Study on the Polymer Morphology and Electro-Optical Performance of Acrylate/Epoxy Resin-Based Polymer-Stabilized Liquid Crystals Based on Stepwise Photopolymerization.

Stepwise photopolymerization is a miraculous strategy modulating the polymer skeleton and electro-optical properties of light modulators based on liquid crystal/polymer composites. However, owing to the indistinct polymerization mechanism and curing condition discrepancy, the required polymer structures and electro-optical properties are hard to be controlled precisely. Herein, a novel polymer-stabilized liquid crystal film based on acrylate/epoxy resin is proposed, fabricated and the relationships between preparation process, polymer content, polymer morphology and electro-optical properties are studied. The in-situ photopolymerization of acrylate/epoxy resin liquid crystalline polymer is fulfilled using cation photo-initiator UV 6976. The distinct photopolymerization speed between acrylate and epoxy resin benefits the polymer morphology control, and with accurate containment of the polymerization process and polymer composition, the superior electro-optical properties at a higher polymer content are acquired. The polymer morphology and electro-optical properties are influenced by the polymer content and mass ratio between acrylate and epoxy resin. The best electro-optical properties among samples are attained by controlling the mass ratio between acrylate and epoxy resin to 1:1, integrating higher densities of scattering centers and lower anchoring effect. With higher polymer content, the strategy of increasing the mass ratio of E6M benefits the improvement of E-O properties for alleviating polymer density. This work provides insights to stepwise polymerization of liquid crystalline monomers and offers a fancy strategy for the preparation of novel liquid crystal dimming films.

Effect of Bone Marrow Stromal Cells Derived miR-26b on Chondrocytes of Osteoporosis Rats.

OBJECTIVE: Osteoporosis is a common bone disease. miR-26b regulates OA-induced osteogenesis and induces osteoporosis. miR-26b is elevated in bone marrow stromal cells (BMSCs) during bone formation; however, we haven't fully revealed whether it is directly involved in this process, which was the aim of this study. METHODS: An oophorectomized rat model of osteoporosis was used. BMSCs were detected by electron microscopy of exosomes, and mir-26b levels were detected by RT-PCR. The correlation between mir-26b and sirt2 was detected by bioinformatics and luciferase activity analysis. Bone microstructure and cartilage moisture content were also measured. The proliferation ability of mir-26b and sirt2 on chondrocytes was detected by cell viability test and flow cytometry. RESULTS: Western blotting further proved that the surface markers of isolated granular exosomes were positive for CD63 and CD81. Further analysis showed that exosomes' diameters ranged from 50 to 150 nm. Mir-26b is elevated in BMSC, and its mimics can promote proliferation. Luciferase showed that mir-26b targets sirt2 and the effect of elevated mir-26b on chondrocytes was completely reversed by silencing sirt2. The proliferation ability of C28/I2 chondrocytes in Mir MICs group was lower than other two groups, while that in Mir inhibition group had stronger proliferation ability than in the Mir NC group. mir-26b was highly expressed in BMSC, indicating that mir-26b comes from secretion of BMSC. CONCLUSION: Mir-26 is highly expressed in OP. mir-26b can therefore target sirt2 to promote proliferation and inhibit apoptosis of OP chondrocytes. It may offer a possibility of a treatment of OP in the future.

Thickness Measurements with EMAT Based on Fuzzy Logic.

Metal thickness measurements are essential in various industrial applications, yet current non-contact ultrasonic methods face limitations in range and accuracy, hindering the widespread adoption of electromagnetic ultrasonics. This study introduces a novel combined thickness measurement method employing fuzzy logic, with the aim of broadening the applicational scope of the EMAT. Leveraging minimal hardware, this method utilizes the short pulse time-of-flight (TOF) technique for initial thickness estimation, followed by secondary measurements guided by fuzzy logic principles. The integration of measurements from the resonance, short pulse echo, and linear frequency modulation echo extends the measurement range while enhancing accuracy. Rigorous experimental validation validates the method's effectiveness, demonstrating a measurement range of 0.3-1000.0 mm with a median error within ±0.5 mm. Outperforming traditional methods like short pulse echoes, this approach holds significant industrial potential.

Reverse-Mode Polymer-Stabilized Liquid Crystal Films with Enhanced Peel Strength and Electro-Optical Performance Based on Photoreactive Self-Assembly Alignment Layers and Patterned Polymer Walls.

