DTI-MLCD: predicting drug-target interactions using multi-label learning with community detection method.

Identifying drug-target interactions (DTIs) is an important step for drug discovery and drug repositioning. To reduce the experimental cost, a large number of computational approaches have been proposed for this task. The machine learning-based models, especially binary classification models, have been developed to predict whether a drug-target pair interacts or not. However, there is still much room for improvement in the performance of current methods. Multi-label learning can overcome some difficulties caused by single-label learning in order to improve the predictive performance. The key challenge faced by multi-label learning is the exponential-sized output space, and considering label correlations can help to overcome this challenge. In this paper, we facilitate multi-label classification by introducing community detection methods for DTI prediction, named DTI-MLCD. Moreover, we updated the gold standard data set by adding 15,000 more positive DTI samples in comparison to the data set, which has widely been used by most of previously published DTI prediction methods since 2008. The proposed DTI-MLCD is applied to both data sets, demonstrating its superiority over other machine learning methods and several existing methods. The data sets and source code of this study are freely available at https://github.com/a96123155/DTI-MLCD.

NeuroPpred-Fuse: an interpretable stacking model for prediction of neuropeptides by fusing sequence information and feature selection methods.

Neuropeptides acting as signaling molecules in the nervous system of various animals play crucial roles in a wide range of physiological functions and hormone regulation behaviors. Neuropeptides offer many opportunities for the discovery of new drugs and targets for the treatment of neurological diseases. In recent years, there have been several data-driven computational predictors of various types of bioactive peptides, but the relevant work about neuropeptides is little at present. In this work, we developed an interpretable stacking model, named NeuroPpred-Fuse, for the prediction of neuropeptides through fusing a variety of sequence-derived features and feature selection methods. Specifically, we used six types of sequence-derived features to encode the peptide sequences and then combined them. In the first layer, we ensembled three base classifiers and four feature selection algorithms, which select non-redundant important features complementarily. In the second layer, the output of the first layer was merged and fed into logistic regression (LR) classifier to train the model. Moreover, we analyzed the selected features and explained the feasibility of the selected features. Experimental results show that our model achieved 90.6% accuracy and 95.8% AUC on the independent test set, outperforming the state-of-the-art models. In addition, we exhibited the distribution of selected features by these tree models and compared the results on the training set to that on the test set. These results fully showed that our model has a certain generalization ability. Therefore, we expect that our model would provide important advances in the discovery of neuropeptides as new drugs for the treatment of neurological diseases.

Polymer-inorganic solid-electrolyte interphase for stable lithium metal batteries under lean electrolyte conditions.

The solid-electrolyte interphase (SEI) is pivotal in stabilizing lithium metal anodes for rechargeable batteries. However, the SEI is constantly reforming and consuming electrolyte with cycling. The rational design of a stable SEI is plagued by the failure to control its structure and stability. Here we report a molecular-level SEI design using a reactive polymer composite, which effectively suppresses electrolyte consumption in the formation and maintenance of the SEI. The SEI layer consists of a polymeric lithium salt, lithium fluoride nanoparticles and graphene oxide sheets, as evidenced by cryo-transmission electron microscopy, atomic force microscopy and surface-sensitive spectroscopies. This structure is different from that of a conventional electrolyte-derived SEI and has excellent passivation properties, homogeneity and mechanical strength. The use of the polymer-inorganic SEI enables high-efficiency Li deposition and stable cycling of 4 V Li|LiNi0.5Co0.2Mn0.3O2 cells under lean electrolyte, limited Li excess and high capacity conditions. The same approach was also applied to design stable SEI layers for sodium and zinc anodes.

Design of a reconfigurable broadband greyscale multiplexed metasurface hologram.

Holograms are a promising state-of-the-art technique that are able to reproduce fully three-dimensional images. However, most elementary holograms only recover a nonadjustable image restricted by a certain amplitude and phase. Recently, the concept of the reconfigurable metasurface has come into sight. The reconfigurable metasurfaces can be tuned dynamically through a physics control signal from outside. Here we design and realize a series of novel, to the best of our knowledge, reconfigurable metasurfaces. Using these devices, an advanced metasurface hologram effect could be easier to achieve. Moreover, the reconfigurable property of such tunable metasurface enables independent control of advanced multiplexed channel functionalities to exist in comparison with the conventional static metasurface holograms. Our method creates unprecedented display and virtual effects, and it opens a novel way to a more flexible methodology of dynamic control of electromagnetic waves.

