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Abstract Lung cancer remains the most common cause of cancer death. Given the continued research into new drugs and combination therapies, outcomes in lung cancer have been improved, and clinical benefits have been expanded to a broader patient population. However, the overall cure and survival rates for lung cancer patients remain low, especially in metastatic cases. Among the available lung cancer treatment options, such as surgery, radiation therapy, chemotherapy, targeted therapies, and alternative therapies, immunotherapy has shown to be the most promising. The exponential progress in immuno-oncology research and recent advancements made in the field of immunotherapy will further increase the survival and quality of life for lung cancer patients. Substantial progress has been made in targeted therapies using tyrosine kinase inhibitors and monoclonal antibody immune checkpoint inhibitors with many US Food And Drug Administration (FDA)-approved drugs targeting the programmed cell death ligand-1 protein (e.g., durvalumab, atezolizumab), the programmed cell death-1 receptor (e.g., nivolumab, pembrolizumab), and cytotoxic T-lymphocyte-associated antigen 4 (e.g., tremelimumab, ipilimumab). Cytokines, cancer vaccines, adoptive T cell therapies, and Natural killer cell mono- and combinational therapies are rapidly being studied, yet to date, there are currently none that are FDA-approved for the treatment of lung cancer. In this review, we discuss the current lung cancer therapies with an emphasis on immunotherapy, including the challenges for future research and clinical applications.

Background Many countries around the world highlight the health in all policies (HiAP). However, most of the related research focused on the influential factors and implementation strategies, with less concern on the evaluation of HiAP. In response to HiAP's call, the Chinese government has proposed health promotion policies (HPPs) in counties or districts, the evaluation of HPPs in sample counties or districts of Sichuan province in China is an essential basis for optimizing policy content, improving policy implementation, and ensuring health promotion's continuous and efficient operation. Methods This paper established an evaluation system for HPPs based on the PMC-Index model and then quantitatively analyzed 37 representative HPPs from the pilot areas in Sichuan province. In addition, a team of experts conducted a field assessment. Results The results showed that the average PMC index of 37 HPPs was 7.091, and correlation analysis showed that there was a significant correlation between the PMC index and expert score. Conclusions This study indicates that the overall consistency of HPPs was good and proves a connection between the formulation and implementation of HPPs.

Developing a novel artificial intelligence (AI) system that can automatically detect pulmonary arterial hypertension (PAH) after correcting the ventricular septal defect (VSD) and to help clinicians make reasonable treatment plans. We analyzed data from 1,316 patients under 1 year old who underwent VSD surgery at Women and Children’s Hospital, Qingdao University and Qingdao Central Hospital from January 2017 to December 2023. Pediatric patients were classified into two groups based on postoperative echocardiography and cardiac catheterization results: a normal pulmonary artery pressure group (NG) and PAH after correcting VSD group (CD). We trained and validated a multimodal multipath AI system (MMAI) using echocardiography (Echo) and chest digital radiography (DR) dataset. Dice similarity coefficient (DSC) is used to measure the effectiveness of the model in automatic contour segmentation of images. We assessed the recognition performance of MMAI using the area under the receiver operating characteristic curve (AUC), accuracy, and F1-score through internal and external test sets. The ResNet-50 model demonstrates good performance in automatic cardiac contour segmentation, with DSC values of 0.950 ± 0.017 (Echo) and 0.946 ± 0.020 (DR). Compared to single image types, the multimodal model based on the ResNet-50 model performs better in the binary classification task in the training and validation sets, with both AUC and accuracy exceeding 90%. In multipath detection, the MMAI system performs well in the NG and CD by combining internal and external test set detection, with AUC, accuracy, and F1-score all exceeding 0.9. Our preliminary study developed an MMAI system using Echo and chest DR images, showing potential for assisting in the detection of CD in VSD patients under 1 year of age prior to surgery. Further validation is needed to confirm clinical applicability.

To achieve a high degree of quantum noise squeezing, nonlinear optical interaction process is often employed. Here, we propose to utilize quasi-bound states in the continuum (quasi-BICs) and Fano resonances to enhance optical squeezing without nonlinearity. The theory of quantization for electromagnetic fields in the periodic nanostructure with dispersion and absorption has been developed by means of the Green's function technique with the plane wave expansion method. The quasi-BICs and Fano resonances of radiation modes are realized by designing the photonic crystal slab structure. Based on these quasi-BICs and Fano resonances, we demonstrate that strong squeezed states can be realized by using the balanced homodyne detection scheme. The squeezing degree can be improved by more than 14 times when a weak squeezed states passes through the structure with quasi-BICs and Fano resonances. The advantage of this method is that it is not only efficient but also easy to implement because the nonlinear optical processes are not employed, which is very beneficial for the quantum information processing and precision metrology.

