal tumors. The advantage of this method lies in its customized shape and innermost porous structure, which promotes bone ingrowth and leads to reduced postoperative complications. Objective The purpose of this study is to assess the effectiveness of 3D-printed auto-stable artificial vertebrae in the en bloc resection and reconstruction of thoracolumbar metastases. Methods This study included patients who underwent en bloc resection of thoracolumbar metastases based on the Weinstein-Boriani-Biagini surgical staging system, between January 2019 and April 2021. The patients were divided into two groups: the observation group, which was reconstructed using 3D-printed auto-stable vertebral bodies, and the control group, treated with titanium cages and allograft bone. Evaluation criteria for the patients included assessment of implant subsidence, instrumentation-related complications, VAS score, and Frankel grading of spinal cord injury. Results The median follow-up period was 21.8 months (range 12–38 months). Among the patients, 10 received a customized 3D-printed artificial vertebral body, while the remaining 10 received a titanium cage. The observation group showed significantly lower operation time, intraoperative blood loss, and postoperative drainage compared to the control group (P

Abstract Ubiquitination is an important modification process in eukaryotic organisms, and ubiquitin ligase (E3) is the most diversified component of this system. APIP6 (AvrPiz-t interacting protein 6) is one of the E3s of rice, and is involved in the recognition of AvrPiz-t, one effector from the pathogen Magnaporthe oryzae, for the initiation of host defense against M. oryzae. However, the structural detail of how APIP6 performs its function remains elusive. Here, we present crystal structure of the RING domain (i.e., the E2-interaction domain) of APIP6 (APIP6-RING). APIP6-RING exists as a homodimer in crystal packing, in solution and in vivo. APIP6-RING consists of one β hairpin and one α helix, and β hairpins of two APIP6-RING molecules interact with each other in a novel ‘shoulder-to-shoulder’ mode to form a β sheet, and also rendering APIP6-RING to form a homodimer. Hydrogen bonds play a major role in the dimer formation of APIP6-RING, while hydrophobic-intermolecular interactions are inconspicuous. Due to the interaction mode between RING-type E3 and E2 is generally conserved, we constructed and verified a model of APIP6-RING/E2 complex, and proposed a working model of APIP6 with E2, ubiquitin, and the substrate AvrPiz-t. Taken together, our research presents the first structure of plant simple RING-type E3 ligase that exists in an unreported dimerization manner, as well as a working model of APIP6.

The investigation of ferroelectric materials is an important aspect of condensed matter physics. Compared to the traditional inorganic ferroelectric ones, organic ferroelectric materials possess unique advantages, including light weight, scalability, flexibility, and solvent treatability. However, the study of organic ferroelectric materials is still in its infancy, especially from the view of supramolecular chemistry; various mechanisms of forming self-assembly and thus diverse building blocks employed are not yet to be further developed. Herein, a pillararene-based charge transfer (CT) self-assembly was produced by utilizing pillar[5]quinone (P5Q) as the electron acceptor and phenothiazine (PTZ) as the electron donor. Compared to the intrinsic P5Q, our fabricated donor–acceptor complex displays particular intriguing features, such as the enhanced second-harmonic generation and ferroelectric responses, benefiting from the CT interaction between P5Q and PTZ. The current work provides a unique strategy for the successful construction of supramolecular ferroelectrics.

Abstract Background Brain lactate concentrations are enhanced in response to cerebral ischemia and promote the formation of reactive astrocytes, which are major components of the neuroinflammatory response and functional recovery, following cerebral ischemia. NDRG2 is upregulated during reactive astrocyte formation. However, its regulation and function are unclear. We studied the relationship between lactate and NDRG2 in astrocytes under conditions of ischemia or oxygen–glucose deprivation (OGD). Methods We examined astrocytic NDRG2 expression after middle cerebral artery occlusion (MCAO) using western blot and immunofluorescence staining. Under hypoxia conditions, we added exogenous L-lactate sodium (lactate) to cultured primary astrocytes to explore the effects of lactate on the ubiquitination modification of NDRG2. We profiled the transcriptomic features of NDRG2 silencing in astrocytes after 8 h of OGD conditions as well as exogenous lactate treatment by performing RNA-seq. Finally, we evaluated the molecular mechanisms of NDRG2 in regulating TNFα under OGD conditions using western blot and immunohistochemistry. Results Reactive astrocytes strongly expressed NDRG2 in a rat model of MCAO. We also showed that lactate stabilizes astrocytic NDRG2 by inhibiting its ubiquitination. NDRG2 inhibition in astrocytes increased inflammation and upregulated immune-associated genes and signaling pathways. NDRG2 knockdown induced TNFα expression and secretion via c-Jun phosphorylation. Conclusions We revealed that under OGD conditions, lactate plays an important anti-inflammatory role and inhibits TNFα expression by stabilizing NDRG2, which is beneficial for neurological functional recovery. NDRG2 may be a new therapeutic target for cerebral ischemia.

