Alkyl effects on charge recombination in copper electrolyte-based dye-sensitized solar cells: Insights for targeted molecular design towards high performance.

Two quinoxaline dyes utilized in copper-electrolyte-based dye-sensitized solar cells (Cu-DSSCs) are theoretically investigated to analyze the impact of alkyl chains on dye performance. The investigation shows that ZS4, known for its record efficiency of up to 13.2 %, exhibits higher electron coupling and fewer binding sites for dye-[Cu(tmby)2]2+ interaction compared to ZS5. Contrary to common belief, alkyl chains are found to not only provide shielding but also hinder the interaction between dye and [Cu(tmby)2]2+ by influencing the optimal conformation of dyes, thereby impeding the charge recombination process. It is crucial to consider the influence of alkyl chains on dye conformation when discussing the relationship between dye structure and performance, rather than oversimplifying it as often done traditionally. Building on these findings, eight dyes are strategically designed by adjusting the position of the alkyl chain to further decrease charge recombination compared to ZS4. Theoretical evaluation of these dyes reveals that changing the alkyl chain on the nitrogen atom from 2-ethylhexyl (ZS4) to 1-hexylheptyl (D3-2) not only reduces the charge recombination rate but also enhances light harvesting ability. Therefore, D3-2 shows potential as a candidate for experimental synthesis of high-performance Cu-DSSCs with improved efficiency.

Photo-assisted conversion of tetracycline in regulated persulfate system: Multiple roles of natural dissolved organic matter.

Advanced oxidation processes (AOPs) using persulfate system can effectively remove organic pollutants. However, dissolved organic matter (DOM) has multiple effects on AOPs efficiency, and the influence of DOMs from natural sources on AOPs is still unclear. In this study, we explored the effects of soil DOM (SDOM) and fertilizer DOM (FDOM) on tetracycline (TC) removal by persulfate systems. DOMs introduction decreased light transmittance, slightly increased the pH of the systems, and destroyed original adsorption-desorption equilibrium. SDOM promoted most reactive species generation in the initial stage, thus improving the initial TC degradation rate. However, introduction of SDOM and FDOM increased the final TC residual rate. FDOM produced more obvious inhibitory effects on TC degradation. The final TC residual rates in systems containing 7.5 and 15 mg L-1 FDOM (F7.5-TC-PS and F15-TC-PS, respectively) were 25.85 % and 25.52 %, respectively. The inhibitory effects of FDOM on TC degradation were related to the combination between TC and FDOM, with humic acid-like component in FDOM being the main contributor. Besides, the main components in DOMs underwent transformation in the persulfate systems. This study sought to provide insights into the regulatory effects of DOM on TC photo-assisted conversion by AOPs.

Nanotechnology based gas delivery system: a "green" strategy for cancer diagnosis and treatment.

Gas therapy, a burgeoning clinical treatment modality, has garnered widespread attention to treat a variety of pathologies in recent years. The advent of nanoscale gas drug therapy represents a novel therapeutic strategy, particularly demonstrating immense potential in the realm of oncology. This comprehensive review navigates the landscape of gases endowed with anti-cancer properties, including hydrogen (H2), carbon monoxide (CO), carbon dioxide (CO2), nitric oxide (NO), oxygen (O2), sulfur dioxide (SO2), hydrogen sulfide (H2S), ozone (O3), and heavier gases. The selection of optimal delivery vectors is also scrutinized in this review to ensure the efficacy of gaseous agents. The paper highlights the importance of engineering stimulus-responsive delivery systems that enable precise and targeted gas release, thereby augmenting the therapeutic efficiency of gas therapy. Additionally, the review examines the synergistic potential of integrating gas therapy with conventional treatments such as starvation therapy, ultrasound (US) therapy, chemotherapy, radiotherapy (RT), and photodynamic therapy (PDT). It also discusses the burgeoning role of advanced multimodal and US imaging in enhancing the precision of gas therapy applications. The insights presented are pivotal in the strategic development of nanomedicine platforms designed for the site-specific delivery of therapeutic gases, heralding a new era in cancer therapeutics.

Resilient water quality management: Insights from Japan's environmental quality standards for conserving aquatic life framework.

