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Breast cancer is the most prevalent malignant neoplasm worldwide, necessitating the development of novel therapeutic strategies owing to the limitations posed by conventional treatment modalities. Immunotherapy is an innovative approach that has demonstrated significant efficacy in modulating a patient's innate immune system to combat tumor cells. In the era of precision medicine, adoptive immunotherapy for breast cancer has garnered widespread attention as an emerging treatment strategy, primarily encompassing cellular therapies such as tumor-infiltrating lymphocyte therapy, chimeric antigen receptor T/natural killer/M cell therapy, T cell receptor gene–engineered T cell therapy, lymphokine-activated killer cell therapy, cytokine-induced killer cell therapy, natural killer cell therapy, and γδ T cell therapy, among others. This treatment paradigm is based on the principles of immune memory and antigen specificity, involving the collection, processing, and expansion of the patient's immune cells, followed by their reintroduction into the patient's body to activate the immune system and prevent tumor recurrence and metastasis. Currently, multiple clinical trials are assessing the feasibility, effectiveness, and safety of adoptive immunotherapy in breast cancer. However, this therapeutic approach faces challenges associated with tumor heterogeneity, immune evasion, and treatment safety. This review comprehensively summarizes the latest advancements in adoptive immunotherapy for breast cancer and discusses future research directions and prospects, offering valuable guidance and insights into breast cancer immunotherapy. [ABSTRACT FROM AUTHOR]

Underwater acoustic channels often have to face the interference of impulsive noise, which is usually modeled by α-stable distribution in simulation experiments. To solve the problem of underwater acoustic channel estimation under impulsive noise, this paper proposes a convex combination–variable-step-size least mean p-norm algorithm. The algorithm incorporates a convex combination into the variable-step-size least mean p-norm algorithm and uses the convex combination of different convergence domains provided by changing the parameters of the Gaussian function to further improve the effect after convergence. The simulation results of channel estimation show that the convex combination–variable-step-size least mean p-norm algorithm provides a more stable, robust, and universal solution than the variable-step-size least mean p-norm algorithm. [ABSTRACT FROM AUTHOR]

To better suppress low-frequency vibrations of flexible manipulators induced by the rotation of motors and eccentricity, a novel type of tuned particle damper (TPD) is designed by combining the advantages of classical dynamic vibration absorber (DVA) and particle dampers (PD). Compared to traditional DVAs, this TPD can reduce additional mass and effectively broaden the frequency band of the DVA. Firstly, an equivalent theoretical model is established to describe the frequency tuning principle of the designed TPD. Based on the theory of a single particle damper, the equivalent damping and stiffness of the particles are calculated through an approximate approach. Then, a three-degree-of-freedom vibration model of the manipulator system with the TPD is built, and the dynamical characteristic of the primary resonance for the coupled system are analyzed by the perturbation method. Finally, the experimental platform is set up to verify the theoretical results. A manipulator is applied to test the low-frequency vibration absorption of the designed TPD, and the vibration suppression effect is discussed both in theoretical analysis and experiments. [ABSTRACT FROM AUTHOR]

Low energy consumption has always been one of the core issues in the routing design of underwater sensor networks. Due to the high cost and difficulty of deployment and replacement of current underwater nodes, many underwater applications require the routing protocol design to consider the network lifetime extension problem. Based on this, we designed a new routing protocol that takes into account both low energy consumption and balanced energy consumption, and achieves effective extension of the network lifetime, called adaptive power-controlled depth-based routing protocol for underwater wireless sensor networks (APCDBRP). The protocol consists of two phases: (1) the route establishment phase and (2) the data transmission phase. In the route establishment phase, the initial path is established by the sink node broadcasting beacon packets at the maximum transmission power. The receiving nodes update their routing tables based on the beacon information and forward the beacon packets. In the data transmission phase, APCDBRP introduces a novel forwarding factor that considers both energy efficiency and energy balance. It selects the optimal next hop based on high energy efficiency and relatively abundant energy, thus extending the network's lifetime. Additionally, APCDBRP proposes a new data protection and route reconstruction mechanism to address issues such as network topology changes due to node mobility and data transmission failures. Our simulation is based on AquaSim–Next Generation, which is a specialized tool built on the NS3 platform for researching underwater networks. Simulation results demonstrate that, compared to other typical routing protocols, APCDBRP exhibits superior performance in reducing network energy consumption and extending the network's lifetime. It also achieves a high packet delivery rate with lower energy consumption. [ABSTRACT FROM AUTHOR]

