Tim-3 regulates the immunosuppressive function of decidual MDSCs via the Fyn-STAT3-C/EBPß pathway during Toxoplasma gondii infection.

Myeloid-derived suppressor cells (MDSCs) play a key role in maintaining maternal-fetal tolerance for a successful pregnancy, but the role of MDSCs in abnormal pregnancy caused by Toxoplasma gondii infection is unknown. Herein, we revealed a distinct mechanism by which T-cell immunoglobulin domain and mucin domain containing protein-3 (Tim-3), an immune checkpoint receptor that balances maternal-fetal tolerance during pregnancy, contributes to the immunosuppressive function of MDSCs during T. gondii infection. The expression of Tim-3 in decidual MDSCs was significantly downregulated following T. gondii infection. The proportion of monocytic MDSCs population, the inhibitory effect of MDSCs on T-cell proliferation, the levels of STAT3 phosphorylation, and the expression of functional molecules (Arg-1 and IL-10) in MDSCs were all decreased in T. gondii-infected pregnant Tim-3 gene knockout (Tim-3KO) mice compared with infected pregnant WT mice. After treatment with Tim-3-neutralizing Ab in vitro, the expression levels of Arg-1, IL-10, C/EBPß, and p-STAT3 were decreased, the interaction between Fyn and Tim-3 or between Fyn and STAT3 was weakened, and the binding ability of C/EBPß to the promoters of ARG1 and IL10 was decreased in human decidual MDSCs with T. gondii infection, while opposite results were observed following treatment with galectin-9 (a ligand for Tim-3). Inhibitors of Fyn and STAT3 also downregulated the expression of Arg-1 and IL-10 in decidual MDSCs and exacerbated adverse pregnancy outcomes caused by T. gondii infection in mice. Therefore, our studies discovered that the decrease of Tim-3 after T. gondii infection could downregulate the functional molecules of Arg-1 and IL-10 expression in decidual MDSCs through the Fyn-STAT3-C/EBPß signaling pathway and weaken their immunosuppressive function, which eventually contribute to the development of adverse pregnancy outcomes.

FoxG1/BNIP3 axis promotes mitophagy and blunts cisplatin resistance in osteosarcoma.

Cisplatin (CDDP) is a commonly used chemotherapeutic for osteosarcoma (OS) patients, and drug resistance remains as a major hurdle to undermine the treatment outcome. Here, we investigated the potential involvement of FoxG1 and BNIP3 in CDDP resistance of OS cells. FoxG1 and BNIP3 expression levels were detected in the CDDP-sensitive and CDDP-resistant OS tumors and cell lines. Mitophagy was observed through transmission electron microscope analysis. The sensitivity to CDDP in OS cells upon FoxG1 overexpression was examined in cell and animal models. We found that FoxG1 and BNIP3 showed significant downregulation in the CDDP-resistant OS tumor samples and cell lines. CDDP-resistant OS tumor specimens and cells displayed impaired mitophagy. FoxG1 overexpression promoted BNIP3 expression, enhanced mitophagy in CDDP-resistant OS cells, and resensitized the resistant cells to CDDP treatment in vitro and in vivo. Our data highlighted the role of the FoxG1/BNIP3 axis in regulating mitophagy and dictating CDDP resistance in OS cells, suggesting targeting FoxG1/BNIP3-dependent mitophagy as a potential strategy to overcome CDDP resistance in OS.

Screening and functional verification of drought resistance-related genes in castor bean seeds.

Drought is one of the natural stresses that greatly impact plants. Castor bean (Ricinus communis L.) is an oil crop with high economic value. Drought is one of the factors limiting castor bean growth. The drought resistance mechanisms of castor bean have become a research focus. In this study, we used castor germinating embryos as experimental materials, and screened genes related to drought resistance through physiological measurements, proteomics and metabolomics joint analysis; castor drought-related genes were subjected to transient silencing expression analysis in castor leaves to validate their drought-resistant functions, and heterologous overexpression and backward complementary expression in Arabidopsis thaliana, and analysed the mechanism of the genes' response to the participation of Arabidopsis thaliana in drought-resistance.Three drought tolerance-related genes, RcECP 63, RcDDX 31 and RcA/HD1, were obtained by screening and analysis, and transient silencing of expression in castor leaves further verified that these three genes corresponded to drought stress, and heterologous overexpression and back-complementary expression of the three genes in Arabidopsis thaliana revealed that the function of these three genes in drought stress response.In this study, three drought tolerance related genes, RcECP 63, RcDDX 31 and RcA/HD1, were screened and analysed for gene function, which were found to be responsive to drought stress and to function in drought stress, laying the foundation for the study of drought tolerance mechanism in castor bean.

