Targeting LIF-mediated paracrine interaction for pancreatic cancer therapy and monitoring.

Pancreatic ductal adenocarcinoma (PDAC) has a dismal prognosis largely owing to inefficient diagnosis and tenacious drug resistance. Activation of pancreatic stellate cells (PSCs) and consequent development of dense stroma are prominent features accounting for this aggressive biology1,2. The reciprocal interplay between PSCs and pancreatic cancer cells (PCCs) not only enhances tumour progression and metastasis but also sustains their own activation, facilitating a vicious cycle to exacerbate tumorigenesis and drug resistance3-7. Furthermore, PSC activation occurs very early during PDAC tumorigenesis8-10, and activated PSCs comprise a substantial fraction of the tumour mass, providing a rich source of readily detectable factors. Therefore, we hypothesized that the communication between PSCs and PCCs could be an exploitable target to develop effective strategies for PDAC therapy and diagnosis. Here, starting with a systematic proteomic investigation of secreted disease mediators and underlying molecular mechanisms, we reveal that leukaemia inhibitory factor (LIF) is a key paracrine factor from activated PSCs acting on cancer cells. Both pharmacologic LIF blockade and genetic Lifr deletion markedly slow tumour progression and augment the efficacy of chemotherapy to prolong survival of PDAC mouse models, mainly by modulating cancer cell differentiation and epithelial-mesenchymal transition status. Moreover, in both mouse models and human PDAC, aberrant production of LIF in the pancreas is restricted to pathological conditions and correlates with PDAC pathogenesis, and changes in the levels of circulating LIF correlate well with tumour response to therapy. Collectively, these findings reveal a function of LIF in PDAC tumorigenesis, and suggest its translational potential as an attractive therapeutic target and circulating marker. Our studies underscore how a better understanding of cell-cell communication within the tumour microenvironment can suggest novel strategies for cancer therapy

Use of nanomaterials in the pretreatment of water samples for environmental analysis

The challenge of providing clean drinking water is of enormous relevance in today’s human civilization, being essential for human consumption, but also for agriculture, livestock and several industrial applications. In addition to remediation strategies, the accurate monitoring of pollutants in water sup-plies, which most of the times are present at low concentrations, is a critical challenge. The usual low concentration of target analytes, the presence of in-terferents and the incompatibility of the sample matrix with instrumental techniques and detectors are the main reasons that renders sample preparation a relevant part of environmental monitoring strategies. The discovery and ap-plication of new nanomaterials allowed improvements on the pretreatment of water samples, with benefits in terms of speed, reliability and sensitivity in analysis. In this chapter, the use of nanomaterials in solid-phase extraction (SPE) protocols for water samples pretreatment for environmental monitoring is addressed. The most used nanomaterials, including metallic nanoparticles, metal organic frameworks, molecularly imprinted polymers, carbon-based nanomaterials, silica-based nanoparticles and nanocomposites are described, and their applications and advantages overviewed. Main gaps are identified and new directions on the field are suggested.publishe

Genome-Wide Survey of Pseudogenes in 80 Fully Re-sequenced Arabidopsis thaliana Accessions

Pseudogenes (Ψs), including processed and non-processed Ψs, are ubiquitous genetic elements derived from originally functional genes in all studied genomes within the three kingdoms of life. However, systematic surveys of non-processed Ψs utilizing genomic information from multiple samples within a species are still rare. Here a systematic comparative analysis was conducted of Ψs within 80 fully re-sequenced Arabidopsis thaliana accessions, and 7546 genes, representing ~28% of the genomic annotated open reading frames (ORFs), were found with disruptive mutations in at least one accession. The distribution of these Ψs on chromosomes showed a significantly negative correlation between Ψs/ORFs and their local gene densities, suggesting a higher proportion of Ψs in gene desert regions, e.g. near centromeres. On the other hand, compared with the non-Ψ loci, even the intact coding sequences (CDSs) in the Ψ loci were found to have shorter CDS length, fewer exon number and lower GC content. In addition, a significant functional bias against the null hypothesis was detected in the Ψs mainly involved in responses to environmental stimuli and biotic stress as reported, suggesting that they are likely important for adaptive evolution to rapidly changing environments by pseudogenization to accumulate successive mutations

Influence of the Amount of Steel Fibers on Fracture Energy and Drying Shrinkage of HPFRCC

The fracture energy of the high-performance fiber-reinforced cement-based composite (HPFRCC) can be modified within wide limits by the variation of the amount of steel fibers added to the fresh mix. First of all, considering the actual engineering conditions in Qingdao, the materials commonly used in Qingdao were selected. The optimal reference mix proportion of the HPFRCC cementing material was proposed through determination of fluidity and flexural strength. Based on the optimal mix proportion, the uniaxial tensile, fracture, and dry shrinkage properties of HPFRCC with different steel fibers are systematically studied. Stress-strain diagrams of the different samples were measured under the uniaxial tensile test, wedge splitting test, and three-point bending test. The steel fiber content was varied between 0 and 200 kg/m3. The load bearing capacity and the fracture energy were determined experimentally. In addition, moisture loss as a function of time and shrinkage was determined in an environment of 20°C and 50% RH (relative humidity). The results indicate that the maximum load increases significantly in the HPFRCC series reinforced by 150 and 200 kg/m3 of steel fibers. Both have a hardening branch developed after the first crack deflection due to the high percentage of fibers bridging the crack surfaces. The load bearing capacity and fracture energy increased almost linearly with the steel fiber content. It was found that the three-point bending test is more applicable in measuring the fracture energy of HPFRCC than the wedge splitting test. The addition of steel fibers decreased the moisture diffusion and consequently the drying shrinkage of HPFRCC, and there was minimum weight loss and deformation when the steel fiber content was 150 kg/m3. The results obtained will be presented and discussed

