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Mengjie Chen,1,&ast; Kan Xu,2,&ast; Yuting He,1,&ast; Jianjun Jin,3 Ruolin Mao,1 Lei Gao,1 Yi Zhang,4 Gang Wang,5 Peng Gao,6 Min Xie,7 Chunfang Liu,8 Zhihong Chen1 1Department of Respiratory and Critical Care Medicine of Zhongshan Hospital, Shanghai Institute of Respiratory Disease, Fudan University, Shanghai, People’s Republic of China; 2Geriatric Department of Zhongshan Hospital, Shanghai Institute of Respiratory Disease, Fudan University, Shanghai, People’s Republic of China; 3Research Center of Zhongshan Hospital, Fudan University, Shanghai, People’s Republic of China; 4Air Liquide Holding Co., Ltd, Shanghai, People’s Republic of China; 5Department of Respiratory and Critical Care Medicine, Clinical Research Center for Respiratory Disease, West China Hospital, Sichuan University, Chengdu, People’s Republic of China; 6Department of Respiratory Medicine, The Second Affiliated Hospital of Jilin University, Changchun, People’s Republic of China; 7Department of Pulmonary and Critical Care Medicine, Tongji Hospital, Tongji Medical 10 College, Huazhong University of Science and Technology, Wuhan, People’s Republic of China; 8Department of Laboratory Medicine, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Zhihong Chen, Department of Respiratory and Critical Care Medicine of Zhongshan Hospital, No. 180 Fenglin Road, Shanghai, People’s Republic of China, Tel +86-21-64041990-2445, Fax +86-21-64187165, Email chen.zhihong@zs-hospital.sh.cn Chunfang Liu, Department of Laboratory Medicine, Huashan Hospital, Shanghai Medical College, Fudan University, 12&num; Wlmq Road, Shanghai, People’s Republic of China, Email Chunfang_liu@fudan.edu.cnPurpose: The progression of an abnormal inflammatory response plays a crucial role in the lung function decline of chronic obstructive pulmonary disease (COPD) patients. Compared to serum biomarkers, inflammatory biomarkers in induced sputum would be a more reliable reflection of inflammatory processes in the airways.Patients and Methods: A total of 102 COPD participants were divided into a mild-to-moderate group (FEV1%pred≥ 50%, n=57) and a severe-to-very-severe group (FEV1%pred< 50%, n=45). We measured a series of inflammatory biomarkers in induced sputum and analyzed their association with lung function and SGRQ in COPD patients. To evaluate the relationship between inflammatory biomarkers and the inflammatory phenotype, we also analyzed the correlation between biomarkers and airway eosinophilic phenotype.Results: We found increased mRNA levels of MMP9, LTB4R, and A1AR and decreased levels of CC16 mRNA in induced sputum in the severe-to-very-severe group. After adjustment for age, sex and other biomarkers, CC16 mRNA expression was positively associated with FEV1%pred (r=0.516, p=0.004) and negatively correlated with SGRQ scores (r=− 0.3538, p=0.043). As previously known, decreased CC16 was related to the migration and aggregation of eosinophils in airway. It was also found that CC16 had a moderate negative correlation with the eosinophilic inflammation in airway (r=− 0.363, p=0.045) in our COPD patients.Conclusion: Low CC16 mRNA expression levels in induced sputum were associated with low FEV1%pred and a high SGRQ score in COPD patients. Sputum CC16 as a potential biomarker for predicting COPD severity in clinical practice might attribute to the involvement of CC16 in airway eosinophilic inflammation.Keywords: COPD, induced sputum, airway inflammation, biomarkers, lung function, CC16

In situ and simultaneous remediation of a variety of pollutants in sediments remains a challenge. In this study, we report that the combination of electrocoagulation (EC) and electrooxidation (EO) is efficient in the immobilization of phosphorus and heavy metals and in the oxidation of ammonium and toxic organic matter. The integrated mixed metal oxide (MMO)/Fe anode system allowed the facile removal of ammonium and phosphorus in the overlying water (99% of 10 mg/L NH

