Midkine promotes renal fibrosis by stabilizing C/EBPß to facilitate endothelial-mesenchymal transition.

Numerous myofibroblasts are arisen from endothelial cells (ECs) through endothelial to mesenchymal transition (EndMT) triggered by TGF-ß. However, the mechanism of ECs transforms to a different subtype, or whether there exists an intermediate state of ECs remains unclear. In present study, we demonstrate Midkine (MDK) mainly expressed by CD31 + ACTA2+ECs going through partial EndMT contribute greatly to myofibroblasts by spatial and single-cell transcriptomics. MDK is induced in TGF-ß treated ECs, which upregulates C/EBPß and increases EndMT genes, and these effects could be reversed by siMDK. Mechanistically, MDK promotes the binding ability of C/EBPß with ACTA2 promoter by stabilizing the C/EBPß protein. In vivo, knockout of Mdk or conditional knockout of Mdk in ECs reduces EndMT markers and significantly reverses fibrogenesis. In conclusion, our study provides a mechanistic link between the induction of EndMT by TGF-ß and MDK, which suggests that blocking MDK provides potential therapeutic strategies for renal fibrosis.

Research on factor analysis and method for evaluating grouting effects using machine learning.

The evaluation of grouting effects constitutes a critical aspect of grouting engineering. With the maturity of the grouting project, the workload and empirical characteristics of grouting effect evaluation are gradually revealed. In the context of the Qiuji coal mine's directional drilling and grouting to limestone aquifer reformation, this study thoroughly analyzes the influencing factors of grouting effects from geological and engineering perspectives, comparing these with various engineering indices associated with drilling and grouting. This led to the establishment of a "dual-process, multi-parameter, and multi-factor" system, employing correlation analysis to validate the selected indices' reasonableness and scientific merit. Utilizing the chosen indices, eight high-performing machine learning models and three parameter optimization algorithms were employed to develop a model for assessing the effectiveness of directional grouting in limestone aquifers. The model's efficacy was evaluated based on accuracy, recall, precision, and F-score metrics, followed by practical engineering validation. Results indicate that the "dual-process, multi-parameter, multi-factor" system elucidates the relationship between influencing factors and engineering parameters, demonstrating the intricacy of evaluating grouting effects. Analysis revealed that the correlation among the eight selected indicators-including the proportion of boreholes in the target rock strata, drilling length, leakage, water level, pressure of grouting, mass of slurry injected, permeability properties of limestone aquifers before being grouted, permeability properties of limestone aquifers after being grouted-is not substantial, underscoring their viability as independent indicators for grouting effect evaluation. Comparative analysis showed that the Adaboost machine learning model, optimized via a genetic algorithm, demonstrated superior performance and more accurate evaluation results. Engineering validation confirmed that this model provides a more precise and realistic assessment of grouting effects compared to traditional methods.

Roxithromycin exposure induces motoneuron malformation and behavioral deficits of zebrafish by interfering with the differentiation of motor neuron progenitor cells.

Roxithromycin (ROX), a commonly used macrolide antibiotic, is extensively employed in human medicine and livestock industries. Due to its structural stability and resistance to biological degradation, ROX persists as a resilient environmental contaminant, detectable in aquatic ecosystems and food products. However, our understanding of the potential health risks to humans from continuous ROX exposure remains limited. In this study, we used the zebrafish as a vertebrate model to explore the potential developmental toxicity of early ROX exposure, particularly focusing on its effects on locomotor functionality and CaP motoneuron development. Early exposure to ROX induces marked developmental toxicity in zebrafish embryos, significantly reducing hatching rates (n=100), body lengths (n=100), and increased malformation rates (n=100). The zebrafish embryos treated with a corresponding volume of DMSO (0.1%, v/v) served as vehicle controls (veh). Moreover, ROX exposure adversely affected the locomotive capacity of zebrafish embryos, and observations in transgenic zebrafish Tg(hb9:eGFP) revealed axonal loss in motor neurons, evident through reduced or irregular axonal lengths (n=80). Concurrently, abnormal apoptosis in ROX-exposed zebrafish embryos intensified alongside the upregulation of apoptosis-related genes (bax, bcl2, caspase-3a). Single-cell sequencing further disclosed substantial effects of ROX on genes involved in the differentiation of motor neuron progenitor cells (ngn1, olig2), axon development (cd82a, mbpa, plp1b, sema5a), and neuroimmunity (aplnrb, aplnra) in zebrafish larvae (n=30). Furthermore, the CaP motor neuron defects and behavioral deficits induced by ROX can be rescued by administering ngn1 agonist (n=80). In summary, ROX exposure leads to early-life abnormalities in zebrafish motor neurons and locomotor behavior by hindering the differentiation of motor neuron progenitor cells and inducing abnormal apoptosis.