In order to accelerate the development of smart agriculture and realize the green transformation of agriculture, the coupling of prospect theory and evolutionary game theory is introduced. Construct a two-party evolutionary game model for the adoption of intelligent spray technology in farmers' cooperatives, analyze the evolution of farmers' cooperatives and government strategy selection and its influencing factors according to the replication dynamic equation, and conduct numerical simulation experiments through Matlab software. The results show that the adoption of intelligent spray technology by farmers' cooperatives and the government's choice of subsidies are the two optimal stable states of the evolutionary system. The government's subsidy policy can effectively stimulate farmers' cooperatives to adopt intelligent spray technology, but when the government subsidy coefficient is greater than or equal to 70%, the decision-making evolution of the government and farmers' cooperatives is unstable. The increase in farmers' awareness of pesticide hazards, the scale of operation of farmers' cooperatives, the price of high-quality agricultural products, and the sensitivity of farmers' cooperatives to profits and losses contribute to the promotion of intelligent spray technology, and the damage probability of intelligent spray technology has a restraining effect.

The current limited efficiency and reliability of tidal current turbines (TCTs) have posed significant challenges in effectively harnessing tidal stream energy. To address this issue, this paper undertakes both numerical and experimental studies to explore the advantages of swept blades over conventional straight blades in terms of energy capture efficiency and cavitation resistance. It is found that both the sweep length and sweep angle of the blade can influence the power generation efficiency of the TCT. For the particular swept blade investigated in this study, the highest power coefficient is achieved when the sweep length is 0.544 m and the sweep angle is 28.88°. The research also demonstrated that the swept-blade TCT shows a higher power generation efficiency than the straight-blade TCT across a broad range of rotor speeds. To be precise, with the swept blades, the power coefficient of the TCT can be improved by 5–17%, depending on the tip speed ratio. Additionally, swept blades exhibit a superior cavitation resistance. This is evidenced by their higher cavitation numbers across all tip speed ratios in comparison to conventional straight blades.

The excessive use of chemical fertilisers seriously worsened the agro-ecological environment in China. Despite the Chinese government enacted a series of policies to reduce chemical fertilisers use, the situation has not been significantly improved. Existing researches about the fertiliser reduction mainly from a single subject, but farmers' chemical fertiliser use behaviour is jointly affected by multiple subjects, including farmers, market and government. To reduce chemical fertilisers use and realize the green and sustainable development of agriculture, this paper builds a tripartite evolution model of the government, farmers and consumers based on evolutionary game theory, and simulates and discusses the behaviour of the government, farmers and consumers in the process of fertiliser reduction. Results indicate: (1) Under different partnership modes, the tripartite of government, farmers and consumers can evolve to reach a stable state. (2) The government's ecological compensation for farmers’ fertiliser reduction and subsidies for consumers' green consumption are inadequate. Raising ecological compensation to 200%–267% of the original level could incentive farmers chemical fertiliser reduction. Raising the price subsidies for consumers’ green consumption to approximately 136% of the original level could help motivate farmers to make a green production transformation through the market mechanism. (3) Farmers' risk expectations of fertiliser reduction is negatively correlated with farmers' chemical fertilisers reduction willingness and consumers' green consumption willingness. Consumers’ trust is positively correlated with farmers' chemical fertilisers reduction willingness and consumers' green consumption willingness. This study provides theoretical guidance for the government, farmers and consumers in making scientific decisions, serving as a policy reference for the government to promote chemical fertiliser reduction.

As the main demand side of rural financial services, farmers’ cooperatives are an important part of China’s rural finance. However, due to the lack of effective collateral, farmers’ cooperatives have problems such as difficulty in obtaining loans or expensive loans, which not only hinder the high-quality development of farmers’ cooperatives, but also limit the development of regional rural finance. Digital credit as a new financing model can effectively alleviate the problems of difficult and expensive loans and has received wide attention from the government and academia. Based on this, this paper analyzes the digital credit behavior of farmers’ cooperatives in detail by applying the “6C” family model to the grounded theory, and constructs a theoretical analysis model of farmers’ cooperatives’ digital credit behavior. The findings are as follows: The motivation for the digital credit of farmers’ cooperatives is that the credit procedures are simple, the loan period is short, and the loan interest rate is low; the condition is the farmers’ cooperative reputation advantage and government policy support,; the main form is the participation of cooperatives in short- and long-cycle digital credit; and the consequence is reflected in increasing the income of cooperative members, improving the availability of cooperative loans, promoting cooperative credit building, and achieving sustainable agricultural development. Different participation motivations have different effects on the form of credit. When motivated by simple credit procedures and short loan periods, farmers’ cooperatives choose “Huinong e-loan”; when motivated by simple procedures and low loan interest rates, farmers’ cooperatives choose “Funong Loan”. Different forms of credit will produce different performances. Farmers’ cooperatives choosing “Huinong e-loan” will produce economic performance; farmers’ cooperatives choosing “Funong Loan” will produce economic performance and social performance. In order to deal with the problem of digital credit of farmers’ cooperatives, the government needs to improve the relevant policies and regulations, reduce credit risks, and establish a sound credit system to provide credit guarantees for cooperatives and farmers. Financial institutions need to improve their financial services and innovate financial products and services to meet the multi-level credit needs of cooperatives.