R2* mapping and reduced field-of-view diffusion-weighted imaging for preoperative assessment of nonenlarged lymph node metastasis in rectal cancer.

The aim of the current study is to investigate the diagnostic value of R2* mapping versus reduced field-of-view diffusion-weighted imaging (rDWI) of the primary lesion of rectal cancer for preoperative prediction of nonenlarged lymph node metastasis (NLNM). Eighty-one patients with pathologically confirmed rectal cancer underwent preoperative R2* mapping and rDWI sequences before total mesorectal excisions and accompanying regional lymph node dissections. Two radiologists independently performed whole-tumor measurements of R2* and apparent diffusion coefficient (ADC) parameters on primary lesions of rectal cancer. Patients were divided into positive (NLNM+) and negative (NLNM-) groups based on their pathological analysis. The tumor location, maximum diameter of the tumor, and maximum short diameter of the lymph node were assessed. R2* and ADC, pT stage, tumor grade, status of mesorectal fascia, and extramural vascular invasion were also studied for their potential relationships with NLNM using multivariate logistic regression analysis. The NLNM+ group had significantly higher R2* (43.56 ± 8.43 vs. 33.87 ± 9.57, p < 0.001) and lower ADC (1.00 ± 0.13 vs. 1.06 ± 0.22, p = 0.036) than the NLNM- group. R2* and ADC were correlated to lymph node metastasis (r = 0.510, p < 0.001 for R2*; r = -0.235, p = 0.035 for ADC). R2* and ADC showed good and moderate diagnostic abilities in the assessment of NLNM status with corresponding area-under-the-curve values of 0.795 and 0.636. R2* provided a significantly better diagnostic performance compared with ADC for the prediction of NLNM status (z = 1.962, p = 0.0498). The multivariate logistic regression analysis demonstrated that R2* was a compelling factor of lymph node metastasis (odds ratio = 56.485, 95% confidence interval: 5.759-554.013; p = 0.001). R2* mapping had significantly higher diagnostic performance than rDWI from the primary tumor of rectal cancer in the prediction of NLNM status.

Aluminum-based plasmonic metasurface for computational spectrometry with full coverage of visible light.

Reconstructive spectrometers/spectral cameras have immense potential for portable applications in various fields, including environmental monitoring, biomedical research and diagnostics, and agriculture and food safety. However, the performance of these spectrometers/spectral cameras is severely limited by the operational bandwidth, spectral diversity, and angle sensitivity of the spectral modulation devices. In this work, we propose a compact spectrometer based on plasmonic metasurfaces that operate across the entire visible wavelength range, covering wavelengths from 400 to 750 nm. We experimentally demonstrate the effective spectral reconstruction achieved by the designed metasurface spectrometer, exhibiting angle tolerance to the incident light within the range of ± 12°. Our results highlight the potential for constructing broadband, large field-of-view hyperspectral cameras.

Basal NAD(H) redox state permits hydrogen peroxide-induced mesenteric artery dilatation.

Smooth muscle voltage-gated K+ (Kv) channels in resistance arteries control vascular tone and contribute to the coupling of blood flow with local metabolic activity. Members of the Kv1 family are expressed in vascular smooth muscle and are modulated upon physiological elevation of local metabolites, including the glycolytic end-product l-lactate and superoxide-derived hydrogen peroxide (H2 O2 ). Here, we show that l-lactate elicits vasodilatation of small-diameter mesenteric arteries in a mechanism that requires lactate dehydrogenase (LDH). Using the inside-out configuration of the patch clamp technique, we show that increases in NADH that reflect LDH-mediated conversion of l-lactate to pyruvate directly stimulate the activity of single Kv1 channels and significantly enhance the sensitivity of Kv1 activity to H2 O2 . Consistent with these findings, H2 O2 -evoked vasodilatation was significantly greater in the presence of 10 mM l-lactate relative to lactate-free conditions, yet was abolished in the presence of 10 mM pyruvate, which shifts the LDH reaction towards the generation of NAD+ . Moreover, the enhancement of H2 O2 -induced vasodilatation was abolished in arteries from double transgenic mice with selective overexpression of the intracellular Kvß1.1 subunit in smooth muscle cells. Together, our results indicate that the Kvß complex of native vascular Kv1 channels serves as a nodal effector for multiple redox signals to precisely control channel activity and vascular tone in the face of dynamic tissue-derived metabolic cues. KEY POINTS: Vasodilatation of mesenteric arteries by elevated external l-lactate requires its conversion by lactate dehydrogenase. Application of either NADH or H2 O2 potentiates single Kv channel currents in excised membrane patches from mesenteric artery smooth muscle cells. The binding of NADH enhances the stimulatory effects of H2 O2 on single Kv channel activity. The vasodilatory response to H2 O2 is differentially modified upon elevation of external l-lactate or pyruvate. The presence of l-lactate enhances the vasodilatory response to H2 O2 via the Kvß subunit complex in smooth muscle.