Metasurface-based focus-tunable mirror.

Varifocal mirrors, which have various applications in optical coherent tomography and three-dimensional displays, are traditionally based on the fluid pressure or mechanical pusher to deform the mirror. The limitations of conventional varifocal mirrors are obvious, such as the heavy size of the device and constraints of tunability, due to their mechanical pressure control elements. The reprogrammable metasurface, a new flat photonic device with multifunction in an ultrathin dimension, paves the way towards an ultrathin and lightweight mirror with precise phase profile. Here, an active reconfigurable metasurface is proposed to achieve the manipulation of the wavefront. The meta-atom in the metasurface is integrated with one varactor diode to manipulate the electromagnetic response. As the bias voltage increases from 0 to 20 V, the resonant frequency shifts from 5.5 to 6.0 GHz, which generates a broad tunable phase region, leading to 5 diopters (about 50%) change without any mechanical element and a broad tunable frequency band. In addition, the focus point can not only be steered in the axial line above the metasurface but also in the whole working plane. The proposed focus-tunable metasurface mirror may be a key in enabling future ultrathin reconfigurable optical devices with applications such as multiphoton microscopy, high speed imaging and confocal microscopy.

Efficacy and safety of Danhong injection for treating myocardial infarction: a systematic review and meta-analysis of randomized controlled trials.

Objective: Danhong injection (DHI) is widely used in the treatment of myocardial infarction (MI). We aimed to systematically review the efficacy and safety of DHI in a randomized controlled experiment on MI. Methods: We searched the randomized controlled trials (RCTs) of DHI for MI published before 2 April 2023 in China National Knowledge Infrastructure (CNKI), Chinese Biomedical Literature Database (CBM), Wanfang database, China Science and Technology Journal Database (VIP), PubMed, Web of Science, Cochrance Library, and Embase databases. The methodological quality of the included studies was evaluated using the Cochrane Handbook 5.3 criteria using the RevMan software, and meta-analysis was performed and a forest map was drawn. Results: A total of 38 trials included 3877 patients, including 2022 cases in the DHI treatment group and 1855 cases in the control group. Meta-analysis showed that the total effective rate (RR = 1.18%, 95% CI [1.14-1.12]) during treatment with DHI was higher than that of the control group. The prevalence of cardiac arrhythmia (RR = 0.55%, 95% CI [0.46-0.65]) was lower than that of the control group. The incidence of heart rate failure (RR = 0.45%, 95% CI [0.30-0.70]) was lower than that of the control group. The prevalence of cardiogenic shock (RR = 0.33%, 95% CI [0.11-1.04]) was p > 0.05, and the difference was not statistically significant. There was no statistically significant difference in LVEF between the two groups (MD = 0.00%, 95% CI [0.00-0.00]). CK-MB (MD = -0.81%, 95% CI [-0.92∼ -0.69]) was lower than the control group. hs-CRP (MD = -1.09, 95% CI [-1.22∼ -0.97]) was lower than the control group. The incidence of adverse reactions (RR = 0.37, The 95% CI [0.17-0.82]) was lower than that in the control group. Conclusion: Basing on our study, the use of DHI in the treatment of myocardial infarction patients is effective, can improve cardiac function, reduce the incidence of adverse reactions, and improve the overall quality of life. Systematic Review Registration: https://www.crd.york.ac.uk/PROSPERO/, identifier CRD42023390973.

Enhancing the Structural Stability and Electrochemical Performance of High-Nickel Cathode Materials through Ti Doping with an Exothermic Non-oxide Precursor.

The foreseeable global cobalt (Co) crisis has driven the demand for cathode materials with less Co dependence, where high-nickel layered oxides are a promising solution due to their high energy density and low cost. However, these materials suffer from poor cycling stability and rapid voltage decay due to lattice displacement and nanostrain accumulation. Here, we introduced an exothermic TiN dopant via a scalable coating method to stabilize LiNi0.917Co0.056Mn0.026O2 (NCM92) materials. The exothermic reaction of TiN conversion generates extra heat during the calcination process on the cathode surface, promotes the lithiation process, and tunes the morphology of the cathode material, resulting in compact and conformal smaller particle sizes to provide better particle integration and lithium diffusion coefficient. Moreover, the Ti dopant substitutes the Ni3+ site to generate stronger Ti-O bonding, leading to higher structural stability and extended cycle life. The Ti-doped NCM (NCM92_TiN) shows a remarkable cycling stability of maintaining 80% capacity retention for 400 cycles, while bare NCM92 can only reach 88 cycles. Furthermore, the NCM92_TiN cathodes demonstrate an enhanced rate capability and achieve a discharge capacity of over 168 mAh g-1 at 5C.

