Dynamics in polymers with phase separated dynamic bonds: the case of a peculiar temperature dependence.

The topic of polymers with dynamic bonds (stickers) appears as an exciting and promising area of materials science, thanks to their attractive self-healable, recyclable, extremely tough, and super extensible properties. Polymers with phase separated dynamic bonds revealed several unique properties, but mechanisms controlling their viscoelastic properties remain poorly understood. In this work, we present a dynamic analysis of a model polymer system with phase separated hydrogen bonding functionalities. The results confirm that terminal relaxation in these systems is independent of polymer segmental dynamics and is instead controlled by structural relaxations in clusters of stickers. Detailed analysis revealed a surprising result: terminal relaxation time of these systems has weaker temperature dependence than that of structural relaxation in clusters, although the former is slower than the latter. Borrowing ideas from the field of block copolymers, we ascribed this unusual result to an LCST-like behavior for the miscibility of the stickers in the polymer matrix. The presented results and ideas deepen the understanding of the viscoelasticity for polymers with dynamic bonds, enabling intelligent design of functional materials with desired macroscopic properties.

A novel machine learning algorithm selects proteome signature to specifically identify cancer exosomes.

Non-invasive early cancer diagnosis remains challenging due to the low sensitivity and specificity of current diagnostic approaches. Exosomes are membrane-bound nanovesicles secreted by all cells that contain DNA, RNA, and proteins that are representative of the parent cells. This property, along with the abundance of exosomes in biological fluids makes them compelling candidates as biomarkers. However, a rapid and flexible exosome-based diagnostic method to distinguish human cancers across cancer types in diverse biological fluids is yet to be defined. Here, we describe a novel machine learning-based computational method to distinguish cancers using a panel of proteins associated with exosomes. Employing datasets of exosome proteins from human cell lines, tissue, plasma, serum, and urine samples from a variety of cancers, we identify Clathrin Heavy Chain (CLTC), Ezrin, (EZR), Talin-1 (TLN1), Adenylyl cyclase-associated protein 1 (CAP1), and Moesin (MSN) as highly abundant universal biomarkers for exosomes and define three panels of pan-cancer exosome proteins that distinguish cancer exosomes from other exosomes and aid in classifying cancer subtypes employing random forest models. All the models using proteins from plasma, serum, or urine-derived exosomes yield AUROC scores higher than 0.91 and demonstrate superior performance compared to Support Vector Machine, K Nearest Neighbor Classifier and Gaussian Naive Bayes. This study provides a reliable protein biomarker signature associated with cancer exosomes with scalable machine learning capability for a sensitive and specific non-invasive method of cancer diagnosis.

Effects of psychological intervention on negative emotions and psychological resilience in breast cancer patients after radical mastectomy.

Breast cancer (BC)is the most common malignant tumor in women, and the treatment process not only results in physical pain but also significant psychological distress in patients. Psychological intervention (PI) has been recognized as an important approach in treating postoperative psychological disorders in BC patients. It has been proven that PI has a significant therapeutic effect on post-operative psychological disorders, improving patients' negative emotions, enhancing their psychological resilience, and effectively enhancing their quality of life and treatment compliance.

Ductile adhesive elastomers with force-triggered ultra-high adhesion strength.

Elastomers play a vital role in many forthcoming advanced technologies in which their adhesive properties determine materials' interface performance. Despite great success in improving the adhesive properties of elastomers, permanent adhesives tend to stick to the surfaces prematurely or result in poor contact depending on the installation method. Thus, elastomers with on-demand adhesion that is not limited to being triggered by UV light or heat, which may not be practical for scenarios that do not allow an additional external source, provide a solution to various challenges in conventional adhesive elastomers. Herein, we report a novel, ready-to-use, ultra high-strength, ductile adhesive elastomer with an on-demand adhesion feature that can be easily triggered by a compression force. The precursor is mainly composed of a capsule-separated, two-component curing system. After a force-trigger and curing process, the ductile adhesive elastomer exhibits a peel strength and a lap shear strength of 1.2 × 104 N m-1 and 7.8 × 103 kPa, respectively, which exceed the reported values for advanced ductile adhesive elastomers. The ultra-high adhesion force is attributed to the excellent surface contact of the liquid-like precursor and to the high elastic modulus of the cured elastomer that is reinforced by a two-phase design. Incorporation of such on-demand adhesion into an elastomer enables a controlled delay between installation and curing so that these can take place under their individual ideal conditions, effectively reducing the energy cost, preventing failures, and improving installation processes.