ANXA2 and Rac1 negatively regulates autophagy and osteogenic differentiation in osteosarcoma cells to confer CDDP resistance.

BACKGROUND: Cisplatin (CDDP) is a mainstay chemotherapeutic agent for OS treatment, but drug resistance has become a hurdle to limit its clinical effect. Autophagy plays an important role in CDDP resistance in OS, and in the present study we explored the role of ANXA2 and Rac1 in dictating CDDP sensitivity in OS cells. METHODS: ANXA2 and Rac1 expression levels were examined by Western blot and autophagy induction was detected by transmission electron miscroscope (TEM) in the clinical samples and OS cell lines. CDDP resistant cells were established by exposing OS cells to increasing doses of CDDP. The effects of ANXA2 and Rac1 knockdown on CDDP sensitivity were evaluated in the cell and animal models. RESULTS: Reduced autophagy was associated with the increased expression of ANXA2 and Rac1 in CDDP resistant OS tumor samples and cells. Autophagy suppression promoted CDDP resistance and inducing autophagy re-sensitized the resistant cells to CDDP treatment in vitro and in vivo. Further, knocking down ANXA2 or Rac1 re-activated autophagy and attenuated CDDP resistance in OS cells. We further demonstrated that CDDP resistant OS cells displayed a poorer osteogenic differentiation state when compared to the parental cell lines, which was significantly reversed by autophagy re-activation and ANXA2 or Rac1 silencing. CONCLUSION: Our findings revealed a complicated interplay of ANXA2/Rac1, autophagy induction, and osteogenic differentiation in dictating CDDP resistance in OS cells, suggesting ANXA2 and Rac1 as promising targets to modulate autophagy and overcome CDDP resistance in OS cells.

Image distortion by ambiguous multiple-photon detections in a superconducting nanowire single-photon imager and the correction method.

Scaling up superconducting nanowire single-photon detectors (SNSPDs) into a large array for imaging applications is the current pursuit. Although various readout architectures have been proposed, they cannot resolve multiple-photon detections (MPDs) currently, which limits the operation of the SNSPD arrays at high photon flux. In this study, we focused on the readout ambiguity of a superconducting nanowire single-photon imager applying time-of-flight multiplexing readout. The results showed that image distortion depended on both the incident photon flux and the imaging object. By extracting multiple-photon detections on idle pixels, which were virtual because of the incorrect mapping from the ambiguous readout, a correction method was proposed. An improvement factor of 1.3~9.3 at a photon flux of µ = 5 photon/pulse was obtained, which indicated that joint development of the pixel design and restoration algorithm could compensate for the readout ambiguity and increase the dynamic range.

Myocardial Blood Flow Control by Oxygen Sensing Vascular Kvß Proteins.

[Figure: see text].

Volumetric visceral fat machine learning phenotype on CT for differential diagnosis of inflammatory bowel disease.

