Photoaged nanoplastics with multienzyme-like activities significantly shape the horizontal transfer of antibiotic resistance genes.

Nanoplastics (NPs), identified as emerging pollutants, pose a great risk to environment and global public health, exerting profound influences on the prevalence and dissemination of antibiotic resistance genes (ARGs). Despite evidence suggesting that nano-sized plastic particles can facilitate the horizontal gene transfer (HGT) of ARGs, it is imperative to explore strategies for inhibiting the transfer of ARGs. Currently, limited information exists regarding the characteristics of environmentally aged NPs and their impact on ARGs propagation. Herein, we investigated the impact of photo-aged NPs on the transfer of ARG-carrying plasmids into Escherichia coli (E. coli) cells. Following simulated sunlight irradiation, photo-aged nano-sized polystyrene plastics (PS NPs) exhibited multiple enzyme-like activities, including peroxidase (POD) and oxidase (OXD), leading to a burst of reactive oxygen species (ROS). At relatively low concentrations (0.1, 1 µg/mL), both pristine and aged PS NPs facilitated the transfer of pUC19 and pHSG396 plasmids within E. coli due to moderate ROS production and enhanced cell membrane permeability. Intriguingly, at relatively high concentrations (5, 10 µg/mL), aged PS NPs significantly suppressed plasmids transformation. The non-unidirectional impact of aged PS NPs involved the overproduction of ROS (•OH and •O2-) via nanozyme activity, directly degrading ARGs and damaging plasmid structure. Additionally, oxidative damage to bacteria resulted from the presence of much toxic free radicals, causing physical damage to cell membranes, reduction of the SOS response and restriction of adenosine-triphosphate (ATP) supply, ultimately leading to inactivation of recipient cells. This study unveils the intrinsic multienzyme-like activity of environmentally aged NPs, highlighting their potential to impede the transfer and dissemination of ARGs.

The effect of time-delayed contrast-enhanced scanning in determining the gross tumor target volume of large-volume brain metastases.

BACKGROUND AND PURPOSE: To assess the variation of large-volume brain metastases (BMs) boundaries and shapes using enhanced magnetic resonance (MR) scanning with different delay times and to provide a basis for determining the gross tumor target volume (GTV) for radiotherapy of BMs. MATERIALS AND METHODS: We prospectively enrolled 155 patients initially diagnosed with BMs (561 lesions > 1 cm). Contrast-enhanced (CE) T1-weighted imaging scans were performed 1, 3, 5, 10, 18, and 20 min after gadolinium-based contrast agent injection and GTVs were determined as GTV-1min, GTV-3min, GTV-5min, GTV-10min, GTV-18min, and GTV-20min, respectively, which were subsequently fused in different phases. Fusion of the six GTVs was defined as GTV-total, which was set as the reference GTV. The volume, shape, and signal intensity of the GTVs and brain white matter (BWM) were compared at different delay times. RESULTS: GTV-3min, GTV-5min, GTV-10min, GTV-18min, and GTV-20min volumes increased by 2.2 %, 3.8 %, 6.5 %, 9.5 %, and 10.6 %, respectively (P < 0.05) compared with GTV-1min. Compared with GTV-total, GTV-1min, GTV-3min, GTV-5min, GTV-10min, GTV-18min, and GTV-20min volumes reduced by 25.4 %, 22.1 %, 18.7 %, 15.0 %, 11.2 %, and 10.3 %, respectively (P < 0.05). Compared with GTV-total, 29 (51.8 %) fused GTVs had a volume reduction rate < 5 %, 45 (80.4 %) had a Dice similarity coefficient > 0.95, and all contained GTV-10min, GTV-18min or GTV-20min. The signal intensity ratio between the GTV and BWM peaked at 5 min (0.351 ± 0.24). CONCLUSION: Enhanced MR scans with different delay times show significant differences in the boundaries and shapes of large-volume BMs, and time-delayed multi-phase CE scanning should be used in GTV determination, with time phases ≥ 10 min being mandatory.

Preclinical Evaluation of JAB-2485, a Potent AURKA Inhibitor with High Selectivity and Favorable Pharmacokinetic Properties.