Purpose The flexible eddy current array sensor has the characteristics of lightweight and flexibility, which has a great application prospect in the field of fatigue crack monitoring. But the exciting layout and feature signal extraction have a great influence on the crack monitoring characteristics of the sensor. This paper aims to propose a method using crack disturbed voltage as sensitivity to characterize crack propagation. Design/methodology/approach Flexible eddy current array sensors with reverse and codirectional exciting layout are proposed, and the advantages and disadvantages of three characterization methods based on the change of trans-impedance amplitude, the change of the trans-impedance’s real and imaginary part and the crack disturbed voltage are compared and analyzed by finite element simulation. Finally, the fatigue crack monitoring experiment is carried out. Findings The crack disturbed voltage and the change of trans-impedance’s imaginary part can effectively characterize the crack propagation for sensors with different exciting layouts. The codirectional exciting layout sensor has better crack identification sensitivity than the reverse exciting layout sensor, especially the induction coil 2. When the distance between the exciting coil and the induction coil is 0.1, 0.2 and 0.3 mm, it is increased by 372.09%, 295.24% and 231.43%, respectively. Originality/value Crack disturbed voltage can effectively characterize the crack propagation for sensors with two different exciting layouts.

Fluid shear stress (FSS) regulates the metastasis of hepatocellular carcinoma (HCC), but the role of the RhoA-YAP1-autophagy pathway in HCC remains unclear. Due to the core role of liver cancer stem cells (LCSCs) in HCC metastasis and recurrence, we explored the RhoA-YAP1-autophagy pathway in LCSCs under FSS. Our results indicate that LCSCs have stronger proliferation and cell spheroidization abilities. FSS (1 dyn/cm

One of the key steps of using CRISPR/Cas9 to obtain gene-edited cells used in generating gene-edited animals combined with somatic cell nuclear transplantation (SCNT) is to harvest monoclonal cells with genetic modifications. However, primary cells used as nuclear donors always grow slowly and fragile after a series of gene-editing operations. The extracellular matrix (ECM) formulated directly from different organs comprises complex proteins and growth factors that can improve and regulate the cellular functions of primary cells. Herein, sodium lauryl ether sulfate (SLES) detergent was first used to perfuse porcine kidney ECM, and the biological properties of the kidney ECM were optimized. Then, we used a porcine kidney ECM pregel to pattern the microarray and developed a novel strategy to shorten the time of obtaining gene-edited monoclonal cell spheroids with low damage in batches. Our results showed that the SLES-perfused porcine kidney ECM pregel displayed superior biological activities in releasing growth factors and promoting cell proliferation. Finally, combined with microarray technology, we quickly obtained monoclonal cells in good condition, and the cells used as nuclear donors to construct recombinant embryos showed a significantly higher success rate than those of the traditional method. We further successfully produced genetically edited pigs.

Purpose Flexible eddy current array (FECA) sensor is flexible and light in weight, which has broad application prospects in structural health monitoring. But, the sensor’s sensing channel number is more, increasing the added mass of sensor networks. This paper aims to reduce the sensing channel number by changing the sensing coil layout. Design/methodology/approach In this paper, FECA sensors with series sensing coil (SSC) layout and interactive sensing coil (ISC) layout are proposed, which reduce the number of sensor’s channels by half. Then, the variation of the output signal of the sensor when the crack expands along both sides of the hole is analyzed by simulation model. Finally, the fatigue crack monitoring experiment is carried out. Findings For the SSC layout, the simulation results show that the amplitude of each SSC group of the sensor increases when the crack propagates to the left or right. For the ISC layout, when the crack propagates on the right side of bolt hole, the induced voltage of each ISC group decreases. When the crack propagates on the left side of bolt hole, the induced voltage of each ISC group increases. The experiment results are consistent with simulation results, which verifies the correctness of simulation model. Compared with SSC layout, the ISC layout can judge the crack propagation direction. And the crack monitoring accuracy is 1 mm. Originality/value The research results provide a certain reference for reducing the number of sensor’s sensing channels. Results of the simulation and experiment show that the ISC layout can judge the crack propagation direction, and the crack monitoring accuracy is 1 mm.

For sake of further enhancing the catalytic performance of Co-MOFs and reducing th leaching of Co2+, Fe-doped Co-MOFs was prepared by one-step solvothermal method. The Fex/Co1 − x-MOFs with the best catalytic activity (Fe0.25Co0.75-MOFs) was obtained by changing the doping ratio of Fe3+. Under the action of 0.1g/L Fe0.25Co0.75-MOFs, pH = 7 and 0.2g/L PMS, 98.4% TC can be efficiently degraded only within 30 min, Moreover, the degradation efficiency increased with the increase of the catalyst and PMS. The effects of initial pH on tetracycline hydrochloride degradation was discussed, showing that Fe0.25Co0.75-MOFs can degrade tetracycline hydrochloride with excellent stability. Furthermore, the Fe0.25Co0.75-MOFs exhibits good reusability and stability in cycling experiments. Ultimately, free radical quenching experiments show that both SO4−• and •OH participated in the degradation of tetracycline hydrochloride, and SO4−• plays a major role. Based on some intermediates identified by lc-mg, possible degradation pathways are proposed.

