Topological wetting states of microdroplets on closed-loop structured surfaces: Breakdown of the Gibbs equation at the microscale

Microdroplets are a class of soft matter that has been extensively employed for chemical, biochemical, and industrial applications. However, fabricating microdroplets with largely controllable contact-area shape and apparent contact angle, a key prerequisite for their applications, is still a challenge. Here, by engineering a type of surface with homocentric closed-loop microwalls/microchannels, we can achieve facile size, shape, and contact-angle tunability of microdroplets on the textured surfaces by design. More importantly, this class of surface topologies (with universal genus value = 1) allows us to reveal that the conventional Gibbs equation (widely used for assessing the edge effect on the apparent contact angle of macrodroplets) seems no longer applicable for water microdroplets or nanodroplets (evidenced by independent molecular dynamics simulations). Notably, for the flat surface with the intrinsic contact angle ~0°, we find that the critical contact angle on the microtextured counterparts (at edge angle 90°) can be as large as >130°, rather than 90° according to the Gibbs equation. Experiments show that the breakdown of the Gibbs equation occurs for microdroplets of different types of liquids including alcohol and hydrocarbon oils. Overall, the microtextured surface design and topological wetting states not only offer opportunities for diverse applications of microdroplets such as controllable chemical reactions and low-cost circuit fabrications but also provide testbeds for advancing the fundamental surface science of wetting beyond the Gibbs equation.

Development of a Serum-Based MicroRNA Signature for Early Detection of Pancreatic Cancer: A Multicenter Cohort Study

BACKGROUND

A grim prognosis of pancreatic cancer (PCa) was attributed to the difficulty in early diagnosis of the disease.

AIMS

Identifying novel biomarkers for early detection of PCa is thus urgent to improve the overall survival rates of patients.

METHODS

The study was performed firstly by identification of candidate microRNAs (miRNAs) in formalin-fixed, paraffin-embedded tissues using microarray profiles, and followed by validation in a serum-based cohort study to assess clinical utility of the candidates. In the cohorts, a total of 1273 participants from four centers were retrospectively recruited as two cohorts including training and validation cohort. The collected serum specimens were analyzed by real-time polymerase chain reaction.

RESULTS

We identified 27 miRNAs expressed differentially in PCa tissues as compared to the benign. Of which, the top-four was selected as a panel whose diagnostic efficacy was fully assessed in the serum specimens. The panel exhibited superior to CA19-9, CA125, CEA and CA242 in discriminating patients with early stage PCa from healthy controls or non-PCa including chronic pancreatitis as well as pancreatic cystic neoplasms, with the area under the curves (AUC) of 0.971 (95% CI 0.956-0.987) and 0.924 (95% CI 0.899-0.949), respectively. Moreover, the panel eliminated interference from other digestive tumors with a specificity of 90.2%.

CONCLUSIONS

A panel of four serum miRNAs was developed showing remarkably discriminative ability of early stage PCa from either healthy controls or other pancreatic diseases, suggesting it may be developed as a novel, noninvasive approach for early screening of PCa in clinic.

Deep-learning segmentation method for optical coherence tomography angiography in ophthalmology

PURPOSE

The optic disc and the macular are two major anatomical structures in the human eye. Optic discs are associated with the optic nerve. Macular mainly involves degeneration and impaired function of the macular region. Reliable optic disc and macular segmentation are necessary for the automated screening of retinal diseases.

METHODS

A swept-source OCTA system was designed to capture OCTA images of human eyes. To address these segmentation tasks, first, we constructed a new Optic Disc and Macula in fundus Image with optical coherence tomography angiography (OCTA) dataset (ODMI). Second, we proposed a Coarse and Fine Attention-Based Network (CFANet).

RESULTS

The five metrics of our methods on ODMI are 98.91 % , 98.47 % , 89.77 % , 98.49 % , and 89.77 % , respectively.

CONCLUSIONS

Experimental results show that our CFANet has achieved good performance on segmentation for the optic disc and macula in OCTA.