Soft Actor-Critic-Driven Adaptive Focusing under Obstacles.

Electromagnetic (EM) waves that bypass obstacles to achieve focus at arbitrary positions are of immense significance to communication and radar technologies. Small-sized and low-cost metasurfaces enable the accomplishment of this function. However, the magnitude-phase characteristics are challenging to analyze when there are obstacles between the metasurface and the EM wave. In this study, we creatively combined the deep reinforcement learning algorithm soft actor-critic (SAC) with a reconfigurable metasurface to construct an SAC-driven metasurface architecture that realizes focusing at any position under obstacles using real-time simulation data. The agent learns the optimal policy to achieve focus while interacting with a complex environment, and the framework proves to be effective even in complex scenes with multiple objects. Driven by real-time reinforcement learning, the knowledge learned from one environment can be flexibly transferred to another environment to maximize information utilization and save considerable iteration time. In the context of future 6G communications development, the proposed method may significantly reduce the path loss of users in an occluded state, thereby solving the open challenge of poor signal penetration. Our study may also inspire the implementation of other intelligent devices.

Yinhuapinggan granule ameliorates lung injury caused by multidrug-resistant Acinetobacter baumannii via inhibiting NF-κB/NLRP3 pathway.

Yinhuapinggan granule (YHPG) is a traditional Chinese medicine prescription with rich clinical experience for the treatment of colds and coughs. The aim of this study is to investigate the protective effect of YHPG on multidrug-resistant (MDR) Acinetobacter baumannii (A. baumannii) infection in vivo and its potential anti-inflammatory mechanism. BALB/c mice were intranasally inoculated with MDR A. baumannii strain to establish the pneumonia infection model, and received intraperitoneally cyclophosphamide to form immunosuppression before attack. YHPG (6, 12 and 18 g/kg) was administered by gavage once a day for 3 consecutive days after infection. The protective effect of YHPG was evaluated by lung index, spleen index, thymus index, pathological changes of lung tissue and inflammatory factors (IL-1ß, IL-6 and TNF-α) in serum. The expression of key targets of NF-κB/NLRP3 signaling pathway in vivo was analyzed by immunohistochemistry, immunofluorescence, reverse transcription quantitative PCR (RT-qPCR) and Western blot. The results showed that YHPG improved the lung index and its inhibition rate, immune organ indexes and lung pathological changes in infected mice, and significantly reduced IL-1ß, IL-6 and TNF-α levels in serum. In addition, YHPG significantly down-regulated the mRNA and protein expression of NF-κB p65, NLRP3, ASC, Caspase-1, TNF-α, IL-6 and IL-1ß in mice lung tissue. The results of the current study demonstrated that YHPG has significant protective effects on mice infected with MDR A.baumannii, which may be related to the regulation of inflammatory factors and NF-κB/NLRP3 signaling pathway, indicating that YHPG has a wide range of clinical application value and provides a theoretical basis for its treatment of MDR A.baumannii infection.

The combination of danhong injection plus tissue plasminogen activator ameliorates mouse tail thrombosis-induced by κ-carrageenan.

