Owing to their unique, nanoscale related optical properties, nanostructures assembled from molecular photosensitizers (PSs) have interesting applications in phototheranostics. However, most ...nanostructured PS assemblies are super‐quenched, thus, preventing their use in photodynamic therapy (PDT). Although some of these materials undergo stimuli‐responsive disassembly, which leads to partial recovery of PDT activity, their therapeutic potentials are unsatisfactory owing to a limited ability to promote generation reactive oxygen species (ROS), especially via type I photoreactions (i.e., not by 1O2 generation). Herein we demonstrate that a new, nanostructured phthalocyanine assembly, NanoPcA, has the ability to promote highly efficient ROS generation via the type I mechanism. The results of antibacterial studies demonstrate that NanoPcA has potential PDT applications.
Photodynamic nanodots self‐assembled from phthalocyanine molecules (NanoPcA) display highly efficient reactive oxygen species generation via a type I mechanism. Antibacterial studies demonstrate that NanoPcA has potential photodynamic therapy applications.
Frost events during the active growth period of plants can cause extensive frost damage with tremendous economic losses and dramatic ecological consequences. A common assumption is that climate ...warming may bring along a reduction in the frequency and severity of frost damage to vegetation. On the other hand, it has been argued that rising temperature in late winter and early spring might trigger the so called “false spring”, that is, early onset of growth that is followed by cold spells, resulting in increased frost damage. By combining daily gridded climate data and 1,489 k in situ phenological observations of 27 tree species from 5,565 phenological observation sites in Europe, we show here that temporal changes in the risk of spring frost damage with recent warming vary largely depending on the species and geographical locations. Species whose phenology was especially sensitive to climate warming tended to have increased risk of frost damage. Geographically, compared with continental areas, maritime and coastal areas in Europe were more exposed to increasing occurrence of frost and these late spring frosts were getting more severe in the maritime and coastal areas. Our results suggest that even though temperatures will be elevated in the future, some phenologically responsive species and many populations of a given species will paradoxically experience more frost damage in the future warming climate. More attention should be paid to the increased frost damage in responsive species and populations in maritime areas when developing strategies to mitigate the potential negative impacts of climate change on ecosystems in the near future.
This study examined the well‐known “increased frost damage” hypothesis by Cannell (1985), based on long‐term phenological records and climate data. Temporal changes in the risk of spring frost damage with recent warming vary largely depending on the species and geographical locations. Species whose phenology was especially sensitive to climate warming tended to have increased risk of frost damage. Geographically, compared with continental areas, maritime and coastal areas in Europe were more exposed to increasing occurrence of frost and these late spring frosts were getting more severe in the maritime and coastal areas.
The challenge of person re-identification (re-id) is to match individual images of the same person captured by different nonoverlapping camera views against significant and unknown cross-view feature ...distortion. While a large number of distance metric/ subspace learning models have been developed for re-id, the cross-view transformations they learned are view-generic and thus potentially less effective in quantifying the feature distortion inherent to each camera view. Learning view-specific feature transformations for re-id (i.e., view-specific re-id), an under-studied approach, becomes an alternative resort for this problem. In this work, we formulate a novel view-specific person re-identification framework from the feature augmentation point of view, called Camera coRrelation Aware Feature augmenTation (CRAFT). Specifically, CRAFT performs cross-view adaptation by automatically measuring camera correlation from cross-view visual data distribution and adaptively conducting feature augmentation to transform the original features into a new adaptive space. Through our augmentation framework, view-generic learning algorithms can be readily generalized to learn and optimize view-specific sub-models whilst simultaneously modelling view-generic discrimination information. Therefore, our framework not only inherits the strength of view-generic model learning but also provides an effective way to take into account view specific characteristics. Our CRAFT framework can be extended to jointly learn view-specific feature transformations for person re-id across a large network with more than two cameras, a largely under-investigated but realistic re-id setting. Additionally, we present a domain-generic deep person appearance representation which is designed particularly to be towards view invariant for facilitating cross-view adaptation by CRAFT. We conducted extensively comparative experiments to validate the superiority and advantages of our proposed framework over state-of-the-art competitors on contemporary challenging person re-id datasets.
