When DNA-damage responses meet innate and adaptive immunity.

When cells proliferate, stress on DNA replication or exposure to endogenous or external insults frequently results in DNA damage. DNA-Damage Response (DDR) networks are complex signaling pathways used by multicellular organisms to prevent DNA damage. Depending on the type of broken DNA, the various pathways, Base-Excision Repair (BER), Nucleotide Excision Repair (NER), Mismatch Repair (MMR), Homologous Recombination (HR), Non-Homologous End-Joining (NHEJ), Interstrand Crosslink (ICL) repair, and other direct repair pathways, can be activated separately or in combination to repair DNA damage. To preserve homeostasis, innate and adaptive immune responses are effective defenses against endogenous mutation or invasion by external pathogens. It is interesting to note that new research keeps showing how closely DDR components and the immune system are related. DDR and immunological response are linked by immune effectors such as the cyclic GMP-AMP synthase (cGAS)-Stimulator of Interferon Genes (STING) pathway. These effectors act as sensors of DNA damage-caused immune response. Furthermore, DDR components themselves function in immune responses to trigger the generation of inflammatory cytokines in a cascade or even trigger programmed cell death. Defective DDR components are known to disrupt genomic stability and compromise immunological responses, aggravating immune imbalance and leading to serious diseases such as cancer and autoimmune disorders. This study examines the most recent developments in the interaction between DDR elements and immunological responses. The DDR network's immune modulators' dual roles may offer new perspectives on treating infectious disorders linked to DNA damage, including cancer, and on the development of target immunotherapy.

Oxygen Vacancies-Induced Antifouling Photoelectrochemical Aptasensor for Highly Sensitive and Selective Determination of α-Fetoprotein.

Accurate measurement of cancer markers in urine is a convenient method for tumor monitoring. However, the concentration of cancer markers in urine is so low that it is difficult to achieve their measurement. Photoelectrochemical (PEC) sensors are a promising technology to realize the detection of trace cancer markers due to their high sensitivity. Currently, the interference of nonspecific biomolecules in urine is the main reason affecting the high sensitivity and selectivity of PEC sensors in detecting cancer markers. In this work, a strategy of oxygen vacancy (OV) modulation is proposed to construct a fouling-resistant PEC aptamer sensing platform for the detection of α-fetoprotein (AFP), a liver cancer marker. The introduction of OVs induces the formation of intermediate localized states in the photoelectric material, which not only facilitates the separation of photogenerated carriers but also leads to the redshift of the light absorption edge. More importantly, OVs with positive electrical properties can be employed to modify the antifouling layer (C-PEG) with negatively charged groups through an electrostatic interaction. The synergistic effect of OVs, antifouling layer, and aptamer resulted in a TiO2/OVs/C-PEG-based PEC sensor achieves a wide linear range from 1 pg/mL to 100 ng/mL and a low detection limit of 0.3 pg/mL for AFP. In addition, the sensor successfully realized the determination of AFP in urine samples and accurately differentiated between normal people and liver cancer patients in the early and advanced stages. This project is of great significance in advancing the application of photoelectrochemical bioanalytical technology to achieve the detection of cancer markers in urine by investigating the construction of an OVs-regulated fouling-resistant sensing interface.

A pH ultra-sensitive hydrated iridium oxyhydroxide films electrochemical sensor for label-free detection of Vibrio parahaemolyticus.

Vibrio parahaemolyticus (V. parahaemolyticus) is a major foodborne pathogen, which can cause serious foodborne illnesses like diarrhoea. Rapid on-site detection of foodborne pathogens is an ideal way to respond to foodborne illnesses. Herein, we provide an electrochemical sensor for rapid on-site detection. This sensor utilized a pH-sensitive metal-oxide material for the concurrent isothermal amplification and label-free detection of nucleic acids. Based on a pH-sensitive hydrated iridium oxide oxyhydroxide film (HIROF), the electrode transforms the hydrogen ion compound generated during nucleic acid amplification into potential, so as to achieve a real-time detection. The results can be transmitted to a smartphone via Bluetooth. Moreover, HIROF was applied in nucleic acid device detection, with a super-Nernst sensitivity of 77.6 mV/pH in the pH range of 6.0-8.5, and the sensitivity showed the best results so far. Detection of V. parahaemolyticus by this novel method showed a detection limit of 1.0 × 103 CFU/mL, while the time consumption was only 30 min, outperforming real-time fluorescence loop-mediated isothermal amplification (LAMP). Therefore, the characteristics of compact, portable, and fast make the sensor more widely used in on-site detection.