For the channel estimation problem under α-stable distributed impulse interference, the traditional fixed-step adaptive filtering cannot satisfy the fast convergence speed and low steady-state error at the same time, whereas the variable-step method is able to effectively solve this contradiction. This paper proposes an improved variable step-size least mean p-power adaptive algorithm that offers good robustness against impulsive noise. The proposed algorithm takes into account the linkage between the errors and uses the adjustment of the step size based on the errors of the current moment and the previous k moments, thus overcoming the problems of poor anti-noise performance and large steady-state fluctuations of the fixed-step size algorithm. This algorithm ensures that the step size does not change abruptly when the system is disturbed by impulse noise and can achieve a lower steady-state error. The simulation results show that the algorithm has better convergence than the traditional fixed step-size algorithm and the existing variable step-size algorithm under the interference of impulsive noise. [ABSTRACT FROM AUTHOR]

The orthogonal time frequency space (OTFS) modulation technique can provide reliable communication in time-varying channels. Due to the dispersive characteristics of underwater acoustic channels, this paper proposes an OTFS-IM underwater acoustic communication system based on Hamming distance optimization to reduce the impact of dispersion in underwater acoustic communication. Firstly, the OTFS-IM underwater acoustic communication system is introduced, which introduces index modulation into the Delay–Doppler (DD) domain to make the OTFS system have stronger anti-Delay–Doppler capability. In contrast, since there is index sequence redundancy in a specific index combination, a Hamming distance optimization model is used to eliminate the redundant combination in the specific index combination sequence and further improve the bit error rate performance of the system. In addition, the Hamming distance optimized OTFS-IM underwater acoustic communication system is verified by simulation analysis. The results show that the proposed Hamming distance optimized OTFS-IM can achieve more reliable bit error rate performance. [ABSTRACT FROM AUTHOR]

To address the problems of the high complexity and poor bit error rate (BER) performance of traditional communication systems in underwater acoustic environments, this paper incorporates the theory of deep learning into a conventional communication system and proposes data-driven underwater acoustic filter bank multicarrier (FBMC) communications based on convolutional autoencoder networks. The proposed system is globally optimized by two one-dimensional convolutional (Conv1D) modules at the transmitter and receiver, it realizes signal reconstruction through end-to-end training, it effectively avoids the inherent imaginary interference of the system, and it improves the reliability of the communication system. Furthermore, dense-block modules are constructed between Conv1D layers and are connected across layers to achieve feature reuse in the network. Simulation results show that the BER performance of the proposed method outperforms that of the conventional FBMC system with channel equalization algorithms such as least squares (LS) estimation and virtual time reversal mirrors (VTRM) under the measured channel conditions at a certain moment in the Qingjiang River. [ABSTRACT FROM AUTHOR]

In recent years, research on modulated signal recognition using deep learning (DL) has achieved remarkable success, allowing automatic modulation recognition (AMR) to play a crucial role in modern communication systems. The emergence of the attention mechanism has then rapidly led to a wide range of applications in image classification and speech recognition, which proves the effectiveness of the attention mechanism. In this paper, the authors propose a network model feed‐forward Attention mechanism with Residuals networks and Long Short‐Term Memory (RLADNN) based on feed‐forward attention mechanism with Residuals networks (Resnet) and Long Short‐Term Memory (LSTM), which takes the advantage that the Attention mechanism can effectively solve some long‐term memory problems in [−20:18] signal‐to‐noise ratio (SNR) for the recognition of 11 modulated signals with different SNR, and effectively improves the recognition rate. [ABSTRACT FROM AUTHOR]