BackgroundThe prognostic performance of four lymph node classifications, the 8th American Joint Committee on Cancer (AJCC) Tumor Node Metastasis (TNM) N stage, lymph node ratio (LNR), log odds of positive lymph nodes (LODDS), and examined lymph nodes (ELN) in early-onset pancreatic cancer (EOPC) remains unclear.MethodsThe Surveillance, Epidemiology, and End Results (SEER) database was searched for patients with EOPC from 2004 to 2016. 1048 patients were randomly divided into training (n = 733) and validation sets (n = 315). The predictive abilities of the four lymph node staging systems were compared using the Akaike information criteria (AIC), receiver operating characteristic area under the curve (AUC), and C-index. Multivariate Cox analysis was performed to identify independent risk factors. A nomogram based on lymph node classification with the strongest predictive ability was established. The nomogram’s precision was verified by the C-index, calibration curves, and AUC. Kaplan–Meier analysis and log-rank tests were used to compare differences in survival at each stage of the nomogram.ResultsCompared with the 8th N stage, LODDS, and ELN, LNR had the highest C-index and AUC and the lowest AIC. Multivariate analysis showed that N stage, LODDS, LNR were independent risk factors associated with cancer specific survival (CSS), but not ELN. In the training set, the AUC values for the 1-, 3-, and 5-year CSS of the nomogram were 0.663, 0.728, and 0.760, respectively and similar results were observed in the validation set. In addition, Kaplan–Meier survival analysis showed that the nomogram was also an important factor in the risk stratification of EOPC.ConclusionWe analyzed the predictive power of the four lymph node staging systems and found that LNR had the strongest predictive ability. Furthermore, the novel nomogram prognostic staging mode based on LNR was also an important factor in the risk stratification of EOPC.

Summary: The immune response of brain cells to invading bacteria in vivo and the mechanism used by pathogenic bacteria to escape brain immune surveillance remain largely unknown. It is believed that microglia eliminate bacteria by phagocytosis based on in vitro data. Here we find that a small percentage of microglia in the brain engulf neonatal meningitis-causing Escherichia coli (NMEC), but more microglia are activated to produce tumor necrosis factor alpha (TNFα), which activates astrocytes to secrete complement component 3 (C3) involved in anti-bacterial activity. To evade anti-bacterial activity of the immune system, NMEC senses low concentration of threonine in cerebrospinal fluid (CSF) to down-modulate the expression of flagellin and reduce microglial TNFα and astrocyte C3 production. Our findings may help develop strategies for bacterial meningitis treatment.

Abstract Background Radiofrequency ablation (RFA) is an effective treatment option for hepatocellular carcinoma (HCC). This study aimed to analyze the prognostic factors of HCC patients treated with RFA and to develop nomograms for outcome prediction. Methods A total of 3142 HCC patients treated with RFA were recruited, and their data were collected from the Surveillance, Epidemiology, and End Results database. Univariate and multifactor Cox analyses were performed to identify independent prognostic factors. These factors were integrated into a nomogram to predict 3- and 5-year cancer-specific survival (CSS) and overall survival (OS). Consistency indices and calibration plots were used to assess the accuracy of the nomograms in both the internal and external cohorts. Results The median follow-up periods for HCC patients treated with RFA were 27 and 29 months for OS and CSS, respectively. Marital status, age, race, histological grade of differentiation, tumor size, T stage, and serum alpha-fetoprotein levels at the time of diagnosis were identified as prognostic factors for OS and CSS. Additionally, M stage was identified as risk factors for OS. These risk factors are included in the nomogram. The calibration plots of the OS and CSS nomograms showed excellent consistency between actual survival and nomogram predictions. The bootstrap-corrected concordance indices of the OS and CSS nomograms were 0.637 (95% CI, 0.628–0.646) and 0.670 (95% 0.661–0.679), respectively. Importantly, our nomogram performed better discriminatory compared with 8th edition tumor-node-metastasis (TNM) stage system for predicting OS and CSS. Conclusions We identified prognostic factors for HCC patients treated with RFA and provided an accurate and personalized survival prediction scheme.

Nicotinamide mononucleotide (NMN) is an essential precursor of nicotinamide adenine dinucleotide (NAD+), which is widely applied in the pharmaceutical and biotech industries. The biosynthesis of NMN is currently attracting much attention because it has non-toxic reaction conditions and low amounts of isomers, whereas chemical synthesis has low yields and is not environmentally friendly. This review systematically describes the two biosynthetic pathways of NMN in detail for the first time and introduces the latest studies on NMN production through different pathways using metabolic engineering strategies. NMN accumulation can be improved by optimizing the activity of key enzymes, enhancing the supply of precursors and co-factors, inhibiting the synthesis of byproducts, and promoting product export. Finally, we also discuss the current challenges of producing NMN and possible solutions for the future.

Heme b, which is characterized by a ferrous ion and a porphyrin macrocycle, acts as a prosthetic group for many enzymes and contributes to various physiological processes. Consequently, it has wide applications in medicine, food, chemical production, and other burgeoning fields. Due to the shortcomings of chemical syntheses and bio-extraction techniques, alternative biotechnological methods have drawn increasing attention. In this review, we provide the first systematic summary of the progress in the microbial synthesis of heme b. Three different pathways are described in detail, and the metabolic engineering strategies for the biosynthesis of heme b via the protoporphyrin-dependent and coproporphyrin-dependent pathways are highlighted. The UV spectrophotometric detection of heme b is gradually being replaced by newly developed detection methods, such as HPLC and biosensors, and for the first time, this review summarizes the methods used in recent years. Finally, we discuss the future prospects, with an emphasis on the potential strategies for improving the biosynthesis of heme b and understanding the regulatory mechanisms for building efficient microbial cell factories.