High-resolution Load Profile Clustering Approach Based on Dynamic Largest Triangle Three Buckets and Multiscale Dynamic Warping Path Under Limited Warping Path Length

With the popularity of smart meters and the growing availability of high-resolution load data, the research on the dynamics of electricity consumption at finely resolved times-cales has become increasingly popular. Many existing algorithms underperform when clustering load profiles contain a large number of feature points. In addition, it is difficult to accurately describe the similarity of profile shapes when load sequences have large fluctuations, leading to inaccurate clustering results. To this end, this paper proposes a high-resolution load profile clustering approach based on dynamic largest triangle three buckets (LTTBs) and multiscale dynamic time warping under limited warping path length (LDTW). Dynamic LTTB is a novel dimensionality reduction algorithm based on LTTB. New sequences are constructed by dynamically dividing the intervals of significant feature points. The extraction of fluctuation characteristics is optimized. New curves with more concentrated features will be applied to the subsequent clustering. The proposed multiscale LDTW is used to generate a similarity matrix for spectral clustering, providing a more comprehensive and flexible matching method to characterize the similarity of load profiles. Thus, the clustering effect of a high-resolution load profile is improved. The proposed approach has been applied to multiple datasets. Experiment results demonstrate that the proposed approach significantly improves the Davies-Bould-in indicator (DBI) and validity index (VI). Therefore, better similarity and accuracy can be achieved using high-resolution load profile clustering

The association between fear of missing out and mobile phone addiction: a meta-analysis

Abstract Background Numerous studies have explored the association between fear of missing out and mobile phone addiction, but there are different viewpoints and the results are inconsistent. This study intends to estimate the strength of the correlation between fear of missing out and mobile phone addiction in general through a meta-analysis, and to analyze the influencing factors of the inconsistent results of previous studies. Methods We Searched China National Knowledge Infrastructure Database, Wan fang Database, CQVIP Journal Database、Web of Science Core Collection, Elsevier SD, Springer Online Journals, Medline, EBSCO-ERIC, SAGE Online Journals, PsycINFO, PsycArticles and ProQuest Dissertations and Theses。85 studies (90 independent effect size) were included from 2016 to 2023。The pooled correlation coefficient of the association between fear of missing out and mobile phone addiction was calculated by a random effects model using Comprehensive Meta-Analysis(Version 3.3). Results The main effect analysis revealed a high positive correlation between fear of missing out and mobile phone addiction (r = 0.47, 95%CI [0.44, 0.50]). Furthermore, the measurements of mobile phone addiction moderated the strength of the association between fear of missing out and mobile phone addiction, with the highest correlation measured using MPATS and the lowest correlation measured using MPDQ. The age, gender, year of publication, cultural background, and the measurements of fear of missing out had no significant effect on the correlation between fear of missing out and mobile phone addiction. Conclusion The results indicated that fear of missing out was closely related to mobile phone addiction, which complied with the I-PACE model. Psychological services and mental health services should be developed to reduce the emergence of fear of missing out in the digital age and thus alleviate dependence on devices

A Nickel/Organoboron-Catalyzed Coupling of Aryl Bromides with Sodium Sulfinates: The Synthesis of Sulfones under Visible Light

An efficient cross-coupling of aryl bromides with sodium sulfinates, using an organoboron photocatalyst with nickel, is described herein. Under the irradiation of white light, this dually catalytic system enables the synthesis of a series of sulfone compounds in moderate to good yields. A broad range of functional groups and heteroaromatic compounds is tolerated under these reaction conditions. The use of an organoboron photocatalyst highlights a sustainable alternative to iridium or ruthenium complexes. These findings contribute to the field of photochemistry and provide a greener approach to sulfone synthesis

RFA: R-Squared Fitting Analysis Model for Power Attack

Correlation Power Analysis (CPA) introduced by Brier et al. in 2004 is an important method in the side-channel attack and it enables the attacker to use less cost to derive secret or private keys with efficiency over the last decade. In this paper, we propose R-squared fitting model analysis (RFA) which is more appropriate for nonlinear correlation analysis. This model can also be applied to other side-channel methods such as second-order CPA and collision-correlation power attack. Our experiments show that the RFA-based attacks bring significant advantages in both time complexity and success rate

Studying Performance and Kinetic Differences between Various Anode Electrodes in Proton Exchange Membrane Water Electrolysis Cell

The electrode, as one of the most critical components in a proton exchange membrane water electrolysis (PEMWE) cell for hydrogen production, has a significant impact on cell performance. Electrodes that are fabricated via various techniques may exhibit different morphologies or properties, which might change the kinetics and resistances of the PEMWE. In this study, we have successfully fabricated several electrodes by different techniques, and the effects of electrode coating methods (ultrasonic spray, blade coating, and rod coating), hot press, and decal transfer processes are comprehensively investigated. The performance differences between various electrodes are due to kinetic or high frequency resistance changes, while the influences are not significant, with the biggest deviation of about 26 mV at 2.0 A cm−2. In addition, the effects of catalyst ink compositions, including ionomer to catalyst ratio (0.1 to 0.3), water to alcohol ratio (1:1 to 3:1), and catalyst weight percentage (10% to 30%), are also studied, and the electrodes’ performance variations are less than 10 mV at 2.0 A cm−2. The results show that the PEMWE electrode has superior compatibility and redundancy, which demonstrates the high flexibility of the electrode and its applicability for large-scale manufacturing