Myocardial reperfusion injury exacerbation due to ALDH2 deficiency is mediated by neutrophil extracellular traps and prevented by leukotriene C4 inhibition.

BACKGROUND AND AIMS: The Glu504Lys polymorphism in the aldehyde dehydrogenase 2 (ALDH2) gene is closely associated with myocardial ischaemia/reperfusion injury (I/RI). The effects of ALDH2 on neutrophil extracellular trap (NET) formation (i.e. NETosis) during I/RI remain unknown. This study aimed to investigate the role of ALDH2 in NETosis in the pathogenesis of myocardial I/RI. METHODS: The mouse model of myocardial I/RI was constructed on wild-type, ALDH2 knockout, peptidylarginine deiminase 4 (Pad4) knockout, and ALDH2/PAD4 double knockout mice. Overall, 308 ST-elevation myocardial infarction patients after primary percutaneous coronary intervention were enrolled in the study. RESULTS: Enhanced NETosis was observed in human neutrophils carrying the ALDH2 genetic mutation and ischaemic myocardium of ALDH2 knockout mice compared with controls. PAD4 knockout or treatment with NETosis-targeting drugs (GSK484, DNase1) substantially attenuated the extent of myocardial damage, particularly in ALDH2 knockout. Mechanistically, ALDH2 deficiency increased damage-associated molecular pattern release and susceptibility to NET-induced damage during myocardial I/RI. ALDH2 deficiency induced NOX2-dependent NETosis via upregulating the endoplasmic reticulum stress/microsomal glutathione S-transferase 2/leukotriene C4 (LTC4) pathway. The Food and Drug Administration-approved LTC4 receptor antagonist pranlukast ameliorated I/RI by inhibiting NETosis in both wild-type and ALDH2 knockout mice. Serum myeloperoxidase-DNA complex and LTC4 levels exhibited the predictive effect on adverse left ventricular remodelling at 6 months after primary percutaneous coronary intervention in ST-elevation myocardial infarction patients. CONCLUSIONS: ALDH2 deficiency exacerbates myocardial I/RI by promoting NETosis via the endoplasmic reticulum stress/microsomal glutathione S-transferase 2/LTC4/NOX2 pathway. This study hints at the role of NETosis in the pathogenesis of myocardial I/RI, and pranlukast might be a potential therapeutic option for attenuating I/RI, particularly in individuals with the ALDH2 mutation.

Nanoplastic Exposure Mediates Neurodevelopmental Toxicity by Activating the Oxidative Stress Response in Zebrafish (Danio rerio).

The global accumulation and adverse effects of nanoplastics (NPs) are a growing concern for the environment and human health. In recent years, more and more studies have begun to focus on the toxicity of plastic particles for early animal development. Different particle sizes of plastic particles have different toxicities to biological development. Nevertheless, the potential toxicological effects of 20 nm NPs, especially on neurodevelopment, have not been well investigated. In this paper, we used fluorescence microscopy to determine neurotoxicity in zebrafish at different concentrations of NPs. Moreover, the behavioral analysis demonstrated that NPs induced abnormal behavior of zebrafish. The results revealed developmental defects in zebrafish embryos after exposure to different concentrations (0, 0.3, 3, and 9 mg/L) of NPs. The morphological deformities, including abnormal body length and the rates of heart, survival, and hatching, were induced after NP exposure in zebrafish embryos. In addition, the development of primary motor neurons was observed the inhibitory effects of NPs on the length, occurrence, and development of primary motor neurons in Tg(hb9:GFP). Quantitative polymerase chain reaction analysis suggested that exposure to NPs significantly affects the expression of the genes involved in the occurrence and differentiation of primary motor neurons in zebrafish. Furthermore, the indicators associated with oxidative stress and apoptosis were found to be modified in zebrafish embryos at 24 and 48 h following exposure to NPs. Our findings demonstrated that NPs could cause toxicity in primary motor neurons by activating the oxidative stress response and inducing apoptosis, consequently impairing motor performance.