Research status of internet-delivered cognitive behavioral therapy in cancer patients.

The latest global cancer burden data released by the International Agency for Research on Cancer of the World Health Organization in 2020 shows that there were 19.29 million new cancer cases worldwide, with 4.57 million in China, ranking first. The number of cancer survivors is increasing, with a 5-year survival rate exceeding 85%, but there are emotional disorders. Cognitive behavioral therapy (CBT) can improve negative emotions and has significant effects on patients. However, there is a limited number of physicians and high costs, so internet interventions have become a solution. The feasibility of web-based interventions for breast cancer patients has been proven. Research on internet-delivered CBT is also increasing. The purpose of this study was to review the concept of web-based CBT and its application status in cancer survivors, in order to provide relevant intervention for scholars and provide reference and supplement for patients to provide psychological therapy.

Highly Recyclable and Tough Elastic Vitrimers from a Defined Polydimethylsiloxane Network.

Despite intensive research on sustainable elastomers, achieving elastic vitrimers with significantly improved mechanical properties and recyclability remains a scientific challenge. Herein, inspired by the classical elasticity theory, we present a design principle for ultra-tough and highly recyclable elastic vitrimers with a defined network constructed by chemically crosslinking the pre-synthesized disulfide-containing polydimethylsiloxane (PDMS) chains with tetra-arm polyethylene glycol (PEG). The defined network is achieved by the reduced dangling short chains and the relatively uniform molecular weight of network strands. Such elastic vitrimers with the defined network, i.e., PDMS-disulfide-D, exhibit significantly improved mechanical performance than random analogous, previously reported PDMS vitrimers, and even commercial silicone-based thermosets. Moreover, unlike the vitrimers with random network that show obvious loss in mechanical properties after recycling, those with the defined network enable excellent thermal recyclability. The PDMS-disulfide-D also deliver comparable electrochemical signals if utilized as substrates for electromyography sensors after the recycling. The multiple relaxation processes are revealed via a unique physical approach. Multiple techniques are also applied to unravel the microscopic mechanism of the excellent mechanical performance and recyclability of such defined network.

Analysis of under-ice ambient noise characteristics of Gakkel Ridge in the Arctic.

This paper presents an analysis of the under-ice acoustic data and environmental parameters measured over a three-month period from August 31 to November 28, 2021, within the area of the Gakkel Ridge in the Arctic. After "spikes" caused by micro-level events are removed, the distribution of the retained under-ice noise related to macro-level events can be described satisfactorily by a Gaussian distribution, as verified by Q-Q plots and kurtosis/skewness analysis. We use sliding window analysis to deal with the features of under-ice ambient noise and model the data by Gaussian interpolation. This shows that the ambient noise level over the low-frequency range (10-100 Hz) is comparatively flat at about 60 dB; with the frequency increases from 100 to 2560 Hz, the ANL decreased to about 40 dB. We then introduce canonical correlation analysis (CCA) to analyze the potential relation between environmental forcing and the under-ice noise level. The results of CCA indicate that the seawater parameters (including temperature, salinity, and sound velocity) close to the ice-water interface have the greatest influence on the under-ice noise level among all environmental parameters recorded in the air, sea-ice, and seawater. Additionally, the under-ice noise level forced by the environment does not exhibit any particular frequency dependence.

KRASG12D inhibition reprograms the microenvironment of early and advanced pancreatic cancer to promote FAS-mediated killing by CD8+ T cells.

