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Abstract Natural antimicrobial peptides (AMPs) and enzymes (AMEs) are promising non-antibiotic candidates against antimicrobial resistance but suffer from low efficiency and poor stability. Here, we develop peptide nanozymes which mimic the mode of action of AMPs and AMEs through de novo design and peptide assembly. Through modelling a minimal building block of IHIHICI is proposed by combining critical amino acids in AMPs and AMEs and hydrophobic isoleucine to conduct assembly. Experimental validations reveal that IHIHICI assemble into helical β-sheet nanotubes with acetate modulation and perform phospholipase C-like and peroxidase-like activities with Ni coordination, demonstrating high thermostability and resistance to enzymatic degradation. The assembled nanotubes demonstrate cascade antifungal actions including outer mannan docking, wall disruption, lipid peroxidation and subsequent ferroptotic death, synergistically killing >90% Candida albicans within 10 min on disinfection pad. These findings demonstrate an effective de novo design strategy for developing materials with multi-antimicrobial mode of actions.

The partner of NOB1 homolog (PNO1) is an RNA-binding protein that participates in ribosome biogenesis and protein modification. The functions of this molecule are largely unknown in cancers, particularly breast cancer. We employed bioinformatics methods to probe the putative oncogenic functions of PNO1 based on expression profiles and clinical data from the cancer genome atlas (TCGA), genotype-tissue expression project (GTEx), human protein atlas (HPA), cancer cell line encyclopedia (CCLE), UALCAN, drug sensitivity in cancer (GDSC) and UCSC XENA databases. Our analyses revealed that PNO1 was overexpressed in 31 malignancies, which excluded kidney chromophobe (KICH) and acute myeloid leukemia (LAML). Prognostic assessments have demonstrated that high PNO1 expression was significantly correlated with poor overall and disease-specific survival in various cancers. The promoter methylation level of PNO1 is significantly decreased in breast invasive carcinoma (BRCA), head and neck squamous cell carcinoma (HNSC), kidney renal papillary cell carcinoma (KIRP), prostate adenocarcinoma (PRAD), thyroid carcinoma (THCA) and uterine corpus endometrial carcinoma (UCEC). Furthermore, inhibition of PNO1 decreased the viability, migration and invasion of breast cancer cells, and these results were confirmed by mouse xenograft models of breast cancer. In addition, we discovered that tumor microenvironment (TME), immune infiltration, and chemotherapy sensitivity were influenced by PNO1 expression. Concordantly, our analyses revealed a significant positive correlation between PNO1 and programmed cell death ligand 1 (PD-L1) expression across breast carcinoma samples. In conclusion, these findings indicate that PNO1 could act as a promising prognostic biomarker and adjunct diagnostic indicator, because it affects tumor growth and invasion. Our study offers valuable new perspectives on the oncogenic role of PNO1 in various types of cancers.

Metformin shows promise in breast cancer prevention, but its underlying mechanisms remain unclear. This study investigated the impact of metformin on the repopulation dynamics of mammary epithelial cells (MECs) and the signaling pathways in non-tumorigenic FVB/N mice. This study aimed to enhance our understanding of the role of metformin in reducing the susceptibility of MECs in premalignant tissues to oncogenic factors. In this study, female mice were administered 200 mg/kg/day of metformin via intraperitoneal (i.p.) injection from 8 to 18 weeks of age. After this treatment period, morphogenesis, flow cytometry, analyses of MEC stemness, and RNA sequencing were performed. The study findings indicated that metformin treatment in adult mice reduced mammary gland proliferation, as demonstrated by decreased Ki67+ cells and lateral bud formation. Additionally, metformin significantly reduced both basal and mammary repopulating unit subpopulations, indicating an impact on mammary epithelial cell repopulation. Mammosphere, colony-forming cell, and 3D culture assays revealed that metformin adversely affected mammary epithelial cell stemness. Furthermore, metformin downregulated signaling in key pathways including AMPK/mTOR, MAPK/Erk, PI3K/Akt, and ER, which contribute to its inhibitory effects on mammary proliferation and stemness. Transcriptome analysis with RNA sequencing indicated that metformin induced significant downregulation of genes involved in multiple critical pathways. KEGG-based pathway analysis indicated that genes in PI3K/Akt, focal adhesion, ECM-receptor, small cell lung cancer and immune-modulation pathways were among the top groups of differentially regulated genes. In summary, our research demonstrates that metformin inhibits MEC proliferation and stemness, accompanied by the downregulation of intrinsic signaling. These insights suggest that the regulatory effects of metformin on premalignant mammary tissues could potentially delay or prevent the onset of breast cancer, offering a promising avenue for developing new preventive strategies.