Polymer Multi-Block and Multi-Block+ Strategies for the Upcycling of Mixed Polyolefins and Other Plastics

Due to a continued rise in the production and use of plastic products, their end-of-life pollution has become a pressing global issue. One of the biggest challenges in plastics recycling is the separation of different polymers. Multi-block copolymers (MBCPs) represent an efficient strategy for the upcycling of mixed plastics via induced compatibilization, but this approach is limited by difficulties associated with synthesis and structural modification. In this contribution, several synthetic strategies are explored to prepare MBCPs with tunable microstructures, which were then used as compatibilizer additives to upcycle mixtures of polyolefins with other plastics. A multi-block+ strategy based on a reactive telechelic block copolymer platform was introduced, which enabled block extension during the in situ melt blending of mixed plastics, leading to better compatibilizing properties as well as better 3D printing capability. This strategy was also applicable to more complex ternary plastic blends. The polymer multi-block strategy enabled by versatile MBCPs synthesis and the multi-block+ strategy enabled by in situ block extension show exciting opportunities for the upcycling of mixed plastics.

Disentangling the latent space of GANs for semantic face editing

Disentanglement research is a critical and important issue in the field of image editing. In order to perform disentangled editing on images generated by generative models, this paper presents an unsupervised, model-agnostic, two-stage trained editing framework. This work addresses the problem of discovering interpretable, disentangled directions of edited image attributes in the latent space of generative models. This effort's primary objective was to address the limitations discovered in previous research, mainly (a) the discovered editing directions are interpretable but significantly entangled, i.e., changes to one attribute affect the others and (b) Prior research has utilized direction discovery and direction disentanglement separately, and they can't work synergistically. More specifically, this paper proposes a two-stage training method that discovers the editing direction with semantics, perturbs the dimension of the direction vector, adjusts it with a penalty mechanism, and makes the editing direction more disentangled. This allows easy distinguishable image editing, such as age and facial expressions in facial images. Experimentally compared to other methods, the proposed method outperforms them both qualitatively and quantitatively in terms of interpretability, disentanglement, and distinguishability of the generated images. The implementation of our method is available at https://github.com/ydniuyongjie/twoStageForFaceEdit.

Situation updating during discourse comprehension recruits right posterior portion of the multiple-demand network

Discourse comprehension involves the construction of a mental representation of the situation model as well as a continuous update of this representation. This mental update is cognitively demanding and likely engages the multiple-demand network. However, there is little evidence for the involvement of the multiple-demand network during situation updating. In this study, we used fMRI to test whether situation updating based on the change of spatial location activated the multiple-demand network. In a discourse comprehension task, readers read two-sentence discourses in which the second sentence either continues or introduces a shift of the spatial location information presented in the first sentence. Compared to situation continuation, situation updating reliably activated the right superior parietal lobule. This area is a part of the multiple-demand network as defined by a digit N-back localizer task and locates within the dorsal attention network as defined in the previous study by Yeo et al. in 2011. Our results provide evidence for the reliable involvement of a specific area of the multiple-demand network in situation updating during high-level discourse processing.

FLI1 Regulates Histamine Decarboxylase Expression to Control Inflammation Signaling and Leukemia Progression

Aim

Histamine decarboxylase (HDC) catalyzes decarboxylation of histidine to generate histamine. This enzyme affects several biological processes including inflammation, allergy, asthma, and cancer, although the underlying mechanism is not fully understood. The present study provides a novel insight into the relationship between the transcription factor FLI1 and its downstream target HDC, and their effects on inflammation and leukemia progression.

Methods

Promoter analysis combined with chromatin immunoprecipitation (ChIp) was used to demonstrate binding of FLI1 to the promoter of HDC in leukemic cells. Western blotting and RT-qPCR were used to determine expression of HDC and allergy response genes, and lentivirus shRNA was used to knock-down target genes. Proliferation, cell cycle, apoptosis assays and molecular docking were used to determine the effect of HDC inhibitors in culture. An animal model of leukemia was employed to test the effect of HDC inhibitory compounds in vivo.

