Multicolor Photochemical Printing Inside Polymer Matrices for Advanced Photonic Anticounterfeiting.

Conventional security inks, generally directly printed on the data page surface, are vulnerable to counterfeiters, thereby raising the risk of chemical structural deciphering. In fact, polymer film-based data pages with customized patterns embedded within polymer matrix, rather than printed on the surface, emerge as a promising solution. Therefore, the key lies in developing fluorophores offering light dose-controlled fluorescent color inside polymer matrices. Though conventional fluorophores often suffer from photobleaching and uncontrolled photoreactions, disqualifying them for this purpose. Herein a diphenanthridinylfumaronitrile-based phototransformers (trans-D5) that undergoes photoisomerization and subsequent photocyclization during photopolymerization of the precursor, successively producing cis- and cyclo-D5 with stepwise redshifted solid-state emissions is developed. The resulting cyclo-D5 exhibits up to 172 nm emission redshift in rigidifying polymer matrices, while trans-D5 experiences a slightly blueshifted emission (≈28 nm), cis-D5 undergoes a modest redshift (≈14 nm). The markedly different rigidochromic behaviors of three D5 molecules within polymer matrices enable multicolor photochemical printing with a broad hue ranging from 38 to 10 via an anticlockwise direction in Munsell color space, yielding indecipherable fluorescent patterns in polymer films. This work provides a new method for document protection and implements advanced security features that are unattainable with conventional inks.

In Situ Optical Detection of Amines at a Parts-per-Quadrillion Level by Severing the Through-Space Conjugated Supramolecular Domino.

Conventional fluorophores suffer from low sensitivity and selectivity in amine detection due to the inherent limitations in their "one-to-one" stoichiometric sensing mechanism. Herein, we propose a "one-to-many" chain reaction-like sensing mechanism by creating a domino chain consisting of one fluorescent molecule (e.g., PTF1) and up to 40 nonemissive polymer chains (pPFPA) comprising over thousand repeating units (PFPA). PTF1 (the domino trigger) interacts with adjacent PFPA units (the following blocks) through polar-π interactions and initiates the domino effect, creating effective through-space conjugation along pPFPA chains and generating amplified yellow fluorescent signals through charge transfer between PTF1 and pPFPA. Amine exposure causes rapid dismantling of the fluorophore-pPFPA-based domino chain and significantly reduces the amplified emissions, thus providing an ultrasensitive method for detecting amines. Relying on the above merits, we achieve a limit of detection of 177 ppq (or 1.67 × 10-12 M) for triethylamine, which is nearly 4 orders lower than that of previous methods. Additionally, the distinct reactivity of pPFPA toward different amines allows for the discrimination of primary, secondary, and tertiary amines. This study presents a "domino effect" sensing mechanism that has not yet been reported and provides a general approach for chemical detection that is beyond the reach of conventional methods.

"Ice and Fire" Supramolecular Cell-Conjugation Drug Delivery Platform for Deep Tumor Ablation and Boosted Antitumor Immunity.

Cancer recurrence and metastasis are two major challenges in the current clinical therapy. In this work, a novel diketopyrrolopyrrole-based photothermal reagent (DCN) with unique J-aggregation-induced redshift is synthesized to achieve efficient tumor thermal ablation under safe power (0.33 W cm-2 ). Meanwhile, S-nitroso-N-acetylpenicillamine (SNAP) is co-loaded with near-infrared-absorbing DCN in amphiphilic polymers to realize heat-induced massive release of nitric oxide (NO), which can form oxidant peroxynitrite (ONOO- ) to active matrix metalloproteinases (MMPs), thereby degrading the compact tumor extracellular matrix to improve the ablation depth and infiltration of immune cells. Through a facile supramolecular assembly method, the DCN/SNAP nanoparticles are anchored to liquid-nitrogen-frozen cancer cells, achieving enhanced antitumor immune responses and effective inhibition of distant tumors and pulmonary metastases after only one treatment. The safety and effectiveness of this supramolecular cell-conjugation platform are verified by 2D/3D cellular experiments and bilateral tumor model, confirming the thermal-ablation-gas-permeation-antigen-presentation therapeutic mode has promising anticancer prospects.

Conventional Non-Fluorescent Polymers: Unconventional Security Inks for Data Storage and Multidimensional Photonic Cryptography.