Abstract The Gabija system is a newly discovered bacterial immune system that consists of GajA and GajB. Here we report the cryo-EM structure of the Gabija complex from Bacillus cereus VD045 at 3.6 Å, which provides the direct evidence of interactions between GajA and GajB. The Gabija complex is an octameric ring structure with four GajA and four GajB. GajA is an OLD nucleases family protein, while GajB belongs to the SF1 helicases. The Gabija complex has sequence-specific DNA nuclease activity and prefers circular rather than linear DNA as substrate, its activity is more sensitive to concentrations change of nucleotides compared to GajA alone. Our data suggest a mechanism of Gabija immunity: the nuclease activity of Gabija complex is inhibited under physiological conditions, while it is activated by depletion of NTP and dNTP upon the replication and transcription of invading phages and cleave the circular DNA to prevent phage DNA replication.

Core 1 β 1,3-galactosyltransferase 1 (C1GALT1) acts as an important glycosyltransferase in the occurrence and development of tumor glycosylation. However, the regulatory mechanisms of C1GALT1 in thyroid cancer (TC) is still unclear. In this study, we discovered that the expression level of C1GALT1 was significantly increased in thyroid adenocarcinoma tissues and cell lines (p

Abstract Amyloid-like assembly is not only associated with pathological events, but also leads to the development of novel nanomaterials with unique properties. Herein, using Fmoc diphenylalanine peptide (Fmoc–F–F) as a minimalistic model, we found that histidine can modulate the assembly behavior of Fmoc–F–F and induce enzyme-like catalysis. Specifically, the presence of histidine rearranges the β structure of Fmoc–F–F to assemble nanofilaments, resulting in the formation of active site to mimic peroxidase-like activity that catalyzes ROS generation. A similar catalytic property is also observed in Aβ assembled filaments, which is correlated with the spatial proximity between intermolecular histidine and F-F. Notably, the assembled Aβ filaments are able to induce cellular ROS elevation and damage neuron cells, providing an insight into the pathological relationship between Aβ aggregation and Alzheimer’s disease. These findings highlight the potential of histidine as a modulator in amyloid-like assembly of peptide nanomaterials exerting enzyme-like catalysis.

Abstract Background Oligodendroglioma is known for its relatively better prognosis and responsiveness to radiotherapy and chemotherapy. However, little is known about the evolution of genetic changes as oligodendroglioma progresses. Methods In this study, we evaluated gene evolution invivo during tumor progression based on deep whole‐genome sequencing data (ctDNA). We analyzed longitudinal genomic data from six patients during tumor evolution, of which five patients developed distant recurrence. Results Whole‐exome sequencing demonstrated that the rate of shared mutations between the primary and recurrent samples was relatively low. In two cases, even well‐known major driver mutations in CIC and FUBP1 that were detected in primary tumors were not detected in the relapse samples. Among these cases, two patients had a conversion from the IDH mutation in the originating state to the IDH1 wild state during the process of gene evolution under chemotherapy treatment, indicating that the cell phenotype and genetic characteristics of oligodendroglioma may change during tumor evolution. Two patients received long‐term temozolomide (TMZ) treatment before the operation, and we found that recurrence tumors harbored mutations in the PI3K/AKT and Sonic hedgehog (SHh) signaling pathways. Hypermutation occurred with mutations in MMR genes in one patient, contributing to the rapid progression of the tumor. Conclusion Oligodendroglioma displayed great spatial and temporal heterogeneity during tumor evolution. The PI3K/AKT and SHh signaling pathways may play an important role in promoting treatment resistance and distant relapse during oligodendroglioma evolution. In addition, there was a tendency to increase the degree of tumor malignancy during evolution. Distant recurrence may be a later event duringoligodendroglioma progression. ClinicalTrials.gov, Identifier: NCT05512325.