Adverse drug reaction signal detection methods in spontaneous reporting system: A systematic review.

BACKGROUND: A series of signal detection methods have been developed to detect adverse drug reaction (ADR) signals in spontaneous reporting system. However, different signal detection methods yield quite different signal detection results, and we do not know which method has the best detection performance. How to choose the most suitable signal detection method is an urgent problem to be solved. In this study, we systematically reviewed the characteristics and application scopes of current signal detection methods, with the goal of providing references for the optimization selection of signal detection methods in spontaneous reporting system. METHODS: We searched six databases from inception to January 2023. The search strategy targeted literatures regarding signal detection methods in spontaneous reporting system. We used thematic analysis approach to summarize the advantages, disadvantages, and application scope of each signal detection method. RESULTS: A total of 93 literatures were included, including 27 reviews and 66 methodological studies. Moreover, 31 signal detection methods were identified in these literatures. Each signal detection method has its inherent advantages and disadvantages, resulting in different application scopes of these methods. CONCLUSION: Our systematic review finds that there are variabilities in the advantages, disadvantages, and application scopes of different signal detection methods. This finding indicates that the most suitable signal detection method varies across different drug safety scenarios. Moreover, when selecting signal detection method in a particular drug safety scenario, the following factors need to be considered: purpose of research, database size, drug characteristics, adverse event characteristics, and characteristics of the relations between drugs and adverse events.

Drug Analysis of Voriconazole Combined with Granulocyte Colony Stimulating Factor.

BACKGROUND: The aim of the study was to improve the clinical cognition of leukemia-like reaction caused by voriconazole and granulocyte colony-stimulating factor and to avoid misdiagnosis or delayed diagnosis. METHODS: A case of drug analysis of Voriconazole combined with granulocyte colony stimulating factor was retrospectively analyzed and related literature was reviewed. RESULTS: Blood routine of the patient on July 29: WBC 13.48 x 109/L, neutrophil 85.3%, lymphocyte 13.4%, hemoglobin 111 g/L, platelet 285 x 109/L. Vancomycin was given to prevent intracranial infection. Lumbar puncture was performed on July 30, cerebrospinal fluid was sent for routine and biochemical examination, leukocytes were 0.15 x 109/L, monocytes 45%, polynuclear cells 55%, protein 1.172 g/L, Acinetobacter baumannii and Candida clorbicus were detected in sputum culture, vancomycin and meropenem static sites were given to prevent intracranial secondary infection. Fungi were detected in urine culture, and voriconazole was given to prevent fungal infection. Blood routine: White blood cell 0.61 x 109/L, neutrophil 23%, lymphocyte 73.8%, red blood cell 2.65 x 1012/L, hemoglobin 77 g/L, platelet 17 x 109/L, bone marrow was extracted after medication. Bone marrow images show poor myelodysplasia, with granulocytes dominated by protoearly cells. Subsequent flow cytometry, chromosomal karyotype, and fusion gene analysis were performed to exclude the possibility of leukemia. Flow cytometry showed that the proportion of myeloid primordial cells was not high, the granulocytes were mainly at the early and young stage, no abnormal phenotype was observed in erythrocytes, monocytes and NK cells, no obvious mature B lymphocytes were observed, and the ratio of CD4+/CD8+ was decreased. Karyotype results showed that there was no mitotic phase. The results of fusion gene analysis showed that the fusion gene was negative or lower than the detection sensitivity. Voliconazole was stopped first, and granulocyte colony stimulating factor was stopped 3 days later. Two weeks later, blood and bone marrow images basically recovered, white blood cell 7.88 x 109/L, neutrophil 46.3%, lymphocyte 48.2%, hemoglobin 126 g/L, platelet 142 x 109/L, bone marrow hyperplasia active. The proportion of three series is roughly normal. CONCLUSIONS: The reason for the occurrence of leukemia-like reaction in this patient was considered to be related to voriconazole and granulocyte colony stimulating factor, cessation of voriconazole and granulocyte colony stimulating factor, and recovery of blood and bone marrow images. In the clinical use of voriconazole and granulocyte colony stimulating factor, close attention should be paid to the drug interaction and individualized medication should be carried out to ensure the safety of medication.