Acute myeloid leukemia (AML) is a hematologic malignancy with increased lethality. We focused on elucidating the role of Neratinib, a tyrosine kinase inhibitor, in the progression of AML and identify the potential mechanisms. Upon the treatment of Neratinib, autophagy suppressor 3‐methyladenine (3‐MA) and ferroptosis stimulator Erastin, the viability and proliferation of HL‐60 cells were evaluated by cell counting kit‐8 and 5‐Ethynyl‐20‐Deoxyuridine staining assays. A flow cytometer was to observe cell cycle and apoptosis. Production of reactive oxygen species (ROS) was tested via 2,7‐dichlorodihydrofluorescein diacetate assay. Additionally, malondialdehyde (MDA) content and Fe2+ activity were examined with commercial kits. LC3‐II expression was examined by using immunofluoresence staining. Western blot analysis ascertained the expression of proliferation, apoptosis, ferroptosis and autophagy‐associated proteins. It was noted that Neratinib notably mitigated cell viability and proliferation, cut down Ki67 and proliferating cell nuclear antigen expression. Moreover, Neratinib hindered cell cycle at G0/G1 phase whereas exacerbated apoptosis. ROS, MDA and Fe2+ activities were elevated by Neratinib, coupled with the reduced glutathione peroxidase 4, ferritin heavy chain 1 expression and enhanced acyl‐CoA synthetase long‐chain family member 4 expression. Furthermore, Neratinib promoted autophagy of HL‐60 cells, evidenced by raised LC3‐II, ATG5, Beclin1 expression and lessened p62 expression. Importantly, 3‐MA eased the impacts of Neratinib on cell ferroptosis, proliferation and apoptosis, which were offset by further administration of Erastin. To conclude, Neratinib could suppress proliferation and promote apoptosis of HL‐60 cells through autophagy‐dependent ferroptosis. [ABSTRACT FROM AUTHOR]

This letter presents the power of deep learning for signal detection in orthogonal frequency division multiplexing with index modulation (OFDM-IM) systems. In this letter, we propose the Y-shaped net-based scheme with fully connected layers (Y-FC) and with bidirectional long short-term memory units (Y-BLSTM) to further optimize the data reception. In the Y-shaped scheme, the active indices and the constellation demapping are learned by two parallel sub-neural networks respectively, the output features are then concatenated and flattened to obtain binary bits. The performance is evaluated under various system parameters, such as modulation methods, number of hidden neural nodes and channel states. Simulation results show that compared with the data-driven signal detection with direct input-output, the proposed scheme achieves several dB of bit-error-rate performance improvement with almost the same running time. [ABSTRACT FROM AUTHOR]

The aircraft control system of the future will be a combination of fly-by-wire technology and Active Control System (ACS) which, based on the artificial feel system, provides a control strategy for both position and force. The ACS has uncertainties, such as the mass of the simulated stick, system inertia, system damping and friction. In this paper, aiming at the servo control method of ACS, a mathematical model of ACS was setup. Then, to eliminate the perturbation of the external environment, such as noise and disturbance torque, a robust control method based on H ∞ was proposed. Finally, to verify the simulation results, the mathematical model was verified via experimental studies. [ABSTRACT FROM AUTHOR]

By contraposing the signal detection for filter bank multicarrier (FBMC) communications with the underwater acoustic (UWA) channel, this paper analyzes the traditional imaginary interference problem and proposes a deep learning-based method. The neural network with feature extraction and automatic learning ability is employed to replace the demodulation modules to recover transmitted signals without explicit channel estimation and equalization. Sufficient data sets are generated according to the measured channel conditions in Qingjiang river, the optimization of network parameters is finished by constraining cost function in offline training, and the signal detection is carried out directly with the well-trained network in online testing. The system performance of various supervised learning models such as multilayer perceptron (MLP), convolutional neural network (CNN), and bidirectional long short-term memory (BLSTM) network is compared under different data sizes, network parameters, and prototype filters. The simulation results show that the bit error rate (BER) performance of the proposed signal detection is better than that of the classic one, which indicates that deep learning is a promising tool in UWA communication systems. [ABSTRACT FROM AUTHOR]