This paper proposes a novel approach to person re-identification, a fundamental task in distributed multi-camera surveillance systems. Although a variety of powerful algorithms have been presented in ...the past few years, most of them usually focus on designing hand-crafted features and learning metrics either individually or sequentially. Different from previous works, we formulate a unified deep ranking framework that jointly tackles both of these key components to maximize their strengths. We start from the principle that the correct match of the probe image should be positioned in the top rank within the whole gallery set. An effective learning-to-rank algorithm is proposed to minimize the cost corresponding to the ranking disorders of the gallery. The ranking model is solved with a deep convolutional neural network (CNN) that builds the relation between input image pairs and their similarity scores through joint representation learning directly from raw image pixels. The proposed framework allows us to get rid of feature engineering and does not rely on any assumption. An extensive comparative evaluation is given, demonstrating that our approach significantly outperforms all the state-of-the-art approaches, including both traditional and CNN-based methods on the challenging VIPeR, CUHK-01, and CAVIAR4REID datasets. In addition, our approach has better ability to generalize across datasets without fine-tuning.
Critical patients with the coronavirus disease 2019 (COVID-19), even those whose nucleic acid test results had turned negative and those receiving maximal medical support, have been noted to progress ...to irreversible fatal respiratory failure. Lung transplantation (LT) as the sole therapy for end-stage pulmonary fibrosis related to acute respiratory distress syndrome has been considered as the ultimate rescue therapy for these patients.
From February 10 to March 10, 2020, three male patients were urgently assessed and listed for transplantation. After conducting a full ethical review and after obtaining assent from the family of the patients, we performed three LT procedures for COVID-19 patients with illness durations of more than one month and extremely high sequential organ failure assessment scores.
Two of the three recipients survived post-LT and started participating in a rehabilitation program. Pearls of the LT team collaboration and perioperative logistics were summarized and continually improved. The pathological results of the explanted lungs were concordant with the critical clinical manifestation, and provided insight towards better understanding of the disease. Government health affair systems, virology detection tools, and modern communication technology all play key roles towards the survival of the patients and their rehabilitation.
LT can be performed in end-stage patients with respiratory failure due to COVID-19-related pulmonary fibrosis. If confirmed positive-turned-negative virology status without organ dysfunction that could contraindicate LT, LT provided the final option for these patients to avoid certain death, with proper protection of transplant surgeons and medical staffs. By ensuring instant seamless care for both patients and medical teams, the goal of reducing the mortality rate and salvaging the lives of patients with COVID-19 can be attained.
Due to its ability to combine multiple base clusterings into a probably better and more robust clustering, the ensemble clustering technique has been attracting increasing attention in recent years. ...Despite the significant success, one limitation to most of the existing ensemble clustering methods is that they generally treat all base clusterings equally regardless of their reliability, which makes them vulnerable to low-quality base clusterings. Although some efforts have been made to (globally) evaluate and weight the base clusterings, yet these methods tend to view each base clustering as an individual and neglect the local diversity of clusters inside the same base clustering. It remains an open problem how to evaluate the reliability of clusters and exploit the local diversity in the ensemble to enhance the consensus performance, especially, in the case when there is no access to data features or specific assumptions on data distribution. To address this, in this paper, we propose a novel ensemble clustering approach based on ensemble-driven cluster uncertainty estimation and local weighting strategy. In particular, the uncertainty of each cluster is estimated by considering the cluster labels in the entire ensemble via an entropic criterion. A novel ensemble-driven cluster validity measure is introduced, and a locally weighted co-association matrix is presented to serve as a summary for the ensemble of diverse clusters. With the local diversity in ensembles exploited, two novel consensus functions are further proposed. Extensive experiments on a variety of real-world datasets demonstrate the superiority of the proposed approach over the state-of-the-art.
Despite clinical and epidemiological evidence suggestive of a link between glioblastoma (GBM) and periodontitis (PD), the shared mechanisms of gene regulation remain elusive. In this study, we ...identify differentially expressed genes (DEGs) that overlap between the GEO datasets GSE4290 GBM and GSE10334 PD. Functional enrichment analysis was conducted, and key modules were identified using protein-protein interaction (PPI) network and weighted gene co-expression network analysis (WGCNA). The expression levels of CXCR4, LY96, and C3 were found to be significantly elevated in both the test dataset and external validation dataset, making them key crosstalk genes. Additionally, immune cell landscape analysis revealed elevated expression levels of multiple immune cells in GBM and PD compared to controls, with the key crosstalk genes negatively associated with Macrophages M2. FLI1 was identified as a potential key transcription factor (TF) regulating the three key crosstalk genes, with increased expression in the full dataset. These findings contribute to our understanding of the immune and inflammatory aspects of the comorbidity mechanism between GBM and PD.