With the rapid development of artificial intelligence and computer vision, deep learning has become widely used for aircraft detection. However, aircraft detection is still a challenging task due to the small target size and dense arrangement of aircraft and the complex backgrounds in remote sensing images. Existing remote sensing aircraft detection methods were mainly designed based on algorithms employed in general object detection methods. However, these methods either tend to ignore the key structure and size information of aircraft targets or have poor detection effects on densely distributed aircraft targets. In this paper, we propose a novel multi-task aircraft detection algorithm. Firstly, a multi-task joint training method is proposed, which provides richer semantic structure features for bounding box localization through landmark detection. Secondly, a multi-task inference algorithm is introduced that utilizes landmarks to provide additional supervision for bounding box NMS (non-maximum suppression) filtering, effectively reducing false positives. Finally, a novel loss function is proposed as a constrained optimization between bounding boxes and landmarks, which further improves aircraft detection accuracy. Experiments on the UCAS-AOD dataset demonstrated the state-of-the-art precision and efficiency of our proposed method compared to existing approaches. Furthermore, our ablation study revealed that the incorporation of our designed modules could significantly enhance network performance.

Therapeutic antibodies blocking programmed death-1 and its ligand (PD-1/PD-L1) induce durable responses in a substantial fraction of melanoma patients. We sought to determine whether the number and/or type of mutations identified using a next-generation sequencing (NGS) panel available in the clinic was correlated with response to anti–PD-1 in melanoma. Using archival melanoma samples from anti–PD-1/PD-L1-treated patients, we performed hybrid capture–based NGS on 236–315 genes and T-cell receptor (TCR) sequencing on initial and validation cohorts from two centers. Patients who responded to anti–PD-1/PD-L1 had higher mutational loads in an initial cohort (median, 45.6 vs. 3.9 mutations/MB; P = 0.003) and a validation cohort (37.1 vs. 12.8 mutations/MB; P = 0.002) compared with nonresponders. Response rate, progression-free survival, and overall survival were superior in the high, compared with intermediate and low, mutation load groups. Melanomas with NF1 mutations harbored high mutational loads (median, 62.7 mutations/MB) and high response rates (74%), whereas BRAF/NRAS/NF1 wild-type melanomas had a lower mutational load. In these archival samples, TCR clonality did not predict response. Mutation numbers in the 315 genes in the NGS platform strongly correlated with those detected by whole-exome sequencing in The Cancer Genome Atlas samples, but was not associated with survival. In conclusion, mutational load, as determined by an NGS platform available in the clinic, effectively stratified patients by likelihood of response. This approach may provide a clinically feasible predictor of response to anti–PD-1/PD-L1. Cancer Immunol Res; 4(11); 959–67. ©2016 AACR.

Supplementary Table 1: Results for samples obtained (less than or equal to) 12 months prior to therapy (optimal) vs. those obtained >12 months from treatment or shortly after starting therapy (non-optimal). Supplementary Table 2: Cox proportional hazards model of OS adjusting for baseline variables. Supplementary Table 3: Cox proportional hazards model of PFS adjusting for baseline variables. Figure S1: (A) Performance of mutational load across a range of potential thresholds. (B) Receiver Operating Curve (ROC) for mutational loads cutoffs of 3.3 mutations/MB (low mutational load group) and 23.1 mutations/MB (high mutational load group). Figure S2: (A) Mutational load in tumors with cutaneous/unknown primaries in responders vs. non-responders. (B) Mutational load in tumors with non-cutaneous primaries (acral, mucosal, uveal) in responders vs. non-responders. (C) Gene amplifications and deletions in responders vs. non-responders. Figure S3: (A) LRP1B mutations/variants of unknown significance in responders vs. non-responders. (B) Total number of mutations among melanomas with and without LRP1B mutations. (C) Association between number of LRP1B mutations and total mutations in the melanoma TCGA. Figure S4: (A) T cell receptor (TCR) clonality in responders vs. non-responders. (B) T cell fraction in responders vs. non-responders. (C) TCR clonality in responders vs. non-responders in ideal samples, defined as those obtained within 4 months of anti-PD-1/PD-L1 treatment without other prior therapies. (D) T cell fraction in these ideal samples. Figure S5: Mutation load correlated with (A) T cell receptor (TCR) clonality and (B) T cell fraction.