Ship radiated noise is an important information source of underwater acoustic targets, and it is of great significance to the identification and classification of ship targets. However, there are a lot of interference noises in the water, which leads to the reduction of the model recognition rate. Therefore, the recognition results of radiated noise targets are severely affected. This paper proposes a machine learning Dempster–Shafer (ML-DS) decision fusion method. The algorithm combines the recognition results of machine learning and deep learning. It uses evidence-based decision-making theory to realize feature fusion under different neural network classifiers and improve the accuracy of judgment. First, deep learning algorithms are used to classify two-dimensional spectrogram features and one-dimensional amplitude features extracted from CNN and LSTM networks. The machine learning algorithm SVM is used to classify the chromaticity characteristics of radiated noise. Then, according to the classification results of different classifiers, a basic probability assignment model (BPA) was designed to fuse the recognition results of the classifiers. Finally, according to the classification characteristics of machine learning and deep learning, combined with the decision-making of D-S evidence theory of different times, the decision-making fusion of radiated noise is realized. The results of the experiment show that the two fusions of deep learning combined with one fusion of machine learning can significantly improve the recognition results of low signal-to-noise ratio (SNR) datasets. The lowest fusion recognition result can reach 76.01%, and the average fusion recognition rate can reach 94.92%. Compared with the traditional single feature recognition algorithm, the recognition accuracy is greatly improved. Compared with the traditional one-step fusion algorithm, it can effectively integrate the recognition results of heterogeneous data and heterogeneous networks. The identification method based on ML-DS proposed in this paper can be applied in the field of ship radiated noise identification. [ABSTRACT FROM AUTHOR]

[Display omitted] • A HN-AD bacterium, Alcaligenes faecalis TF-1 was isolated from landfill leachate. • NH 4 +-N tolerance of the strain TF-1 reached 2000 mg·L−1 with 65% of NH 4 +-N removal. • 52.87% of NH 4 +-N removal was realized under 70 g·L−1 salinity and 919.20 mg·L−1 NH 4 +-N. • The optimum C/N, pH and carbon source of the strain were 16, 7 and sodium citrate. • HN-AD pathway of TF-1 was revealed: NH 4 +-N → NH 2 OH → NO → N 2 O → N 2. A novel heterotrophic nitrifying bacterium with high salt and high ammonia nitrogen tolerance, Alcaligenes faecalis TF-1, was isolated from the leachate of a landfill. The verification of nitrogen removal efficiency of different nitrogen sources and PCR amplification electrophoresis results showed that the HN-AD pathway of the strain TF-1 was NH 4 + → NH 2 OH → NO → N 2 O → N 2. The results of parameter optimization showed that the optimal nitrogen removal conditions were as follows: sodium citrate as carbon source, C/N = 16, pH = 7, and NH 4 +-N loading of 808.21 mg/L. The strain TF-1 could remove about 94.60% of ammonia nitrogen (1963.94 mg/L). The salinity tolerance range of the strain TF-1 was 0–70 g/L, and the removal efficiency was 52.87% at salinity 70 g/L and NH 4 +-N concentration 919.20 mg/L and 55.67% at pH = 10 and NH 4 +-N concentration 994.82 mg/L. The extreme environmental adaptability and remarkable nitrogen removal performance make this strain a promising candidate in leachate treatment. [ABSTRACT FROM AUTHOR]

Background: Tuberculosis (TB) remains a major public health concern worldwide. Previous studies have demonstrated that IL-17 plays an important role in initial immune response and is involved in both immune-mediated protection and pathology following infection with Mycobacterium tuberculosis (MTB). However, the alterations and regulation of plasma IL-17 level during TB treatment remain unclear. Moreover, the cell type responsible for the production of IL-17 in TB patients requires further study.Methods: A total of 20 acid-fast bacilli smear-positive (AFB-positive) pulmonary TB patients and 20 age- and gender-matched healthy volunteers were included in our study. Blood samples were collected in heparinized tubes at the time of diagnosis (AFB-positive group) and 3 weeks after the initiation of therapy, when the sputum smear conversion (AFB-negative group) occurred, followed by symptomatic improvement. IL-17 levels and IL-17-producing cells in PBMCs were detected. Lymphocyte populations in the peripheral blood between the AFB-positive and AFB-negative groups were compared by flow-cytometry. A549 cells, a cell line of alveolar epithelial cells, were applied to determine the extent of the pathological damage mediated by IL-17 following MTB infection. Recombinant human IL-10 was used to investigate the regulation of IL-17 expression after sputum smear conversion in AFB-positive pulmonary TB patients.Results: Plasma IL-17 level were elevated in patients with sputum AFB-positive pulmonary TB, but substantially decreased after TB treatment and smear conversion. Our data indicate that NKT-like cells might be the main source of IL-17, in addition to conventional T cells in AFB-positive pulmonary TB patients. The secretion of IL-17 may be suppressed by regulatory T (Treg) cells and IL-10 during TB treatment. Moreover, the IL-17 levels were positively correlated to both the C-reactive protein and erythrocyte sedimentation rate. Therefore, IL-17 was capable of alveolar epithelial cell damage following MTB infection.Conclusion: The increase in the frequency of Treg cells and IL-10 levels was associated with a decrease in IL-17 in patients receiving TB treatment. Thus, IL-10 and Tregs may function to inhibit immune-mediated pathology in TB patients. [ABSTRACT FROM AUTHOR]