Multi-Omics Analysis Reveals the Role of Changes in Platelet Activation Pathways in the Survival Outcome of Patients with Esophageal Squamous Cell Carcinoma.

Objective: The objective of this study was to integrate metabolomics and transcriptomics data to identify key diagnostic and prognostic markers for esophageal squamous cell carcinoma (ESCC). Plasma samples were collected from 85 ESCC patients at different stages and 50 healthy volunteers for non-targeted metabolomic analysis. Methods: Liquid chromatography-tandem mass spectrometry (LC-MS/MS) was employed for non-targeted metabolomic analysis. Subsequently, we integrated the metabolomic data with transcriptomic data from the Gene Expression Omnibus (GEO) and prognosis data from The Cancer Genome Atlas Program (TCGA) to perform pathway analysis. Our focus was on pathways that involve both metabolites and upstream genes, as they often exhibit higher accuracy. Results: Through the integration of metabolomics and transcriptomics, we identified significant alterations in the platelet activation pathway in ESCC. This pathway involves the participation of both metabolites and genes, making it a more accurate reflection of pathological changes associated with the disease. Notably, metabolite arachidonic acid (AA) and chemokine receptor type 2(CXCR2) were significantly downregulated in ESCC, while genes collagen type I alpha 1(COL1A1), collagen type I alpha 2(COL1A2), collagen type III alpha 1(COL3A1), type 3 inositol 1,4,5-trisphosphate receptor (ITPR3), and insulin-like growth factor II mRNA binding protein 3(IGF2BP3) were significantly upregulated, indicating the presence of tumor-induced platelet activation in ESCC. Further analysis of prognosis data revealed that high expression of COL1A1, IGF2BP3, and ITPR3 was associated with a favorable prognosis for ESCC, while high CXCR2 expression was linked to an adverse prognosis. In addition, we combined COL1A1, ITPR3, IGF2BP3, CXCR2, and AA to form a diagnostic biomarker panel. The receiver operating characteristic curve (ROC) demonstrated excellent diagnostic capability (AUC=0.987). Conclusion: Our study underscores the significant role of platelet activation pathways and related genes in the diagnosis and prognosis of ESCC patients. These findings offer promising insights for improving the clinical management of ESCC.

Increased circulating phenylacetylglutamine concentration elevates the predictive value of cardiovascular event risk in heart failure patients.

BACKGROUND: Phenylacetylglutamine (PAGln)-a newly discovered microbial metabolite produced by phenylalanine metabolism-is reportedly associated with cardiovascular events via adrenergic receptors. Nonetheless, its association with cardiovascular outcomes in heart failure (HF) patients remains unknown. OBJECTIVES: This study aimed to prospectively investigate the prognostic value of PAGln for HF. METHODS: Plasma PAGln levels were quantified by liquid chromatography-tandem mass spectrometry. We first assessed the association between plasma PAGln levels and the incidence of adverse cardiovascular events in 3152 HF patients (including HF with preserved and reduced ejection fraction) over a median follow-up period of 2 years. The primary endpoint was the composite of cardiovascular death or heart transplantation. We then assessed the prognostic role of PAGln in addition to the classic biomarker N-terminal pro-B-type natriuretic peptide (NT-proBNP). The correlation between PAGln levels and ß-blocker use was also investigated. RESULTS: In total, 520 cardiovascular deaths or heart transplantations occurred in the HF cohort. Elevated PAGln levels were independently associated with a higher risk of the primary endpoint in a dose-response manner, regardless of HF subtype. Concurrent assessment of PAGln and NT-proBNP levels enhanced risk stratification among HF patients. PAGln further showed prognostic value at low NT-proBNP levels. Additionally, the interaction effects between PAGln and ß-blocker use were not significant. CONCLUSIONS: Plasma PAGln levels are an independent predictor of an increased risk of adverse cardiovascular events in HF. Our work could provide joint and complementary prognostic value to NT-proBNP levels in HF patients.

High-Performance Electrocatalytic Reduction of Nitrite to Ammonia under Ambient Conditions on a FeP@TiO2 Nanoribbon Array.