Currently, chemicals and waste are recognized as key drivers of habitat degradation and biodiversity loss in aquatic ecosystems. To ensure vibrant habitats for aquatic species and maintain a sustainable aquatic food supply system, Japan promulgated its Environmental Quality Standards for the Conservation of Aquatic Life (EQS-CAL), based on its own aquatic life water quality criteria (ALWQC) derivation method and application mechanism. Here we overview Japan's EQS-CAL framework and highlight their best practices by examining the framework systems and related policies. Key experiences from Japan's EQS-CAL system include: (1) Classifying six types of aquatic organisms according to their adaptability to habitat status; (2) Using a risk-based chemical screening system for three groups of chemical pollutants; (3) Recommending a five-step method for determining ALWQC values based on the most sensitive life stage of the most sensitive species; (4) Applying site-specific implementation mechanisms through a series of Plan-Do-Check-Act loops. This paper offers scientific references for other jurisdictions, aiding in the development of more resilient ALWQC systems that can maintain healthy environments for aquatic life and potentially mitigate ongoing threats to human societies and global aquatic biodiversity.

A QuEChERS method based on octadecyl-bonded hectorite for the determination of ten mycotoxins in yak ghee.

To develop a clean-up material suitable for high-fat food matrices for detecting mycotoxins in yak ghee, an octadecyl-bonded hectorite (Hectorite@NHCO(CH2)17CH3) was synthesized through multi-step chemical reactions. A modified QuEChERS-HPLC-MS/MS method for detecting ten mycotoxins in sesame oil in yak ghee was established using Hectorite@NHCO(CH2)17CH3 as clean-up agent. It involved extracting mycotoxin contaminants using acidified acetonitrile and employing the Hectorite@NHCO(CH2)17CH3 to remove interfering substances from the extract. The purified samples were then analyzed using HPLC-MS/MS. Within a linear range of 1.0-500 µg/kg, there was a good linear relationship between the quantification ion peak area of the target analytes and the corresponding concentrations (R2 ≥ 0.9991). The limit of detection (LOD) ranged from 0.10 µg/kg to 18.62 µg/kg and the limit of quantitation (LOQ) ranged 0.32-62.07 µg/kg. The recoveries at low, medium and high concentrations (25, 100 and 500 µg/kg) ranged from 72.2% to 113.9%, with relative standard deviations (RSD) between 3.2% and 17.5%. The intra-day and inter-day precision met experimental requirements. The proposed method was characterized by a high accuracy and precision, and it could cater to the current demand for detecting ten mycotoxins in yak ghee.

Rapamycin and Hyperoside-Co-loaded Macrophage Delivery System Enhanced Pulmonary Fibrosis Therapy by Autophagy Upregulation and Epithelial-to-Mesenchymal Transition Inhibition.

Pulmonary fibrosis is a lethal interstitial lung disease, for which current treatments are inadequate in halting its progression. A significant factor contributing to the development of fibrosis is insufficient autophagy, which leads to increased fibroblast proliferation and collagen deposition. However, treatments aimed at upregulating autophagy often cause further lung pathology due to the disruption of epithelial cell balance. In response, we have developed a novel macrophage delivery system loaded with an epithelial-to-mesenchymal transition inhibitor, hyperoside (HYP), and an autophagy inducer, rapamycin (RAP). This system targets the fibrotic areas of the lung through chemotaxis, releases liposomes via macrophage extracellular traps, and effectively inhibits fibroblast proliferation while restoring the alveolar structure through the combined effects of RAP and HYP, ultimately reducing lung pathology without causing systemic toxicity. Our findings not only highlight a promising method to enhance autophagy-based treatments for pulmonary fibrosis but also demonstrate the potential of macrophages as effective nanocarriers for drug delivery.

A novel fluorescent probe based on dicyanoisophorone derivatives for hypochlorite detection in living cells.

This study presents a long-wavelength fluorescent probe CNC for the detection of ClO- in vitro and in vivo. Upon interaction with ClO-, this probe exhibited a significant increase in fluorescence, with a significant Stokes shift (169 nm), lower detection limit (1.38 µM), high sensitivity and selectivity. Moreover, the probe demonstrated excellent cell permeability and minimal cytotoxicity, allowing for successful imaging of both endogenous and exogenous ClO- in living cells.

Structure Tailoring of Hemicyanine Dyes for In Vivo Shortwave Infrared Imaging.