Background/Aims: Osteopontin (OPN) expression is increased during the course of various chronic inflammatory diseases, including tuberculosis (TB). However, its prognostic value in TB management remains unclear. This study aimed to determine whether OPN could associate with other cytokines serving as a reliable biomarker for evaluating the effectiveness of early anti-TB treatments. Methods: Smear-positive pulmonary TB patients (n = 20) were recruited, and the plasma levels of OPN, IP-10, TNF-α, and IL-12 were measured by ELISA before initiation of anti-TB therapy and after sputum smear conversion. The C-reactive protein (CRP) levels and erythrocyte sedimentation rate (ESR) were also tracked during anti-TB treatment. Results: OPN expression was significantly elevated in patients with smear-positive pulmonary TB, and was closely related with disease severity. Monitoring during the treatment course revealed that its expression, along with that of IFN-γ-induced protein 10 (IP-10), decreased significantly only after sputum smear conversion. Moreover, OPN levels positively correlated with CRP levels before and after anti-TB treatment. Furthermore, OPN markedly promoted IP-10 expression in peripheral blood mononuclear cells. Conclusion: Association between OPN and IP-10 may serve as a reliable prognostic indicator for improvement during the early treatment of pulmonary TB, and may help clinicians in tailoring an effective TB treatment regimen. © 2015 S. Karger AG, Basel [ABSTRACT FROM AUTHOR]

This paper presents a novel method to solve the unit commitment (UC) problem by solving a sequence of increasingly tight continuous relaxations based on the techniques of reformulation and lift-and-project (L&P). After projecting the power output of unit onto [0, 1], the continuous relaxation of the UC problem can be tightened with the reformulation techniques. Then, a tighter model which is called L&P-TMIP is established by strengthening the continuous relaxation of the feasible region of the tight UC problem iteratively using L&P. High-quality suboptimal solutions can be obtained from the solutions of the relaxation for this tight model. The simulation results for realistic instances that range in size from 10 to 200 units over a scheduling period of 24 h show that the proposed tight relaxation method is competitive with general-purpose mixed integer programming solvers based methods for large-scale UC problems due to the excellent performance and the good quality of the solutions it generates. [ABSTRACT FROM PUBLISHER]

In order to reduce the fuel cost of thermal units, a semidefinite programming (SDP) method is used to solve a hydrothermal coordination (HTC) optimization problem. By manipulating the structure of decision variable matrix, the original nonconvex problem is reformulated into a convex SDP relaxation model without sacrificing the nonlinear relation among hydropower generation, reservoir storage volume, and discharge water. A global minimum is therefore guaranteed and well-developed convex optimization theories can thus be employed to solve the problem. Both sparse matrix techniques and a simplified SDP model are discussed to reduce computational cost. One mostly used HTC case is employed to test the performance of the proposed method. Detailed comparisons between the proposed and other methods show that the final result of SDP model is by far the best result ever. In addition, a large-sized HTC case shows the potential of SDP in practical use. Finally, we prove that as a relaxation technique, the SDP solution, which satisfies all the constraints, is indeed the optimal solution of the original nonconvex problem. [ABSTRACT FROM PUBLISHER]