Traditional security inks relying on fluorescent/phosphorescent molecules are facing increasing risks of forgery or tampering due to their simple readout scheme (i.e., UV-light irradiation) and the advancement of counterfeiting technologies. In this work, a multidimensional data-encryption method based on non-fluorescent polymers via a "lock-key" mechanism is developed. The non-fluorescent invisible polymer inks serve as the "lock" for data-encryption, while the anti-rigidochromic fluorophores that can distinctively light up the polymer inks with programed emissions are "keys" for decryption. The emission of decrypted data is prescribed by polymer chemical structure, molecular weight, topology, copolymer sequence, and phase structure, and shows distinct intensity, wavelength, and chirality compared with the intrinsic emission of fluorophores. Therefore, the data is triply encrypted and naturally gains a high-security level, e.g., only one out of 20 000 keys can access the only correct readout from 40 000 000 possible outputs in a three-polymers-based data-encryption matrix. Note that fluorophores lacking anti-rigidochrimism cannot selectively light up the inks and fail in data-decryption. Further, the diverse topologies, less well-defined structures, and random-coiled shapes of polymers make it impossible for them to be imitated. This work offers a new design for security inks and boosts data security levels beyond the reach of conventional fluorescent inks.

Cyclodextrin-Derived ROS-Generating Nanomedicine with pH-Modulated Degradability to Enhance Tumor Ferroptosis Therapy and Chemotherapy.

Nowadays, destruction of redox homeostasis to induce cancer cell death is an emerging anti-cancer strategy. Here, the authors utilized pH-sensitive acetalated ß-cyclodextrin (Ac-ß-CD) to efficiently deliver dihydroartemisinin (DHA) for tumor ferroptosis therapy and chemodynamic therapy in a synergistic manner. The Ac-ß-CD-DHA based nanoparticles are coated by an iron-containing polyphenol network. In response to the tumor microenvironment, Fe2+ /Fe3+ can consume glutathione (GSH) and trigger the Fenton reaction in the presence of hydrogen peroxide (H2 O2 ), leading to the generation of lethal reactive oxygen species (ROS). Meanwhile, the OO bridge bonds of DHA are also disintegrated to enable ferroptosis of cancer cells. Their results demonstrate that these nanoparticles acted as a ROS generator to break the redox balance of cancer cells, showing an effective anticancer efficacy, which is different from traditional approaches.

Roles of M6A Regulators in Hepatocellular Carcinoma: Promotion or Suppression.

Hepatocellular carcinoma (HCC) is the sixth globally diagnosed cancer with a poor prognosis. Although the pathological factors of hepatocellular carcinoma are well elucidated, the underlying molecular mechanisms remain unclear. N6-methyladenosine (M6A) is adenosine methylation occurring at the N6 site, which is the most prevalent modification of eukaryotic mRNA. Recent studies have shown that M6A can regulate gene expression, thus modulating the processes of cell self-renewal, differentiation, and apoptosis. The methyls in M6A are installed by methyltransferases ("writers"), removed by demethylases ("erasers") and recognized by M6A-binding proteins ("readers"). In this review, we discuss the roles of the above regulators in the progression and prognosis of HCC, and summarize the clinical association between M6A modification and hepatocellular carcinoma, so as to provide more valuable information for clinical treatment.

The Development of Machine Learning Methods in Discriminating Secretory Proteins of Malaria Parasite.

Malaria caused by Plasmodium falciparum is one of the major infectious diseases in the world. It is essential to exploit an effective method to predict secretory proteins of malaria parasites to develop effective cures and treatment. Biochemical assays can provide details for accurate identification of the secretory proteins, but these methods are expensive and time-consuming. In this paper, we summarized the machine learningbased identification algorithms and compared the construction strategies between different computational methods. Also, we discussed the use of machine learning to improve the ability of algorithms to identify proteins secreted by malaria parasites.

Modeling better in vitro models for the prediction of nanoparticle toxicity: a review.

Exposure to nanoparticles (NPs) is plausible in real life due to ambient particulate exposure or development of nanotechnologies, hence the evaluation of NP toxicity as well as mechanism-based studies are necessary. The in vitro models allow rapid testing of NP toxicity, but it is required that the developed in vitro models are reliable to reflect the toxicity of NPs. In this review, we discussed the principles to model better in vitro models to predict the toxicity of NPs based on our own experiences and works of literature. We suggested that in vitro nanotoxicological studies should consider (1) using normal cells because the commonly used cancer cell lines might not reflect the toxicity of NPs to normal tissues; (2) the possible influence of biological molecules to reflect the toxicity of NPs in a biological microenvironment; (3) the influence of pathophysiological conditions to mimic the responses of NPs under different in vivo conditions; and (4) developing advanced tissue-based models to reflect the responses of tissues/organs to NPs. It is our hope that this review may provide useful information for the future design of in vitro nanotoxicological studies.

Induction of lipid droplets in THP-1 macrophages by multi-walled carbon nanotubes in a diameter-dependent manner: A transcriptomic study.