As a critical mitotic regulator, Aurora kinase A (AURKA) is aberrantly activated in a wide range of cancers. Therapeutic targeting of AUKRA is a promising strategy for the treatment of solid tumors. In this study, we evaluated the preclinical characteristics of JAB-2485, a small-molecule inhibitor of AURKA currently in Phase I/IIa clinical trial in the US (NCT05490472). Biochemical studies demonstrated that JAB-2485 is potent and highly selective on AURKA, with subnanomolar IC50 and around 1500-fold selectivity over AURKB or AURKC. In addition, JAB-2485 exhibited favorable pharmacokinetic properties featured by low clearance and good bioavailability, strong dose-response relationship, as well as low risk for hematotoxicity and off-target liability. As a single agent, JAB-2485 effectively induced G2/M cell cycle arrest and apoptosis and inhibited the proliferation of small cell lung cancer, triple-negative breast cancer, and neuroblastoma cells. Furthermore, JAB-2485 exhibited robust in vivo antitumor activity both as monotherapy and in combination with chemotherapies or the bromodomain inhibitor JAB-8263 in xenograft models of various cancer types. Together, these encouraging preclinical data provide a strong basis for safety and efficacy evaluations of JAB-2485 in the clinical setting.

Using RegGAN to generate synthetic CT images from CBCT images acquired with different linear accelerators.

BACKGROUND: The goal was to investigate the feasibility of the registration generative adversarial network (RegGAN) model in image conversion for performing adaptive radiation therapy on the head and neck and its stability under different cone beam computed tomography (CBCT) models. METHODS: A total of 100 CBCT and CT images of patients diagnosed with head and neck tumors were utilized for the training phase, whereas the testing phase involved 40 distinct patients obtained from four different linear accelerators. The RegGAN model was trained and tested to evaluate its performance. The generated synthetic CT (sCT) image quality was compared to that of planning CT (pCT) images by employing metrics such as the mean absolute error (MAE), peak signal-to-noise ratio (PSNR), and structural similarity index measure (SSIM). Moreover, the radiation therapy plan was uniformly applied to both the sCT and pCT images to analyze the planning target volume (PTV) dose statistics and calculate the dose difference rate, reinforcing the model's accuracy. RESULTS: The generated sCT images had good image quality, and no significant differences were observed among the different CBCT modes. The conversion effect achieved for Synergy was the best, and the MAE decreased from 231.3 ± 55.48 to 45.63 ± 10.78; the PSNR increased from 19.40 ± 1.46 to 26.75 ± 1.32; the SSIM increased from 0.82 ± 0.02 to 0.85 ± 0.04. The quality improvement effect achieved for sCT image synthesis based on RegGAN was obvious, and no significant sCT synthesis differences were observed among different accelerators. CONCLUSION: The sCT images generated by the RegGAN model had high image quality, and the RegGAN model exhibited a strong generalization ability across different accelerators, enabling its outputs to be used as reference images for performing adaptive radiation therapy on the head and neck.

Sparsity-guided multiple functional connectivity patterns for classification of schizophrenia via convolutional network.

The explorations of brain functional connectivity network (FCN) using resting-state functional magnetic resonance imaging can provide crucial insights into discriminative analysis of neuropsychiatric disorders, such as schizophrenia (SZ). Pearson's correlation (PC) is widely used to construct a densely connected FCN which may overlook some complex interactions of paired regions of interest (ROIs) under confounding effect of other ROIs. Although the method of sparse representation takes into account this issue, it penalizes each edge equally, which often makes the FCN look like a random network. In this paper, we establish a new framework, called convolutional neural network with sparsity-guided multiple functional connectivity, for SZ classification. The framework consists of two components. (1) The first component constructs a sparse FCN by integrating PC and weighted sparse representation (WSR). The FCN retains the intrinsic correlation between paired ROIs, and eliminates false connection simultaneously, resulting in sparse interactions among multiple ROIs with the confounding effect regressed out. (2) In the second component, we develop a functional connectivity convolution to learn discriminative features for SZ classification from multiple FCNs by mining the joint spatial mapping of FCNs. Finally, an occlusion strategy is employed to explore the contributive regions and connections, to derive the potential biomarkers in identifying associated aberrant connectivity of SZ. The experiments on SZ identification verify the rationality and advantages of our proposed method. This framework also can be used as a diagnostic tool for other neuropsychiatric disorders.

