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The creation of new bonds via C-F bond cleavage of readily available per- or oligofluorinated compounds has received growing interest. Using such a strategy, a myriad of valuable partially fluorinated products can be prepared, which otherwise are difficult to make by the conventional C-F bond formation methods. Visible light photoredox catalysis has been proven as an important and powerful tool for defluorinative reactions due to its mild, easy to handle, and environmentally benign characteristics. Compared to the classical C-F activation that proceeds via two-electron processes, radicals are the key intermediates using visible light photoredox catalysis, providing new modes for the cleavage of C-F bonds. In this review, a summary of the visible light-promoted C-F bond cleavage since 2018 was presented. The contents were classified by the fluorosubstrates, including polyfluorinated arenes, gem-difluoroalkenes, trifluoromethyl arenes, and trifluoromethyl alkenes. An emphasis is placed on the discussion of the mechanisms and limitations of these reactions. Finally, my personal perspective on the future development of this rapidly emerging field was provided.

In 2018, US government imposed a ban on Chinese electronics firm ZTE, prohibiting it from procuring chip products from American companies for a duration of seven years. Subsequently, ZTE experienced a shutdown. The concept of \"bottleneck technology\" gained prominence in diverse media outlets. Chinese government acknowledged the importance of identifying pertinent bottleneck technologies in specific sectors, particularly in electronic manufacturing. It underscored the significance of promptly analyzing the evolutionary traits of these technologies within the industry and engaging in research and development endeavors to safeguard national technological security. To address this issue, the study initially extracted pertinent industry enterprises from the Orbis database. Subsequently, it utilized the technical codes associated with the patent data of these enterprises to establish a social network, pinpoint key technologies, and compute the technical share metrics for these pivotal technology codes. Numerous technologies are exclusively controlled by a limited number of enterprises, leading to the identification of bottleneck technologies. This, in turn, enables the determination of critical paths to reveal the developmental history and distinctive features of these bottlenecks. The research indicates that the electronic manufacturing industry faces various bottleneck technologies, which extend beyond chips to include production equipment, materials, processes, and inspection devices. Numerous technologies have a significant developmental background, necessitating substantial technological development to achieve parity. However, in swiftly advancing technological domains, China possesses the capability to make advancements at an accelerated rate.

•A decomposed convolutional neural network model was established based on rs-fMRI connectivity.•The model paired with the Dos_160 atlas can be effectively applied to the diagnosis of tinnitus.•This study pinpointed key brain regions for subjective tinnitus using a data-driven approach. Many studies have investigated aberrant functional connectivity (FC) using resting-state functional MRI (rs-fMRI) in subjective tinnitus patients. However, no studies have verified the efficacy of resting-state FC as a diagnostic imaging marker. We established a convolutional neural network (CNN) model based on rs-fMRI FC to distinguish tinnitus patients from healthy controls, providing guidance and fast diagnostic tools for the clinical diagnosis of subjective tinnitus. A CNN architecture was trained on rs-fMRI data from 100 tinnitus patients and 100 healthy controls using an asymmetric convolutional layer. Additionally, a traditional machine learning model and a transfer learning model were included for comparison with the CNN, and each of the three models was tested on three different brain atlases. Of the three models, the CNN model outperformed the other two models with the highest area under the curve, especially on the Dos_160 atlas (AUC = 0.944). Meanwhile, the model with the best classification performance highlights the crucial role of the default mode network, salience network, and sensorimotor network in distinguishing between normal controls and patients with subjective tinnitus. Our CNN model could appropriately tackle the diagnosis of tinnitus patients using rs-fMRI and confirmed the diagnostic value of FC as measured by rs-fMRI.