Multi-object Tracking is an important issue that has been widely investigated in computer vision. However, in practical applications, moving targets are often occluded due to complex changes in the background, which leads to frequent pedestrian ID switches in multi-object tracking. To solve the problem, we present a multi-object tracking algorithm based on FairMOT and Circle Loss. In this paper, HRNet is adopted as the baseline. Then, Polarized Self-Attention is added to HRNet-w32 to obtain weights of helpful information based on its modeling advantages. Moreover, the re-identification branch is optimized, and the Circle Loss is selected as the loss function to acquire more discriminative pedestrian features and to distinguish different pedestrians. The method proposed is assessed on the public MOT17 datasets. The experimental results show that the MOTA score achieves 69.5%, IDF1 reaches 70.0%, and the number of ID switches (IDs) decreases 636 times compared to the TraDes algorithm.

Deformable medical image registration estimates corresponding deformation to align the regions of interest (ROIs) of two images to a same spatial coordinate system. However, recent unsupervised registration models only have correspondence ability without perception, making misalignment on blurred anatomies and distortion on task-unconcerned backgrounds. Label-constrained (LC) registration models embed the perception ability via labels, but the lack of texture constraints in labels and the expensive labeling costs causes distortion internal ROIs and overfitted perception. We propose the first few-shot deformable medical image registration framework, Perception-Correspondence Registration (PC-Reg), which embeds perception ability to registration models only with few labels, thus greatly improving registration accuracy and reducing distortion. 1) We propose the Perception-Correspondence Decoupling which decouples the perception and correspondence actions of registration to two CNNs. Therefore, independent optimizations and feature representations are available avoiding interference of the correspondence due to the lack of texture constraints. 2) For few-shot learning, we propose Reverse Teaching which aligns labeled and unlabeled images to each other to provide supervision information to the structure and style knowledge in unlabeled images, thus generating additional training data. Therefore, these data will reversely teach our perception CNN more style and structure knowledge, improving its generalization ability. Our experiments on three datasets with only five labels demonstrate that our PC-Reg has competitive registration accuracy and effective distortion-reducing ability. Compared with LC-VoxelMorph(lambda=1), we achieve the 12.5%, 6.3% and 1.0% Reg-DSC improvements on three datasets, revealing our framework with great potential in clinical application.

The considerable kinetic role of Laplace pressure in contact angles of superamphobic surfaces can be utilized for robust superamphibic surfaces with an enlarged area fraction via the narrow parallel channel design.

HighlightsAn adaptive group eggs segmentation was proposed, which separates a single egg from the group eggs image.Key color features and texture features were extracted from the RGB and HSI histograms, respectively.The Support Vector Machine (SVM) model and Least Squares Support Vector Machine (LS-SVM) model were built to distinguish infertile egg and dead-embryo egg, respectively.LS-SVM model reached 100% accuracy for infertile eggs on day 4 of incubation, and dead-embryo eggs on day 10 of incubation.Abstract. For the incubation factory, it is of vital importance to detect infertile eggs and dead-embryo eggs in the industrial egg trays as early as possible. In this article, an activity detection computer vision system was proposed and evaluated. Due to the dense layout of eggs in industrial egg trays, the image segmentation task to separate each single egg becomes difficult. To this end, an adaptive image segmentation method for group eggs was proposed. Firstly, the binary image was obtained by the Canny operator using dynamic threshold and processed to reduce redundant information. Then ellipse fitting was employed to obtain the egg contour of the single egg. Moreover, the Red, Green, Blue (RGB) and Hue, Saturation, Intensity (HSI) histograms were selected for feature extraction. According to the analysis on color features and texture features of the images, 13 features [positions for peak values of R and I in histogram, peak values of G and I within histogram, averages of R and G, variances of R and G, contrast, roughness, inverse different moment (IDM), correlation and angular second moment (ASM)] were chosen as the criterion for detecting dead-embryo eggs. Meanwhile, 12 features (positions for peak values of R, G, H, and I in histogram, averages of R and G, slope and variance of G, contrast, roughness, IDM, and correlation) were selected for detecting infertile eggs. Lastly, the Support Vector Machine (SVM) model and Lease Squares Support Vector Machine (LS-SVM) model were built to distinguish infertile egg and dead-embryo egg, respectively. According to the comparison, the LS-SVM model reached higher accuracy in determining infertile egg and dead-embryo egg than the SVM model, with less time consumed. The LS-SVM model reached 100% accuracy in detection for infertile eggs on day 4 of incubation, as well as for dead-embryo eggs on day 10 of incubation. The result demonstrated that the proposed method can conduct the activity detection for group eggs both accurately and fast, which meets the commercial requirement for non-destructive detection in the hatchery industry. Keywords: Adaptive image segmentation, Computer vision, Fertility, Group hatching eggs, LS-SVM, Non-destructive detection, SVM