To improve the low pollutant removal efficiency of traditional biological methods for treating livestock and poultry breeding wastewater under a relatively low temperature, a rotating biological contactor (RBC) inoculated with heterotrophic nitrification-aerobic denitrification (HN-AD) bacteria was designed. A quick start-up process and a well removal performance had been achieved in the novel RBC. To elucidate the anti-load shock ability of the novel RBC, the effects of C/N ratio on nitrogen removal and microbial assemblage were focused under a low temperature (12 ± 2 °C). Results showed that the highest NH 4 +-N and TN removal efficiency were 99.57 ± 0.31% and 68.41 ± 0.52%. Microbial diversity analysis based on high throughput sequencing technique showed that Arcobacter and Flavobacterium with an increasing relative abundance were the key to ensure high nitrogen removal efficiently at a low C/N ratio and temperature. Moreover, nitrogen transferring pathways of the novel RBC was revealed and dissimilatory nitrate reduction and denitrification were the main pathways. The excellent pollutant removal performance demonstrates that the novel RBC is a promising process to effectively treat wastewater with low C/N ratio and low temperature. [Display omitted] • Rotating biological contactor (RBC) started up by HN-AD bacteria has been proposed. • A short start-up time and a high nitrogen removal efficiency were achieved. • Impact of C/N ratio on pollutant removal and microbial assemblage were evaluated. • Arcobacter and Flavobacterium played a key role at low C/N ratio and temperature. • DNRA and denitrification were the main nitrogen transferring pathways in the H-RBC. [ABSTRACT FROM AUTHOR]

The regulation mechanism of parameters on microorganisms and carbon source metabolism of solid carbon source simultaneous nitrification and denitrification (SND) process is not clear. In this paper, the effects of dissolved oxygen (DO) and biodegradable polymer (BDPs) types ((Polycaprolactone, PCL) and (Polybutylene succinate, PBS)) on treatment performance and microbial characteristics were investigated. The results show that the total nitrogen (TN) removal efficiency of SND process using PBS and PCL as fillers reached 93.02% and 97.28% under optimal parameter of DO 5 mg/L, respectively. The dominant genus with nitrogen removal performance in the PCL carbon source system are Hydrogenophaga and Acidovorax , and the main genus in the PBS system are Acidovorax and unclassified_Comamonadaceae. The co-metabolic network in PCL is more complex and easier to be regulated by DO. The BDPs types mainly affect the co-metabolic network with nodes of Thiothrix and Chryseomicrobium , ultimately leading to changes in the community structure. By comparison, BDPs types have a more significant impact on community structure than DO under low DO conditions (1 and 2 mg/L), but not under high DO condition(5 mg/L). Further, the distribution of functional enzymes may conflict between nitrification and carbon source degradation under high DO condition. Controlling the DO within the range of 2 mg–5 mg can further improve carbon source utilization efficiency. [Display omitted] • DO 5 mg/L and PCL are more conducive to solid carbon source SND process. • DO affects the microbial community of the PCL system through a co-metabolic network. • Differences in PBS and PCL systems are mainly determined by metabolic networks. • Carbon source metabolism pattern of PBS and PCL is established at enzyme level. • Controlling DO within the range of 2 mg–5 mg can improve nitrification efficiency. [ABSTRACT FROM AUTHOR]

To evaluate the simultaneous nitrification and denitrification (SND) performance of the aeration solid-phase denitrification (SPD) process and improve the operating efficiency, aeration SPD process using polybutanediol succinate as carbon source was optimized and the process was bioaugmented with heterotrophic nitrification-aerobic denitrification bacteria for the treatment of real wastewater. The results showed that after bioaugmentation, the total nitrogen removal efficiency of the aeration SPD process increased by 50.46 % under condition of dissolved oxygen (DO) 3 mg/L. According to Illumina MiSeq sequencing and correlation analyses, the microbial community can perform SND under the conditions of DO 5 mg and HRT 6 h, but is susceptible to DO. Bioaugmentation mainly affected the carbon source metabolic network with heterotrophic bacteria Methyloversatilis , Thiothrix , and norank_Lentimicrobiaceae as nodes to change the community structure, thereby improving the performance of the functional microbial community. Kyoto Encyclopedia of Genes and Genomes analysis suggested that narB , narG , narH , nirK and narI were the key genes involved in the response to bioaugmentation. This work provides new insights for the application of the SPD process in wastewater treatment. [Display omitted] • The effect of DO on aeration SPD system was more significant than that of HRT. • After bioaugmentation, aeration SPD process TN removal rate increased by 50.46 %. • HN-AD bioaugmentation improved the abundance of Leucobacter and Hydrogenophaga. • Methyloversatilis and norank_Lentimicrobiaceae caused community structural changes. • HN-AD bioaugmentation could improve the abundance of denitrification-related genes. [ABSTRACT FROM AUTHOR]