An Effective Approach to Improve the Automatic Segmentation and Classification Accuracy of Brain Metastasis by Combining Multi-phase Delay Enhanced MR Images.

The objective of this study is to analyse the diffusion rule of the contrast media in multi-phase delayed enhanced magnetic resonance (MR) T1 images using radiomics and to construct an automatic classification and segmentation model of brain metastases (BM) based on support vector machine (SVM) and Dpn-UNet. A total of 189 BM patients with 1047 metastases were enrolled. Contrast-enhanced MR images were obtained at 1, 3, 5, 10, 18, and 20 min following contrast medium injection. The tumour target volume was delineated, and the radiomics features were extracted and analysed. BM segmentation and classification models in the MR images with different enhancement phases were constructed using Dpn-UNet and SVM, and differences in the BM segmentation and classification models with different enhancement times were compared. (1) The signal intensity for BM decreased with time delay and peaked at 3 min. (2) Among the 144 optimal radiomics features, 22 showed strong correlation with time (highest R-value = 0.82), while 41 showed strong correlation with volume (highest R-value = 0.99). (3) The average dice similarity coefficients of both the training and test sets were the highest at 10 min for the automatic segmentation of BM, reaching 0.92 and 0.82, respectively. (4) The areas under the curve (AUCs) for the classification of BM pathology type applying single-phase MRI was the highest at 10 min, reaching 0.674. The AUC for the classification of BM by applying the six-phase image combination was the highest, reaching 0.9596, and improved by 42.3% compared with that by applying single-phase images at 10 min. The dynamic changes of contrast media diffusion in BM can be reflected by multi-phase delayed enhancement based on radiomics, which can more objectively reflect the pathological types and significantly improve the accuracy of BM segmentation and classification.

MRI-based two-stage deep learning model for automatic detection and segmentation of brain metastases.

OBJECTIVES: To develop and validate a two-stage deep learning model for automatic detection and segmentation of brain metastases (BMs) in MRI images. METHODS: In this retrospective study, T1-weighted (T1) and T1-weighted contrast-enhanced (T1ce) MRI images of 649 patients who underwent radiotherapy from August 2019 to January 2022 were included. A total of 5163 metastases were manually annotated by neuroradiologists. A two-stage deep learning model was developed for automatic detection and segmentation of BMs, which consisted of a lightweight segmentation network for generating metastases proposals and a multi-scale classification network for false-positive suppression. Its performance was evaluated by sensitivity, precision, F1-score, dice, and relative volume difference (RVD). RESULTS: Six hundred forty-nine patients were randomly divided into training (n = 295), validation (n = 99), and testing (n = 255) sets. The proposed two-stage model achieved a sensitivity of 90% (1463/1632) and a precision of 56% (1463/2629) on the testing set, outperforming one-stage methods based on a single-shot detector, 3D U-Net, and nnU-Net, whose sensitivities were 78% (1276/1632), 79% (1290/1632), and 87% (1426/1632), and the precisions were 40% (1276/3222), 51% (1290/2507), and 53% (1426/2688), respectively. Particularly for BMs smaller than 5 mm, the proposed model achieved a sensitivity of 66% (116/177), far superior to one-stage models (21% (37/177), 36% (64/177), and 53% (93/177)). Furthermore, it also achieved high segmentation performance with an average dice of 81% and an average RVD of 20%. CONCLUSION: A two-stage deep learning model can detect and segment BMs with high sensitivity and low volume error. KEY POINTS: • A two-stage deep learning model based on triple-channel MRI images identified brain metastases with 90% sensitivity and 56% precision. • For brain metastases smaller than 5 mm, the proposed two-stage model achieved 66% sensitivity and 22% precision. • For segmentation of brain metastases, the proposed two-stage model achieved a dice of 81% and a relative volume difference (RVD) of 20%.