Classification of Molecular Binding Traces for Dynamic Single-Molecule Sensing.

Interference from nonspecific binding imposes a fundamental limit in the sensitivity of biosensors that is dependent on the affinity and specificity of the available sensing probes. The dynamic single-molecule sensing (DSMS) strategy allows ultrasensitive detection of biomarkers at the femtomolar level by identifying specific binding according to molecular binding traces. However, the accuracy in classifying binding traces is not sufficient from separate features, such as the bound lifetime. Here, we establish a DSMS workflow to improve the sensitivity and linearity by classifying molecular binding traces in surface plasmon resonance microscopy with multiple kinetic features. The improvement is achieved by correlation analysis to select key features of binding traces, followed by unsupervised k-clustering. The results show that this unsupervised classification approach improves the sensitivity and linearity in microRNA (hsa-miR155-5p, hsa-miR21-5p, and hsa-miR362-5p) detection to achieve a limit of detection at the subfemtomolar level.

Dual roles of BK Polyomavirus in promoting urothelial carcinoma progression via regulating CLDN1.

Uncontrolled productive infection of BK polyomaviruses (BKV) in immunocompromised patients was reported to result in serious diseases, especially renourinary malignancies. However, the mechanism of BKV as a role of human carcinogen is still unknown. In this study, we showed that there is a significant association between BKV infection and metastasis of urothelial carcinoma (UCA). BKV-infected tumor tissues exhibit invasive histologic phenomena with vascular invasion and myometrial invasion. Then we identified that BKV promotes UCA invasion in a mode of dual regulation of tumor cells (TCs) invasion and endothelial cells (ECs) adhesion by encoding miRNAs. In cancer cells, BKV-B1-miR-5p promotes cell motility and invasiveness by directly targeting CLDN1. Moreover, exosomal-BKV-B1-miR-3p derived from BK-infected BC cells would be transferred to ECs and increase its adhesion to tumor cells by switching on the CLDN1 enhancer, which subsequently destroyed endothelial monolayers and increased permeability. In a human urothelial cancer metastasis mouse model, BK-inoculated cells exhibited higher incidence of vascular leakage and liver colonization. However, the vascular leakage and liver metastasis could be reduced when knocking down miRNAs in BK-inoculated cells. Our research delineates the bifunctional impact of BKV-encoded microRNAs on the expression of CLDN1 within both TCs and ECs, which orchestrates the establishment of a pre-metastatic niche in UCA.

JQ1 attenuates contrast-induced acute kidney injury through the upregulation of autophagy and inhibition of inflammation.

PURPOSE: Contrast-induced acute kidney injury (CI-AKI) is the third most common cause of hospital-acquired AKI. However, there is a paucity of efficacious interventions for the management of CI-AKI. Here, we aim to investigate the effects of JQ1 in CI-AKI and provide theoretical data and a  foundation for  novel ideas for the clinical treatment of CI-AKI. METHODS: In this study, we performed in vivo and in vitro experiments with mice and HK2 cells injury models respectively. The levels of serum creatinine (Cr) and blood urea nitrogen (BUN) were determined by an automatic analyzer for the measurements of renal function. The viability of HK-2 cells was analyzed using the Cell Counting Kit-8 (CCK-8) kit. Additionally, the kidney changes in the mice were detected using histopathology (H&E) and immunofluorescent staining. The mRNA and protein expressions were assessed using Quantitative real-time PCR and western blot, respectively. Autophagy and apoptosis was analyzed by Transmission electron microscopy (TEM) and TUNEL assay respectively. RESULTS: The results demonstrated that JQ1 exhibited potency of attenuating CI-AKI in mouse and HK2 cells. JQ1 increased the expression levels of Atg5, Atg7 and LC3B-II, and decreased the protein levels of p62 in the kidney and HK-2 cells. However, the combined use of JQ1 with chloroquine reversed the effects of JQ1. JQ1 also inhibited the inflammatory cells and downregulated the expression of some inflammatory cytokines (IL-6, IL-1ß, TNF-α, and IFN-γ). CONCLUSION: JQ1 protects against CI-AKI by promoting autophagy and inhibiting inflammation and JQ1 may be a promising therapeutic strategy for CI-AKI.