Purely organic room-temperature phosphorescence has attracted attention for bioimaging but can be quenched in aqueous systems. Here we report a water-soluble ultralong organic room-temperature phosphorescent supramolecular polymer by combining cucurbit[n]uril (CB[7], CB[8]) and hyaluronic acid (HA) as a tumor-targeting ligand conjugated to a 4-(4-bromophenyl)pyridin-1-ium bromide (BrBP) phosphor. The result shows that CB[7] mediated pseudorotaxane polymer CB[7]/HA–BrBP changes from small spherical aggregates to a linear array, whereas complexation with CB[8] results in biaxial pseudorotaxane polymer CB[8]/HA–BrBP which transforms to relatively large aggregates. Owing to the more stable 1:2 inclusion complex between CB[8] and BrBP and the multiple hydrogen bonds, this supramolecular polymer has ultralong purely organic RTP lifetime in water up to 4.33 ms with a quantum yield of 7.58%. Benefiting from the targeting property of HA, this supramolecular polymer is successfully applied for cancer cell targeted phosphorescence imaging of mitochondria. Room-temperature phosphorescence has attracted attention for bioimaging, but quenching in aqueous systems is an issue. Here, the authors report on the synthesis of a water soluble organic phosphorescent polymer and demonstrate application is cancer cell targeting and imaging.

Background There is increasing evidence that the existence of systemic inflammation response is correlated with poor prognosis in several solid tumors. The aim of this retrospective study was to investigate the association between systemic immune-inflammation index (SII) and therapy response and overall survival in patients with stage III non-small cell lung cancer (NSCLC). The prognostic values of neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), and prognostic nutritional index (PNI) were also evaluated. Methods In total, 332 patients with new diagnosis of stage III NSCLC were included in this retrospective analysis. SII was defined as platelet counts × neutrophil counts/lymphocyte counts. Receiver operating characteristic (ROC) curve was used to evaluate the optimal cut-off value for SII, NLR, PLR and PNI. Univariate and multivariate survival analysis were performed to identify the factors correlated with overall survival. Results Applying cut-offs of ≥ 660 (SII), ≥ 3.57 (NLR), ≥ 147 (PLR), ≤ 52.95 (PNI), SII ≥ 660 was significantly correlated with worse ECOG PS (< 0.001), higher T stage (< 0.001), advanced clinical stage ( p  = 0.019), and lower response rate ( p  = 0.018). In univariate analysis, SII ≥ 660, NLR ≥ 3.57, PLR ≥ 147, and PNI ≤ 52.95 were significantly associated with worse overall survival ( p all  < 0.001). Patients with SII ≥ 660 had a median overall survival of 10 months, and patients with SII < 660 showed a median overall survival of 30 months. In multivariate analysis only ECOG PS (HR, 1.744; 95% CI 1.158–2.626; p  = 0.008), T stage (HR, 1.332; 95% CI 1.032–1.718; p  = 0.028), N stage (HR, 1.848; 95% CI 1.113–3.068; p  = 0.018), SII (HR, 2.105; 95% CI 1.481–2.741; p  < 0.001) and NLR ≥ 3.57 (HR, 1.934; 95% CI 1.448–2.585; p  < 0.001) were independently correlated with overall survival. Conclusions This study demonstrates that the SII is an independent prognostic indicator of poor outcomes for patients with stage III NSCLC and is superior to other inflammation-based factors in terms of prognostic ability.

Abandoned object detection is a critical task in the field of public safety. However, existing methods perform poorly when detecting small and occluded objects, leading to high false detection and missed detection rates. To address this issue, this paper proposes an abandoned object detection method that integrates an adaptive dual-background model with SAO-YOLO (Small Abandoned Object YOLO). The goal is to reduce false and missed detection rates for small and occluded objects, thereby improving overall detection accuracy. First, the paper introduces an adaptive dual-background model that adjusts according to scene changes, reducing noise interference in the background model. When combined with an improved PFSM (Pixel-based Finite State Machine) model, this enhances detection accuracy and robustness. Next, a network model called SAO-YOLO is designed. Key improvements within this model include the SAO-FPN (Small Abandoned Object FPN) feature extraction network, which fully extracts features of small objects, and a lightweight decoupled head, SODHead (Small Object Detection Head), which precisely extracts local features and enhances detection accuracy through multi-scale feature fusion. Finally, experimental results show that SAO-YOLO increases mAP@0.5 and mAP@0.5:0.95 by 9.0% and 5.1%, respectively, over the baseline model. It outperforms other advanced detection models. Ultimately, after a series of experiments on the ABODA, PETS2006, and AVSS2007 datasets, the proposed method achieved an average detection precious of 91.1%, surpassing other advanced methods. It significantly outperforms other advanced detection methods. This approach notably reduces false and missed detections, especially for small and occluded objects.