The KRASG12D mutation is present in nearly half of pancreatic adenocarcinomas (PDAC). We investigated the effects of inhibiting the KRASG12D mutant protein with MRTX1133, a non-covalent small molecule inhibitor of KRASG12D, on early and advanced PDAC and its influence on the tumor microenvironment. Employing 16 different models of KRASG12D-driven PDAC, we demonstrate that MRTX1133 reverses early PDAC growth, increases intratumoral CD8+ effector T cells, decreases myeloid infiltration, and reprograms cancer-associated fibroblasts. MRTX1133 leads to regression of both established PanINs and advanced PDAC. Regression of advanced PDAC requires CD8+ T cells and immune checkpoint blockade (ICB) synergizes with MRTX1133 to eradicate PDAC and prolong overall survival. Mechanistically, inhibition of KRASG12D in advanced PDAC and human patient derived organoids induces FAS expression in cancer cells and facilitates CD8+ T cell-mediated death. Collectively, this study provides a rationale for a synergistic combination of MRTX1133 with ICB in clinical trials.

Elimination of oncogenic KRAS in genetic mouse models eradicates pancreatic cancer by inducing FAS-dependent apoptosis by CD8+ T cells.

Oncogenic KRASG12D (KRAS∗) is critical for the initiation and maintenance of pancreatic ductal adenocarcinoma (PDAC) and is a known repressor of tumor immunity. Conditional elimination of KRAS∗ in genetic mouse models of PDAC leads to the reactivation of FAS, CD8+ T cell-mediated apoptosis, and complete eradication of tumors. KRAS∗ elimination recruits activated CD4+ and CD8+ T cells and promotes the activation of antigen-presenting cells. Mechanistically, KRAS∗-mediated immune evasion involves the epigenetic regulation of Fas death receptor in cancer cells, via methylation of its promoter region. Furthermore, analysis of human RNA sequencing identifies that high KRAS expression in PDAC tumors shows a lower proportion of CD8+ T cells and demonstrates shorter survival compared with tumors with low KRAS expression. This study highlights the role of CD8+ T cells in the eradication of PDAC following KRAS∗ elimination and provides a rationale for the combination of KRAS∗ targeting with immunotherapy to control PDAC.

A novel machine learning algorithm selects proteome signature to specifically identify cancer exosomes.

Non-invasive early cancer diagnosis remains challenging due to the low sensitivity and specificity of current diagnostic approaches. Exosomes are membrane-bound nanovesicles secreted by all cells that contain DNA, RNA, and proteins that are representative of the parent cells. This property, along with the abundance of exosomes in biological fluids makes them compelling candidates as biomarkers. However, a rapid and flexible exosome-based diagnostic method to distinguish human cancers across cancer types in diverse biological fluids is yet to be defined. Here, we describe a novel machine learning-based computational method to distinguish cancers using a panel of proteins associated with exosomes. Employing datasets of exosome proteins from human cell lines, tissue, plasma, serum and urine samples from a variety of cancers, we identify Clathrin Heavy Chain (CLTC), Ezrin, (EZR), Talin-1 (TLN1), Adenylyl cyclase-associated protein 1 (CAP1) and Moesin (MSN) as highly abundant universal biomarkers for exosomes and define three panels of pan-cancer exosome proteins that distinguish cancer exosomes from other exosomes and aid in classifying cancer subtypes employing random forest models. All the models using proteins from plasma, serum, or urine-derived exosomes yield AUROC scores higher than 0.91 and demonstrate superior performance compared to Support Vector Machine, K Nearest Neighbor Classifier and Gaussian Naive Bayes. This study provides a reliable protein biomarker signature associated with cancer exosomes with scalable machine learning capability for a sensitive and specific non-invasive method of cancer diagnosis.

Puncture-resistant self-healing polymers with multi-cycle adhesion and rapid healability.

The structural design of self-healing materials determines the ultimate performance of the product that can be used in a wide range of applications. Incorporating intrinsic self-healing moieties into puncture-resistant materials could significantly improve the failure resistance and product longevity, since their rapidly rebuilt bonds will provide additional recovery force to resist the external force. Herein, we present a series of tailored urea-modified poly(dimethylsiloxane)-based self-healing polymers (U-PDMS-SPs) that exhibit excellent puncture-resistant properties, fast autonomous self-healing, multi-cycle adhesion capabilities, and well-tunable mechanical properties. Controlling the composition of chemical and physical cross-links enables the U-PDMS-SPs to have an extensibility of 528% and a toughness of 0.6 MJ m-3. U-PDMS-SPs exhibit fast autonomous self-healability with 25% strain recovery within 2 minutes of healing, and over 90% toughness recovery after 16 hours. We further demonstrate its puncture-resistant properties under the ASTM D5748 standard with an unbreakable feature. Furthermore, the multi-cycle adhesive properties of U-PDMS-SPs are also revealed. High puncture resistance (>327 mJ) and facile adhesion with rapid autonomous self-healability will have a broad impact on the design of adhesives, roofing materials, and many other functional materials with enhanced longevity.