OBJECTIVES: To investigate whether volumetric visceral adipose tissue (VAT) features extracted using radiomics and three-dimensional convolutional neural network (3D-CNN) approach are effective in differentiating Crohn's disease (CD) and ulcerative colitis (UC). METHODS: This retrospective study enrolled 316 patients (mean age, 36.25 ± 13.58 [standard deviation]; 219 men) with confirmed diagnosis of CD and UC who underwent CT enterography between 2012 and 2021. Volumetric VAT was semi-automatically segmented on the arterial phase images. Radiomics analysis was performed using principal component analysis (PCA) and the least absolute shrinkage and selection operator (LASSO) logistic regression algorithm. We developed a 3D-CNN model using VAT imaging data from the training cohort. Clinical covariates including age, sex, modified body mass index, and disease duration that impact VAT were added to the machine learning model for adjustment. The model's performance was evaluated on the testing cohort separating from the model's development process by its discrimination and clinical utility. RESULTS: Volumetric VAT radiomics analysis with LASSO had the highest AUC value of 0.717 (95% CI, 0.614-0.820), though difference of diagnostic performance among the 3D-CNN model (AUC = 0.693; 95% CI, 0.587-0.798) and radiomics analysis with PCA (AUC = 0.662; 95% CI, 0.548-0.776) and LASSO have not reached statistical significance (all p > 0.05). The radiomics score was higher in UC than in CD on the testing cohort (mean ± SD, UC 0.29 ± 1.05 versus CD -0.60 ± 1.25; p < 0.001). The LASSO model with adjustment of clinical covariates reached an AUC of 0.775 (95%CI, 0.683-0.868). CONCLUSION: The developed volumetric VAT-based radiomics and 3D-CNN models provided comparable and effective performance for the characterization of CD from UC. KEY POINTS: • High-output feature data extracted from volumetric visceral adipose tissue on CT enterography had an effective diagnostic performance for differentiating Crohn's disease from ulcerative colitis. • With adjustment of clinical covariates that cause difference in volumetric visceral adipose tissue, adjusted clinical machine learning model reached stronger performance when distinguishing Crohn's disease patients from ulcerative colitis patients.

Bone marrow mesenchymal stem cell-derived exosomal miR-34c-5p ameliorates RIF by inhibiting the core fucosylation of multiple proteins.

Renal interstitial fibrosis (RIF) is an incurable pathological lesion in chronic kidney diseases. Pericyte activation is the major pathological characteristic of RIF. Fibroblast and macrophage activation are also involved in RIF. Studies have revealed that core fucosylation (CF), an important post-translational modification of proteins, plays a key role in pericyte activation and RIF by regulating multiple profibrotic signaling pathways as a hub-like target. Here, we reveal that mesenchymal stem cell (MSC)-derived exosomes reside specifically in the injured kidney and deliver microRNA (miR)-34c-5p to reduce cellular activation and RIF by inhibiting CF. Furthermore, we showed that the CD81-epidermal growth factor receptor (EGFR) ligand-receptor complex aids the entry of exosomal miR-34c-5p into pericytes, fibroblasts, and macrophages. Altogether, our findings reveal a novel role of MSC-derived exosomes in inhibiting multicellular activation via CF and provide a potential intervention strategy for renal fibrosis.

On-Chip Compressive Sensing with a Single-Photon Avalanche Diode Array.

Single-photon avalanche diodes (SPADs) are novel image sensors that record photons at extremely high sensitivity. To reduce both the required sensor area for readout circuits and the data throughput for SPAD array, in this paper, we propose a snapshot compressive sensing single-photon avalanche diode (CS-SPAD) sensor which can realize on-chip snapshot-type spatial compressive imaging in a compact form. Taking advantage of the digital counting nature of SPAD sensing, we propose to design the circuit connection between the sensing unit and the readout electronics for compressive sensing. To process the compressively sensed data, we propose a convolution neural-network-based algorithm dubbed CSSPAD-Net which could realize both high-fidelity scene reconstruction and classification. To demonstrate our method, we design and fabricate a CS-SPAD sensor chip, build a prototype imaging system, and demonstrate the proposed on-chip snapshot compressive sensing method on the MINIST dataset and real handwritten digital images, with both qualitative and quantitative results.

Multiparametric MRI-Based Radiomic Signature for Preoperative Evaluation of Overall Survival in Intrahepatic Cholangiocarcinoma After Partial Hepatectomy.