BACKGROUND: After thrombosis, t-PA thrombolysis is the first choice, but the use of t-PA can easily lead to hemorrhagic injury and neurotoxicity. The combination of Danhong injection (DHI) and tissue plasminogen activator (t-PA) therapy may be a new strategy to find high-efficiency anti-thrombosis and low bleeding risk. However, nothing is about the effect of DHI plus t-PA on platelet activation. PURPOSE: The present research was to explore the optimal dose of DHI and t-PA in vivo and mechanisms involved with the treatment of combining DHI and t-PA for thrombotic disease and determined whether DHI plus t-PA affects thrombotic processes related to platelet activation. METHODS: Mice were induced by administering κ-carrageenan intraperitoneally, the ratio of different doses of DHI and t-PA in vivo, and the optimal dose effects on platelet aggregation, platelet adhesion, thrombosis formation, and platelet activation were determined. The effects of the αIIbß3 signaling pathway were analyzed in mice. RESULTS: In vitro, DHI (62% v/v), t-PA (1 mg/ml), and DHI + t-PA (62% v/v + 1 mg/ml) decreased rat platelet aggregation and adhesion, with a stronger effect from the combination as compared to t-PA monotherapy. In vivo, injections of κ-carrageenan were used to induce BALB/c mice. The optimal dose of DHI, t-PA, and DHI + t-PA is 12 ml/kg, 10 mg/kg, and 12 ml/kg + 7.5 mg/kg. The administration of DHI (12 ml/kg), t-PA (10 mg/kg), and DHI + t-PA (12 ml/kg + 7.5 mg/kg) decreased thrombi in mouse tissue vessels. Furthermore, the reduction of thrombosis formation by DHI, t-PA, and DHI + t-PA was related to lower collagen deposition, and lowered expressions of collagen I, matrix metalloproteinase 2 (MMP-2), and metalloproteinase 9 (MMP-9) in mouse tails, with increased efficacy in combination as compared to t-PA alone. The anti-thrombosis actions of DHI, t-PA, and their combination regulated the expression of CD41, purinergic receptor (P2Y12), guanine nucleotide-binding protein G (q) subunit alpha (GNAQ), phosphatidylinositol phospholipase c beta (PLCß), Ras-related protein 1 (Rap1), RIAM, talin1, fibrinogen alpha chain (FG), kindlin-3, and RAS guany1-releasing protein 1 (RasGRP1). CONCLUSIONS: Based on expression, the mechanism responsible for thrombosis may be attributed to platelet activation via the αIIbß3 signaling pathway. Combination therapy with DHI and t-PA exerted potent thrombolytic effects. Thus, our data can be used as a foundation for further clinical studies examining the efficacy of traditional Chinese medicines for the treatment of thrombosis.

Clinical Efficacy Protocol of Yinhuapinggan Granules: A Randomized, Double-Blind, Parallel, and Controlled Clinical Trial Program for the Intervention of Community-Acquired Drug-Resistant Bacterial Pneumonia as a Complementary Therapy.

Background: Community-acquired bacterial pneumonia (CABP) is an important health care concern in the worldwide, and is associated with significant morbidity, mortality, and health care expenditure. Streptococcus pneumoniae is the most frequent causative pathogen of CABP. Common treatment for hospitalized patients with CABP is empiric antibiotic therapy using ß-lactams in combination with macrolides, respiratory fluoroquinolones, or tetracyclines. However, overuse of antibiotics has led to an increased incidence of drug-resistant S. pneumoniae, exacerbating the development of community-acquired drug-resistant bacterial pneumonia (CDBP) and providing a challenge for physicians to choose empirical antimicrobial therapy. Methods: Traditional Chinese medicine (TCM) is widely used as a complementary treatment for CDBP. Yinhuapinggan granules (YHPG) is widely used in the adjuvant treatment of CDBP. Experimental studies and small sample clinical trials have shown that YHPG can effectively reduce the symptoms of CDBP. However, there is a lack of high-quality clinical evidence for the role of YHPG as a complementary drug in the treatment of CDBP. Here, we designed a randomized, double-blind, placebo-controlled clinical trial to explore the efficacy and safety of YHPG. A total of 240 participants will be randomly assigned to the YHPG or placebo group in a 1:1 ratio. YHPG and placebo will be added to standard treatment for 10 days, followed by 56 days of follow-up. The primary outcome is the cure rate of pneumonia, and the secondary outcomes includes conversion rate of severe pneumonia, lower respiratory tract bacterial clearance, lactic acid (LC) clearance rate, temperature, C-reactive protein (CRP), criticality score (SMART-COP score), acute physiological and chronic health assessment system (APACHEII score) and clinical endpoint events. Adverse events will be monitored throughout the trial. Data will be analyzed according to a pre-defined statistical analysis plan. This research will disclose the efficacy of YHPG in acquired drug-resistant pneumonia. Clinical Trial Registration: https://clinicaltrials.gov, identifier ChiCTR2100047501.

Screening of Antiviral Components of Yinhuapinggan Granule and Protective Effects of Yinhuapinggan Granule on MDCK Cells with Influenza A/H1N1 Virus.