ALKBH5 induces fibroblast-to-myofibroblast transformation during hypoxia to protect against cardiac rupture after myocardial infarction.

INTRODUCTION: N6-methyladenosine (m6A) methylation produces a marked effect on cardiovascular diseases. The m6A demethylase AlkB homolog 5 (ALKBH5), as an m6A "eraser", is responsible for decreased m6A modification. However, its role in cardiac fibroblasts during the post-myocardial infarction (MI) healing process remains elusive. OBJECTIVES: To investigate the effect of ALKBH5 in cardiac fibroblasts during infarct repair. METHODS: MI was mimicked by permanent left anterior descending artery ligation in global ALKBH5-knockout, ALKBH5-knockin, and fibroblast-specific ALKBH5-knockout mice to study the function of ALKBH5 during post-MI collagen repair. Methylated RNA immunoprecipitation sequencing was performed to explore potential ALKBH5 targets. RESULTS: Dramatic alterations in ALKBH5 expression were observed during the early stages post-MI and in hypoxic fibroblasts. Global ALKBH5 knockin reduced infarct size and ameliorated cardiac function after MI. The global and fibroblast-specific ALKBH5-knockout mice both exhibited low survival rates along with poor collagen repair, impaired cardiac function, and cardiac rupture. Both in vivo and in vitro ALKBH5 loss resulted in impaired fibroblast activation and decreased collagen deposition. Additionally, hypoxia, but not TGF-ß1 or Ang II, upregulated ALKBH5 expression in myofibroblasts by HIF-1α-dependent transcriptional regulation. Mechanistically, ALKBH5 promoted the stability of ErbB4 mRNA and the degradation of ST14 mRNA via m6A demethylation. Fibroblast-specific ErbB4 overexpression ameliorated the impaired fibroblast-to-myofibroblast transformation and poor post-MI repair due to ALKBH5 knockout. CONCLUSION: Fibroblast ALKBH5 positively regulates post-MI healing by stabilization of ErbB4 mRNA in an m6A-dependent manner. ALKBH5/ErbB4 might be potential therapeutic targets for post-MI cardiac rupture.

The prediction of Chongqing's GDP based on the LASSO method and chaotic whale group algorithm-back propagation neural network-ARIMA model.

Accurate GDP forecasts are vital for strategic decision-making and effective macroeconomic policies. In this study, we propose an innovative approach for Chongqing's GDP prediction, combining the LASSO method with the CWOA-BP-ARIMA model. Through meticulous feature selection based on Pearson correlation and Lasso regression, we identify key economic indicators linked to Chongqing's GDP. These indicators serve as inputs for the optimized CWOA-BP-ARIMA model, demonstrating its superiority over Random Forest, MLP, GA-BP, and CWOA-BP models. The CWOA-BP-ARIMA model achieves a remarkable 95% reduction in MAE and a significant 94.2% reduction in RMSE compared to Random Forest. Furthermore, it shows substantial reductions of 80.6% in MAE and 77.8% in RMSE compared to MLP, along with considerable reductions of 77.3% in MAE and 75% in RMSE compared to GA-BP. Moreover, compared to its own CWOA-BP counterpart, the model attains an impressive 30.7% reduction in MAE and a 20.46% reduction in RMSE. These results underscore the model's predictive accuracy and robustness, establishing it as a reliable tool for economic planning and decision-making. Additionally, our study calculates GDP prediction intervals at different confidence levels, further enhancing forecasting accuracy. The research uncovers a close relationship between GDP and key indicators, providing valuable insights for policy formulation. Based on the predictions, Chongqing's GDP is projected to experience positive growth, reaching 298,880 thousand yuan in 2022, 322,990 thousand yuan in 2023, and 342,730 thousand yuan in 2024. These projections equip decision-makers with essential information to formulate effective policies aligned with economic trends. Overall, our study provides valuable knowledge and tools for strategic decision-making and macroeconomic policy formulation, showcasing the exceptional performance of the CWOA-BP-ARIMA model in GDP prediction.

Recent Advances of Biosensors for Detection of Multiple Antibiotics.