Exposure to multi-walled carbon nanotubes (MWCNTs) might induce lipid droplet (LD) biogenesis, but the roles of physicochemical properties of MWCNTs, as well as the mechanisms, remain poorly understood. In this study, we investigated lipid laden foam formation in THP-1 macrophages exposed to MWCNTs of different diameters, and attempted transcriptomic analysis to study the possible mechanisms. We observed diameter-dependent cytotoxicity, lipid accumulation and intracellular reactive oxygen species production that were more pronounced for MWCNTs with smaller diameters compared with those with larger diameters. However, more MWCNTs with larger diameters were retained in macrophages after 24 h exposure. One possible explanation for the inverse relationship between MWCNT bio-effects and internalization is that macrophages altered the expression of exocytotic genes to export toxic MWCNTs. Transcriptomic data showed that MWCNTs with smaller diameters more effectively altered the expression of genes related with cytotoxicity and lipid metabolism, and KEGG pathway analysis suggested that MWCNTs with smaller diameters activated peroxisome proliferator-activated receptor (PPAR) signalling pathway (map03320), leading to over-expression of perilipin 2, the surface proteins of LDs. Western blot confirmed that MWCNTs effectively promoted CD36, PPARγ and perilipin 2, key components in map03320. Moreover, inhibition of PPARγ by chemicals or siRNA significantly inhibited lipid accumulation induced by MWCNTs with smaller diameters, and perilipin 2 proteins in MWCNT-exposed macrophages could be decreased by PPARγ siRNA. In conclusion, the results of this study revealed the induction of LDs by MWCNTs in a diameter-dependent manner through the activation of PPAR signalling pathway.

ApoPred: Identification of Apolipoproteins and Their Subfamilies With Multifarious Features.

Apolipoprotein is a group of plasma proteins that are associated with a variety of diseases, such as hyperlipidemia, atherosclerosis, Alzheimer's disease, and diabetes. In order to investigate the function of apolipoproteins and to develop effective targets for related diseases, it is necessary to accurately identify and classify apolipoproteins. Although it is possible to identify apolipoproteins accurately through biochemical experiments, they are expensive and time-consuming. This work aims to establish a high-efficiency and high-accuracy prediction model for recognition of apolipoproteins and their subfamilies. We firstly constructed a high-quality benchmark dataset including 270 apolipoproteins and 535 non-apolipoproteins. Based on the dataset, pseudo-amino acid composition (PseAAC) and composition of k-spaced amino acid pairs (CKSAAP) were used as input vectors. To improve the prediction accuracy and eliminate redundant information, analysis of variance (ANOVA) was used to rank the features. And the incremental feature selection was utilized to obtain the best feature subset. Support vector machine (SVM) was proposed to construct the classification model, which could produce the accuracy of 97.27%, sensitivity of 96.30%, and specificity of 97.76% for discriminating apolipoprotein from non-apolipoprotein in 10-fold cross-validation. In addition, the same process was repeated to generate a new model for predicting apolipoprotein subfamilies. The new model could achieve an overall accuracy of 95.93% in 10-fold cross-validation. According to our proposed model, a convenient webserver called ApoPred was established, which can be freely accessed at http://tang-biolab.com/server/ApoPred/service.html. We expect that this work will contribute to apolipoprotein function research and drug development in relevant diseases.

Palmitate enhanced the cytotoxicity of ZnO nanomaterials possibly by promoting endoplasmic reticulum stress.

We recently synthesized ZnO nanomaterials (denoted as ZnO nanorods [NRs] and Mini-NRs) and suggested that their cytotoxicity could be related with the activation of endoplasmic reticulum (ER) stress apoptosis. However, in a complex biological microenvironment, the ER stress-apoptosis pathway could also be modulated by biological molecules, such as free fatty acids, leading to unpredicted biological effects. In this study, we investigated the combined toxicity of ZnO NRs/Mini-NRs and palmitate (PA) to THP-1 macrophages. PA influenced the zeta potential and solubility of ZnO NRs and ZnO Mini-NRs in water, which indicated a change of colloidal stability. Exposure to ZnO NRs and Mini-NRs dose-dependent decreased cellular viability and release of soluble monocyte chemotactic protein 1 (sMCP-1), and these effects were significantly promoted with the presence of PA. However, ZnO NR- and Mini-NR-induced intracellular Zn ions or reactive oxygen species were not significantly affected by PA. ZnO NRs and ZnO Mini-NRs significantly promoted the expression of ER stress genes HSPA5, DDIT3, XBP-1s and apoptotic gene CASP3, whereas PA also modestly promoted the expression of HSPA5, DDIT3 and CASP3. Interestingly, the ER stress inducer thapsigargin showed a similar effect as PA to promote the cytotoxicity of ZnO NRs and ZnO Mini-NRs. It is suggested that PA might promote the cytotoxicity of ZnO NRs and ZnO Mini-NRs possibly by promoting ER stress.