Alzheimer’s disease (AD) is an irreversible neurodegenerative disease with a high prevalence in the elderly population over 65 years of age. Intervention in the early stages of AD is of great significance to alleviate the symptoms. Recent advances in deep learning have shown extreme advantages in computer-aided diagnosis of AD. However, most studies only focus on extracting features from slices in specific directions or whole brain images, ignoring the complementarity between features from different angles. To overcome the above problem, attention-based multi-view slice fusion (AMSF) is proposed for accurate early diagnosis of AD. It adopts the fusion of three-dimensional (3D) global features with multi-view 2D slice features by using an attention mechanism to guide the fusion of slice features for each view, to generate a comprehensive representation of the MRI images for classification. The experiments on the public dataset demonstrate that AMSF achieves 94.3% accuracy with 1.6–7.1% higher than other previous promising methods. It indicates that the better solution for AD early diagnosis depends not only on the large scale of the dataset but also on the organic combination of feature construction strategy and deep neural networks.

Summary: The evolutionary trajectories of genomic alterations underlying distant recurrence in glioma remain largely unknown. To elucidate glioma evolution, we analyzed the evolutionary trajectories of matched pairs of primary tumors and relapse tumors or tumor in situ fluid (TISF) based on deep whole-genome sequencing data (ctDNA). We found that MMR gene mutations occurred in the late stage in IDH-mutant glioma during gene evolution, which activates multiple signaling pathways and significantly increases distant recurrence potential. The proneural subtype characterized by PDGFRA amplification was likely prone to hypermutation and distant recurrence following treatment. The classical and mesenchymal subtypes tended to progress locally through subclonal reconstruction, trunk genes transformation, and convergence evolution. EGFR and NOTCH signaling pathways and CDNK2A mutation play an important role in promoting tumor local progression. Glioma subtypes displayed distinct preferred evolutionary patterns. ClinicalTrials.gov, NCT05512325.

In order to solve the problem that it is difficult for a single sensor to accurately characterize the running state of rotating bearings under complex working conditions, this paper proposes a data-level fusion method based on multi-source isomorphic sensors to monitor spindle bearings. First, new vibration signals in the X,Y,Z direction were obtained through the process of decomposing, de-noise, and reconstructing. Second, the PCA algorithm was used to select the time-domain and frequency-domain features of the vibration signals, construct the feature matrix, and perform dimensionality reduction in the feature matrix. Finally, the entropy weight method was introduced to obtain the initial weights of the three directions as the inputs of the adaptive function. The chaotic particle swarm optimization algorithm proposed in this paper helps particles jump out of the local optimum. Chaotic mapping is used to initialize the velocity and position of the particles, which calculates globally optimal weights in three directions. In order to extract bearing signal features more accurately and efficiently, a DenseNet and Transformer (DAT) feature extraction model is proposed to deal with the complex changes and noise interference of bearing signals. Through the open data set of Jiangnan University and the data collected by our own experimental platform, the maximum accuracy of the DAT model was verified to be 100%.