In vivo bioimaging using shortwave infrared (SWIR) (1000-2000 nm) molecular dyes enables deeper penetration and higher contrast compared to visible and near-infrared-I (NIR-I, 700-900 nm) dyes. Developing new SWIR molecules is still quite challenging. This study developed SRHCYs, a panel of fluorescent dyes based on hemicyanine, with adjustable absorbance (830-1144 nm) and emission (886-1217 nm) wavelength. The photophysical attributes of these dyes are precisely tailored by strengthening the donor parts and extending polymethine chains. SRHCY-3, with its clickable azido group, was chosen for high-performance imaging of blood vessels in living mice, enabling the precise detection of brain and lung cancer. The combination of these probes achieved in vivo multicolor imaging with negligible optical crosstalk. This report presents a series of SWIR hemicyanine dyes with promising spectroscopic properties for high-contrast bioimaging and multiplexing detection.

Metabolic tumor volume from baseline [18 F]FDG PET/CT at diagnosis improves the IPI stratification in patients with diffuse large B-cell lymphoma.

PURPOSE: Although several different parameters of PET/CT were reported to be predictive of survival in DLBCL, the best parameter remains to be elucidated and whether it could improve the risk stratification of IPI in patients with DLBCL. PROCEDURES: 262 DLBCL patients including in the training and validation cohort were retrospectively analyzed in this study. RESULTS: Among different parameters, MTV was identified as the optimal prognostic parameter with a maximum area under the curve (AUC) of 0.652 ± 0.112 than TLG and SDmax (0.645 ± 0.113 and 0.600 ± 0.117, respectively). Patients with high MTV were associated with inferior PFS (p < 0.001 and p = 0.021, respectively) and OS (p < 0.001 and p < 0.001, respectively) in both the training and validation cohort. The multivariate analysis revealed that high MTV was an unfavorable factor for PFS (relative ratio [RR], 2.295; 95% confidence interval [CI], 1.457-3.615; p < 0.01) and OS (RR, 2.929; 95% CI 1.679-5.109; p < 0.01) independent of IPI. CONCLUSIONS: Further analysis showed MTV could improve the risk stratification of IPI for both PFS and OS (p < 0.01 and p < 0.01, respectively). In conclusion, our study suggests that MTV was an optimal prognostic parameter of PET/CT for survival and it could improve the risk stratification of IPI in DLBCL, which may help to guide treatment in clinical trial.

Development of a hybrid rhodamine-hydrazine NIR fluorescent probe for sensitive detection and imaging of peroxynitrite in necrotizing enterocolitis model.

This study describes the synthesis and characterization of a novel near-infrared (NIR) fluorescent probe RBNE based on a hybrid rhodamine dye, which shows excellent optical capability for detecting and imaging ONOO- in necrotizing enterocolitis (NEC) mouse model. The probe RBNE undergoes hydrazine redox-process, and subsequently the spirocyclic structure's opening, resulting in a turn-on fluorescence emission with the presence of ONOO-, which exhibits several excellent features, including a significant Stokes shift of 108 nm, near-infrared emission at 668 nm, a lower detection limit of 56 nM, low cytotoxicity, and excellent imaging ability for ONOO- both in vitro and in vivo. The presented study introduces a novel optical tool that has the potential to significantly advance our understanding of peroxynitrite (ONOO-) behaviors in necrotizing enterocolitis (NEC).

Optics-free Spatial Genomics for Mapping Mouse Brain Aging.

Spatial transcriptomics has revolutionized our understanding of cellular network dynamics in aging and disease by enabling the mapping of molecular and cellular organization across various anatomical locations. Despite these advances, current methods face significant challenges in throughput and cost, limiting their utility for comprehensive studies. To address these limitations, we introduce IRISeq (Imaging Reconstruction using Indexed Sequencing), a optics-free spatial transcriptomics platform that eliminates the need for predefined capture arrays or extensive imaging, allowing for the rapid and cost-effective processing of multiple tissue sections simultaneously. Its capacity to reconstruct images based solely on sequencing local DNA interactions allows for profiling of tissues without size constraints and across varied resolutions. Applying IRISeq, we examined gene expression and cellular dynamics in thirty brain regions of both adult and aged mice, uncovering region-specific changes in gene expression associated with aging. Further cell type-centric analysis further identified age-related cell subtypes and intricate changes in cell interactions that are distinct to certain spatial niches, emphasizing the unique aspects of aging in different brain regions. The affordability and simplicity of IRISeq position it as a versatile tool for mapping region-specific gene expression and cellular interactions across various biological systems.

Determination of the rat estrous cycle vased on EfficientNet.