Results

Results presented herein demonstrate that FLI1 transcriptionally regulates HDC by direct binding to its promoter. Using genetic and pharmacological inhibition of HDC, or the addition of histamine, the enzymatic product of HDC, we show neither have a discernable effect on leukemic cell proliferation in culture. However, HDC controls several inflammatory genes including IL1B and CXCR2 that may influence leukemia progression in vivo through the tumor microenvironment. Indeed, diacerein, an IL1B inhibitor, strongly blocked Fli-1-induced leukemia in mice. In addition to allergy, FLI1 is shown to regulate genes associated with asthma such as IL1B, CPA3 and CXCR2. Toward treatment of these inflammatory conditions, epigallocatechin (EGC), a tea polyphenolic compound, is found strongly inhibit HDC independently of FLI1 and its downstream effector GATA2. Moreover, the HDC inhibitor, tetrandrine, suppressed HDC transcription by directly binding to and inhibiting the FLI1 DNA binding domain, and like other FLI1 inhibitors, tetrandrine strongly suppressed cell proliferation in culture and leukemia progression in vivo.

Conclusion

These results suggest a role for the transcription factor FLI1 in inflammation signaling and leukemia progression through HDC and point to the HDC pathway as potential therapeutics for FLI1-driven leukemia.

Combinatorial interactions between viral proteins expand the potential functional landscape of the tomato yellow leaf curl virus proteome

Viruses manipulate the cells they infect in order to replicate and spread. Due to strict size restrictions, viral genomes have reduced genetic space; how the action of the limited number of viral proteins results in the cell reprogramming observed during the infection is a long-standing question. Here, we explore the hypothesis that combinatorial interactions may expand the functional landscape of the viral proteome. We show that the proteins encoded by a plant-infecting DNA virus, the geminivirus tomato yellow leaf curl virus (TYLCV), physically associate with one another in an intricate network, as detected by a number of protein-protein interaction techniques. Importantly, our results indicate that intra-viral protein-protein interactions can modify the subcellular localization of the proteins involved. Using one particular pairwise interaction, that between the virus-encoded C2 and CP proteins, as proof-of-concept, we demonstrate that the combination of viral proteins leads to novel transcriptional effects on the host cell. Taken together, our results underscore the importance of studying viral protein function in the context of the infection. We propose a model in which viral proteins might have evolved to extensively interact with other elements within the viral proteome, enlarging the potential functional landscape available to the pathogen.

Viruses are obligate intracellular parasites that depend on the molecular machinery of their host cell to complete their life cycle. For this purpose, viruses co-opt host processes, modulating or redirecting them. Most viruses have small genomes, and hence limited coding capacity. During the viral invasion, virus-encoded proteins will be produced in large amounts and coexist in the infected cell, which enables physical or functional interactions among viral proteins, potentially expanding the virus-host functional interface by increasing the number of potential targets in the host cell and/or synergistically modulating the cellular environment. Examples of interactions between viral proteins have been recently documented for both animal and plant viruses; however, the hypothesis that viral proteins might have a combinatorial effect, which would lead to the acquisition of novel functions, lacks systematic experimental validation. Here, we use the geminivirus tomato yellow leaf curl virus (TYLCV), a plant-infecting virus with reduced proteome and causing devastating diseases in crops, to test the idea that combinatorial interactions between viral proteins exist and might underlie an expansion of the functional landscape of the viral proteome. Our results indicate that viral proteins prevalently interact with one another in the context of the infection, which can result in the acquisition of novel functions.

A 3,000-year-old, basal S. enterica lineage from Bronze Age Xinjiang suggests spread along the Proto-Silk Road

Salmonella enterica (S. enterica) has infected humans for a long time, but its evolutionary history and geographic spread across Eurasia is still poorly understood. Here, we screened for pathogen DNA in 14 ancient individuals from the Bronze Age Quanergou cemetery (XBQ), Xinjiang, China. In 6 individuals we detected S. enterica. We reconstructed S. enterica genomes from those individuals, which form a previously undetected phylogenetic branch basal to Paratyphi C, Typhisuis and Choleraesuis-the so-called Para C lineage. Based on pseudogene frequency, our analysis suggests that the ancient S. enterica strains were not host adapted. One genome, however, harbors the Salmonella pathogenicity island 7 (SPI-7), which is thought to be involved in (para)typhoid disease in humans. This offers first evidence that SPI-7 was acquired prior to the emergence of human-adapted Paratyphi C around 1,000 years ago. Altogether, our results show that Salmonella enterica infected humans in Eastern Eurasia at least 3,000 years ago, and provide the first ancient DNA evidence for the spread of a pathogen along the Proto-Silk Road.