IntroductionThe impact of different types of reconstruction, including tissue reconstruction, implant reconstruction and combined reconstruction, on patient survival were not illustrated completely. We tried to investigate the impact of patient survival between different types of reconstruction.MethodsWe enrolled 6271 patients with tumors in the central and nipple portion of breast cancer from the Surveillance, Epidemiology, and End Results database. Factors associated with survival were identified by Cox regression analyses. The mortality rates per 1,000 person-years were calculated and compared. Survival curves were produced by Kaplan-Meier analyses using log-rank tests and cox proportional hazards regression quantified the risk of survival.ResultsReconstructive types, region, insurance, race, marial status, grade, stage, ER status, PR status, HER-2 status and chemotherapy were significant prognostic factors associated with breast cancer-specific survival. The breast cancer mortality rates per 1,000 person-years for patients with tissue, implant and combined group were 26.01,21.54 and 19.83 which showed a downward trend. The HR of implant and combined reconstruction adjusted for demographic, pathological, and therapeutic data was 0.82 (95% CI: 0.67-1.00, p=0.052) and 0.73(95% CI:0.55-0.97, p=0.03) compared with tissue reconstruction.ConclusionBreast cancer-related mortality between implant reconstruction and autologous tissue reconstruction showed no significantly different, but the risk of BCSS of compound reconstruction was lower than tissue reconstruction.

Abstract Background Cervical cancer (CC) is one of the most common gynecological tumors that threatens women's health and lives. Aberrant expression of PIWI-interacting RNA (piRNA) is closely related with a range of cancers and can serve as a tumor promoter or suppressor in proliferation, migration and invasion. In this study, the aim was not only to discover differential expression of piRNA in CC tissue (CC cells) and normal cervical tissue (normal cervical epithelium cells), but also to investigate the biological function and action mechanism of piRNA in CC. Methods The DESeq2 approach was used to estimate fold change in piRNA between CC tissue and normal cervical tissue. The relative expressions of piRNAs (piRNA-20657, piRNA-20497, piRNA-14633 and piRNA-13350) and RNA m6A methyltransferases/demethylases were detected using RT-qPCR. After intervention with piRNA-14633 and METTL14 expression, the viability of CaSki cells and SiHa cells was detected by CCK8. CC cell proliferation was detected by colony formation assay. Apoptosis rate and cell cycle were detected by flow cytometry. Transwell assay was performed to detect cell migration and invasion. EpiQuik m6A RNA Methylation Quantification Kit was used to evaluate m6A RNA methylation levels. Expression of methyltransferase-like protein 14 (METTL14), PIWIL-proteins and CYP1B1 were detected by RT-qPCR and western blot. The effect of piRNA-14633 on METTL14 was evaluated by a dual-luciferase reporter assay. The in vivo effects of piRNA-14633 on CC was assessed by nude mice experiments. Results piRNA-14633 showed high expression in CC tissues and cells, piRNA-14633 mimic (piRNA-14633 overexpression) promoted viability, proliferation, migration and invasion of CaSki cells and SiHa cells. Besides, piRNA-14633 mimic increased m6A RNA methylation levels and METTL14 mRNA stability. Results of dual luciferase reporter assays indicated that METTL14 was a directed target gene of piRNA-14633. Knockdown of METTL14 with siRNA attenuated proliferation, migration and invasion of CC cells. piRNA-14633 increased CYP1B1 expression, while silencing of METTL14 impaired its expression. The effect of piRNA overexpression on METTL14 expression has concentration-dependent characteristics. Results from in vivo experiment indicated that piRNA-14633 promoted cervical tumor growth. Conclusion piRNA-14633 promotes proliferation, migration and invasion of CC cells by METTL14/CYP1B1 signaling axis, highlighting the important role of piRNA-14633 in CC.