A new strategy for the synthesis of high-value biochemical 2,5-dimethylphenol was constructed by lignocellulose catalytic pyrolysis and selective hydroxylation.

Novel porous non-carbon-based microwave-absorbing materials were established, which exhibit excellent microwave absorption properties comparable with those of carbon-based materials.

TADF dendrimers with a D–A–D structure, with multi-carbazole as the donor and di(pyridine-3-yl)methanone as the acceptor, are synthesized and their solution-processed OLEDs achieved a CEmax of 52.6 vs. 27.0 cd A−1 and an EQEmax of 20.4% vs. 9.2%.

As a prevalent epigenetic modification, the role of m6A has been increasingly highlighted in the alteration of numerous RNAs implicated with multiple biological processes, such as formation, export, translation, and degradation. With further the understanding of m6A, accumulating evidence shows that m6A modification similarly affects metabolic process of non-coding genes. But the specifical interplay of m6A and ncRNAs (non-coding RNAs) in gastrointestinal cancers still lacks complete discussion. Thus, we analyzed and summarized how ncRNAs affect the regulators of m6A and by what means the expression of ncRNAs is altered via m6A in gastrointestinal cancers. We focused on the effect of the interaction of m6A and ncRNAs on the molecular mechanisms of malignant behavior in gastrointestinal cancers, revealing more possibilities of ncRNAs for diagnosis and treatment in term of epigenetic modification.

Background Intratumoral microbial communities have been recently discovered to exist in a variety of cancers and have been found to be intricately involved in tumour progression. Therefore, investigating the profiles and functions of intratumoral microbial distribution in hepatocellular carcinoma (HCC) is imperative. Methods To verify the presence of microorganisms in HCC, we performed fluorescence in situ hybridization (FISH) using HCC tissues and conducted MiSeq using 99 HCC and paracancerous tissues to identify the key microorganisms and changes in metabolic pathways affecting HCC progression through a variety of bioinformatics methods. Results Microbial diversity was significantly higher in HCC tissues than in adjacent tissues. The abundances of microorganisms such as Enterobacteriaceae, Fusobacterium and Neisseria were significantly increased in HCC tissues, while the abundances of certain antitumour bacteria such as Pseudomonas were decreased. Processes such as fatty acid and lipid synthesis were significantly enhanced in the microbiota in HCC tissues, which may be a key factor through which intratumoral microbes influence tumour progression. There were considerable differences in the microbes and their functions within tumour tissue collected from patients with different clinical features. Conclusion We comprehensively evaluated the intratumoral microbial atlas of HCC tissue and preliminarily explored the mechanism of the effects of the microbial community involving changes in lipid metabolism and effects on HCC progression, which lays the foundation for further research in this field.

Both the reactive oxygen species (ROS) level and Phosphatidylinositol 3 Kinase (PI3K) protein content are two crucial parameters for characterizing states of cell apoptosis. Current methods measure these parameters with two different techniques, respectively, which usually lead to evaluation contingency. Ginsenoside Rg3 exhibits an excellent anticancer effect, which is enacted by the Phosphatidylinositol 3 Kinase/Protein Kinase B (PI3K/Akt) pathway involving ROS; however, the precise mechanism that induces cell apoptosis remains unknown. This is due to the lack of information on quantitative intracellular ROS and PI3K. Here, we used a surface-enhanced Raman scattering (SERS)-based boric acid nanoprobe to monitor the intracellular ROS level and phosphatidylinositol-3,4,5-triphosphate (PI(3,4,5)P3) content, which reflects the regulatory effect of the PI3K/Akt pathway. After treatment with ginsenoside Rg3, the PI3K/Akt content first increased and then decreased as the ROS level increased. Moreover, when the ROS level significantly increased, the mitochondrial membrane potential reduced, thus indicating the dynamic regulation effect of intracellular ROS level on the PI3K/Akt pathway. Importantly, in addition to avoiding evaluation contingency, which is caused by measuring the aforementioned parameters with two different techniques, this SERS-based dual-parameter monitoring nanoprobe provides an effective solution for simultaneous ROS level and PI3K content measurements during cell apoptosis. Furthermore, the intracellular ROS level was also able to have a dynamic regulatory effect on the PI3K/Akt pathway, which is essential for studying ROS/PI3K/Akt-pathway-related cell apoptosis and its activation mechanism.