Urban visual localization is the process of determining the pose (position and attitude) of the imaging sensor (or platform) with the help of existing geo-referenced data. This task is critical and challenging for many applications, such as autonomous navigation, virtual and augmented reality, and robotics, due to the dynamic and complex nature of urban environments that may obstruct Global Navigation Satellite Systems (GNSS) signals. This paper proposes a block-wise matching strategy for urban visual localization by using geo-referenced Google Street View (GSV) panoramas as the database. To determine the pose of the monocular query images collected from a moving vehicle, neighboring GSVs should be found to establish the correspondence through image-wise and block-wise matching. First, each query image is semantically segmented and a template containing all permanent objects is generated. The template is then utilized in conjunction with a template matching approach to identify the corresponding patch from each GSV image within the database. Through the conversion of the query template and corresponding GSV patch into feature vectors, their image-wise similarity is computed pairwise. To ensure reliable matching, the query images are temporally grouped into query blocks, while the GSV images are spatially organized into GSV blocks. By using the previously computed image-wise similarities, we calculate a block-wise similarity for each query block with respect to every GSV block. A query block and its corresponding GSV blocks of top-ranked similarities are then input into a photogrammetric triangulation or structure from motion process to determine the pose of every image in the query block. A total of three datasets, consisting of two public ones and one newly collected on the Purdue campus, are utilized to demonstrate the performance of the proposed method. It is shown it can achieve a meter-level positioning accuracy and is robust to changes in acquisition conditions, such as image resolution, scene complexity, and the time of day.

Background Lung cancer has high morbidity and mortality rates, which results in a poor prognosis. Cuproptosis is a novel cell death mechanism. The aim of this study was to examine the biological characteristics and clinical significance of genes associated with cuproptosis in lung adenocarcinoma (LUAD), and to understand the molecular mechanisms underlying the occurrence and progression of LUAD. Methods We targeted 10 cuproptosis-related genes from previous studies and used the datasets from GEO and TCGA databases to identify differential genes related to cuproptosis; then the data were analyzed by R package, Cytoscape, TISDB, cBioPortal, STRING, CancerSEA, and Disgenet; and finally, the data were detected by immunohistochemistry validation was performed. Results CDKN2A and MTF1 were cuproptosis-associated LUAD differential genes and were differentially expressed in immune subtypes. The expression of CDKN2A and MTF1 showed correlation with multiple functional states of LUAD.CDKN2A was negatively correlated with LUAD survival prognosis. Conclusion CDKN2A and MTF1 were correlated with the diagnosis of LUAD, and CDKN2A was negatively correlated with the survival and prognosis of LUAD. CDKN2A has the potential to contribute to the early diagnosis and prognosis analysis of LUAD.

Extensive research on zeolitic imidazolate framework (ZIF-8) and its derivatives has highlighted their unique properties in nanomedicine. ZIF-8 exhibits advantages such as pH-responsive dissolution, easy surface functionalization, and efficient drug loading, making it an ideal nanosystem for intelligent drug delivery and phototherapy. These characteristics have sparked significant interest in its potential applications in tissue regeneration, particularly in bone, skin, and nerve regeneration. This review provides a comprehensive assessment of ZIF-8’s feasibility in tissue engineering, encompassing material synthesis, performance testing, and the development of multifunctional nanosystems. Furthermore, the latest advancements in the field, as well as potential limitations and future prospects, are discussed. Overall, this review emphasizes the latest developments in ZIF-8 in tissue engineering and highlights the potential of its multifunctional nanoplatforms for effective complex tissue repair.

With the rapid development of the computer and sensor field, inertial sensor data have been widely used in human activity recognition. At present, most relevant studies divide human activities into basic actions and transitional actions, in which basic actions are classified by unified features, while transitional actions usually use context information to determine the category. For the existing single method that cannot well realize human activity recognition, this paper proposes a human activity classification and recognition model based on smartphone inertial sensor data. The model fully considers the feature differences of different properties of actions, uses a fixed sliding window to segment the human activity data of inertial sensors with different attributes and, finally, extracts the features and recognizes them on different classifiers. The experimental results show that dynamic and transitional actions could obtain the best recognition performance on support vector machines, while static actions could obtain better classification effects on ensemble classifiers; as for feature selection, the frequency-domain feature used in dynamic action had a high recognition rate, up to 99.35%. When time-domain features were used for static and transitional actions, higher recognition rates were obtained, 98.40% and 91.98%, respectively.