BACKGROUND: The clinical outcomes of patients with intrahepatic cholangiocarcinoma (ICC) after partial hepatectomy remain suboptimal. Identifying patients with poor outcomes before surgery is urgently required. PURPOSE: To develop a multiparametric magnetic resonance imaging (MRI)-based radiomic signature to evaluate overall survival (OS) preoperatively and to investigate its incremental value for disease stratification. STUDY TYPE: Retrospective. SUBJECTS: One hundred and sixty-three patients with pathologically defined ICC, divided into training (N = 115) and validation sets (N = 48). SEQUENCE: Three-dimensional T1-weighted gradient-echo sequence with and without contrast agent, T2-weighted fast spin-echo sequence, and diffusion-weighted imaging with single-shot echo-planar sequence at 1.5 T or 3.0 T. ASSESSMENT: OS was defined as the time from the date of surgery to death or last contact. The radiomic signature was built based on the least absolute shrinkage and selection operator regression model. A clinicopathologic-radiographic (CPR) model and a combined model integrating radiomic signature with CPR factors were developed with multivariable Cox regression models. STATISTICAL TESTS: Harrell's concordance index (C-index) was used to compare the discrimination of different models. Net reclassification index (NRI) and integrated discrimination improvement (IDI) were used to quantify the improvement of prognostic accuracy after adding radiomic signature. RESULTS: The high-risk patients of death defined by the radiomic signature showed significantly lower OS compared with low-risk patients in validation set (3-year OS 17.1% vs. 56.4%, P < 0.001). Integrating radiomic signature into tumor, node, and metastasis (TNM) staging system significantly improved the prognostic accuracy compared with TNM stage alone (validation set C-index 0.745 vs. 0.649, P = 0.039, NRI improvement 39.9%-43.8%, IDI improvement 16.1%-19.4%). The radiomic signature showed no significant difference of C-index with postoperative CPR model (validation set, 0.698 vs. 0.674, P = 0.752). Incorporating the radiomic signature into CPR model significantly improved prognostic accuracy (NRI improvement 32.5%-34.3%, IDI improvement 8.1%-12.9%). DATA CONCLUSION: Multiparametric MRI-based radiomic signature is a potential biomarker for preoperative prognostic evaluation of ICC patients. LEVEL OF EVIDENCE: 4 TECHNICAL EFFICACY: Stage 4.

A sensing system constructed by combining a structure-switchable molecular beacon with nicking-enhanced rolling circle amplification for highly sensitive miRNA detection.

The detection of disease-related biomarkers, including microRNA (miRNA), is of crucial importance in reducing the morbidity and mortality of cancer. Thus, there is a great desire to develop an efficient and simple sensing method to fulfill the detection of miRNAs. In this study, a novel amplification assay strategy is demonstrated for the highly sensitive detection of miRNA-21 by combining a structure-switchable molecular beacon with nicking-enhanced rolling circle amplification (SMB-NRCA). A circular padlock probe (CPP) contains a target recognition sequence, two binding sites for nicking endonuclease and three hybridization sites for SMBs. miRNA-21 can hybridize with the CPP and act as polymerization primer that initiates the rolling circle amplification (RCA) reaction and two different nicking-mediated RCA processes, releasing a large amount of SMBs and leading to a significantly amplified fluorescence signal originating from the restoration of pre-quenched fluorescence via their structural switching. Via the signal amplification based on the combination of RCA, nicking and SDA, this assay system can quantitatively detect miRNA-21 in a linear change of three orders of magnitude with a detection limit of 1 pM. The assay specificity is very high so that there is no interference from coexisting miRNAs. Moreover, the sensing system possesses ideal anti-interference ability in complicated milieux such as human serum. The novel sensing strategy shows tremendous prospects for application in tumor diagnosis and clinical therapy guidance.

Role of Cholinergic Anti-Inflammatory Pathway in Protecting Sepsis-Induced Acute Lung Injury through Regulation of the Conventional Dendritic Cells.

BACKGROUND: The cholinergic anti-inflammatory pathway connects the immune response system and the nervous system via the vagus nerve. The key regulatory receptor is the α7-subtype of the nicotinic acetylcholine receptor (α7nAChR). Cholinergic anti-inflammatory pathway has been proved to be effective in suppressing the inflammation responses in acute lung injury (ALI). Dendritic cells (DCs), the important antigen-presenting cells, also express the α7nAChR. Past studies have indicated that reducing the quantity of mature conventional DCs and inhibiting the maturation of pulmonary DCs may prove effective for the treatment of ALI. However, the effects of cholinergic anti-inflammatory pathway on maturation, function, and quantity of DCs and conventional DCs in ALI remain unclear. OBJECTIVE: It was hypothesized that cholinergic anti-inflammatory pathway may inhibit the inflammatory response of ALI by regulating maturation, phenotype, and quantity of DCs and conventional DCs. METHODS: GTS-21 (GTS-21 dihydrochloride), an α7nAchR agonist, was prophylactically administered in sepsis-induced ALI mouse model and LPS-primed bone marrow-derived dendritic cells. The effects of GTS-21 were observed with respect to maturation, phenotype, and quantity of DCs, conventional DCs, and conventional DCs2 (type 2 conventional DCs) and the release of DC-related proinflammatory cytokines in vivo and in vitro. RESULTS: The results of the present study revealed that GTS-21 treatment decreased the maturation of DCs and the production of DC-related proinflammatory cytokines in vitro and in sepsis-induced ALI mouse model; it reduced the quantity of CD11c+MHCII+ conventional DCs and CD11c+CD11b+ conventional DCs2 in vivo experiment. CONCLUSIONS: Cholinergic anti-inflammatory pathway contributes to the reduction in the inflammatory response in ALI by regulating maturation, phenotype, and quantity of DCs, conventional DCs, and conventional DCs2.