Abstract Background Human bone marrow-derived mesenchymal stem cells (hBMSCs) have chondrocyte differentiation potential and are considered to be a cell source for cell-transplantation-mediated repair of cartilage defects, including those associated with osteoarthritis (OA). However, chondrocyte hypertrophic differentiation is a major obstacle for the application of hBMSCs in articular cartilage defect treatment. We have previously shown that microRNA-27b (miR-27b) inhibits hypertrophy of chondrocytes from rat knee cartilage. In this study, we investigated the role of miR-27b in chondrocyte hypertrophic differentiation of hBMSCs. Methods Chondrogenic marker and microRNA expression in hBMSC chondrogenic pellets were evaluated using RT-qPCR and immunohistochemistry. The hBMSCs were transfected with miR-27b before inducing differentiation. Gene and protein expression levels were analyzed using RT-qPCR and western blot. Coimmunoprecipitation was used to confirm interaction between CBFB and RUNX2. Luciferase reporter assays were used to demonstrate that CBFB is a miR-27b target. Chondrogenic differentiation was evaluated in hBMSCs treated with shRNA targeting CBFB. Chondrogenic hBMSC pellets overexpressing miR-27b were implanted into cartilage lesions in model rats; therapeutic effects were assessed based on histology and immunohistochemistry. Results The hBMSCs showed typical MSC differentiation potentials. During chondrogenic differentiation, collagen 2 and 10 (COL2 and COL10), SOX9, and RUNX2 expression was upregulated. Expression of miR-140, miR-143, and miR-181a increased over time, whereas miR-27b and miR-221 were downregulated. Cartilage derived from hBMSC and overexpressing miR-27b exhibited higher expression of COL2 and SOX9, but lower expression of COL10, RUNX2, and CBFB than did the control cartilage. CBFB and RUNX2 formed a complex, and CBFB was identified as a novel miR-27b target. CBFB knockdown by shRNA during hBMSC chondrogenic differentiation led to significantly increased COL2 and SOX9 expression and decreased COL10 expression. Finally, miR-27b-overexpressing hBMSC chondrogenic pellets had better hyaline cartilage morphology and reduced expression of hypertrophic markers and tend to increase repair efficacy in vivo. Conclusion MiR-27b plays an important role in preventing hypertrophic chondrogenesis of hBMSCs by targeting CBFB and is essential for maintaining a hyaline cartilage state. This study provides new insights into the mechanism of hBMSC chondrocyte differentiation and will aid in the development of strategies for treating cartilage injury based on hBMSC transplantation.

Dihydromyricetin (DHY), the main flavonoid component in Ampelopsis grossedentata, has important benefits for health. The present study aimed to investigate the exact effects and possible mechanisms of DHY on diabetic cardiomyopathy (DCM). Male C57BL/6 mice and sirtuin 3 (SIRT3) knockout (SIRT3-KO) mice were injected with streptozotocin (STZ) to induce a diabetic model. Two weeks later, DHY (250 mg/kg) or carboxymethylcellulose (CMC) were administrated once daily by gavage for twelve weeks. We found that DHY alleviated fasting blood glucose (FBG) and triglyceride (TG) as well as glycosylated hemoglobin (HbA1c) levels; increased fasting insulin (FINS); improved cardiac dysfunction; ameliorated myocardial hypertrophy, fibrosis and injury; suppressed oxidative stress, inflammasome and necroptosis; but improved SIRT3 expression in STZ-induced mice. Neonatal rat cardiomyocytes were pre-treated with DHY (80 μM) with or without high glucose (HG) stimulation. The results showed that DHY attenuated cell damage but improved SIRT3 expression and inhibited oxidative stress, inflammasome and necroptosis in cardiomyocytes with high glucose stimulation. Moreover, the above protective effects of DHY on DCM were unavailable in SIRT3-KO mice, implying a promising medical potential of DHY for DCM treatment. In sum, DHY improved cardiac dysfunction; ameliorated myocardial hypertrophy, fibrosis and injury; and suppressed oxidative stress, inflammation and necroptosis via SIRT3 activation in STZ-induced diabetic mice, suggesting DHY may serve as a candidate for an agent to attenuate diabetic cardiomyopathy.