The senescence of alveolar type II (AT2) cells impedes self-repair of the lung epithelium and contributes to lung injury in the setting of idiopathic pulmonary fibrosis (IPF). Yes-associated protein 1 (YAP1) is essential for cell growth and organ development; however, the role of YAP1 in AT2 cells during pulmonary fibrosis is still unclear. YAP1 expression was found to be downregulated in the AT2 cells of PF patients. Deletion of YAP1 in AT2 cells resulted in lung injury, exacerbated extracellular matrix (ECM) deposition, and worsened lung function. In contrast, overexpression of YAP1 in AT2 cells promoted alveolar regeneration, mitigated pulmonary fibrosis, and improved lung function. In addition, overexpression of YAP1 alleviated bleomycin (BLM) -induced senescence of alveolar epithelial cells both in vivo and in vitro. Moreover, YAP1 promoted the expression of peroxiredoxin 3 (Prdx3) by directly interacting with TEAD1. Forced expression of Prdx3 inhibited senescence and improved mitochondrial dysfunction in BLM-treated MLE-12 cells, whereas depletion of Prdx3 partially abrogated the protective effect of YAP1. Furthermore, overexpression of Prdx3 facilitated self-repair of the injured lung and reduced ECM deposition, while silencing Prdx3 attenuated the antifibrotic effect of YAP1. In conclusion, this study demonstrated that YAP1 alleviates lung injury and pulmonary fibrosis by regulating Prdx3 expression to improve mitochondrial dysfunction and block senescence in AT2 cells, revealing a potential novel therapeutic strategy for pulmonary fibrosis. Alveolar YAP1: Key to lung regeneration and fibrosis prevention Idiopathic pulmonary fibrosis is still not fully understood, and effective treatments are scarce. This study investigates the role of a protein, YAP1, in lung fibrosis. Researchers used mice and human lung samples to study how YAP1 influences lung cell aging and lung structure. The findings showed that increasing YAP1 levels in alveolar type II cells reduced lung fibrosis by improving the function of mitochondria and decreasing cell aging. Specifically, YAP1 worked through a pathway involving a molecule, Prdx3. However, reducing YAP1 levels worsened lung fibrosis. The researchers suggest that enhancing YAP1 activity in lung cells could be a potential treatment for lung fibrosis. This method targets lung cell aging and promotes healthy lung tissue repair. The results pave the way for developing treatments for IPF and possibly other similar lung diseases. This summary was initially drafted using artificial intelligence, then revised and fact-checked by the author.

The addition of photosynthetically active radiation (PAR, 400–700 nm) with a specific quantity of far-red photons (FR, 700–750 nm) has been demonstrated to positively influence biomass accumulation and nutritional quality in greenhouse lettuce. However, current relevant studies seldom consider comprehensive and systematic comparisons of the efficacy of different approaches: substitution versus supplementation. The present work aimed to compare the two aforementioned strategies, evaluate how they impact plant growth, development and metabolic processes, and analyse the light use efficiency. In this study, loose-leaf lettuce (cv. ‘Dasusheng’) grown in a glass Venlo-type greenhouse was exposed to six supplementary light treatments, including white-red (WR) light-emitting diodes (LEDs), FR LEDs, and WR plus FR LEDs [WR130 + FR30 (the number was the photon flux density provided by WR or FR LEDs, respectively), WR130 + FR50, WR100 + FR30, and WR80 + FR50]. Lettuce that was grown only under natural light (NL) conditions was considered the control. According to the results of the present study, supplementary light increased biomass accumulation, and the contents of ascorbic acid, total soluble sugar, and starch relative to the control. Lettuce plants treated with WR130 + FR50 treatment presented the highest shoot and root fresh/dry weights, the highest total chlorophyll content, and the best nutritional quality, whereas the lettuce weight did not differ between the WR130 + FR30 and WR100 + FR30 treatments. Compared with that of NL, the stacking of thylakoids increased most intensely in response to the WR130 + FR50 and WR100 + FR30 treatments. Biomass accumulation, nutritional quality, stomatal area, chloroplast area, and expression of photosynthesis-related genes ( LHCb , PsbA , rbcL , and rbcS ) in lettuce plants, as well as light use efficiency, presented increasing-to-decreasing trends as the FR fraction increased. In conclusion, partially substituting PAR with FR photons coincidentally aligns with the supplementation of FR photons, and a supplementary FR fraction of 0.50 to 0.56 is suitable for greenhouse-grown lettuce under weak light conditions because of the increased photochemical efficiency, biomass accumulation, and carbohydrate content.