Effect of g-C3N4 on biodiversity and structure of bacterial community in sediment of Xiangjiang River under tetracycline pressure.

Photocatalysts have been widely prepared and used in wastewater treatment. Although the influence of photocatalyst application on survival and activity of organisms has been examined, its impact on composition and diversity of microbial community is not fully understood. In this study, the impact of photocatalyst g-C3N4 (Graphitic carbon nitride) on microbial communities in riverbed sediments polluted by antibiotic tetracycline (TC) was investigated. The sediment samples collected from the Xiangjiang River of China were exposed to different concentrations of TC, g-C3N4 and TC/g-C3N4 and the bacterial community were analyzed by Illumina sequencing. The results showed that the dominant bacterial phyla were Acidobacteriota, Proteobacteria, Actinobacteriota, and Chloroflexi in the study site. When compared to the control treatments, the application of TC, g-C3N4 and TC/g-C3N4 exhibited distinguishable effects on bacterial community structure in sediments. The presence of TC had greater influence on bacterial composition, while g-C3N4 and TC/g-C3N4 had less influence on bacteria. The diversity and richness of microorganisms in sediment increased under g-C3N4 application and reached the highest values when g-C3N4 was 75 mg/kg. The photocatalyst g-C3N4 restored bacterial community diversity affected by TC, reduced the TC residues in aquatic environment, and eliminated the side effects of TC application in sediments. Our study indicated that g-C3N4 was an environmentally friendly photocatalyst with lightly negative effects on microbial community in riverbed sediments, and could be used for effective remediation of TC-contaminated environments.

ACPNet: A Deep Learning Network to Identify Anticancer Peptides by Hybrid Sequence Information.

Cancer is one of the most dangerous threats to human health. One of the issues is drug resistance action, which leads to side effects after drug treatment. Numerous therapies have endeavored to relieve the drug resistance action. Recently, anticancer peptides could be a novel and promising anticancer candidate, which can inhibit tumor cell proliferation, migration, and suppress the formation of tumor blood vessels, with fewer side effects. However, it is costly, laborious and time consuming to identify anticancer peptides by biological experiments with a high throughput. Therefore, accurately identifying anti-cancer peptides becomes a key and indispensable step for anticancer peptides therapy. Although some existing computer methods have been developed to predict anticancer peptides, the accuracy still needs to be improved. Thus, in this study, we propose a deep learning-based model, called ACPNet, to distinguish anticancer peptides from non-anticancer peptides (non-ACPs). ACPNet employs three different types of peptide sequence information, peptide physicochemical properties and auto-encoding features linking the training process. ACPNet is a hybrid deep learning network, which fuses fully connected networks and recurrent neural networks. The comparison with other existing methods on ACPs82 datasets shows that ACPNet not only achieves the improvement of 1.2% Accuracy, 2.0% F1-score, and 7.2% Recall, but also gets balanced performance on the Matthews correlation coefficient. Meanwhile, ACPNet is verified on an independent dataset, with 20 proven anticancer peptides, and only one anticancer peptide is predicted as non-ACPs. The comparison and independent validation experiment indicate that ACPNet can accurately distinguish anticancer peptides from non-ACPs.

EGFAFS: A Novel Feature Selection Algorithm Based on Explosion Gravitation Field Algorithm.