The abuse of antibiotics has caused a serious threat to human life and health. It is urgent to develop sensors that can detect multiple antibiotics quickly and efficiently. Biosensors are widely used in the field of antibiotic detection because of their high specificity. Advanced artificial intelligence/machine learning algorithms have allowed for remarkable achievements in image analysis and face recognition, but have not yet been widely used in the field of biosensors. Herein, this paper reviews the biosensors that have been widely used in the simultaneous detection of multiple antibiotics based on different detection mechanisms and biorecognition elements in recent years, and compares and analyzes their characteristics and specific applications. In particular, this review summarizes some AI/ML algorithms with excellent performance in the field of antibiotic detection, and which provide a platform for the intelligence of sensors and terminal apps portability. Furthermore, this review gives a short review of biosensors for the detection of multiple antibiotics.

Elucidating the Mass Transportation Behavior of Gas Diffusion Layers via a H2 Limiting Current Test.

The gas diffusion layer (GDL), as a key component of proton exchange membrane fuel cells (PEMFCs), plays a crucial role in PEMFC's polarization performance, particularly in mass transport properties at high current densities. To elucidate the correlation between GDLs' structure and their mass transport properties, a limiting current test with the H2 molecular probe was established and employed to investigate three representative GDLs with and without the microporous layer (MPL). By varying humidity and back pressure, the mass transport resistance of three GDLs was measured in an operating fuel cell, and an elaborate analysis of H2 transport was conducted. The results showed that the transport resistance (RDM) of GDLs was affected by the thickness and pore size distribution of the macroporous substrate (MPS) and the MPL. In the process of gas transport, the smaller pore size and thicker MPL increase the force of gas on the pore wall, resulting in an increase in transmission resistance. Through further calculation and analysis, the total transport resistance can be divided into pressure-related resistance (RP) and pressure-independent resistance (RNP). RP mainly originates from the transport resistance in both MPLs and the substrate layers of GDLs, exhibiting a linear relationship to the pressure; RNP mainly originates from the transport resistance in the MPLs. 29BC with thick MPL shows the largest RNP, and T060 without MPL shows the RNP = 0. This methodology enables in situ measurements of mass transport resistances for gas diffusion media, which can be easily applied for developing and deploying PEMFCs.

Effects of Sleep Reactivity on Sleep Macro-Structure, Orderliness, and Cortisol After Stress: A Preliminary Study in Healthy Young Adults.

Purpose: To investigate changes and links of stress and high sleep reactivity (H-SR) on the macro-structure and orderliness of sleep and cortisol levels in good sleepers (GS). Patients and Methods: Sixty-two GS (18-40 years old) were recruited, with 32 in the stress group and 30 in the control group. Each group was further divided into H-SR and low SR subgroups based on the Ford Insomnia Response to Stress Test. All participants completed two nights of polysomnography in a sleep laboratory. Before conducting polysomnography on the second night, the stress group completed the Trier Social Stress Test and saliva was collected. Results: The duration of NREM sleep stages 1, 2 (N1, N2) and rapid eye movement sleep (REM) decreased, and the values of approximate entropy, sample entropy, fuzzy entropy, and multiscale entropy increased under stress and SR effects. Stress increased rapid eye movement density, and H-SR increased cortisol reactivity. Conclusion: Stress can damage the sleep and increase cortisol release in GS, especially those with H-SR. N1, N2 and REM sleep are more easily affected, while NREM sleep stage 3 sleep is relatively stable.

A dual-channel fluorescent nanoprobe for accurate cancer diagnosis by sequential detection of adenosine triphosphate and sulfur dioxide.

Cancer is one of the major diseases that seriously endanger the health of all mankind. Accurate diagnosis of early cancer is the most promising way to reduce cancer harm and improve patient survival. However, many developed fluorescent probes for cancer imaging only have the function of identifying one marker, which cannot meet the needs of accurate diagnosis. Here, a fluorescent nanoprobe (CPH@ZIF-90) utilizing ZIF-90 to encapsulate SO2-sensitive dye (CPH) is synthesized for the sequential detection of ATP and SO2. The nanoprobe first interacts with ATP to release CPH, thus increasing the fluorescence at 685 nm and realizing the near-infrared (NIR) fluorescence detection of ATP. Then, SO2 acts on the released CPH through nucleophilic addition, affecting the π-conjugated structure of CPH and resulting in enhanced fluorescence at 580 nm. CPH@ZIF-90 exhibits satisfactory sensitivity and selectivity for sequential detection of ATP and SO2. Excitedly, CPH@ZIF-90 can sequentially image the endogenous ATP and SO2 in cells, showing sensitive fluorescence changes in dual channels (red and green). Due to the NIR emission properties of CPH@ZIF-90 and its ability to enrich in tumor, it is applied to monitor ATP and SO2 in mice and distinguish normal mice from tumor mice. The ability of CPH@ZIF-90 to sequentially detect two cancer-related biomarkers makes it provide meaningful assistance in accurate early diagnosis of cancer.