In the pursuit of automating the entire underground drilling process in coal mines, the automatic rod feeding technology of drilling robots plays a crucial role. However, the current lack of positional accuracy in automatic rod feeding leads to frequent accidents. To address this issue, this paper presents an algorithm for compensating positioning errors in automatic rod feeding. The algorithm is based on a theoretical mathematical model and manual teaching methods. To enhance the positioning accuracy, we first calibrate the pull rope sensor to correct its measurement precision. Subsequently, we establish a theoretical mathematical model for rod feeding positions by employing spatial coordinate system transformations. We determine the target rod feeding position using a manual teaching-based approach. Furthermore, we analyze the relationship between the theoretical rod delivery position and the target rod delivery position and propose an anisotropic spatial difference compensation technique that considers both distance and direction. Finally, we validate the feasibility of our proposed algorithm through automatic rod feeding tests conducted on a coal mine underground drilling robot. The results demonstrate that our algorithm significantly improves the accuracy of rod feeding positions for coal mine underground drilling robots.

Misalignment or unbalanced loading of machine tool spindle bearings often results in skewed bearing operation, which makes the spindle more susceptible to failure. In addition, due to the weak impact signal of the bearing in skewed operation, a single feature information cannot accurately characterize the operation status of the bearing. To address the above problems, this paper proposes a method to monitor the uneven running state of bearing load based on a dual-channel fusion improved dense connection (DenseNet) network. First, the original signal is pre-processed by overlapping sampling method, and the dual-channel experimental data are obtained by frequency-domain and time-frequency-domain algorithms; then the processed data are input into the improved 1D-DenseNet and 2D-DenseNet models respectively for feature extraction; then the frequency-domain and time-frequency-domain features are fused by concat splicing operation, and the output belongs to each category The probability distribution is used to characterize the operating state of the bearings. Finally, the validity of the algorithm model is verified by using the Case Western Reserve University public rolling bearing data set, and an experimental bench is designed and built for experimental verification of the uneven bearing load operation. The comparative analysis of the experimental results in this paper shows that the algorithm can extract the features of the input signal more comprehensively and finally achieve 100% recognition accuracy.

Background and objective: Asthma is a common chronic inflammatory disease of the airways with no known cure. Lipid mediators (LMs) are a kind of inflammatory signaling molecules which are believed to be involved in the development of asthma. Hyssopus cuspidatus Boriss. is a traditional Uyghur medicine, which is widely used in the treatment of asthma and other respiratory diseases. Extraction of Hyssopus cuspidatus Boriss. was reported to neutralize asthma symptoms. The purpose of the study was to investigate both the anti-inflammatory and immunoregulation properties of the Hyssopus cuspidatus Boriss. extract (SXCF) and its main active constituent, rosmarinic acid (RosA), in vivo. The effect of RosA, a major constituent of SXCF, was evaluated on an asthmatic model, with both anti-inflammatory and immunoregulation properties. Materials and methods: Anti-inflammatory effect of SXCF and RosA was assessed using OVA-induced asthma model mice by UPLC-MS/MS method. Results: Overall, RosA played a critical role in anti-asthma treatment. In total, 90% of LMs species that were significantly regulated by SXCF were covered. On the most important LMs associated with asthma, RosA equivalent induced similar effects as SXCF did. It is believed that some constituents in SXCF could neutralize RosA excessive impacts on LMs.

It is significant for the practical application of space-borne mesh-shaped reflectors to reduce the structural complexity under the condition of the far-field electromagnetic (EM) performance being satisfied. To address this problem, an optimal topology configuration design method is proposed for the mesh-shaped reflectors. First, a multifrequency optimization model is established to obtain the mesh-shaped reflector. The reflector nodal deviations in the x-, y-, and z-directions are simultaneously selected as design variables to design the shape of the mesh reflector and realize the required contoured beams within the whole frequency band. Then, based on the multifrequency optimization model, an iterative design technology is proposed to obtain the optimal topology configuration of the mesh-shaped reflector. Finally, a typical example of a mesh reflector with contoured beams covering the continental United States (CONUS) is investigated to demonstrate the feasibility of the method.