Algorithms and computing power have consistently been the two driving forces behind the development of artificial intelligence. The computational power of a platform has a significant impact on the implementation cost, performance, power consumption, and flexibility of an algorithm. Currently, AI algorithmic models are mainly trained using high-performance GPU platforms, and their inferencing can be implemented using GPU, CPU, and FPGA. On the one hand, due to its high-power consumption and extreme cost, GPU is not suitable for power and cost-sensitive application scenarios. On the other hand, because the training and inference of the neural network use different computing power platforms, the data of the neural network model needs to be transmitted on platforms with varying computing power, which affects the data processing capability of the network and affects the real-time performance and flexibility of the neural network. This paper focuses on the high computing power implementation method of the integration of convolutional neural network (CNN) training and inference in artificial intelligence and proposes to implement the process of CNN training and inference by using high-performance heterogeneous architecture (HA) devices with field programmable gate array (FPGA) as the core. Numerous repeated multiplication and accumulation operations in the process of CNN training and inference have been implemented by programmable logic (PL), which significantly improves the speed of CNN training and inference and reduces the overall power consumption, thus providing a modern implementation method for neural networks in an application field that is sensitive to power, cost, and footprint. First, based on the data stream containing the training and inference process of the CNN, this study investigates methods to merge the training and inference data streams. Secondly, high-level language was used to describe the merged data stream structure, and a high-level description was converted to a hardware register transfer level (RTL) description by the high-level synthesis tool (HLS), and the intellectual property (IP) core was generated. The PS was used for overall control, data preprocessing, and result analysis, and it was then connected to the IP core via an on-chip AXI bus interface in the HA device. Finally, the integrated implementation method was tested and validated with the Xilinx HA device, and the MNIST handwritten digit validation set was used in the tests. According to the test results, compared with using a GPU, the model trained in the HA device PL achieves the same convergence rate with only 78.04 percent training time. With a processing time of only 3.31 ms and 0.65 ms for a single frame image, an average recognition accuracy of 95.697%, and an overall power consumption of only 3.22 W @ 100 MHz, the two convolutional neural networks mentioned in this paper are suitable for deployment in lightweight domains with limited power consumption.

Background: Lymph node (LN) metastasis is considered one of the most important risk factors affecting the prognosis of distal cholangiocarcinoma (DCC). This study aimed to demonstrate the superiority of log odds of positive lymph nodes (LODDS) compared with other LN stages, and to establish a novel prognostic nomogram to predict the cancer-specific survival (CSS) of DCC.Methods: From the Surveillance, Epidemiology and End Results (SEER) database, the data of 676 patients after DCC radical operation were screened, and patients were randomly divided into training (n = 474) and validation sets (n = 474). The prognostic evaluation performance of the LODDS and American Joint Commission on Cancer (AJCC) N stage and lymph node ratio (LNR) were compared using the Akaike information criteria, receiver operating characteristic area under the curve (AUC), and C-index. Multivariate Cox analysis was used to screen independent risk factors, and a LODDS-based nomogram prognostic staging model was established. The nomogram's precision was verified by C-index, calibration curves, and AUC, and the results were compared with those of the AJCC TNM staging system.Results:Compared with the other two stages of LN metastasis, LODDS was most effective in predicting CSS in patients with DCC. Multivariate analysis proved that LODDS, histologic grade, SEER historic stage, and tumor size were independent risk factors for DCC. The C-index of the nomogram, based on the above factors, in the validation set was 0.663. The 1-, 3-, and 5-y AUCs were 0.735, 0.679, and 0.745, respectively. Its good performance was also verified by calibration curves. In addition, the C-index and Kaplan-Meier analysis showed that the nomogram performed better than the AJCC TNM staging system.Conclusion:For postoperative patients with DCC, the LODDS stage yielded better prognostic efficiency than the AJCC N and LNR stages. Compared with the AJCC TNM staging system, the nomogram, based on the LODDS, demonstrated superior performance.

BackgroundRecent studies have shown that the systemic inflammation and nutritional indicators are prognostic for a variety of malignancies. However, only limited data have so far demonstrated their usefulness in gastrointestinal mesenchymal tumors (GIST).MethodsWe retrospectively analyzed the data of GIST patients who underwent radical surgery in Beijing hospital from October 2004 to July 2018. The area under the receiver operating characteristic curve (AUC) was used to compare several commonly used inflammatory and nutritional indicators. The indicators with largest AUC were further analysis. Optimal cut-off values of those indicators in predicting recurrence-free survival (RFS) were determined. Kaplan-Meier curve and the time-dependent receiver operating characteristic (ROC) curve were used to assess the prognostic values. We then used univariate and multivariate Cox regression analyses to identify prognostic factors that were associated with RFS.ResultsIn total, 160 patients who underwent surgery for GIST were included in the study. The median survival time was 34.5 months, with 1-, 3-, and 5-year RFS rates of 96.1%, 84.7%, and 80.8%, respectively. The inflammatory and nutritional indicators with largest AUC were Systemic immunoinflammatory Index (SII) and Geriatric Nutrition Risk Index (GNRI), reached 0.650 and 0.713, respectively. The optimal cutoff of GNRI and SII were 98.3, and 820.0, respectively. Univariate analysis showed that GNRI, SII, KI67, surgery method, tumor location, tumor size, and mitotic index were all significant prognostic indicators of RFS. After multivariate Cox analysis, independent prognostic factors for RFS in GIST included tumor location, mitotic index, tumor size, and GNRI (HR=2.802,95% CI: 1.045 to 7.515, p = 0.041). Besides, SII also tended to be associated with RFS (HR = 2.970, 95% CI: 0.946 to 9.326, p = 0.062).ConclusionsHigh GNRI is an independent prognostic factor for RFS in GIST, while SII can be considered as a prognostic factor. GNRI and SII can be used as tools to evaluate the prognosis of patients before surgery, helping doctors to better treat high-risk patients.