Pathological mutations in human mitochondrial genomes (mtDNA) can cause a series of neurological, behavioral, and developmental defects, but the underlying molecular mechanisms are poorly understood. We show here that the energy-sensing adenosine monophosphate (AMP)-activated protein kinase (AMPK) signaling pathway plays a key role in mediating similar defects caused by different mtDNA mutations in Caenorhabditis elegans , including loss or reduction of osmotic, chemical and olfactory sensing, locomotion, and associative learning and memory, as well as increased embryonic lethality. mtDNA mutations cause reduced ATP (adenosine triphosphate) levels, activation of C. elegans AMPK AAK-2, and nuclear translocation of the FOXO transcription factor DAF-16. Activated DAF-16 up-regulates the expression of inositol triphosphate receptor ITR-1, an endoplasmic reticulum calcium channel, leading to increased basal cytosolic Ca 2+ levels, decreased neuronal responsiveness, compromised synapses, and increased embryonic death. Treatment of mtDNA mutants with vitamin MK-4 restores cellular ATP and cytosolic Ca 2+ levels, improves synaptic development, and suppresses sensory and behavioral defects and embryonic death. Our study provides crucial mechanistic insights into neuronal and developmental defects caused by mtDNA mutations and will improve understanding and treatment of related mitochondrial diseases.

In order to improve the accuracy of air pollution management and promote the efficiency of coordinated inter-regional prevention and control, this study analyzes the interaction of O 3 in Qilihe District, Lanzhou City, China. Data used for analysis was obtained from 63 air quality monitoring stations between November 2017 and October 2018. This paper uses complex network theory to describe the network structure characteristics of O 3 pollution spatial correlation. On this basis, the node importance method is used to mine the sub-network with the highest spatial correlation in the O 3 network, and use transfer entropy theory to analyse the interaction of pollutants between regions. The results show that the O 3 area of Qilihe District, Lanzhou City can be divided into three parts: the urban street community type areas in urban areas, the township and village type areas in mountain areas and the scattered areas represented by isolated nodes. An analysis of the mutual influence of O 3 between each area revealed that the impact of O 3 on each monitoring station in adjacent areas will vary considerably. Therefore these areas cannot be governed as a whole, and the traditional extensive management measures based on administrative divisions cannot be used to replace all other regional governance measures. There is the need to develop a joint prevention and control mechanism tailored to local conditions in order to improve the accuracy and efficiency of O 3 governance., Competing Interests: The authors declare that they have no competing interests., (© 2021 Zhang et al.)

Purpose: To investigate the antifungal and anti-inflammatory effects of baicalein on Aspergillus fumigatus (A. fumigatus) keratitis and the underlying mechanisms., Methods: The noncytotoxic antifungal concentration of baicalein was determined using CCK8, cell scratch assay, minimum inhibitory concentration, biofilm formation, scanning electron microscopy, propidium iodide uptake test and adherence assay in vitro and Draize test in vivo. In fungal keratitis (FK) mouse models, clinical score and plate count were used to evaluate FK severity, and myeloperoxidase assay and immunofluorescence staining were performed to examine neutrophil infiltration and activity. Real-time PCR, ELISA, and Western blot were performed to explore the anti-inflammatory activity of baicalein and the underlying mechanisms in vivo and in vitro., Results: Baicalein at 0.25 mM (noncytotoxic) significantly inhibited A. fumigatus growth, biofilm formation, and adhesion in vitro. In A. fumigatus keratitis mice, baicalein mitigated FK severity, reduced fungal load, and inhibited neutrophil infiltration and activity. Baicalein not only suppressed mRNA and protein levels of proinflammatory factors IL-1β, IL-6, and TNF-α, but also inhibited the expression of thymic stromal lymphopoietin (TSLP) and TSLP receptor (TSLPR) in vivo and in vitro. In HCECs, mRNA and protein levels of IL-1β, IL-6, and TNF-α were significantly lower in the TSLP siRNA-treated group, while higher in the rTSLP-treated group than in the corresponding control. Baicalein treatment significantly inhibited rTSLP induced the expression of IL-1β, IL-6, and TNF-α., Conclusions: Baicalein plays a protective role in mouse A. fumigatus keratitis by inhibiting fungal growth, biofilm formation, and adhesion, and suppressing inflammatory response via downregulation of the TSLP/TSLPR pathway.