Polymer-stabilized liquid crystal (PSLC) is a promising material toward the practical application of serving as energy-saving reverse-mode smart windows owing to its superior electro-optical (E-O) properties, simple and efficient processability, and compatibility to most practical circumstances. However, its feeble peel strength originated from low polymer content and poor adhesion between polymer networks and substrates inhibited its large-scale flexible film production. It is still a challenging task to derive good mechanical properties and superior E-O performance for PSLCs at the same time. In this study, a highly durable liquid crystal/polymer composite film showing enhanced peel strength and excellent E-O properties was attained by simultaneously building photoreactive self-assemble alignment layers through an efficient one-step method and the sculpture of a patterned polymer wall structure. This film has comprehensive ascendant E-O properties of lower driving voltages, faster response times, and higher contrast ratio, together with an over 30 times lift of the peel strength. The effectuation mechanisms of the alignment, E-O properties, peel-strength, microstructures, and cyclic durability of the films have been systematically studied. This novel liquid crystal/polymer composite film demonstrates advantages in every aspect of performance compared to traditional PSLC devices, which hoards promising applications in smart windows for cars and buildings.

Gut microbiota composition links to variation in functional domains across psychiatric disorders.

OBJECTIVE: Changes in microbial composition are observed in various psychiatric disorders, but their specificity to certain symptoms or processes remains unclear. This study explores the associations between the gut microbiota composition and the Research Domain Criteria (RDoC) domains of functioning, representing symptom domains, specifically focusing on stress-related and neurodevelopmental disorders in patients with and without psychiatric comorbidity. METHODS: The gut microbiota was analyzed in 369 participants, comprising 272 individuals diagnosed with a mood disorder, anxiety disorder, attention deficit/hyperactivity disorder, autism spectrum disorder, and/or substance use disorder, as well as 97 psychiatrically unaffected individuals. The RDoC domains were estimated using principal component analysis (PCA) with oblique rotation on a range of psychiatric, psychological, and personality measures. Associations between the gut microbiota and the functional domains were assessed using multiple linear regression and permanova, adjusted for age, sex, diet, smoking, medication use and comorbidity status. RESULTS: Four functional domains, aligning with RDoC's negative valence, social processes, cognitive systems, and arousal/regulatory systems domains, were identified. Significant associations were found between these domains and eight microbial genera, including associations of negative valence with the abundance of the genera Sellimonas, CHKCI001, Clostridium sensu stricto 1, Oscillibacter, and Flavonifractor; social processes with Sellimonas; cognitive systems with Sporobacter and Hungatella; and arousal/regulatory systems with Ruminococcus torques (all pFDR < 0.05). CONCLUSION: Our findings demonstrate associations between the gut microbiota and the domains of functioning across patients and unaffected individuals, potentially mediated by immune-related processes. These results open avenues for microbiota-focused personalized interventions, considering psychiatric comorbidity. However, further research is warranted to establish causality and elucidate mechanistic pathways.

Unsupervised underwater imaging based on polarization and binocular depth estimation.

Scattering caused by suspended particles in the water severely reduces the radiance of the scene. This paper proposes an unsupervised underwater restoration method based on binocular estimation and polarization. Based on the correlation between the underwater transmission process and depth, this method combines the depth information and polarization information in the scene, uses the neural network to perform global optimization and the depth information is recalculated and updated in the network during the optimization process, and reduces the error generated by using the polarization image to calculate parameters, so that detailed parts of the image are restored. Furthermore, the method reduces the requirement for rigorous pairing of data compared to previous approaches for underwater imaging using neural networks. Experimental results show that this method can effectively reduce the noise in the original image and effectively preserve the detailed information in the scene.

Principal and independent genomic components of brain structure and function.

The highly polygenic and pleiotropic nature of behavioural traits, psychiatric disorders and structural and functional brain phenotypes complicate mechanistic interpretation of related genome-wide association study (GWAS) signals, thereby obscuring underlying causal biological processes. We propose genomic principal and independent component analysis (PCA, ICA) to decompose a large set of univariate GWAS statistics of multimodal brain traits into more interpretable latent genomic components. Here we introduce and evaluate this novel methods various analytic parameters and reproducibility across independent samples. Two UK Biobank GWAS summary statistic releases of 2240 imaging-derived phenotypes (IDPs) were retrieved. Genome-wide beta-values and their corresponding standard-error scaled z-values were decomposed using genomic PCA/ICA. We evaluated variance explained at multiple dimensions up to 200. We tested the inter-sample reproducibility of output of dimensions 5, 10, 25 and 50. Reproducibility statistics of the respective univariate GWAS served as benchmarks. Reproducibility of 10-dimensional PCs and ICs showed the best trade-off between model complexity and robustness and variance explained (PCs: |rz - max| = 0.33, |rraw - max| = 0.30; ICs: |rz - max| = 0.23, |rraw - max| = 0.19). Genomic PC and IC reproducibility improved substantially relative to mean univariate GWAS reproducibility up to dimension 10. Genomic components clustered along neuroimaging modalities. Our results indicate that genomic PCA and ICA decompose genetic effects on IDPs from GWAS statistics with high reproducibility by taking advantage of the inherent pleiotropic patterns. These findings encourage further applications of genomic PCA and ICA as fully data-driven methods to effectively reduce the dimensionality, enhance the signal to noise ratio and improve interpretability of high-dimensional multitrait genome-wide analyses.