The improvement of grain processing capacity is crucial to the realization of grain security. Enterprises are important grain processing bodies and their productivity directly determines grain processing capacity. Chinese grain processing enterprises still have difficulties, and how to further improve grain processing capacity and the total factor productivity of grain processing enterprises may be an important aspect. We used the meta-frontier Malmquist index to measure the total factor productivity of grain enterprises as well as judge the change trend and regional gap, applying the classical regression model to test the convergence of China’s overall and regional grain enterprises’ total factor productivity. This research finds that the total factor productivity of grain processing enterprises increased by 1.18% annually during the sample period, and that of the central region rose more quickly than the other areas of China. Technical progress contributes more to enterprises’ total factor productivity, but technical efficiency may become a key factor in determining it. The difference in the growth rate of the grain processing enterprises’ total factor productivity among different ones in the eastern and western regions is gradually narrowing, while that of the central region is gradually expanding; there is an obvious technological catch-up effect between and within the regions, especially in the central area of China.

Reducing food waste is a priority for all sectors of society as it threatens national food security and the sustainability of global agriculture. Many studies on food waste have focused on a single subject, and the psychological factors of consumer waste are often overlooked. Based on evolutionary game theory, this paper introduces consumers’ normative illusion, constructs an evolutionary game model in which the government, caterers and consumers collaborate to reduce food waste, and simulates and analyses the behavioural strategies of the three stakeholders. The results show that: Firstly, food waste can be reduced under certain conditions by incentive-guided and punishment-inhibited policies. Moreover, incentive-guided policies can reduce government expenditures more than punishment-inhibited ones. Secondly, implementation of prior intervention, the resultant intervention and reducing the probability of consumers’ aversion to the intervention of caterers can optimise the government’s punishment-inhibited policy. Finally, under the punishment-inhibited policy, caterers can bear 60% of the prior intervention costs for food waste management. When caterers invest 40–60% of the prior intervention costs, both caterers and consumers can achieve the ideal state of cooperation; caterers can accept 40% of the resultant intervention cost for food waste management, and when the resultant intervention cost is less than 40%, consumers choose not to waste. Both caterers and consumers are involved in reducing food waste when the probability of consumer dissatisfaction with a caterer’s intervention is reduced to less than 40%.

The phenomenon of “separation of people and land” between urbanized farmers and rural land hinders the optimal allocation of land resources and is not conducive to the development of agricultural modernization and the implementation of rural revitalization strategies. Although the “separation of three rights” in agricultural land partially solves this problem, it also causes social inequity in the phenomenon of urbanized wealthy farmers collecting rent from poor farmers who depend on the land for a living. The Chinese government carried out a pilot reform aimed at the withdrawal of urbanized farmers from contracted land, and proposed a paid withdrawal policy, but the reform results were unsatisfactory. Based on evolutionary game theory and prospect theory, this paper constructed a two-party evolutionary game model between the government and farmers and simulated the behavioral strategies of the government and farmers in the contracted land withdrawal problem. The results show that first, the initial probability of government policy choice will affect the decision-making behavior of the government and farmers. Second, when the government’s economic compensation for farmers is higher than the farmers’ ideal expectation for land withdrawal compensation, the implementation of individualized withdrawal policy has a positive effect on farmers’ willingness to withdraw from contracted land. Third, farmers’ emotional needs for land, farmers’ ideal economic compensation, and farmers’ risk aversion all impede farmers’ withdrawal from contracted land. The government’s implementation of individualized withdrawal policy can improve farmers’ willingness to withdraw from contracted land by reducing farmers’ concerns about unstable land rights, improving the government’s security compensation, and reducing farmers’ sensitivity to profit and loss.

As the prevalence of obesity increases, so does the occurrence of obesity-related complications, such as cardiovascular and cerebrovascular diseases, diabetes, and some cancers. Increased adipose tissue is the main cause of harm in obesity. To better understand obesity and its related complications, we analyzed the mRNA expression profiles of adipose tissues from 126 patients with obesity and 275 non-obese controls. Using an integrated bioinformatics method, we explored the functions of 113 differentially expressed genes (DEGs) between them. Gene ontology (GO) and kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analyses revealed that upregulated DEGs were enriched in immune cell chemotaxis, complement-related cascade activation, and various inflammatory signaling pathways, while downregulated DEGs enriched in nutrient metabolism. The CIBERSORT algorithm indicated that an increase in macrophages may be the main cause of adipose tissue inflammation, while decreased γδ T cells reduce sympathetic action, leading to dysregulation of adipocyte thermogenesis. A protein-protein interaction network was constructed using the STRING database, and the top 10 hub genes were identified using the cytoHubba plug-in in Cytoscape. All were confirmed to be obesity-related using a separate dataset. In addition, we identified chemicals related to these hub genes that may contribute to obesity. In conclusion, we have successfully identified several hub genes in the development of obesity, which provide insights into the possible mechanisms controlling obesity and its related complications, as well as potential biomarkers and therapeutic targets for further research.