Emodin Alleviates Sodium Taurocholate-Induced Pancreatic Ductal Cell Damage by Inhibiting the S100A9/VNN1 Signaling Pathway.

OBJECTIVES: Because the pathogenesis of the disease is unclear, the treatment of patients with acute pancreatitis, especially severe acute pancreatitis, is still a major challenge for clinicians. Emodin is an anthraquinone compound extracted from rhubarb that can alleviate the damage to pancreatic ductal epithelial cells induced by adenosine triphosphate, but whether it has a similar protective effect on sodium taurocholate (STC)-stimulated pancreatic ductal cells and the underlying mechanism has not yet been reported. METHODS: A model of STC-induced HPDE6-C7 human pancreatic ductal epithelial cell injury was established, and then apoptosis and the levels of reactive oxygen species (ROS), glutathione, gamma-glutamylcysteine synthetase, and inflammatory cytokines were assessed in the presence or absence of emodin pretreatment. S100 calcium binding protein A9 (S100A9) and Vanin1 (VNN1) protein expression was also measured. RESULTS: Emodin significantly increased HPDE6-C7 cell viability, inhibited apoptosis and ROS release, and elevated glutathione levels and gamma-glutamylcysteine synthetase activity. Furthermore, emodin downregulated S100A9 and VNN1 protein expression and inhibited the production of inflammatory factors, such as interleukin (IL)-1ß, IL-6, IL-8, and IL-18. CONCLUSIONS: Emodin attenuates STC-induced pancreatic ductal cell injury possibly by inhibiting S100A9/VNN1-mediated ROS release. This finding provides evidence for the future development of emodin as a therapeutic agent.

Antitumor Activity and Mechanism of Action of the Antimicrobial Peptide AMP-17 on Human Leukemia K562 Cells.

Cancer is one of the most common malignant diseases in the world. Hence, there is an urgent need to search for novel drugs with antitumor activity against cancer cells. AMP-17, a natural antimicrobial peptide derived from Musca domestica, has antimicrobial activity against Gram-positive bacteria, Gram-negative bacteria, and fungi. However, its antitumor activity and potential mechanism of action in cancer cells remain unclear. In this study, we focused on evaluating the in vitro antitumor activity and mechanism of AMP-17 on leukemic K562 cells. The results showed that AMP-17 exhibited anti-proliferative activity on K562 cells with an IC50 value of 58.91 ± 3.57 µg/mL. The membrane integrity of K562 was disrupted and membrane permeability was increased after AMP-17 action. Further observation using SEM and TEM images showed that the cell structure of AMP-17-treated cells was disrupted, with depressions and pore-like breaks on the cell surface, and vacuolated vesicles in the cytoplasm. Furthermore, further mechanistic studies indicated that AMP-17 induced excessive production of reactive oxygen species and calcium ions release in K562 cells, which led to disturbance of mitochondrial membrane potential and blocked ATP synthesis, followed by activation of Caspase-3 to induce apoptosis. In conclusion, these results suggest that the antitumor activity of AMP-17 may be achieved by disrupting cell structure and inducing apoptosis. Therefore, AMP-17 is expected to be a novel potential agent candidate for leukemia treatment.

The effect of time delay for magnetic resonance contrast-enhanced scan on imaging for small-volume brain metastases.