Feature selection (FS) is a vital step in data mining and machine learning, especially for analyzing the data in high-dimensional feature space. Gene expression data usually consist of a few samples characterized by high-dimensional feature space. As a result, they are not suitable to be processed by simple methods, such as the filter-based method. In this study, we propose a novel feature selection algorithm based on the Explosion Gravitation Field Algorithm, called EGFAFS. To reduce the dimensions of the feature space to acceptable dimensions, we constructed a recommended feature pool by a series of Random Forests based on the Gini index. Furthermore, by paying more attention to the features in the recommended feature pool, we can find the best subset more efficiently. To verify the performance of EGFAFS for FS, we tested EGFAFS on eight gene expression datasets compared with four heuristic-based FS methods (GA, PSO, SA, and DE) and four other FS methods (Boruta, HSICLasso, DNN-FS, and EGSG). The results show that EGFAFS has better performance for FS on gene expression data in terms of evaluation metrics, having more than the other eight FS algorithms. The genes selected by EGFAGS play an essential role in the differential co-expression network and some biological functions further demonstrate the success of EGFAFS for solving FS problems on gene expression data.

Detection and structural characterization of the metabolites of dihydroresveratrol in rats by liquid chromatography coupled to high-resolution tandem mass spectrometry.

RATIONALE: Dihydroresveratrol has been demonstrated to possess a wide spectrum of bioactivities, such as anti-oxidant and anti-inflammatory effects. The aim of the present study was to investigate the metabolic profiles of dihydroresveratrol in rats. METHODS: The in vitro metabolism was elucidated by incubating dihydroresveratrol with rat hepatocytes for 2 h at 37°C. For in vivo metabolism, dihydroresveratrol was orally administered to rats at a single dose of 50 mg/kg and the resulting biliary and urinary samples were collected. All the samples were analyzed by liquid chromatography combined with electrospray ionization high-resolution mass spectrometry. The structures of the metabolites were proposed based on their accurate masses and their MS/MS product ions. RESULTS: A total of 16 metabolites including three phase I metabolites and 13 phase II metabolites were detected and structurally proposed. Among these metabolites, M6 and M14 were unambiguously identified as 3'-hydroxylresveratrol and resveratrol, respectively, using reference standards. Dihydroresveratrol was mainly metabolized into resveratrol (M14) and a glucuronide conjugate (M12), which were excreted into urine and bile as the major metabolites. CONCLUSIONS: The metabolic pathways of dihydroresveratrol involved hydroxylation, dehydrogenation, glucuronidation, glutathione (GSH) conjugation and methylation. The present study provided useful information with regard to the metabolic profiles of dihydroresveratrol in rats.

ATP/P2X7r axis mediates the pathological process of allergic asthma by inducing M2 polarization of alveolar macrophages.

Recent studies revealed that macrophages are polarized towards the M2 phenotype in an ovalbumin (OVA)-induced asthmatic model. Alveolar macrophages (AMs) are immune barriers in alveoli to various pathogens in the respiratory tract; AMs suppress Th2 cell proliferation, inhibit interleukin (IL)-4, IL-5, and IL-13 secretion, and protect against airway hyperresponsiveness in allergic asthma. However, the polarization status and effects of different types of AMs in the pathogenesis of asthma are not known. ATP/P2X7r, expressed mainly on macrophages and dendritic cells, is associated with acute and chronic asthmatic airway inflammation and Th2 immune responses in mice and humans and functions by activating the NLRP3 inflammasome complex and inducing proinflammatory cytokine release (IL-1ß and IL-18). Therefore, we evaluated the association between the ATP/P2X7r axis and different types of AMs in the pathology of allergic asthma. A murine AM-depleted asthma model was established by administration of clodronate-encapsulated liposomes, and M1-or M2-AMs were adoptively transferred to confirm the effects of different AMs in allergic asthma. Brilliant Blue G and BzATP were administered to OVA/HDM-induced mice in vivo. Lipopolysaccharide + OVA, ATP, Brilliant Blue G, and BzATP were used to stimulate AMs isolated from control and asthmatic mice. We found that selective depletion of AMs aggravated lung inflammation in asthmatic mice. Further, M2-type AMs may play a key role in mediating asthmatic inflammatory responses via the adoptive transfer of M2-type AMs to AM-depleted asthmatic mice, and the phenotype of AMs differentiated to M2 type in asthma. P2X7r expression in M2-type AMs was higher than that in M1-type AMs. Activating P2X7r induced polarization of M2-type AMs and inhibited polarization of M1-type AMs, while blockage of P2X7r had the opposite effect. The ATP/P2X7r axis may participate in the pathogenesis of asthma by mediating the M2-type AM polarization.