The spike (S) protein of coronaviruses is responsible for receptor recognition and the fusion between the viral membrane and the of cell host membrane. Here the authors report a cryo-EM structure of SARS-CoV post-fusion S2 trimer, providing insights into the fusion mechanism that could be useful for therapeutic development against coronaviruses.

ObjectivesTo explore the efficacy of diffusion weighted imaging (DWI)-derived metrics under different models as surrogate indicators for molecular biomarkers and tumor microenvironment in gliomas.MethodsA retrospective study was performed for 41 patients with gliomas. The standard apparent diffusion coefficient (ADCst) and ADC under ultra-high b values (ADCuh) (b values: 2500 to 5000 s/mm2) were calculated based on monoexponential model. The fraction of fast diffusion (f), pseudo ADC (ADCfast) and true ADC (ADCslow) were calculated by bi-exponential model (b values: 0 to 2000 s/mm2). The apparent diffusional kurtosis (Kapp) was derived from the simplified diffusion kurtosis imaging (DKI) model (b values: 200 to 3000 s/mm2). Potential correlations between DWI parameters and immunohistological indices (i.e. Aquaporin (AQP)1, AQP4, AQP9 and Ki-67) were investigated and DWI parameters were compared between high- and low-grade gliomas, and between tumor center and peritumor. Receiver operator characteristic (ROC) curve and area under the curve (AUC) were calculated to determine the performance of independent or combined DWI parameters in grading gliomas.ResultsThe ADCslow and ADCuh at tumor center showed a stronger correlation with Ki-67 than other DWI metrics. The ADCst, ADCslow and ADCuh at tumor center presented correlations with AQP1 and AQP4 while AQP9 did not correlate with any DWI metric. Kapp showed a correlation with Ki-67 while no significant correlation with AQPs. ADCst (p < 0.001) and ADCslow (p = 0.001) were significantly lower while the ADCuh (p = 0.006) and Kapp (p = 0.005) were significantly higher in the high-grade than in the low-grade gliomas. ADCst, f, ADCfast, ADCslow, ADCuh, Kapp at the tumor center had significant differences with those in peritumor when the gliomas grade became high (p < 0.05). Involving ADCuh and Kapp simultaneously into an independent ADCst model (AUC = 0.833) could further improve the grading performance (ADCst+ADCuh+Kapp: AUC = 0.923).ConclusionDifferent DWI metrics fitted within different b-value ranges (low to ultra-high b values) have different efficacies as a surrogate indicator for molecular expression or microstructural complexity in gliomas. Further studies are needed to better explain the biological meanings of these DWI parameters in gliomas.

In this paper, a quasi-static angular contact ball bearing model, considering assembly accuracy is constructed, while a numerical solution method for bearing stiffness under bad assembly state is established. A 7014C angular contact ball bearing is used as the research object and five groups of different spacer inclinations are designed to imitate the installation error of the spindle bearing. The bearing stiffness performance was comparatively analyzed, according to the five spacers. The effect of preload and rotation speed on bearing stiffness are systematically investigated, considering different parallelism errors, as induced by the spacers. The influence mechanism of the badly assembled bearing on the respective stiffness anisotropy is studied based on the proposed model. The results show that the variations of the inclination between the inner and outer rings of the bearing exhibit a very weak effect on the axial stiffness, while the influence on the radial and angular stiffness is more significant.