Electrochemical nitrite (NO2-) reduction is recognized as a promising strategy for synthesizing valuable ammonia (NH3) and degrading NO2- pollutants in wastewater. The six-electron process for the NO2- reduction reaction is complex and necessitates a highly selective and stable electrocatalyst for efficient conversion of NO2- to NH3. Herein, a FeP nanoparticle-decorated TiO2 nanoribbon array on a titanium plate (FeP@TiO2/TP) is proposed as an efficient catalyst for NH3 production under ambient conditions. In 0.1 M NaOH with 0.1 M NO2-, such a FeP@TiO2/TP affords a large NH3 yield of 346.6 µmol h-1 cm-2 and a high Faradaic efficiency of 97.1%. Additionally, it demonstrates excellent stability and durability during long-term cycling tests and electrolysis experiments.

Significance of Cuproptosis-related genes in immunological characterization, diagnosis and clusters classification in Parkinson's disease.

Parkinson's disease (PD) is a progressive neurological disorder that affects millions of people throughout the world. Cuproptosis is a newly discovered form of programmed cell death linked to several neurological disorders. Nevertheless, the precise mechanisms of Cuproptosis-related genes (CRGs) in PD remain unknown. This study investigated immune infiltration and CRG expression profiling in patients with Parkinson's disease and healthy controls. Subsequently, we construct a predictive model based on 5 significant CRGs. The performance of the predictive model was validated by nomograms and external datasets. Additionally, we classified PD patients into two clusters based on CRGs and three gene clusters based on differentially expressed genes (DEG) of CRGs clusters. We further evaluated immunological characterization between the different clusters and created the CRGs scores to quantify CRGs patterns. Finally, we investigate the prediction of CRGs drugs and the ceRNA network, providing new insights into the pathogenesis and management of PD.

Liver injury in children: signal analysis of suspected drugs based on the food and drug administration adverse event reporting system.

BACKGROUND: Evidence of drug-induced liver injury is abundant in adults but is lacking in children. Our aim was to identify suspected drug signals associated with pediatric liver injury. METHODS: Hepatic adverse events (HAEs) among children reported in the Food and Drug Administration Adverse Event Reporting System were analyzed. A descriptive analysis was performed to summarize pediatric HAEs, and a disproportionality analysis was conducted by evaluating reporting odds ratios (RORs) and proportional reporting ratios to detect suspected drugs. RESULTS: Here, 14,143 pediatric cases were reported, specifically 49.6% in males, 45.1% in females, and 5.2% unknown. Most patients (68.8%) were 6-18 years old. Hospitalization ranked first among definite outcomes (7,207 cases, 37.2%). In total, 264 disproportionate drug signals were identified. The top 10 drugs by the number of reports were paracetamol (1,365; ROR, 3.6; 95% confidence interval (CI), 3.4-3.8), methotrexate (878; ROR, 2.5; 95% CI, 2.3-2.7), vincristine (649; ROR, 3.0; 95% CI, 2.8-3.3), valproic acid (511; ROR, 3.2; 95% CI, 2.9-3.6), cyclophosphamide (490; ROR, 2.4; 95% CI, 2.2-2.6), tacrolimus (427; ROR, 2.4; 95% CI, 2.2-2.7), prednisone (416; ROR, 2.1; 95% CI, 1.9-2.3), prednisolone (401; ROR, 2.3; 95% CI, 2.1-2.5), etoposide (378; ROR, 2.3; 95% CI, 2.1-2.6), and cytarabine (344; ROR, 2.8; 95% CI, 2.5-3.2). After excluding validated hepatotoxic drugs, six were newly detected, specifically acetylcysteine, thiopental, temazepam, nefopam, primaquine, and pyrimethamine. CONCLUSIONS: The hepatotoxic risk associated with 264 signals needs to be noted in practice. The causality of hepatotoxicity and mechanism among new signals should be verified with preclinical and clinical studies.

The salt secretion of leaves promotes the competitiveness of Reaumuria soongarica in a desert grassland.