In the field of biomedical research, rats are widely used as experimental animals due to their short gestation period and strong reproductive ability. Accurate monitoring of the estrous cycle is crucial for the success of experiments. Traditional methods are time-consuming and rely on the subjective judgment of professionals, which limits the efficiency and accuracy of experiments. This study proposes an EfficientNet model to automate the recognition of the estrous cycle of female rats using deep learning techniques. The model optimizes performance through systematic scaling of the network depth, width, and image resolution. A large dataset of physiological data from female rats was used for training and validation. The improved EfficientNet model effectively recognized different stages of the estrous cycle. The model demonstrated high-precision feature capture and significantly improved recognition accuracy compared to conventional methods. The proposed technique enhances experimental efficiency and reduces human error in recognizing the estrous cycle. This study highlights the potential of deep learning to optimize data processing and achieve high-precision recognition in biomedical research. Future work should focus on further validation with larger datasets and integration into experimental workflows.

A lightweight grape detection model in natural environments based on an enhanced YOLOv8 framework.

Grapefruit and stem detection play a crucial role in automated grape harvesting. However, the dense arrangement of fruits in vineyards and the similarity in color between grape stems and branches pose challenges, often leading to missed or false detections in most existing models. Furthermore, these models' substantial parameters and computational demands result in slow detection speeds and difficulty deploying them on mobile devices. Therefore, we propose a lightweight TiGra-YOLOv8 model based on YOLOv8n. Initially, we integrated the Attentional Scale Fusion (ASF) module into the Neck, enhancing the network's ability to extract grape features in dense orchards. Subsequently, we employed Adaptive Training Sample Selection (ATSS) as the label-matching strategy to improve the quality of positive samples and address the challenge of detecting grape stems with similar colors. We then utilized the Weighted Interpolation of Sequential Evidence for Intersection over Union (Wise-IoU) loss function to overcome the limitations of CIoU, which does not consider the geometric attributes of targets, thereby enhancing detection efficiency. Finally, the model's size was reduced through channel pruning. The results indicate that the TiGra-YOLOv8 model's mAP(0.5) increased by 3.33% compared to YOLOv8n, with a 7.49% improvement in detection speed (FPS), a 52.19% reduction in parameter count, and a 51.72% decrease in computational demand, while also reducing the model size by 45.76%. The TiGra-YOLOv8 model not only improves the detection accuracy for dense and challenging targets but also reduces model parameters and speeds up detection, offering significant benefits for grape detection.

Deconvoluting Surface and Bulk Charge Storage Processes in Redox-Active Oxides by Integrating Electrochemical and Optical Insights.

Redox-active transition metal oxides (TMOs) play crucial roles in diverse energy storage and conversion technologies, such as batteries and pseudocapacitors. These materials show intricate electrochemical charge storage processes, encompassing both bulk ion-intercalation, typical of battery electrodes, and pseudocapacitive-like behavior localized near the surfaces. However, understanding the underlying mechanisms of charge storage in redox-active TMOs is challenging due to the coexistence of these behaviors. In this study, we propose an integrated approach that combines operando electrochemical and optical techniques to disentangle the contributions of bulk and surface phenomena. Using birnessite δ-MnO2-x as a model system, we account for surface pseudocapacitive-like layers and employ a refined model that incorporates both surface reactions and bulk chemical diffusion. This methodology allows us to extract essential kinetic parameters, establishing a fundamental framework for unraveling surface and bulk electrochemical processes. This advancement provides a valuable tool for the rational design of energy storage devices, enhancing our ability to tailor these materials for specific applications.

Relevance and regulation of alternative splicing in plant secondary metabolism: current understanding and future directions.

The secondary metabolism of plants is an essential life process enabling organisms to navigate various stages of plant development and cope with ever-changing environmental stresses. Secondary metabolites, abundantly found in nature, possess significant medicinal value. Among the regulatory mechanisms governing these metabolic processes, alternative splicing stands out as a widely observed post-transcriptional mechanism present in multicellular organisms. It facilitates the generation of multiple mRNA transcripts from a single gene by selecting different splicing sites. Selective splicing events in plants are widely induced by various signals, including external environmental stress and hormone signals. These events ultimately regulate the secondary metabolic processes and the accumulation of essential secondary metabolites in plants by influencing the synthesis of primary metabolites, hormone metabolism, biomass accumulation, and capillary density. Simultaneously, alternative splicing plays a crucial role in enhancing protein diversity and the abundance of the transcriptome. This paper provides a summary of the factors inducing alternative splicing events in plants and systematically describes the progress in regulating alternative splicing with respect to different secondary metabolites, including terpenoid, phenolic compounds, and nitrogen-containing compounds. Such elucidation offers critical foundational insights for understanding the role of alternative splicing in regulating plant metabolism and presents novel avenues and perspectives for bioengineering.