In recent years, the continuous development of artificial intelligence has largely been driven by algorithms and computing power. This paper mainly discusses the training and inference methods of artificial intelligence from the perspective of computing power. To address the issue of computing power, it is necessary to consider performance, cost, power consumption, flexibility, and robustness comprehensively. At present, the training of artificial intelligence models mostly are based on GPU platforms. Although GPUs offer high computing performance, their power consumption and cost are relatively high. It is not suitable to use GPUs as the implementation platform in certain application scenarios with demanding power consumption and cost. The emergence of high-performance heterogeneous architecture devices provides a new path for the integration of artificial intelligence training and inference. Typically, in Xilinx and Intel’s multi-core heterogeneous architecture, multiple high-performance processors and FPGAs are integrated into a single chip. When compared with the current separate training and inference method, heterogeneous architectures leverage a single chip to realize the integration of AI training and inference, providing a good balance of training and inference of different targets, further reducing the cost of training and implementation of AI inference and power consumption, so as to achieve the lightweight goals of computation, and to improve the flexibility and robustness of the system. In this paper, based on the LeNet-5 network structure, we first introduced the process of network training using a multi-core CPU in Xilinx’s latest multi-core heterogeneous architecture device, MPSoC. Then, the method of converting the network model into hardware logic implementation was studied, and the model parameters were transferred from the processing system of the device to the hardware accelerator structure, composed of programmable logic through the bus interface AXI provided on the chip. Finally, the integrated implementation method was tested and verified in Xilinx MPSoC. According to the test results, the recognition accuracy of this lightweight deployment scheme on MNIST dataset and CIFAR-10 dataset reached 99.5 and 75.4% respectively, while the average processing time of the single frame was only 2.2 ms. In addition, the power consumption of the network within the SoC hardware accelerator is only 1.363 W at 100 MHz.

Increasing grain production and ensuring food security are always major issues in China, which are related to the sustainable development of the nation. The sudden outbreak of COVID-19 in 2020 has brought new challenges to global food security, which highlights the “ballast stone” and “stabilizer” role of food. China’s food security must rely on domestic production. As an important production factor, the Internet is also an important channel for farmers to obtain agricultural information, which can effectively reduce the information search cost and information asymmetry. Existing studies have mainly focused on the impact of Internet use on agricultural inputs, agricultural prices, and agricultural efficiency; there are few studies on the impact of Internet use on grain production. To fill this gap, based on the micro survey data of 1242 maize farmers in 13 provinces in China, this paper employs linear regression models and PSM methods to deeply explore the impact of Internet use on farmers’ grain production. The results show that Internet use has a significant positive impact on the grain production of farmers. Compared with the farmers who do not use the Internet, Internet use increases the maize yield of farmers by 14.25%. The heterogeneity analysis further shows that the impact of Internet use on the grain production of different farmers varies significantly: the maize yield per ha after using the Internet for farmers of younger, low education level, large-scale, and living in well-developed villages had increased by 13.65%, 15.38%, 23.94%, and 10.64%, respectively, compared with the counterfactual scenario of farmers who do not use the Internet. The results of this paper have passed the robustness test.

Escherichia coli K1 is the leading cause of meningitis in newborns. Understanding the molecular basis of E. coli K1 pathogenicity will help develop treatment of meningitis and prevent neurological sequelae. E. coli K1 replicates in host blood and forms a high level of bacteremia to cause meningitis in human. However, the mechanisms that E. coli K1 employs to sense niche signals for survival in host blood are poorly understood. We identified one intergenic region in E. coli K1 genome that encodes a novel small RNA, sRNA-17. The expression of sRNA-17 was downregulated by ArcA in microaerophilic blood. The ΔsRNA-17 strain grew better in blood than did the wild-type strain and enhanced invasion frequency in human brain microvascular endothelial cells. Transcriptome analyses revealed that sRNA-17 regulates tens of differentially expressed genes. These data indicate that ArcA downregulates the sRNA-17 expression to benefit bacterial survival in blood and penetration of the blood–brain barrier. Our findings reveal a signaling mechanism in E. coli K1 for host adaptation.

Background The role of miR-26a-5p expression in cardiac hypertrophy remains unclear. Herein, the effect of miR-26a-5p on cardiac hypertrophy was investigated using phenylephrine (PE)-induced cardiac hypertrophy in vitro and in a rat model of hypertension-induced hypertrophy in vivo. Methods The PE-induced cardiac hypertrophy models in vitro and vivo were established. To investigate the effect of miR-26a-5p activation on autophagy, the protein expression of autophagosome marker (LC3) and p62 was detected by western blot analysis. To explore the effect of miR-26a-5p activation on cardiac hypertrophy, the relative mRNA expression of cardiac hypertrophy related mark GSK3β was detected by qRT-PCR in vitro and vivo. In addition, immunofluorescence staining was used to detect cardiac hypertrophy related mark α-actinin. The cell surface area was measured by immunofluorescence staining. The direct target relationship between miR-26a-5p and GSK3β was confirmed by dual luciferase report. Results MiR-26a-5p was highly expressed in PE-induced cardiac hypertrophy. MiR-26a-5p promoted LC3II and decreased p62 expression in PE-induced cardiac hypertrophy in the presence or absence of lysosomal inhibitor. Furthermore, miR-26a-5p significantly inhibited GSK3β expression in vitro and in vivo. Dual luciferase report results confirmed that miR-26a-5p could directly target GSK3β. GSK3β overexpression significantly reversed the expression of cardiac hypertrophy-related markers including ANP, ACTA1 and MYH7. Immunofluorescence staining results demonstrated that miR-26a-5p promoted cardiac hypertrophy related protein α-actinin expression, and increased cell surface area in vitro and in vivo. Conclusion Our study revealed that miR-26a-5p promotes myocardial cell autophagy activation and cardiac hypertrophy by regulating GSK3β, which needs further research.