WMSA 2: a multiple DNA/RNA sequence alignment tool implemented with accurate progressive mode and a fast win-win mode combining the center star and progressive strategies.

Multiple sequence alignment is widely used for sequence analysis, such as identifying important sites and phylogenetic analysis. Traditional methods, such as progressive alignment, are time-consuming. To address this issue, we introduce StarTree, a novel method to fast construct a guide tree by combining sequence clustering and hierarchical clustering. Furthermore, we develop a new heuristic similar region detection algorithm using the FM-index and apply the k-banded dynamic program to the profile alignment. We also introduce a win-win alignment algorithm that applies the central star strategy within the clusters to fast the alignment process, then uses the progressive strategy to align the central-aligned profiles, guaranteeing the final alignment's accuracy. We present WMSA 2 based on these improvements and compare the speed and accuracy with other popular methods. The results show that the guide tree made by the StarTree clustering method can lead to better accuracy than that of PartTree while consuming less time and memory than that of UPGMA and mBed methods on datasets with thousands of sequences. During the alignment of simulated data sets, WMSA 2 can consume less time and memory while ranking at the top of Q and TC scores. The WMSA 2 is still better at the time, and memory efficiency on the real datasets and ranks at the top on the average sum of pairs score. For the alignment of 1 million SARS-CoV-2 genomes, the win-win mode of WMSA 2 significantly decreased the consumption time than the former version. The source code and data are available at https://github.com/malabz/WMSA2.

Periosteum-derived mesenchymal stem cell alleviates renal fibrosis through mTOR-mediated Treg differentiation.

BACKGROUND: Mesenchymal stem cells (MSCs) are the hotspots of cellular therapy due to their low immunogenicity, potent immunoregulation, and unique renoprotection. The present study aimed to investigate the effects of periosteum-derived MSCs (PMSCs) in ischemia-reperfusion (IR)-mediated renal fibrosis. METHODS: Using cell proliferation assay, flow cytometry, immunofluorescence, and histologic analysis, the differences in cell characteristics, immunoregulation, and renoprotection of PMSCs were compared to the bone marrow-derived MSCs (BMSCs), the most frequently studied stem cells in cellular therapy. In addition, the mechanism of PMSC renoprotection was investigated by 5' end of the RNA transcript sequencing (SMART-seq) and mTOR knockout mice. RESULTS: The proliferation and differentiation capabilities of PMSCs were stronger than those of BMSCs. Compared with BMSCs, the PMSCs exerted a better effect on alleviating renal fibrosis. Meanwhile, the PMSCs more effectively promote Treg differentiation. Treg exhaustion experiment indicated that Tregs exerted an important effect on inhibiting renal inflammation and acted as a critical mediator in PMSC renoprotection. Additionally, SMART-seq results implied that the PMSCs promoted Treg differentiation, possibly via the mTOR pathway. In vivo and in vitro experiments showed that PMSC inhibited mTOR phosphorylation of Treg. After mTOR knockout, the PMSCs failed to promote Treg differentiation. CONCLUSIONS: Compared with BMSCs, the PMSCs exerted stronger immunoregulation and renoprotection that was mainly attributed to PMSC promotion for Treg differentiation by inhibiting the mTOR pathway.

Monomethyl fumarate prevents alloimmune rejection in mouse heart transplantation by inducing tolerogenic dendritic cells.