International audience; One-to-multiple medical image segmentation aims to directly test a segmentation model trained with the medical images of a one-domain site on those of a multiple-domain site, suffering from segmentation performance degradation on multiple domains. This process avoids additional annotations and helps improve the application value of the model. However, no successful one-to-multiple unsupervised domain adaptation (O2M-UDA) work has been reported in one-to-multiple medical image segmentation due to its inherent challenges: distribution differences among multiple target domains (among-target differences) caused by different scanning equipment and distribution differences between one source domain and multiple target domains (source–target differences). In this paper, we propose an O2M-UDA framework called dynamic domain adaptation (DyDA), for one-to-multiple medical image segmentation, which has two innovations: (1) dynamic credible sample strategy (DCSS) dynamically extracts credible samples from the target site and iteratively updates their number, thus iteratively expanding the generalization boundary of the model and minimizing the among-target differences; (2) hybrid uncertainty learning (HUL) reduces the voxel-level and domain-level uncertainty simultaneously, thus minimizing the source–target differences from the detail and entire perspective concurrently. Experiments on two one-to-multiple medical image segmentation tasks have been conducted to demonstrate the performance of the proposed DyDA. The proposed DyDA achieved competitive segmentation results and high adaptation with an average of 83.8% and 48.1% dice for the two tasks, respectively, which has improved by 21.7% and 9.2% compared with no adaptation, respectively. The code developed in this study code can be downloaded at https://github.com/ZoeyJiang/DyDA. © 2023 Elsevier B.V.

This work aims to demonstrate that cresol, an important high added value chemical in petrochemical industry, can be directionally produced using cellulose. This novel controllable transformation process was achieved by selective catalytic pyrolysis of cellulose and catalytic oxidation. The zinc oxide-doped strong acidic zeolite catalyst promoted the formation of toluene intermediate in the catalytic pyrolysis of cellulose. The CuCr2O4@MCM-41 catalyst exhibited high activity and good reusability in the catalytic oxidation process. The highest cresol selectivity of 87.5% with conversion of 83.0% was obtained using the CuCr2O4@MCM-41 catalyst and hydrogen peroxide as a green oxidant under the optimized reaction conditions (60 °C, 4 h). Based on the study of the model compounds and catalyst characterizations, the reaction pathways and possible reaction mechanism for the catalytic transformation of cellulose to bio-based cresol have been proposed.

Severe plastic deformation is known to induce grain refinement and gradient structure on metals’ surfaces and improve their mechanical properties. However, the fundamental mechanisms behind the grain refinement and micromechanical properties of materials subjected to severe plastic deformation are not still well studied. Here, ultrasonic surface rolling process (USRP) was used to create a gradient microstructure, consisting of amorphous, equiaxed nano-grained, nano-laminated, ultrafine laminated and ultrafine grained structure on the surface of TB8 β titanium alloy. High energy and strain drove element co-segregation on sample surface leading to an amorphous structure during USRP processing. In situ transmission electron microscope compression tests were performed in the submicron sized pillar extracted from gradient structure and coarse grain, in order to reveal the micromechanics behavior of different grain morphologies. The ultrafine grained layer exhibited the lowest yield stress in comparison with single crystal and amorphous-nanocrystalline layers; the ultrafine grained layer and single crystal had an excellent strain hardening rate. The discrepancy among the grain sizes and activated dislocation sources led to the above mentioned different properties. Dislocation activities were observed in both compression test and microstructure evolution of USRP-treated TB8 alloy. An evolution of dislocation tangles and dislocation walls into low angle grain boundaries and subsequent high angle grain boundaries caused the grain refinement, where twinning could not be found and no phase transformation occurred.