Wearable Dual-Signal NH3 Sensor with High Sensitivity for Non-invasive Diagnosis of Chronic Kidney Disease.

NH3 gas in human exhaled breath contains abundant physiological information related to human health, especially chronic kidney disease (CKD). Unfortunately, up to now, most wearable NH3 sensors show inevitable defects (low sensitivity, easy to be interfered by the environment, etc.), which may lead to misdiagnosis of CKD. To solve the above dilemma, a nanoporous, heterogeneous, and dual-signal (optical and electrical) wearable NH3 sensor mask is developed successfully. More specifically, a polyacrylonitrile/bromocresol green (PAN/BCG) nanofiber film as a visual NH3 sensor and a polyacrylonitrile/polyaniline/reduced graphene oxide (PAN/PANI/rGO) nanofiber film as a resistive NH3 sensor are constructed. Due to the high specific surface area and abundant NH3 binding sites of these two nanofiber films, they exhibit good NH3 sensing performance. However, although the visual NH3 sensor (PAN/BCG nanofiber film) is simple without the need of any detecting facilities and quite stable when temperature and humidity change, it shows poor sensitivity and resolution. In comparison, the resistive NH3 sensor (PAN/PANI/rGO nanofiber film) is of high sensitivity, fast response, and good resolution, but its electrical signal is easily interfered by the external environment (such as humidity, temperature, etc.). Considering that the sensing principles between a visual NH3 sensor and resistive NH3 sensor are significantly different, a wearable dual-signal NH3 sensor containing both a visual NH3 sensor and resistive NH3 sensor is further explored. Our data prove that the two sensing signals in this dual-signal NH3 sensor mask can not only work well without interference with each other but also complement each other to improve the sensing accuracy, indicating its potential application in non-invasive diagnosis of CKD.

Antigen-presenting type-I conventional dendritic cells facilitate curative checkpoint blockade immunotherapy in pancreatic cancer.

Inflammation and tissue damage associated with pancreatitis can precede or occur concurrently with pancreatic ductal adenocarcinoma (PDAC). We demonstrate that in PDAC coupled with pancreatitis (ptPDAC), antigen-presenting type-I conventional dendritic cells (cDC1s) are specifically activated. Immune checkpoint blockade therapy (iCBT) leads to cytotoxic CD8 + T cell activation and eradication of ptPDAC with restoration of lifespan even upon PDAC re-challenge. Such eradication of ptPDAC was reversed following specific depletion of dendritic cells. Employing PDAC antigen-loaded cDC1s as a vaccine, immunotherapy-resistant PDAC was rendered sensitive to iCBT with a curative outcome. Analysis of the T-cell receptor (TCR) sequences in the tumor infiltrating CD8 + T cells following cDC1 vaccination coupled with iCBT identified unique CDR3 sequences with potential therapeutic significance. Our findings identify a fundamental difference in the immune microenvironment and adaptive immune response in PDAC concurrent with, or without pancreatitis, and provides a rationale for combining cDC1 vaccination with iCBT as a potential treatment option.

Oncogenic Kras G12D specific non-covalent inhibitor reprograms tumor microenvironment to prevent and reverse early pre-neoplastic pancreatic lesions and in combination with immunotherapy regresses advanced PDAC in a CD8 + T cells dependent manner.