PURPOSE: To study the effect of different enhancement timings of magnetic resonance (MR) on small-volume brain metastases (BM) visualisation and provide a basis for the contour of tumour targets. METHOD: We prospectively enrolled 101 patients with BM who received radiotherapy. All patients underwent computed tomography (CT) and MR simulations. Contrast-enhanced MR scans at 1, 3, 5, 10, 18, and 20 min after injection of contrast medium were performed. The tumour target was determined on MR images at different enhancement times, and the differences of tumour target volume, maximum diameter, and MR signal intensity were compared. RESULTS: (1) Of the 453 metastatic lesions, 24 (5.2 %) were not detected at 1 min and 8 (1.8 %) were not detected at 3 min; however, all metastases were detected after 5 min. The volume and maximum diameter of the 28 (6.2 %) metastases were stable at any time. (2) The average volume of metastatic lesions at 1, 3, 5, 10, 18, and 20 min was 0.09 cm3, 0.10 cm3, 0.12 cm3, 0.12 cm3, 0.13 cm3, and 0.13 cm3, respectively. Compared to 1 min, BM volume at other times increased by 13.1 %, 21.5 %, 31.6 %, 39.6 %, and 41.7 %, and the difference between the maximum and minimum volumes was statistically significant (p < 0.05). (3) The distribution of the maximum ratio of tumours to white matter mean signal intensity at different times were 39.6 %, 20 %, 14.6 %, 8.0 %, 10.4 %, and 10 %, respectively. CONCLUSION: The visualisation of small-volume BM was significantly different at different enhancement times. Our results suggest that multi-timing enhancement scans for small-volume BM should be implemented and that scanning at >10 min is essential.

Identification of Peptoniphilus vaginalis-Like Bacteria, Peptoniphilus septimus sp. nov., From Blood Cultures in a Cervical Cancer Patient Receiving Chemotherapy: Case and Implications.

A 39-year-old woman with a 3-year human papillomavirus (HPV) 18 infection history was admitted to the hospital for a 16-day history of vaginal bleeding after sex. She was diagnosed with cervical cancer based on the results of the electronic colposcopy, cervical cytology, microscopy, and magnetic resonance imaging (MRI). Then, she received chemotherapy, with paclitaxel 200 mg (day 1), cisplatin 75 mg (day 2), and bevacizumab 700 mg (day 3) twice with an interval of 27 days. During the examination for the diagnosis and treatment, many invasive operations, including removal of intrauterine device, colposcopy, and ureteral dilatation, were done. After that, the patient was discharged and entered the emergency department about 2.5 months later with a loss of consciousness probably caused by septic shock. The patient finally died of multiple organ failure and bacterial infection, although she has received antimicrobial therapy. The blood cultures showed a monobacterial infection with an anaerobic Gram-positive bacterial strain, designated as SAHP1. Matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) indicated that the patient was infected with Peptoniphilus asaccharolyticus, while molecular analysis and genome-based taxonomy confirmed the infection with a novel Peptoniphilus species that has a close genetic relationship with Peptoniphilus vaginalis and proposed provisionally as Peptoniphilus septimus sp. nov., which may also act as a commensal of the human vagina. Genomic features of SAHP1 have been fully described, and comparative genomic analysis reveals the known prokaryote relative of Peptoniphilus septimus sp. nov. in the genus Peptoniphilus. The invasive operations on the genital tract during the diagnosis and treatment of the patient and the tumor tissue damage and bleeding may have a certain role in the bloodstream infection. This study casts a new light on the Peptoniphilus bacteria and prompts clinicians to include anaerobic blood cultures as part of their blood culture procedures, especially on patients with genital tract tumors. Furthermore, due to the incomplete database and unsatisfying resolution of the MALDI-TOF MS for Peptoniphilus species identification, molecular identification, especially whole-genome sequencing, is required for those initially identified as bacteria belonging to Peptoniphilus in the clinical laboratory.

Hybridizing aggregated gold nanoparticles with a hydrogel to prepare a flexible SERS chip for detecting organophosphorus pesticides.

Surface enhanced Raman scattering (SERS) is an ultrasensitive analytic technique. However, the application of SERS in quantitative analysis usually suffers from poor reliability due to the limitations of currently developed SERS substrates. In the present work, aggregated gold nanoparticles (a-AuNPs) fabricated by Ca2+-mediated assembly are dispersed in polyvinyl alcohol solution to prepare a novel hydrogel SERS chip through a physical crosslinking method. Taking advantage of the uniform distribution of SERS active a-AuNPs in the three-dimension hydrogel and the excellent barrier effect of hydrogel towards oxygen and macromolecules, the obtained hydrogel SERS chips show many outstanding advantages including high sensitivity, good repeatability, long-term stability, and a robust anti-interference ability. These advantages enable hydrogel SERS chips to be used to quantitatively analyse some complex samples without complex sample preprocessing. As a model, the hydrogel SERS chips are used for the detection of triazophos and phosmet in orange samples. The good recoveries suggest good applicability of the hydrogel SERS chips in food safety detection. This work provides a reliable and convenient platform for the quick detection and on-site monitoring of chemical contaminants and would promote greatly the performance of SERS techniques in quantitative analysis.