Non-invasive monitoring of gastrointestinal drug release in vivo is extremely challenging because of the limited spatial resolution and long scanning time of existing bioimaging modalities, such as X-ray radiation and magnetic resonance. Here, we report a novel microcarrier that can retain drugs and withstand the harsh conditions of gastrointestinal tract. Significantly, we can track the microcarrier fate and semi-quantitatively monitor the content of drug released in vivo in real time by measuring the fluorescence signals in the second near-infrared window of lanthanide-based downconversion nanoparticles with an absorption competition-induced emission bioimaging system. The microcarriers show a prolonged residence time of up to 72 h in the gastrointestinal tract, releasing up to 62% of their content. Moreover, minimal deposition of the microcarriers is found in non-target organs, such as the liver, spleen and kidney. These findings provide novel insights for the development of therapeutic and bioimaging strategies of orally administered drugs. The sustained release of drugs within the gastrointestinal tract as well as their detection following administration is a challenge. Here, the authors develop a microcarrier that supported sustained drug release in the gastrointestinal tract in vivo and could be monitored with real-time imaging.

Vaccines to induce effective and sustained antitumor immunity have great potential for postoperative cancer therapy. However, a robust cancer vaccine simultaneously eliciting tumor-specific immunity and abolishing immune resistance continues to be a challenge. Here we present a personalized cancer vaccine (PVAX) for postsurgical immunotherapy. PVAX is developed by encapsulating JQ1 (a BRD4 inhibitor) and indocyanine green (ICG) co-loaded tumor cells with a hydrogel matrix. Activation of PVAX by 808 nm NIR laser irradiation significantly inhibits the tumor relapse by promoting the maturation of dendritic cells and eliciting tumor infiltration of cytotoxic T lymphocytes. A mechanical study reveals that NIR light-triggered antigen release and JQ1-mediated PD-L1 checkpoint blockade cumulatively contribute to the satisfied therapeutic effect. Furthermore, PVAX prepared from the autologous tumor cells induces patient-specific memory immune response to prevent tumor recurrence and metastasis. The PVAX model might provide novel insights for postoperative immunotherapy. Cancer vaccines represent a promising personalized therapeutic approach to treating cancer. Here, the authors report the efficacy in a metastatic model of a cancer vaccine-mediated postoperative immunotherapy, based on the coencapsulation of the JQ1 and a photosensitizer ICG together with inactivated tumor cells into a hydrogel matrix.

Imitation is an important learning heuristic in animal and human societies. Previous explorations report that the fate of individuals with cooperative strategies is sensitive to the protocol of imitation, leading to a conundrum about how different styles of imitation quantitatively impact the evolution of cooperation. Here, we take a different perspective on the personal and external social information required by imitation. We develop a general model of imitation dynamics with incomplete information in networked systems, which unifies classical update rules including the death-birth and pairwise-comparison rule on complex networks. Under pairwise interactions, we find that collective cooperation is most promoted if individuals neglect personal information. If personal information is considered, cooperators evolve more readily with more external information. Intriguingly, when interactions take place in groups on networks with low degrees of clustering, using more personal and less external information better facilitates cooperation. Our unifying perspective uncovers intuition by examining the rate and range of competition induced by different information situations. Studies of the evolution of cooperation often assume information use that is inconsistent with empirical observations. Here, the authors’ research on general imitation dynamics reveals that cooperation is fostered by individuals using less personal information and more social information.

Metasurfaces, ultrathin metamaterials constructed by planar meta-atoms with tailored electromagnetic (EM) responses, have attracted tremendous attention due to their exotic abilities to freely control EM waves. With active elements incorporated into metasurface designs, one can realize tunable and/or reconfigurable metadevices with functionalities controlled by external stimuli, opening a new platform to dynamically manipulate EM waves. In this article, we briefly review recent progress on tunable/reconfigurable metasurfaces, focusing on their working mechanisms and practical applications. We first describe available approaches, categorized into different classes based on external stimuli applied, to realize homogeneous tunable/reconfigurable metasurfaces, which can offer uniform manipulations on EM waves. We next summarize recent achievements on inhomogeneous tunable/reconfigurable metasurfaces with constitutional meta-atoms locally tuned by external knobs, which can dynamically control the wave-fronts of EM waves. We conclude this review by presenting our own perspectives on possible future directions and existing challenges in this fast developing field.