Displacement Detection Decoupling in Counter-Propagating Dual-Beams Optical Tweezers with Large-Sized Particle

As a kind of ultra-sensitive acceleration sensing platform, optical tweezers show a minimum measurable value inversely proportional to the square of the diameter of the levitated spherical particle. However, with increasing diameter, the coupling of the displacement measurement between the axes becomes noticeable. This paper analyzes the source of coupling in a forward-scattering far-field detection regime and proposes a novel method of suppression. We theoretically and experimentally demonstrated that when three variable irises are added into the detection optics without changing other parts of optical structures, the decoupling of triaxial displacement signals mixed with each other show significant improvement. A coupling detection ratio reduction of 49.1 dB and 22.9 dB was realized in radial and axial directions, respectively, which is principally in accord with the simulations. This low-cost and robust approach makes it possible to accurately measure three-dimensional mechanical quantities simultaneously and may be helpful to actively cool the particle motion in optical tweezers even to the quantum ground state in the future.

Rice qGL3/OsPPKL1 Functions with the GSK3/SHAGGY-Like Kinase OsGSK3 to Modulate Brassinosteroid Signaling

Brassinosteroids (BRs) are steroid hormones that play essential roles in plant growth and development. We previously cloned qGL3, a major quantitative trait locus regulating grain length in rice (Oryza sativa). The O. sativa japonica var N411 has extra-large grains compared with the O. sativa indica var 9311, and the recessive qgl3 allele from N411 contributes positively to grain length. qGL3 encodes a putative protein phosphatase with Kelch-like repeat domains, an ortholog of Arabidopsis (Arabidopsis thaliana) brassinosteroid-insensitive1 SUPPRESSOR1 (BSU1). BSU1 positively regulates BR signaling, while overexpression of qGL3 induced BR loss-of-function phenotypes. Both qGL3N411 and qGL39311 physically interact with the rice glycogen synthase kinase 3 (GSK3)/SHAGGY-like kinase 3 (OsGSK3), an ortholog of Arabidopsis BR INSENSITIVE2 (BIN2). qGL39311 dephosphorylates OsGSK3, but qGL3N411 lacks this activity. Knocking out OsGSK3 enhances BR signaling and induces nuclear localization of O. sativa BRASSINAZOLE RESISTANT1 (OsBZR1). Unlike the dephosphorylation of BIN2 (which leads to protein degradation) in Arabidopsis, qGL3 dephosphorylates and stabilizes OsGSK3 in rice. These results demonstrate that qGL3 suppresses BR signaling by regulating the phosphorylation and stability of OsGSK3, which modulates OsBZR1 phosphorylation and subcellular distribution. Our study clarifies the role of qGL3 in the regulation of grain length and provides insight into BR signaling, including the differences between rice and Arabidopsis.

Single-pixel computational ghost imaging with helicity-dependent metasurface hologram

Different optical imaging techniques are based on different characteristics of light. By controlling the abrupt phase discontinuities with different polarized incident light, a metasurface can host a phase-only and helicity-dependent hologram. In contrast, ghost imaging (GI) is an indirect imaging modality to retrieve the object information from the correlation of the light intensity fluctuations. We report single-pixel computational GI with a high-efficiency reflective metasurface in both simulations and experiments. Playing a fascinating role in switching the GI target with different polarized light, the metasurface hologram generates helicity-dependent reconstructed ghost images and successfully introduces an additional security lock in a proposed optical encryption scheme based on the GI. The robustness of our encryption scheme is further verified with the vulnerability test. Building the first bridge between the metasurface hologram and the GI, our work paves the way to integrate their applications in the fields of optical communications, imaging technology, and security.