BACKGROUND: For better understanding the mechanism of Reaumuria soongarica community formation in a salt stressed grassland ecosystem, we designed a field experiment to test how leaves salt secretion changes the competitive relationship between species in this plant communities. RESULTS: Among the three species (R. soongarica, Stipa glareosa and Allium polyrhizum) of the salt stressed grassland ecosystem, the conductivity of R. soongarica rhizosphere soil was the highest in five soil layers (0-55 cm depth). The high soil conductivity can increase the daily salt secretion rate of plant leaves of R. soongarica. In addition, we found the canopy size of R. soongarica was positively related to the distance from S. glareosa or A. polyrhizum. The salt-tolerance of R. soongarica was significantly higher than the other two herbs (S. glareosa and A. polyrhizum). Moreover, there was a threshold (600 µS/cm) for interspecific competition of plants mediated by soil conductivity. When the soil conductivity was lower than 600 µS/cm, the relative biomass of R. soongarica increased with the soil conductivity increase. CONCLUSIONS: The efficient salt secretion ability of leaves increases soil conductivity under the canopy. This leads the formation of a "saline island" of R. soongarica. Meanwhile R. soongarica have stronger salt tolerance than S. glareosa and A. polyrhizum. These promote the competitiveness of R. soongarica and inhibit interspecies competition advantage of the other two herbs (S. glareosa and A. polyrhizum) in the plant community. It is beneficial for R. soongarica to establish dominant communities in saline regions of desert grassland.

Large-Scale Production of Ligand-Engineered Robust Lead Halide Perovskite Nanocrystals by a Droplet-Based Microreactor System.

Cesium lead halide perovskite nanocrystals (CLHP NCs) have a wide range of potential applications benefited from the properties of high photoluminescence quantum yield (PLQY), wide luminous gamut, and narrow half peak width. However, due to the ionic nature and sensitivity to moisture, oxygen, or heat, perovskite nanocrystals are too fragile to maintain their crystal structure and optical properties. This work proposes solutions to two key issues in the development of CLHP NCs. First, a productive droplet-based microreactor system is designed to accomplish the scale-up production of CLHP NCs, obtaining sub-gram high-purity nanocrystal powders in a single production process. Second, CLHP NCs which are stable in polar solvents, air environment, and high temperature by using 3-aminopropyl triethoxysilane (APTES) as basic ligand are obtained. Wrapped with Si-O-Si generated by APTES, the CLHP NCs exhibit a longer fluorescence lifetime and higher quantum yield. Especially, the PLQY of CsPbBr3 @APTES can be stable at higher than 90% for more than 10 days. The Si-O-Si protective layer can also suppress the anion exchange between CsPbBr3 and CsPbI3 , maintaining the monochromaticity of nanocrystal luminescence. Eventually, full-spectrum quantum light-emitting diode (QLED) beads with robust nanocrystals are fabricated. The gamut of CsPbX3 @APTES encompasses 140% of the NTSC color gamut standard.

A parallel model of DenseCNN and ordered-neuron LSTM for generic and species-specific succinylation site prediction.

Lysine succinylation (Ksucc) regulates various metabolic processes, participates in vital life processes, and is involved in the occurrence and development of numerous diseases. Accurate recognition of succinylation sites can reveal underlying functional mechanisms and pathogenesis. However, most remain undetected. Moreover, a deep learning architecture focusing on generic and species-specific predictions is still lacking. Thus, we proposed a deep learning-based framework named Deep-Ksucc, combining a dense convolutional network and ordered-neuron long short-term memory in parallel, which took the cascading characteristics of sequence information and physicochemical properties as the input. The results of the generic and species-specific predictions indicated that Deep-Ksucc can identify sequence patterns of different organisms and recognize plenty of succinylation sites. The case study showed that Deep-Ksucc can serve as a reliable tool for biology verification and computer-aided recognition of succinylation sites.

Comprehensive Effect of Oxidant Addition in an FGD Slurry on the Removal and Distribution of Selenium: A Field Study.

Flue gas desulfurization (FGD) scrubbers capture selenium in coal-fired power plants, leading to a high concentration of selenium in the slurry. This research proves that SO32- is preferentially oxidized compared to SeO32- by S2O82-. With the increase in the oxidation-reduction potential (ORP) caused by S2O82- addition, the conversion rate of SO32- increased and the size of gypsum grains grew from 31.2 to 34.6 µm. SeO32- migrates into gypsum grains during the growth of CaSO4·2H2O, leading to selenium fixation in gypsum. In a field study of a 350 MW unit, the ORP increased from 142 to 450 mV when Na2S2O8 was fed into the FGD slurry. With the addition of the oxidant, 65.1% of selenium in the liquid phase migrated into gypsum. The concentration of selenium in the leachate of gypsum after oxidant addition decreased by 68.0%. A 2.34% increase in the selenium removal rate was observed in the scrubber. This study focuses on the migration and conversion of selenium in an actual FGD slurry via a field test. The results found in the 350 MW unit are consistent with laboratory results. The change in ORP has been proven to be effective in adjusting the selenium distribution in the FGD slurry.