Transcriptome analysis reveals high concentration of resveratrol promotes lipid synthesis and induces apoptosis in Siberian sturgeon (Acipenser baerii).

Resveratrol has been reported to promote immunity and decrease oxidative stress, but which demonstrates biphasic effects relied on the use concentration. In this study, the effects of diet supplement with a relative high concentration of resveratrol (0.32 mg/kg) on metabolism, antioxidation and apoptosis of liver were investigated in Siberian sturgeon. The results showed that resveratrol significantly increased the lipid synthesis and the apoptosis, but did not either activate the antioxidant NRF2/KEAP1 pathway or enhance the antioxidant enzyme activity. Transcriptome analysis revealed significant changes in regulatory pathways related to glycolipid, including PPAR signaling pathway, Insulin signaling pathway, Fatty acid biosynthesis, and Glycolysis/Gluconeogenesis. In addition, resveratrol significantly increased the lipid synthesis genes (accα and fas), fatty acid transport gene (fatp 6) and gluconeogenesis gene (gck), but decreased the survival-promoting genes (gadd45ß and igf 1). These findings highlight a significant effect of resveratrol on glycolipid metabolism in Siberian sturgeon. Moreover, this study also demonstrated that 0.32 mg/kg resveratrol has physiological toxicity to the liver of Siberian sturgeon, indicating that this dose is too high for Siberian sturgeon. Thus, our study provides a valuable insight for future research and application of resveratrol in fish.

Multimodal integrated and broadband light-driven antibacterial cellulose fabric based on π-π coupling enhanced intermolecular FRET.

Fabrication of antimicrobial photodynamic therapy (aPDT) materials based on organic photosensitizers has garnered considerable attention within functional textiles. However, the UV- or narrow-band absorption range of the photosensitizers results in poor photon utilization of the fabrics, limiting the photodynamic efficiency and wasting solar energy. In this study, a broadband light-driven antibacterial cellulose fabric (CF-ZnPc/NAD) was developed by loading carboxyl-modified zinc(II) phthalocyanine photosensitizer (CAZnPc) and cationic 1,8-naphthalimide fluorescent molecule (NAD) on the fabric via covalent binding and electrostatic adsorption assembly, facilitating the intermolecular π-π coupling and fluorescence resonance energy transfer (FRET) process. There is a 2.54-fold increase in photo-induced ROS generation capacity of CF-ZnPc/NAD via the FRET process compared to that of CF-ZnPc, and it also exhibited a strong photothermal effect (PTT), wherein the temperature of the fabric increased from 24.5 to 53.5 °C within 80 s of illumination (λ > 400 nm, 75 mW/cm2). CF-ZnPc/NAD exhibited strong light-harvesting capacity and a combination of aPDT and PTT, achieving excellent antibacterial performance against Staphylococcus aureus (Gram-positive, S. aureus) and Escherichia coli (Gram-negative, E.coli) with 99.99 % bacterial reduction under 90 min of illumination (λ > 400 nm, 10 ± 1 mW/cm2). This study demonstrates a novel and facile strategy for successfully fabricating high-performance antibacterial cellulose fabrics with potential biomedical prospects.

Predicting postacute phase anaemia after aneurysmal subarachnoid haemorrhage: nomogram development and validation.

BACKGROUND: Anaemia is a severe and common complication in patients with aneurysmal subarachnoid haemorrhage (aSAH). Early intervention for at-risk patients before anaemia occurs is indicated as potentially beneficial, but no validated method synthesises patients' complicated clinical features into an instrument. The purpose of the current study was to develop and externally validate a nomogram that predicted postacute phase anaemia after aSAH. METHODS: We developed a novel nomogram for aSAH patients to predict postacute phase anaemia (3 days after occurrence of aSAH, prior to discharge) on the basis of demographic information, imaging, type of treatment, aneurysm features, blood tests and clinical characteristics. We designed the model from a development cohort and tested the nomogram in external and prospective validation cohorts. We included 456 aSAH patients from The First Affiliated Hospital for the development, 220 from Sanmen People's Hospital for external validation and a prospective validation cohort that included 13 patients from Hangzhou Red Cross Hospital. We assessed the performance of the nomogram via concordance statistics and evaluated the calibration of predicted anaemia outcome with observed anaemia occurrence. RESULTS: Variables included in the nomogram were age, treatment method (open surgery or endovascular therapy), baseline haemoglobin level, fasting blood glucose level, systemic inflammatory response syndrome score on admission, Glasgow Coma Scale score, aneurysm size, prothrombin time and heart rate. In the validation cohort, the model for prediction of postacute phase anaemia had a c-statistic of 0.910, with satisfactory calibration (judged by eye) for the predicted and reported anaemia outcome. Among forward-looking forecasts, our predictive model achieved an 84% success rate, which showed that it has some clinical practicability. CONCLUSIONS: The developed and validated nomogram can be used to calculate individualised anaemia risk and has the potential to serve as a practical tool for clinicians in devising improved treatment strategies for aSAH.