Multi-polygenic scores in psychiatry: From disorder specific to transdiagnostic perspectives.

The dense co-occurrence of psychiatric disorders questions the categorical classification tradition and motivates efforts to establish dimensional constructs with neurobiological foundations that transcend diagnostic boundaries. In this study, we examined the genetic liability for eight major psychiatric disorder phenotypes under both a disorder-specific and a transdiagnostic framework. The study sample (n = 513) was deeply phenotyped, consisting of 452 patients from tertiary care with mood disorders, anxiety disorders (ANX), attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorders, and/or substance use disorders (SUD) and 61 unaffected comparison individuals. We computed subject-specific polygenic risk score (PRS) profiles and assessed their associations with psychiatric diagnoses, comorbidity status, as well as cross-disorder behavioral dimensions derived from a rich battery of psychopathology assessments. High PRSs for depression were unselectively associated with the diagnosis of SUD, ADHD, ANX, and mood disorders (p < 1e-4). In the dimensional approach, four distinct functional domains were uncovered, namely the negative valence, social, cognitive, and regulatory systems, closely matching the major functional domains proposed by the Research Domain Criteria (RDoC) framework. Critically, the genetic predisposition for depression was selectively reflected in the functional aspect of negative valence systems (R2 = 0.041, p = 5e-4) but not others. This study adds evidence to the ongoing discussion about the misalignment between current psychiatric nosology and the underlying psychiatric genetic etiology and underscores the effectiveness of the dimensional approach in both the functional characterization of psychiatric patients and the delineation of the genetic liability for psychiatric disorders.

Super-resolution non-line-of-sight imaging based on temporal encoding.

Non-line-of-sight (NLOS) imaging techniques have the ability to reconstruct objects beyond line-of-sight view, which would be useful in a variety of applications. In transient NLOS techniques, a fundamental problem is that the time resolution of imaging depends on the single-photon timing resolution (SPTR) of a detector. In this paper, a temporal super-resolution method named temporal encoding non-line-of-sight (TE-NLOS) is proposed. Specifically, by exploiting the spatial-temporal correlation among transient images, high-resolution transient images can be reconstructed through modulator encoding. We have demonstrated that the proposed method is capable of reconstructing transient images with a time resolution of 20 picoseconds from a detector with a limited SPTR of approximately nanoseconds. In systems with low time jitter, this method exhibits superior accuracy in reconstructing objects compared to direct detection, and it also demonstrates robustness against miscoding. Utilizing high-frequency modulation, our framework can reconstruct accurate objects with coarse-SPTR detectors, which provides an enlightening reference for solving the problem of hardware defects.

Prognostic significance of PD-L1 expression in pancreatic cancer: evidence from an updated meta-analysis.

Recent studies revealed that programmed cell death ligand 1 (PD-L1) expression was associated with unfavorable prognosis in various solid tumors, but its clinical relevance for pancreatic cancer has not yet been well established. This meta-analysis summarizes the potential prognostic value of PD-L1 in pancreatic cancer. A quantitative meta-analysis was performed by a systematic search of databases including PubMed, EMBASE, Web of Science, Cochrane library, Scopus and Ovid for eligible studies on the prognostic significance of PD-L1 in pancreatic cancer patients. Pooled hazard ratios (HRs) and their 95% confidence intervals (CIs) were calculated to evaluate the strength of the link between PD-L1 expression and clinical prognosis of patients. Seventeen eligible studies with 2669 patients were included in our study. A significant association was observed between PD-L1 abundance and poor overall survival (OS) of patients with pancreatic cancers, with a pooled hazard ratio (HR) of 1.902, 95% CI: 1.657-2.184. Sensitivity analysis confirmed the reliability of our results. Subgroup analysis shows that differences in regions and detection methods of PD-L1 did not change the overall predictive value of PD-L1 for poor prognosis in pancreatic cancer patients. This meta-analysis indicated that the expression of PD-L1 is associated with a worse OS in pancreatic cancer patients. Additionally, PD-L1 may act as a potential parameter for predicting poor prognosis and thus providing a promising target for anticancer therapy in pancreatic cancer.