BACKGROUND: Traditional Chinese medicine Yinhuapinggan granule (YHPG) has been used for treating upper respiratory tract infection like influenza, cough, and viral pneumonia. However, its active ingredients that really exert the main efficacy have not been well elucidated. This study is aimed at screening its antiviral components and investigating the potential therapeutic mechanisms of YHPG against the influenza A/PR8/34 (H1N1) virus in Madin Darby canine kidney (MDCK). METHODS: MDCK cells were infected with the influenza virus and then treated with ribavirin, YHPG, and main active ingredients in YHPG. Based on the maximum nontoxic concentration (TC0), half-maximal toxic concentration (TC50), half-maximal inhibitory concentration (IC50), and therapeutic index (TI), interferon-ß (IFN-ß) and interleukin-6 (IL-6) levels were measured using enzyme-linked immunosorbent assay (ELISA), and the gene expression of TLR7, MyD88, tumor necrosis factor receptor-associated factor 6 (TRAF6), c-Jun amino terminal kinase (JNK), p38 mitogen-activated protein kinase (p38 MAPK), and p65 nuclear transcription factor-kappa B (p65 NF-κB) was quantified using reverse transcription-polymerase chain reaction (RT-PCR). RESULTS: The results indicated that the components of YHPG, such as ephedrine hydrochloride, pseudoephedrine hydrochloride, chlorogenic acid, and emodin, had significant antiviral effects. High and medium doses of YHPG effectively reduced the cytopathic effect (CPE) and significantly decreased IFN-ß and IL-6 levels in the supernatant. Simultaneously, the transcript levels of TLR7, MyD88, TRAF6, JNK, p38 MAPK, and p65 NF-κB decreased in infected MDCK cells. Moreover, a certain dose-dependent relationship among different groups of YHPG was observed. CONCLUSIONS: These results indicated that YHPG and the components of YHPG had a significant inhibitory function on the proliferation of the H1N1 virus. The mechanism might be associated with suppressing the activation of the TLR7/MyD88 signaling pathway, a decrease in the mRNA expression of key target genes, and inhibition of IFN-ß and IL-6 secretion.

Corrigendum: Clinical efficacy protocol of yinhuapinggan granules: A randomized, double-blind, parallel, and controlled clinical trial program for the intervention of community-acquired drug-resistant bacterial pneumonia as a complementary therapy.

[This corrects the article DOI: 10.3389/fphar.2022.852604.].

T4SE-XGB: Interpretable Sequence-Based Prediction of Type IV Secreted Effectors Using eXtreme Gradient Boosting Algorithm.

Type IV secreted effectors (T4SEs) can be translocated into the cytosol of host cells via type IV secretion system (T4SS) and cause diseases. However, experimental approaches to identify T4SEs are time- and resource-consuming, and the existing computational tools based on machine learning techniques have some obvious limitations such as the lack of interpretability in the prediction models. In this study, we proposed a new model, T4SE-XGB, which uses the eXtreme gradient boosting (XGBoost) algorithm for accurate identification of type IV effectors based on optimal features based on protein sequences. After trying 20 different types of features, the best performance was achieved when all features were fed into XGBoost by the 5-fold cross validation in comparison with other machine learning methods. Then, the ReliefF algorithm was adopted to get the optimal feature set on our dataset, which further improved the model performance. T4SE-XGB exhibited highest predictive performance on the independent test set and outperformed other published prediction tools. Furthermore, the SHAP method was used to interpret the contribution of features to model predictions. The identification of key features can contribute to improved understanding of multifactorial contributors to host-pathogen interactions and bacterial pathogenesis. In addition to type IV effector prediction, we believe that the proposed framework can provide instructive guidance for similar studies to construct prediction methods on related biological problems. The data and source code of this study can be freely accessed at https://github.com/CT001002/T4SE-XGB.

Direct current remote cloak for arbitrary objects.

Hiding an arbitrary object with a cloak at a distance from an object is of great significance in scientific research, but remains unrealized as a practical device. In this paper, we propose the first experimental realization of a remote cloaking device that makes any object located at a certain distance invisible at direct current (DC) frequency. A negative resistor network with active elements is used to achieve the remote function of the DC cloak. Based on this network, the cloak can remotely generate a hidden region without distorting the currents far from the cloaked region. The experimental results show that any object in the hidden region is invisible to a DC detector. Our cloak does not require any knowledge of the hidden object. The experimental demonstration shows the superiority of this remote cloaking device, which may find potential applications in medical or geologic research.