Quantitative study of the changes in brain white matter before and after radiotherapy by applying multi-sequence MR radiomics.

PURPOSE: To analyse the changes in brain white matter before and after radiotherapy (RT) by applying multisequence MR radiomics features and to establish a relationship between the changes in radiomics features and radiation dose. METHODS: Eighty-eight patients with brain tumours who had undergone RT were selected in this study, and MR images (T1, T1+C, T2FLAIR, T2, DWI, and ASL) before and after RT were obtained. The brain white matter was delineated as an ROI under dose gradients of 0-5 Gy, 5-10 Gy, 10-15 Gy, 15-20 Gy, 20-30 Gy, 30-40 Gy, and 40-50 Gy. The radiomics features of each ROI were extracted, and the changes in radiomics features before and after RT for different sequences under different dose gradients were compared. RESULTS: At each dose gradient, statistically significant features of different MR sequences were mainly concentrated in three dose gradients, 5-10 Gy, 20-30 Gy, and 30-40 Gy. The T1+C sequence held the most features (66) under the 20-30 Gy dose gradient. There were 20 general features at dose gradients of 20-30 Gy, 30-40 Gy, and 40-50 Gy, and the changes in features first decreased and then increased following dose escalation. With dose gradients of 5-10 Gy and 10-15 Gy, only T1 and T2FLAIR had general features, and the rates of change were - 24.57% and - 29.32% for T1 and - 3.08% and - 10.87% for T2FLAIR, respectively. The changes showed an upward trend with increasing doses. For different MR sequences that were analysed under the same dose gradient, all sequences with 5-10 Gy, 20-30 Gy and 30-40 Gy had general features, except the T2FLAIR sequence, which was concentrated in the FirstOrder category feature, and the changes in features of T1 and T1+C were more significant than those of the other sequences. CONCLUSIONS: MR radiomics features revealed microscopic changes in brain white matter before and after RT, although there was no constant dose-effect relationship for each feature. The changes in radiomics features in different sequences could reveal the radiation response of brain white matter to different doses.

Distributions and trends of the global burden of COPD attributable to risk factors by SDI, age, and sex from 1990 to 2019: a systematic analysis of GBD 2019 data.

BACKGROUND: Global distributions and trends of the risk-attributable burdens of chronic obstructive pulmonary disease (COPD) have rarely been systematically explored. To guide the formulation of targeted and accurate strategies for the management of COPD, we analyzed COPD burdens attributable to known risk factors. METHODS: Using detailed COPD data from the Global Burden of Disease study 2019, we analyzed disability-adjusted life years (DALYs), years lived with disability (YLDs), years of life lost (YLLs), and deaths attributable to each risk factor from 1990 to 2019. Additionally, we calculated estimated annual percentage changes (EAPCs) during the study period. The population attributable fraction (PAF) and summary exposure value (SEV) of each risk factor are also presented. RESULTS: From 1990 to 2019, the age-standardized DALY and death rates of COPD attributable to smoking and household air pollution, occupational particles, secondhand smoke, and low temperature presented consistently declining trends in almost all socio-demographic index (SDI) regions. However, the decline in YLD was not as dramatic as that of the death rate. In contrast, the COPD burden attributable to ambient particulate matter, ozone, and high temperature exposure showed undesirable increasing trends in the low- and low-middle-SDI regions. In addition, the age-standardized DALY and death rates attributable to each risk factor except household air pollution and low temperature were the highest in the low-middle-SDI region. In 2019, the COPD burden attributable to smoking ambient particulate matter, ozone, occupational particles, low and high temperature was obviously greater in males than in females. Meanwhile, the most important risk factors for female varied across regions (low- and low-middle-SDI regions: household air pollution; middle-SDI region: ambient particles; high-middle- and high-SDI region: smoking). CONCLUSIONS: Increasing trends of COPD burden attributable to ambient particulate matter, ozone, and high temperature exposure in the low-middle- and low-SDI regions call for an urgent need to implement specific and effective measures. Moreover, considering the gender differences in COPD burdens attributable to some risk factors such as ambient particulate matter and ozone with similar SEV, further research on biological differences between sexes in COPD and relevant policy-making of disease prevention are required.