Pancreatic ductal adenocarcinoma (PDAC) is associated with mutations in Kras, a known oncogenic driver of PDAC; and the KRAS G12D mutation is present in nearly half of PDAC patients. Recently, a non-covalent small molecule inhibitor (MRTX1133) was identified with specificity to the Kras G12D mutant protein. Here we explore the impact of Kras G12D inhibition by MRTX1133 on advanced PDAC and its influence on the tumor microenvironment. Employing different orthotopic xenograft and syngeneic tumor models, eight different PDXs, and two different autochthonous genetic models, we demonstrate that MRTX1133 reverses early PDAC growth, increases intratumoral CD8 + effector T cells, decreases myeloid infiltration, and reprograms cancer associated fibroblasts. Autochthonous genetic mouse models treated with MRTX1133 leads to regression of both established PanINs and advanced PDAC. Regression of advanced PDAC requires CD8 + T cells and immune checkpoint blockade therapy (iCBT) synergizes with MRTX1133 to eradicate PDAC and prolong overall survival. Mechanistically, inhibition of mutant Kras in advanced PDAC and human patient derived organoids (PDOs) induces Fas expression in cancer cells and facilitates CD8 + T cell mediated death. These results demonstrate the efficacy of MRTX1133 in different mouse models of PDAC associated with reprogramming of stromal fibroblasts and a dependency on CD8 + T cell mediated tumor clearance. Collectively, this study provides a rationale for a synergistic combination of MRTX1133 with iCBT in clinical trials.

Intrinsically Self-Healing Polymers: From Mechanistic Insight to Current Challenges.

Self-healing materials open new prospects for more sustainable technologies with improved material performance and devices' longevity. We present an overview of the recent developments in the field of intrinsically self-healing polymers, the broad class of materials based mostly on polymers with dynamic covalent and noncovalent bonds. We describe the current models of self-healing mechanisms and discuss several examples of systems with different types of dynamic bonds, from various hydrogen bonds to dynamic covalent bonds. The recent advances indicate that the most intriguing results are obtained on the systems that have combined different types of dynamic bonds. These materials demonstrate high toughness along with a relatively fast self-healing rate. There is a clear trade-off relationship between the rate of self-healing and mechanical modulus of the materials, and we propose design principles of polymers toward surpassing this trade-off. We also discuss various applications of intrinsically self-healing polymers in different technologies and summarize the current challenges in the field. This review intends to provide guidance for the design of intrinsic self-healing polymers with required properties.

Single-Ion Conducting Polymeric Protective Interlayer for Stable Solid Lithium-Metal Batteries.

With many reported attempts on fabricating single-ion conducting polymer electrolytes, they still suffer from low ionic conductivity, narrow voltage window, and high cost. Herein, we report an unprecedented approach on improving the cationic transport number (tLi+) of the polymer electrolyte, i.e., single-ion conducting polymeric protective interlayer (SIPPI), which is designed between the conventional polymer electrolyte (PVEC) and Li-metal electrode. Satisfied ionic conductivity (1 mS cm-1, 30 °C), high tLi+ (0.79), and wide-area voltage stability are realized by coupling the SIPPI with the PVEC electrolyte. Benefiting from this unique design, the Li symmetrical cell with the SIPPI shows stable cycling over 6000 h at 3 mA cm-2, and the full cell with the SIPPI exhibits stable cycling performance with a capacity retention of 86% over 1000 cycles at 1 C and 25 °C. This incorporated SIPPI on the Li anode presents an alternative strategy for enabling high-energy density, long cycling lifetime, and safe and cost-effective solid-state batteries.

Maslinic Acid Suppresses High Glucose-induced Inflammation by Epigenetically Inhibiting TXNIP Expression.

OBJECTIVE: Hyperglycemia-induced inflammation and subsequent endothelial injuries ultimately lead to the pathogenesis of cardiovascular diseases associated with high mortality, such as atherosclerosis. Maslinic acid (MA) is a phytochemical with anti-inflammatory activity. However, it remains unknown whether it can inhibit diabetes-associated cardiovascular inflammation. The present study aimed to determine the effect of MA on high glucose-induced endothelial inflammation and apoptosis in human umbilical vein endothelial cells (HUVECs) and to explore the underlying mechanism. METHODS: HUVECs were treated with high glucose to induce inflammation and apoptosis. Apoptosis was determined by flow cytometry. CCK-8 assay was used to examine cell viability. Production levels of cytokines were detected by quantitative realtime PCR (qPCR) and ELISA. Protein expression levels and signaling pathways activation were detected by Western blotting. RNA immunoprecipitation and qPCR were used to determine the N6-methyladenosine (m6A) levels of target mRNAs. RESULTS: MA promoted the recruitment of RNA demethylase ALKBH5 to TXNIP mRNA, and subsequently enhanced its m6A demethylation. By this means, MA decreased the stability of TXNIP mRNA and downregulated its expression level. Subsequently, reactive oxygen species (ROS) and production of pro-inflammatory cytokines, including TNF-α, IL-6 and IL-1ß, were inhibited. And high glucose-induced apoptosis in HUVECs was inhibited by MA. CONCLUSION: MA ameliorates high glucose-induced endothelial inflammation and injury, serving as a new potential therapeutic application for protecting against diabetes-associated atherosclerosis and other inflammatory diseases.