An improved density-based spatial clustering of applications with noise (IDBSCAN) analysis approach based on kurtosis and sample entropy (SE) is presented for the identification of operational state in order to provide accurate monitoring of spindle operation condition. This is because of the low strength of the shock signal created by bearing of precision spindle of misalignment or imbalanced load, and the difficulties in extracting shock features. Wavelet noise reduction begins by dividing the recorded vibration data into equal lengths. Features like kurtosis and entropy in the frequency domain are used to generate feature vectors that indicate the bearing operation state. IDBSCAN cluster analysis is then utilized to establish the ideal neighborhood radius (Eps) and the minimum number of objects contained within the neighborhood radius (MinPts) of the vector set, which are combined to identify the bearing operating condition features. Finally, utilizing data from the University of Cincinnati, the approach was validated and assessed, attaining a condition detection accuracy of 99.2%. As a follow-up, the spindle’s vibration characteristics were studied utilizing an unbalanced bearing’s load bench. Bearing state recognition accuracy was 98.4%, 98.4%, and 96.7%, respectively, under mild, medium, and overload circumstances, according to the results of the experimental investigation. Moreover, it shows that conditions of bearings under various unbalanced loads can be precisely monitored using the proposed method without picking up on specific sorts of failures.

Alphaviruses are enveloped RNA viruses that contain several human pathogens. Here, the authors use block-based reconstruction method and provide a 3.5 Å cryo-EM structure of sindbis virus that identifies a conserved hydrophobic pocket near the viral membrane that is stabilized by an unknown pocket factor.

Resistance to CDK4/6 inhibitors (CDKis) is emerging as a clinical challenge. Identification of the factors contributing to CDKi resistance, with mechanistic insight, is of pivotal significance. Recent studies linked aberrant FGFR signaling to CDKi resistance. However, detailed mechanisms are less clear. Based on control and FGFR1 overexpressing luminal A cell line models, we demonstrated that FGFR1 overexpression rendered the cells resistant to palbociclib. FGFR1 overexpression abolished palbociclib-mediated cell cycle arrest, as well as the attenuated palbociclib-induced inhibition of G1/S transition regulators (pRb, E2F1, and cyclin D3) and factors that promote G2/M transition (cyclin B1, cdc2/CDK1, and cdc25). Importantly, FGFR1-induced palbociclib resistance was associated with promotion of cancer cell stemness and the upregulation of Wnt/β-catenin signaling. We found that palbociclib may function as an ER agonist in MCF-7/FGFR1 cells. Upregulation of the ER-mediated transcription in MCF-7/FGFR1 cells was associated with ERα phosphorylation and enhanced receptor tyrosine kinase signaling. The combination of palbociclib with FGFR-targeting AZD4547 resulted in remarkable synergistic effects on MCF-7/FGFR1 cells, especially for the inhibition of cancer cell stemness. Our findings of FGFR1-induced palbociclib resistance, promotion of cancer stem cells and associated molecular changes advance our mechanistic understanding of CDKi resistance, which will facilitate the development of strategies targeting CDKi resistance in breast cancer treatment.

OBJECTIVE: To compare 2D and 3D radiomics features prognostic performance differences in CT images of non-small cell lung cancer (NSCLC). METHOD: We enrolled 588 NSCLC patients from three independent cohorts. Two sets of 463 patients from two different institutes were used as the training cohort. The remaining cohort with 125 patients was set as the validation cohort. A total of 1014 radiomics features (507 2D features and 507 3D features correspondingly) were assessed. Based on the dichotomized survival data, 2D and 3D radiomics indicators were calculated for each patient by trained classifiers. We used the area under the receiver operating characteristic curve (AUC) to assess the prediction performance of trained classifiers (the support vector machine and logistic regression). Kaplan–Meier and Cox hazard survival analyses were also employed. Harrell's concordance index (C-Index) and Akaike's information criteria (AIC) were applied to assess the trained models. RESULTS: Radiomics indicators were built and compared by AUCs. In the training cohort, 2D_AUC = 0.653, 3D_AUC = 0.671. In the validation cohort, 2D_AUC = 0.755, 3D_AUC = 0.663. Both 2D and 3D trained indicators achieved significant results (P