Pancreatic adenocarcinoma (PAAD) is the most malignant digestive tumor. The global incidence of pancreatic cancer has been rapidly trending upwards, necessitating an exploration of potential prognostic biomarkers and mechanisms of disease development. One of the most prevalent RNA modifications is 5-methylcytosine (m5C); however, its contribution to PAAD remains unclear. Data from The Cancer Genome Atlas (TCGA) database, including genes, copy number variations (CNVs), and simple nucleotide variations (SNVs), were obtained in the present study to identify gene signatures and prognostic values for m5C regulators in PAAD. Regulatory gene m5C changes were significantly correlated with TP53, BRCA1, CDKN2A, and ATM genes, which play important roles in PAAD pathogenesis. In particular, there was a significant relationship between m5C regulatory gene CNVs, especially in genes encoding epigenetic “writers”. According to m5C-regulated gene expression in clinically graded cases, one m5C-regulated genes, DNMT3A, showed both a strong effect on CNVs and a significant correlation between expression level and clinical grade (P DNMT3A expression was not only associated with poor PAAD patient prognosis but also with the ribosomal processing. The relationship between low DNMT3A expression and poor prognosis was confirmed in an International Cancer Genome Consortium (ICGC) validation dataset.

Background: Decompensated liver cirrhosis (DLC), a terminal-stage complication of liver disease, is a major cause of morbidity and mortality in patients with hepatopathie. Human umbilical cord mesenchymal stem cell (hUCMSCs) therapy has emerged as a treatment novel alternative for the treatment of DLC. However, optimized therapy protocols and the associated mechanisms are not completely understood. Methods: We constructed a DLC rat model consistent with the typical clinical characteristics combined use of PB and CCL4. By performing dynamic detection of liver morphology and function in rats for 11 weeks, the various disease characteristics of DLC and the therapeutic effect of hUCMSCs on DLC in experimental rats were fully investigated, according to ascites examination, histopathological and related blood biochemical analyses. Flow-cytometry analysis of rat liver, immunofluorescence and RT-qPCR were performed to examine the changes of liver immune microenvironment after hucMSCs treatment. RNA-seq analysis of liver and primary macrophages and hUCMSCs co-culture system in vitro were performed to explore possible signaling pathways. PPARγ antagonist, GW9662, and clodronate liposomes were used to inhibit PPAR activation and pre-exhaustion of macrophages in DLC rats’ liver respectively. Results: We found that changing of the two key issues, the frequency and initial phase of hUCMSCs infusion can affect the efficacy of hUCMSCs and the optimal hUCMSCs treatment schedule is once every week for three weeks at the early-stage of DLC progression, providing the best therapeutic effect in reducing mortality and ascites, and improving liver function in DLC rats. hUCMSCs treatment skewed the macrophage phenotype from M1-type to M2-type through activating PPARγ signaling pathway in liver, which was approved by primary macrophages and hUCMSCs co-culture system in vitro. Both inhibition of PPARγ activation with GW9662 and pre-exhaustion of macrophages in DLC rats’ liver abolished the regulation of hUCMSCs on macrophage polarization, thus attenuating the beneficial effect of hUCMSCs treatment in DLC rats. Conclusions: HUCMSCs treatment on DLC were attributed to the activation of the PPARγ signaling pathway in liver macrophages of DLC rats, which polarizes M1-type macrophages to M2-type, thus inhibiting inflammation and promoting the repair of damaged liver tissue. Our results about different infusion regimens comparison and mechanisms exploration provide a robust theoretical foundation for the future study design of Mesenchymal Stem Cells therapy on DLC.

Hexahydromethanocarbazole is a privileged scaffold in the discovery of new drugs and photoactive organic materials due to its good balance between structural complexity and minimized entropy penalty upon receptor binding. To address the difficulty of synthesizing this highly desirable bridged polycyclic scaffold, we designed a convenient multicomponent reaction cascade as intercepted Heck addition/C-H activation/C-palladacycle formation/electrophilic attack of ANP/N-palladacycle formation/Buchwald amination. A distinguishing feature of this sophisticated strategy is the successive generation of two key phenylnorbornyl palladium species to control the reaction flow towards desired products. DFT calculations further reveal the crucial roles of Cs2CO3 and 5,6-diester substitutions on the norbornene reactant in preventing multiple side-reactions. This innovative method exhibits a broad scope with good yields, and therefore will enable the construction of natural-product-like compound libraries based on hexahydromethanocarbazole.