Ferroptosis is a new type of cell death that was discovered in recent years and is usually accompanied by a large amount of iron accumulation and lipid peroxidation during the cell death process; the ...occurrence of ferroptosis is iron-dependent. Ferroptosis-inducing factors can directly or indirectly affect glutathione peroxidase through different pathways, resulting in a decrease in antioxidant capacity and accumulation of lipid reactive oxygen species (ROS) in cells, ultimately leading to oxidative cell death. Recent studies have shown that ferroptosis is closely related to the pathophysiological processes of many diseases, such as tumors, nervous system diseases, ischemia-reperfusion injury, kidney injury, and blood diseases. How to intervene in the occurrence and development of related diseases by regulating cell ferroptosis has become a hotspot and focus of etiological research and treatment, but the functional changes and specific molecular mechanisms of ferroptosis still need to be further explored. This paper systematically summarizes the latest progress in ferroptosis research, with a focus on providing references for further understanding of its pathogenesis and for proposing new targets for the treatment of related diseases.
Retinal vein occlusion (RVO) is a common retinal vascular disease that can cause severe visual impairment. Many observational studies have shown that type 2 diabetes (T2DM) is associated with RVO, ...but it remains unknown if the association is causal. The present study aimed to perform Mendelian randomization (MR) analyses to evaluate the causal contribution of genetically predicted T2DM to RVO.
We obtained summary-level data from a genome-wide association study meta-analysis including 48,286 cases and 250,671 controls for T2DM and from a genome wide association study of 372 cases and 182,573 controls in the FinnGen project for RVO. To verify the robustness of the results, an independent validation dataset for T2DM (12,931 cases and 57,196 controls) was used. In addition to the main MR analysis using the inverse variance weighted (fixed effect) approach, sensitivity analyses and multivariable MR adjusting for common risk factors of RVO were conducted.
Genetically predicted T2DM was found to be causally associated with RVO risk (odds ratio (OR)=2.823, 95% confidence interval (CI): 2.072-3.847,
=4.868×10
). This association was supported by sensitivity analyses using the weighted median (OR=2.415, 95% CI: 1.411-4.132,
=1.294×10
), weighted mode (OR=2.370, 95% CI: 1.321-4.252,
=5.159×10
), maximum likelihood (OR=2.871, 95% CI: 2.100-3.924,
=3.719×10
), MR-PRESSO (OR=2.823, 95% CI: 2.135-3.733,
=5.150×10
), and MR-Egger (OR=2.441, 95% CI: 1.149-5.184,
=2.335×10
) methods. In addition, this association persisted in multivariable MR after accounting for common RVO risk factors (OR=1.748, 95% CI: 1.238-2.467, P=1.490×10
). The MR analyses using the validation dataset obtained consistent results.
This study indicates that genetically predicted T2DM may have a causal contribution to RVO. Future studies are required to elucidate the underlying mechanisms.
Results from various studies reveal that the role of G protein‐coupled oestrogen receptor (GPER) is cancer‐context dependent, and the function of GPER in non–small‐cell lung cancer (NSCLC) is still ...unclear. The present study demonstrated that neoplasm lung tissues expressed higher level of GPER compared with the normal lung tissues. The clinical data also showed that GPER expression level was positively correlated with the tumour stage of NSCLC. Our experimental data confirmed that GPER played an oncogenic role to promote cell growth of NSCLC cells. Mechanistic dissection revealed that GPER could modulate the NOTCH1 pathway to regulate cell growth in NSCLC cells. Further exploration of the mechanism demonstrated that GPER could up‐regulate circNOTCH1, which could compete with NOTCH1 mRNA for METTL14 binding. Because of the lack of m6A modification by METTL14 on the NOTCH1 mRNA, NOTCH1 mRNA was more stable and much easier to undergo protein translation. Subsequently, we found that GPER could prevent YAP1 phosphorylation and promote YAP1‐TEAD's transcriptional regulation on QKI, a transacting RNA‐binding factor involved in circRNA biogenesis, to facilitate circNOTCH1 generation. Supportively, data from preclinical mice model with implantation of H1299 cells also demonstrated that knock‐down of circNOTCH1 could block GPER‐induced NOTCH1 to suppress NSCLC tumour growth. Together, our data showed that GPER could promote NSCLC cell growth via regulating the YAP1/QKI/circNOTCH1/m6A methylated NOTCH1 pathway, and targeting our identified molecules may be a potentially therapeutic approach to suppress NSCLC development.
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