Poplar wood is the main source of renewable biomass energy worldwide, and is also considered to be a model system for studying woody plants. The Full-length cDNA Over-eXpressing (FOX) gene hunting system is an effective method for generating gain-of-function mutants. Large numbers of novel genes have successfully been identified from many herbaceous plants according to the phenotype of gain-of-function mutants under normal or abiotic stress conditions using this system. However, the system has not been used for functional gene identification with high-throughput mutant screening in woody plants. In this study, we constructed a FOX library from the Chinese white poplar, Populus tomentosa. The poplar cDNA library was constructed into the plant expression vector pEarleyGate101 and further transformed into Arabidopsis thaliana (thale cress). We collected 1749 T1 transgenic plants identified by PCR. Of these, 593 single PCR bands from different transgenic lines were randomly selected for sequencing, and 402 diverse sequences of poplar genes were isolated. Most of these genes were involved in photosynthesis, environmental adaptation, and ribosome biogenesis based on Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway annotation. We characterized in detail two mutant lines carrying PtoCPCa or PtoWRKY13 cDNA insertions. Phenotypic characterization showed that overexpression of these genes in A. thaliana affected trichome development or secondary cell wall (SCW) deposition, respectively. Together, the Populus-FOX-Arabidopsis library generated in our experiments will be helpful for efficient discovery of novel genes in poplar.

The precision and crack-free surface of brittle silicon carbide (SiC) ceramic was achieved in the nanoscale ductile grinding. However, the nanoscale scratching mechanism and the root causes of SiC ductile response, especially in the atomistic aspects, have not been fully understood yet. In this study, the SiC atomistic scale scratching mechanism was investigated by single diamond grain scratching simulation based on molecular dynamics. The results indicated that the ductile scratching process of SiC could be achieved in the nanoscale depth of cut through the phase transition to an amorphous structure with few hexagonal diamond structure. Furthermore, the silicon atoms in SiC could penetrate into diamond grain which may cause wear of diamond grain. It was further found out that the chip material in the front of grain flowed along the grain side surface to form the groove protrusion as the scratching speed increases. The higher scratching speed promoted more atoms to transfer into the amorphous structure and reduced the hexagonal diamond and dislocation atoms number, which resulted in higher temperature, smaller scratching force, smaller normal stress, and thinner subsurface damage thickness, due to larger speed impaction causing more bonds broken which makes the SiC more ductile.

Objective To explore the pathological features of ganglioglioma with tanycytic ependymoma as the glial component. Methods One case of ganglioglioma was studied by paraffin slices, HE staining, immunohistochemistry markers and observed under microscopy. Results A 21 ⁃ year ⁃ old woman mainly presented with intermittent physical convulsion and dizziness. Magnetic resonance imaging (MRI) demonstrated an occupying lesion in right parietal lobe. It was seen in the operation that the tumor was located in right parietal lobe. The tumor measuring about 4.50 cm × 4.00 cm × 4.00 cm was tenacious and grey⁃red in color. The blood supply was general. Most parts of the tumor boundary were clear. After removing the tumor, it was found that the operated cavity was communicated with lateral ventricle. Under microscope it was seen that the tumor was composed of tumorous glial cells and gangliocytes. The glial components were tanycytic ependymoma cells and glial cells arranged in a spreading bundle pattern. Perivascular pseudorosettes could be seen in the tumor. The distribution of gangliocytes was not uiform. Most gangliocytes were well⁃differentiated. Immunohistochemistry showed that tanycytic ependymoma cells were reactive with antibodies of glial fibrillary acidic protein (GFAP), vimentin (Vim) and epithelial membrane antigen (EMA), while gangliocytes were reactive with antibodies of neuronal nuclei (NeuN) and neurofilament protein (NF). Conclusion Ganglioglioma is a kind of rare tumor originated from neurepithelium. It is well⁃differentiated and retardation in growth. It is composed of tumorous glial cells and gangliocytes. The most tumorous glial components are astrocytes. Ganglioglioma with tanycytic ependymoma as the glial component is very rare. Grasping the tumor pathological features is useful in the diagnosis and treatment of this disease. DOI：10.3969/j.issn.1672-6731.2011.03.018