Bridging Li7La3Zr2O12 Nanofibers with Poly(ethylene oxide) by Coordination Bonds to Enhance the Cycling Stability of All-Solid-State Lithium Metal Batteries.

A solid-state composite polymer electrolyte comprising Li7La3Zr2O12 nanofibers (LLZO NFs) as fillers has the advantages of flexibility, ease of processing, and being low cost, thus being considered to be a promising electrolyte material for use in the next generation of highly safe lithium metal batteries. However, poor compatibility of organic parts and inorganic materials leads to quick capacity decay after long-term charge/discharging running because of inorganic/organic interface deterioration and thus, the related ineffective lithium-ion (Li+) conduction. Herein, a "Boston ivy-style" method is proposed to prepare a solid ceramic/polymer hybrid electrolyte that exhibits a dense interface structure. After grafting on Dynasylan IMEO (DI), the modified LLZO NFs are used as ligands to bond with coordinatively unsaturated metal centers of Ca2+. Furthermore, these Ca2+ bridge the modified LLZO NFs with poly(ethylene oxide) (PEO) via the ether oxygen atoms they possess. The bridges built between the two phases, PEO and LLZO NFs, are effective to interface strengthening and guarantee rapid Li+ conduction even after 900 cycles. The PEO/LLZO NFs-DI-Ca2+/LiTFSI electrolyte shows a high Li+ transference number of 0.72 (60 °C). The Li||LiFePO4 cell delivers excellent cycling stability (capacity retention of 70.8% after 900 cycles, 0.5 C) and rate performance. The bridge strategy is proved to be effective and probably a promotion to the application of ceramic polymer-based solid-state electrolytes.

A plasmon-enhanced theranostic nanoplatform for synergistic chemo-phototherapy of hypoxic tumors in the NIR-II window.

Development of simple and effective synergistic therapy by combination of different therapeutic modalities within one single nanostructure is of great importance for cancer treatment. In this study, by integrating the anticancer drug DOX and plasmonic bimetal heterostructures into zeolitic imidazolate framework-8 (ZIF-8), a stimuli-responsive multifunctional nanoplatform, DOX-Pt-tipped Au@ZIF-8, has been successfully fabricated. Pt nanocrystals with catalase-like activity were selectively grown on the ends of the Au nanorods to form Pt-tipped Au NR heterostructures. Under single 1064 nm laser irradiation, compared with Au NRs and Pt-covered Au NRs, the Pt-tipped Au nanorods exhibit outstanding photothermal and photodynamic properties owing to more efficient plasmon-induced electron-hole separation. The heat generated by laser irradiation can enhance the catalytic activity of Pt and improve the O2 level to relieve tumor hypoxia. Meanwhile, the strong absorption in the NIR-II region and high-Z elements (Au, Pt) of the DOX-Pt-tipped Au@ZIF-8 provide the possibility for photothermal (PT) and computed tomography (CT) imaging. Both in vitro and in vivo experimental results illustrated that the DOX-Pt-tipped Au@ZIF-8 exhibits remarkably synergistic plasmon-enhanced chemo-phototherapy (PTT/PDT) and successfully inhibited tumor growth. Taken together, this work contributes to designing a rational theranostic nanoplatform for PT/CT imaging-guided synergistic chemo-phototherapy under single laser activation.

High temperature requirement A1 in cancer: biomarker and therapeutic target.