Efficacy and safety of intranasal midazolam versus intranasal ketamine as sedative premedication in pediatric patients: a meta-analysis of randomized controlled trials.

BACKGROUND: Intranasal midazolam and ketamine have been widely used as sedative premedication in children. It is difficult to determine which one yields better sedative effects for clinical practice. We conducted the present meta-analysis by summarizing the evidences to evaluate the efficacy and safety of intranasal midazolam versus intranasal ketamine as sedative premedication in pediatric patients. METHODS: We searched PubMed, Embase, and Cochrane Library from inception to April 2022. All randomized controlled trials (RCTs) used intranasal midazolam and ketamine as sedatives in children were enrolled. The risk of bias in RCTs was assessed by Cochrane risk of bias tool. Condition of parental separation, anesthesia induction or facemask acceptance, sedation level, different hemodynamic parameters and adverse events were considered as the outcomes in our study. RESULTS: A total of 16 studies with 1066 patients were enrolled. Compared with midazolam, administration of intranasal ketamine might be associated with severer changes in hemodynamics parameters including mean blood pressure (SMD = -0.53, with 95% CI [-0.93, -0.13]) and heart rate (HR) (SMD = -1.39, with 95% CI [-2.84, 0.06]). Meanwhile, administration of intranasal midazolam was associated with more satisfactory sedation level (61.76% vs 40.74%, RR = 1.53, with 95%CI [1.28, 1.83]), more rapid onset of sedation (SMD = -0.59, with 95%CI [-0.90, -0.28]) and more rapid recovery (SMD = -1.06, with 95%CI [-1.83, -0.28]). Current evidences also indicated that the differences of various adverse effects between two groups were not significant. CONCLUSIONS: Given that administration of midazolam via intranasal route provides more satisfactory sedative level with less fluctuation of hemodynamics parameters and more rapid onset and recovery, it might be considered as the preferred sedative premedication for pediatric patients compared to ketamine. However, the widespread evidences with low or moderate quality indicated that superiority of intranasal midazolam in pediatric sedation needs to be confirmed by more studies with high quality and large sample size in future. TRIAL REGISTRATION: The protocol of present study was registered with PROSPERO (CRD42022321348).

PD-BertEDL: An Ensemble Deep Learning Method Using BERT and Multivariate Representation to Predict Peptide Detectability.

Peptide detectability is defined as the probability of identifying a peptide from a mixture of standard samples, which is a key step in protein identification and analysis. Exploring effective methods for predicting peptide detectability is helpful for disease treatment and clinical research. However, most existing computational methods for predicting peptide detectability rely on a single information. With the increasing complexity of feature representation, it is necessary to explore the influence of multivariate information on peptide detectability. Thus, we propose an ensemble deep learning method, PD-BertEDL. Bidirectional encoder representations from transformers (BERT) is introduced to capture the context information of peptides. Context information, sequence information, and physicochemical information of peptides were combined to construct the multivariate feature space of peptides. We use different deep learning methods to capture the high-quality features of different categories of peptides information and use the average fusion strategy to integrate three model prediction results to solve the heterogeneity problem and to enhance the robustness and adaptability of the model. The experimental results show that PD-BertEDL is superior to the existing prediction methods, which can effectively predict peptide detectability and provide strong support for protein identification and quantitative analysis, as well as disease treatment.

CL-ACP: a parallel combination of CNN and LSTM anticancer peptide recognition model.

BACKGROUND: Anticancer peptides are defence substances with innate immune functions that can selectively act on cancer cells without harming normal cells and many studies have been conducted to identify anticancer peptides. In this paper, we introduce the anticancer peptide secondary structures as additional features and propose an effective computational model, CL-ACP, that uses a combined network and attention mechanism to predict anticancer peptides. RESULTS: The CL-ACP model uses secondary structures and original sequences of anticancer peptides to construct the feature space. The long short-term memory and convolutional neural network are used to extract the contextual dependence and local correlations of the feature space. Furthermore, a multi-head self-attention mechanism is used to strengthen the anticancer peptide sequences. Finally, three categories of feature information are classified by cascading. CL-ACP was validated using two types of datasets, anticancer peptide datasets and antimicrobial peptide datasets, on which it achieved good results compared to previous methods. CL-ACP achieved the highest AUC values of 0.935 and 0.972 on the anticancer peptide and antimicrobial peptide datasets, respectively. CONCLUSIONS: CL-ACP can effectively recognize antimicrobial peptides, especially anticancer peptides, and the parallel combined neural network structure of CL-ACP does not require complex feature design and high time cost. It is suitable for application as a useful tool in antimicrobial peptide design.