Schwann cell (SC) transplantation is a promising approach for the treatment of spinal cord injury (SCI); however, SC grafts show a low migratory capacity within the astrocytic environment, which inevitably hampers their therapeutic efficacy. The purpose of this study was to explore mechanisms to modify the characteristics of SCs and astrocytes (ASs), as well as to adjust the SC-AS interface to break the SC-AS boundary, thus improving the benefits of SCI treatment. We observed that the expression levels of miR-124 in SCs and ASs were significantly lower than those in the normal spinal cord. Furthermore, overexpressing miR-124 in SCs (miR-124-SCs) significantly inhibited gene and protein expression levels of SC-specific markers, such as GFAP and Krox20. The expression of neurotrophic factors, Bdnf and Nt-3, was up-regulated in miR-124-SCs without affecting their proliferation. Further, the boundary assay showed an increased number of miR-124-SCs that had actively migrated and entered the astrocytic region to intermingle with ASs, compared with normal SCs. In addition, although Krox20 protein expression was down-regulated in miR-124-SCs, the luciferase assay showed that Krox20 is not a direct target of miR-124. RNA sequencing of miR-124-SCs revealed seven upregulated and eleven downregulated genes involved in cell migration and motility. Based on KEGG pathway and KOG functional analyses, changes in these genes corresponded to the activation of Hippo, FoxO, and TGF-beta signaling pathways, cytokine-cytokine receptor interactions, and the cell cycle. Finally, co-culturing of miR-124-SCs and ASs in a transwell system revealed that GFAP and p-STAT3 protein expression in ASs was significantly reduced. Collectively, these results show that overexpression of miR-124 in SCs promotes SC-AS integration in vitro and may attenuate the capacity of ASs to form glial scars. Thus, this study provides novel insights into modifying SCs by overexpressing miR-124 to improve their therapeutic potential in SCI.

Background It has been confirmed that mutations in solute carrier family 26 member 4 (SLC26A4) contribute to pendred syndrome. However, the role of SLC26A4 in cardiac hypertrophy and the signaling pathways remain unclear. Methods Cardiomyocytes were treated by 200 µM phenylephrine (PE) to induce cardiac hypertrophy. Also, the expression of SLC26A4, GSK3, cardiac hypertrophy markers including atrial natriuretic peptide (ANP) and brain natriuretic peptide (BNP) was detected through real-time quantitative polymerase chain reaction (RT-qPCR). Flow cytometry assay was used to test the apoptosis of PE-induced cardiomyocytes transfected by small interfere RNA (siRNA)-SLC26A4. Furthermore, we detected the expression of autophagy-related markers including light chain 3 (LC3) and P62. Finally, we established a rat model of abdominal aortic constriction (AAC)-induced cardiac hypertrophy in vivo. Results RT-qPCR results showed that the mRNA expression of SLC26A4 was significantly up-regulated in PE-induced cardiac hypertrophy. After inhibiting SLC26A4, the release of ANP and BNP was significantly decreased and GSK3β was elevated in vivo and in vitro. Furthermore, inhibiting SLC26A4 promoted apoptosis of cardiac hypertrophy cells. In addition, LC3 was down-regulated and P62 was enhanced after transfection of siRNA-SLC26A4. Conclusion Our findings revealed that SLC26A4 increases cardiac hypertrophy, and inhibiting SLC26A4 could decrease the release of ANP/BNP and promote the expression of GSK-3β in vitro and in vivo. Moreover, SLC26A4 silencing inhibits autophagy of cardiomyocytes and induces apoptosis of cardiomyocytes. Therefore, SLC26A4 possesses potential value to be a therapeutic target of cardiac hypertrophy, and our study provides new insights into the mechanisms of cardiac hypertrophy.

This study aimed to determine the antimicrobial activity of thymoquinone (TQ) against Listeria monocytogenes, and to examine its inhibitory effects on biofilm formation, motility, hemolysin production, and attachment-invasion of host cells. The minimum inhibitory concentrations (MICs) of TQ against eight different L. monocytogenes strains ranged from 6.25—12.50 μg/mL. Crystal violet staining showed that TQ clearly reduced biofilm biomass at sub-MICs in a dose-dependent manner. Scanning electron microscopy suggested that TQ inhibited biofilm formation on glass slides and induced an apparent collapse of biofilm architecture. At sub-MICs, TQ effectively inhibited the motility of L. monocytogenes ATCC 19115, and significantly impacted adhesion to and invasion of human colon adenocarcinoma cells as well as the secretion of listeriolysin O. Supporting these findings, real-time quantitative polymerase chain reaction analysis revealed that TQ down-regulated the transcription of genes associated with motility, biofilm formation, hemolysin secretion, and attachment-invasion in host cells. Overall, these findings confirm that TQ has the potential to be used to combat L. monocytogenes infection.