As the life expectancy of the population increases worldwide, cancer is becoming a substantial public health problem. Considering its recurrence and mortality rates, most cancer cases are difficult to cure. In recent decades, a large number of studies have been carried out on different cancer types; unfortunately, tumor incidence and mortality have not been effectively improved. At present, early diagnostic biomarkers and accurate therapeutic strategies for cancer are lacking. High temperature requirement A1 (HtrA1) is a trypsin-fold serine protease that is also a chymotrypsin-like protease family member originally discovered in bacteria and later discovered in mammalian systems. HtrA1 gene expression is decreased in diverse cancers, and it may play a role as a tumor suppressor for promoting the death of tumor cells. This work aimed to examine the role of HtrA1 as a cell type-specific diagnostic biomarker or as an internal and external regulatory factor of diverse cancers. The findings of this study will facilitate the development of HtrA1 as a therapeutic target.

S100 Proteins in Pancreatic Cancer: Current Knowledge and Future Perspectives.

Pancreatic cancer (PC) is a highly malignant tumor occurring in the digestive system. Currently, there is a lack of specific and effective interventions for PC; thus, further exploration regarding the pathogenesis of this malignancy is warranted. The S100 protein family, a collection of calcium-binding proteins expressed only in vertebrates, comprises 25 members with high sequence and structural similarity. Dysregulated expression of S100 proteins is a biomarker of cancer progression and prognosis. Functionally, these proteins are associated with the regulation of multiple cellular processes, including proliferation, apoptosis, growth, differentiation, enzyme activation, migration/invasion, Ca2+ homeostasis, and energy metabolism. This review highlights the significance of the S100 family in the diagnosis and prognosis of PC and its vital functions in tumor cell metastasis, invasion and proliferation. A further understanding of S100 proteins will provide potential therapeutic targets for preventing or treating PC.

Dual targeting of DDX3 and eIF4A by the translation inhibitor rocaglamide A.

The translation inhibitor rocaglamide A (RocA) has shown promising antitumor activity because it uniquely clamps eukaryotic initiation factor (eIF) 4A onto polypurine RNA for selective translational repression. As eIF4A has been speculated to be a unique target of RocA, alternative targets have not been investigated. Here, we reveal that DDX3 is another molecular target of RocA. Proximity-specific fluorescence labeling of an O-nitrobenzoxadiazole-conjugated derivative revealed that RocA binds to DDX3. RocA clamps the DDX3 protein onto polypurine RNA in an ATP-independent manner. Analysis of a de novo-assembled transcriptome from the plant Aglaia, a natural source of RocA, uncovered the amino acid critical for RocA binding. Moreover, ribosome profiling showed that because of the dominant-negative effect of RocA, high expression of eIF4A and DDX3 strengthens translational repression in cancer cells. This study indicates that sequence-selective clamping of DDX3 and eIF4A, and subsequent dominant-negative translational repression by RocA determine its tumor toxicity.

Down-Regulation of AHNAK2 Inhibits Cell Proliferation, Migration and Invasion Through Inactivating the MAPK Pathway in Lung Adenocarcinoma.

AHNAK nucleoprotein 2 (AHNAK2) has been emerged as a crucial protein for neuroblast differentiation and cell migration, thereby involving in the development of various cancers. However, the specific molecular mechanism of AHNAK2 in lung adenocarcinoma is inconclusive. By accessing to the Oncomine dataset and GEPIA website, a higher expression level of AHNAK2 was observed in lung adenocarcinoma tissue samples. Overall survival (OS) curve plotted by Kaplan-Meier method showed that up-regulation of AHNAK2 was related with poor prognosis of lung adenocarcinoma patients. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) analysis and western blot were conducted to examine the expression level of genes in lung adenocarcinoma cells. Through functional in vitro experiments, cell proliferation, migration and invasion were all suppressed after AHNAK2 knockdown using Cell counting kit-8 (CCK-8) assay, wound-healing and transwell analysis. Reduction of AHNAK2 decreased the apoptosis rate using flow cytometry analysis. Moreover, the key markers of MAPK pathway, p-MEK, p-ERK and p-P90RSK were decreased due to the transfection of si-AHNAK2 in A549 cells. U0126, a MEK inhibitor, showed the similar effects on MAPK-related protein levels with si-AHNAK2. To sum up, AHNAK2 is significantly increased in lung adenocarcinoma and plays a carcinogenic role by activating the MAPK signaling pathway, providing a novel insight and raising possibility for lung adenocarcinoma treatment.