Unravelling the Influence of Surface Modification on the Ultimate Performance of Carbon Fiber/Epoxy Composites.

The overall performance of polymer composites depends on not only the intrinsic properties of the polymer matrix and inorganic filler but also the quality of interfacial adhesion. Although many reported approaches have been focused on the chemical treatment for improving interfacial adhesion, the examination of ultimate mechanical performance and long-term properties of polymer composites has been rarely investigated. Herein, we report carbon fiber (CF)/epoxy composites with improved interfacial adhesion by covalent bonding between CFs and the epoxy matrix. This leads to the improved ultimate mechanical properties and enhanced thermal aging performance. Raman mapping demonstrates the formation of an interphase region derived from the covalent bonding between CFs and the epoxy matrix, which enables the uniform fiber distribution and eliminates phase separation during thermal cycling. The covalent attachment of the CF to the epoxy matrix suppresses its migration during temperature fluctuations, preserving the mechanical performance of resulting composites under the thermal aging process. Furthermore, the finite elemental analysis reveals the effectiveness of the chemical treatment of CFs in improving the interfacial strength and toughness of silane-treated CF/epoxy composites. The insight into the mechanical improvement of CF/epoxy composites suggests the high potential of surface modification of inorganic fillers toward polymer composites with tunable properties for different applications.

Drug-Target Network Study Reveals the Core Target-Protein Interactions of Various COVID-19 Treatments.

The coronavirus disease 2019 (COVID-19) pandemic has caused a dramatic loss of human life and devastated the worldwide economy. Numerous efforts have been made to mitigate COVID-19 symptoms and reduce the death rate. We conducted literature mining of more than 250 thousand published works and curated the 174 most widely used COVID-19 medications. Overlaid with the human protein-protein interaction (PPI) network, we used Steiner tree analysis to extract a core subnetwork that grew from the pharmacological targets of ten credible drugs ascertained by the CTD database. The resultant core subnetwork consisted of 34 interconnected genes, which were associated with 36 drugs. Immune cell membrane receptors, the downstream cellular signaling cascade, and severe COVID-19 symptom risk were significantly enriched for the core subnetwork genes. The lung mast cell was most enriched for the target genes among 1355 human tissue-cell types. Human bronchoalveolar lavage fluid COVID-19 single-cell RNA-Seq data highlighted the fact that T cells and macrophages have the most overlapping genes from the core subnetwork. Overall, we constructed an actionable human target-protein module that mainly involved anti-inflammatory/antiviral entry functions and highly overlapped with COVID-19-severity-related genes. Our findings could serve as a knowledge base for guiding drug discovery or drug repurposing to confront the fast-evolving SARS-CoV-2 virus and other severe infectious diseases.

Closed-loop additive manufacturing of upcycled commodity plastic through dynamic cross-linking.

A sustainable closed-loop manufacturing would become reality if commodity plastics can be upcycled into higher-performance materials with facile processability. Such circularity will be realized when the upcycled plastics can be (re)processed into custom-designed structures through energy/resource-efficient additive manufacturing methods, especially by approachable and scalable fused filament fabrication (FFF). Here, we introduce a circular model epitomized by upcycling a prominent thermoplastic, acrylonitrile butadiene styrene (ABS) into a recyclable, robust adaptive dynamic covalent network (ABS-vitrimer) (re)printable via FFF. The full FFF processing of ABS-vitrimer overcomes the major challenge of (re)printing cross-linked materials and produces stronger, tougher, solvent-resistant three-dimensional objects directly reprintable and separable from unsorted plastic waste. This study thus offers an imminently adoptable approach for advanced manufacturing toward the circular plastics economy.