Real­world evidence of advanced non­small cell lung carcinoma treated with an immune checkpoint inhibitor plus chemotherapy.

Immunotherapy is an effective treatment strategy for patients with advanced non-small cell lung cancer (NSCLC). Although clinical trials on immunotherapy have provided promising results, real-world research in clinical practice is needed to assess the effectiveness and safety of immunotherapy. The present study aimed to characterize real-world outcomes in patients with advanced NSCLC treated with immune checkpoint inhibitor (ICI)-based regimens. The medical records of patients with advanced NSCLC, who were treated with programmed cell death protein-1 (PD-1)/programmed cell death 1 ligand 1 (PD-L1) inhibitors, were reviewed for data collection. The primary objectives were to evaluate progression-free survival (PFS) and overall survival (OS). Therefore, multiple Cox regression models were used to investigate the predictive factors for survival outcomes. Furthermore, survival curves for PFS and OS were created using Kaplan-Meier estimates and compared using the log-rank test. The present study included a total of 133 patients with advanced NSCLC who received therapy with ICIs between January 1, 2019 and December 31, 2022. The final follow-up date was August 24, 2023. The median PFS and OS times were 9.8 and 27.2 months, respectively. Univariate Cox regression analysis demonstrated that sex, clinical stage, PD-L1 status, previous systemic therapy, and brain and liver metastases were associated with PFS, while Eastern Cooperative Oncology Group (ECOG) status, clinical stage, PD-L1 status and brain metastasis were associated with OS. Furthermore, multivariate Cox regression analysis demonstrated that a PD-L1 tumor proportion score (TPS) of ≥50% was an indicator of favorable PFS and OS. An ECOG performance status score of ≥1 was also associated with poor OS but not with PFS. Furthermore, brain metastasis was an indicator for poor PFS and OS, while liver metastasis was only associated with a poor PFS. Finally, the results of the present study demonstrated that PD-L1 status was an independent predictor for PFS and OS in patients with advanced NSCLC, especially adenocarcinoma, who were treated with ICIs plus chemotherapy. The results also suggested that patients with a PD-L1 TPS of ≥50% could benefit when the aforementioned regimens were administrated as a first-line or later-line therapy.

Prediction of immunotherapy response of bladder cancer with a pyroptosis-related signature indicating tumor immune microenvironment.

Background: Although prognostic models based on pyroptosis-related genes (PRGs) have been constructed in bladder cancer (BLCA), the comprehensive impact of these genes on tumor microenvironment (TME) and immunotherapeutic response has yet to be investigated. Methods: Based on expression profiles of 52 PRGs, we utilized the unsupervised clustering algorithm to identify PRGs subtypes and ssGSEA to quantify immune cells and hallmark pathways. Moreover, we screened feature genes of distinct PRGs subtypes and validated the associations with immune infiltrations in tissue using the multiplex immunofluorescence. Univariate, LASSO, and multivariate Cox regression analyses were employed to construct the scoring scheme. Results: Four PRGs clusters were identified, samples in cluster C1 were infiltrated with more immune cells than those in others, implying a favorable response to immunotherapy. While the cluster C2, which shows an extremely low level of most immune cells, do not respond to immunotherapy. CXCL9/CXCL10 and SPINK1/DHSR2 were identified as feature genes of cluster C1 and C2, and the specimen with high CXCL9/CXCL10 was characterized by more CD8 + T cells, macrophages and less Tregs. Based on differentially expressed genes (DEGs) among PRGs subtypes, a predictive model (termed as PRGs score) including five genes (CACNA1D, PTK2B, APOL6, CDK6, ANXA2) was built. Survival probability of patients with low-PRGs score was significantly higher than those with high-PRGs score. Moreover, patients with low-PRGs score were more likely to benefit from anti-PD1/PD-L1 regimens. Conclusion: PRGs are closely associated with TME and oncogenic pathways. PRGs score is a promising indicator for predicting clinical outcome and immunotherapy response.