An arbitrary high-order discontinuous Galerkin method with local time-stepping for linear acoustic wave propagation.

This paper presents a numerical scheme of arbitrary order of accuracy in both space and time, based on the arbitrary high-order derivatives methodology, for transient acoustic simulations. The scheme combines the nodal discontinuous Galerkin method for the spatial discretization and the Taylor series integrator (TSI) for the time integration. The main idea of the TSI is a temporal Taylor series expansion of all unknown acoustic variables in which the time derivatives are replaced by spatial derivatives via the Cauchy-Kovalewski procedure. The computational cost for the time integration is linearly proportional to the order of accuracy. To increase the computational efficiency for simulations involving strongly varying mesh sizes or material properties, a local time-stepping (LTS) algorithm accompanying the arbitrary high-order derivatives discontinuous Galerkin (ADER-DG) scheme, which ensures correct communications between domains with different time step sizes, is proposed. A numerical stability analysis in terms of the maximum allowable time step sizes is performed. Based on numerical convergence analysis, we demonstrate that for nonuniform meshes, a consistent high-order accuracy in space and time is achieved using ADER-DG with LTS. An application to the sound propagation across a transmissive noise barrier validates the potential of the proposed method for practical problems demanding high accuracy.

miR-550a-3/NFIC plays a driving role in esophageal squamous cell cancer cells proliferation and metastasis partly through EMT process.

In this study, the functional role of miR-550a-3 and its direct target nuclear factor IC (NFIC) in esophageal squamous cell cancer (ESCC) cells were explored. Differential expression of miR-550a-3 in ESCC tissues was acquired from TCGA database, and Kaplan-Meier method was used to determine the relationship between miR-550a-3 expression and survival time of ESCC patients. Expression level of miR-550a-3 in several ESCC cell lines was measured by qRT-PCR. Two cell lines including Eca109 and JAR were used to perform proliferation, cloning, invasion and migration experiments. Targeted relationship between miR-550a-3 and NFIC was speculated by predication software and confirmed by dual luciferase assay. Additionally, potential relationship between miR-550a-3 and NFIC was analyzed by Spearman rank correlation analysis and western blot. Rescue assays were performed to explore the function of miR-550a-3/NFIC in ESCC cells biological behaviors. Expression levels of key proteins involved in epithelial-to-mesenchymal transition (EMT) process were determined by western blot. By consulting TCGA database, we found that high expression of miR-550a-3 was positively connected with the poor prognosis of patients with ESCC. In addition, overexpression of miR-550a-3 promoted the proliferation, colony formation and metastasis of ESCC cells. Moreover, rescue assays revealed that overexpression of NFIC attenuated the promoting effects of miR-550a-3 on ESCC cells malignant behaviors. While the promoting effects of miR-550a-3 on EMT process were inhibited by NFIC. Our results illustrate the importance of miR-550a-3/NFIC in regulation of ESCC cells growth and metastasis, which could contribute to developing novel target for early diagnosis or neoteric therapeutic target for ESCC.

Time-domain impedance boundary condition modeling with the discontinuous Galerkin method for room acoustics simulations.

The time-domain nodal discontinuous Galerkin (TD-DG) method is emerging as a potential wave-based method for three-dimensional (3D) room acoustics modeling, where high-order accuracy in the low frequency range, geometrical flexibility, and accurate modeling of boundary conditions are of critical importance. This paper presents a formulation of broadband time-domain impedance boundary conditions (TDIBCs) of locally-reacting surfaces in the framework of the TD-DG method. The formulation is based on the approximation of the plane-wave reflection coefficient at normal incidence in the frequency domain using a sum of template rational functions, which can be directly transformed to the time-domain. The coupling of the TDIBCs with the discontinuous Galerkin discretization is achieved through the characteristic waves of the upwind flux along the boundary, where a series of first-order auxiliary differential equations is time-integrated in a high-order way. To verify the performance of the formulation, various numerical tests of single reflection scenarios are shown to demonstrate the cost efficiency and memory-efficiency of high-order basis functions, among which a 3D application to an impedance boundary of rigidly backed glass-wool baffle for room acoustic purposes is presented.