Dendritic cells (DCs) are important targets for eliciting allograft rejection after transplantation. Previous studies have demonstrated that metabolic reprogramming of DCs can transform their immune functions and induce their differentiation into tolerogenic DCs. In this study, we aim to investigate the protective effects and mechanisms of monomethyl fumarate (MMF), a bioactive metabolite of fumaric acid esters, in a mouse model of allogeneic heart transplantation. Bone marrow-derived DCs are harvested and treated with MMF to determine the impact of MMF on the phenotype and immunosuppressive function of DCs by flow cytometry and T-cell proliferation assays. RNA sequencing and Seahorse analyses are performed for mature DCs and MMF-treated DCs (MMF-DCs) to investigate the underlying mechanism. Our results show that MMF prolongs the survival time of heart grafts and inhibits the activation of DCs in vivo. MMF-DCs exhibit a tolerogenic phenotype and function in vitro. RNA sequencing and Seahorse analyses reveal that MMF activates the Nrf2 pathway and mediates metabolic reprogramming. Additionally, MMF-DC infusion prolongs cardiac allograft survival, induces regulatory T cells, and inhibits T-cell activation. MMF prevents allograft rejection in mouse heart transplantation by inducing tolerogenic DCs.

Light-Programmed Bistate Colloidal Actuation Based on Photothermal Active Plasmonic Substrate.

Active particles have been regarded as the key models to mimic and understand the complex systems of nature. Although chemical and field-powered active particles have received wide attentions, light-programmed actuation with long-range interaction and high throughput remains elusive. Here, we utilize photothermal active plasmonic substrate made of porous anodic aluminum oxide filled with Au nanoparticles and poly(N-isopropylacrylamide) (PNIPAM) to optically oscillate silica beads with robust reversibility. The thermal gradient generated by the laser beam incurs the phase change of PNIPAM, producing gradient of surface forces and large volume changes within the complex system. The dynamic evolution of phase change and water diffusion in PNIPAM films result in bistate locomotion of silica beads, which can be programmed by modulating the laser beam. This light-programmed bistate colloidal actuation provides promising opportunity to control and mimic the natural complex systems.

Research on a working face gas concentration prediction model based on LASSO-RNN time series data.

The effective prediction of gas concentration trends and timely and reasonable extraction measures can provide valuable references for gas control. The gas concentration prediction model proposed in this paper has the advantages of a large sample size and long time span for training data selection. It is suitable for more gas concentration change scenarios and can be used to adjust the data prediction length according to demand. To improve the applicability and practicability of the model, this paper proposes a prediction model based on the LASSO-RNN (least absolute shrinkage and selection operator) for mine face gas concentration based on actual gas monitoring data from a mine. First, the LASSO method is used to select the key eigenvectors that affect the gas concentration change. Second, the basic structural parameters of the RNN prediction model are preliminarily determined based on the broad strategy. Then, the MSE (mean square error) and the running time are used as the evaluation indicators to select the appropriate batch size and number of epochs. Finally, the appropriate prediction length is selected based on the optimized gas concentration prediction model. The results show that the RNN gas concentration prediction model has a better prediction effect than the LSTM (long short-term memory) prediction model. The average mean square error of the model fit can be reduced to 0.0029, and the predicted average absolute error can be reduced to 0.0084. The maximum absolute error of 0.0202, especially at the time inflection point of the change in the gas concentration curve, can better reflect the superiority of the RNN prediction model, that is, higher precision, robustness and applicability than LSTM.

Inhibition of ALKBH5 attenuates I/R-induced renal injury in male mice by promoting Ccl28 m6A modification and increasing Treg recruitment.

Ischemia reperfusion injury (IRI) is a common cause of acute kidney injury (AKI). The role of N6-methyladenosine (m6A) modification in AKI remains unclear. Here, we characterize the role of AlkB homolog 5 (ALKBH5) and m6A modification in an I/R-induced renal injury model in male mice. Alkbh5-knockout mice exhibit milder pathological damage and better renal function than wild-type mice post-IRI, whereas Alkbh5-knockin mice show contrary results. Also conditional knockout of Alkbh5 in the tubular epithelial cells alleviates I/R-induced AKI and fibrosis. CCL28 is identified as a target of ALKBH5. Furthermore, Ccl28 mRNA stability increases with Alkbh5 deficiency, mediating by the binding of insulin-like growth factor 2 binding protein 2. Treg recruitment is upregulated and inflammatory cells are inhibited by the increased CCL28 level in IRI-Alkbh5fl/flKspCre mice. The ALKBH5 inhibitor IOX1 exhibits protective effects against I/R-induced AKI. In summary, inhibition of ALKBH5 promotes the m6A modifications of Ccl28 mRNA, enhancing its stability, and regulating the Treg/inflammatory cell axis. ALKBH5 and this axis is a potential AKI treatment target.