Interleukin-7-based identification of liver lymphatic endothelial cells reveals their unique structural features.

Background & Aims: The lymphatic system plays crucial roles in maintaining fluid balance and immune regulation. Studying the liver lymphatics has been considered challenging, as common lymphatic endothelial cell (LyEC) markers are expressed by other liver cells. Additionally, isolation of sufficient numbers of LyECs has been challenging because of their extremely low abundance (<0.01% of entire liver cell population) in a normal liver. Methods: Potential LyEC markers was identified using our published single-cell RNA sequencing (scRNA-seq) dataset (GSE147581) in mouse livers. Interleukin-7 (IL7) promoter-driven green fluorescent protein knock-in heterozygous mice were used for the validation of IL7 expression in LyECs in the liver, for the development of liver LyEC isolation protocol, and generating liver ischemia/reperfusion (I/R) injury. Scanning electron microscopy was used for the structural analysis of LyECs. Changes in LyEC phenotypes in livers of mice with I/R were determined by RNA-seq analysis. Results: Through scRNA-seq analysis, we have identified IL7 as an exclusive marker for liver LyECs, with no overlap with other liver cell types. Based on IL7 expression in liver LyECs, we have established an LyEC isolation method and observed distinct cell surface structures of LyECs with fenestrae and cellular pores (ranging from 100 to 400 nm in diameter). Furthermore, we identified LyEC genes that undergo alterations during I/R liver injuries. Conclusions: This study not only identified IL7 as an exclusively expressed gene in liver LyECs, but also enhanced our understanding of LyEC structures and demonstrated transcriptomic changes in injured livers. Impact and implications: Understanding the lymphatic system in the liver is challenging because of the absence of specific markers for liver LyEC. This study has identified IL7 as a reliable marker for LyECs, enabling the development of an effective method for their isolation, elucidating their unique cell surface structure, and identifying LyEC genes that undergo changes during liver damage. The development of IL7 antibodies for detecting it in human liver specimens will further advance our understanding of the liver lymphatic system in the future.

Exploring cellular diversity in lung adenocarcinoma epithelium: Advancing prognostic methods and immunotherapeutic strategies.

Immunotherapy has brought significant advancements in the treatment of lung adenocarcinoma (LUAD), but identifying suitable candidates remains challenging. In this study, we investigated tumour cell heterogeneity using extensive single-cell data and explored the impact of different tumour cell cluster abundances on immunotherapy in the POPLAR and OAK immunotherapy cohorts. Notably, we found a significant correlation between CKS1B+ tumour cell abundance and treatment response, as well as stemness potential. Leveraging marker genes from the CKS1B+ tumour cell cluster, we employed machine learning algorithms to establish a prognostic and immunotherapeutic signature (PIS) for LUAD. In multiple cohorts, PIS outperformed 144 previously published signatures in predicting LUAD prognosis. Importantly, PIS reliably predicted genomic alterations, chemotherapy sensitivity and immunotherapy responses. Immunohistochemistry validated lower expression of immune markers in the low-PIS group, while in vitro experiments underscored the role of the key gene PSMB7 in LUAD progression. In conclusion, PIS represents a novel biomarker facilitating the selection of suitable LUAD patients for immunotherapy, ultimately improving prognosis and guiding clinical decisions.

Integrating machine learning and single-cell analysis to uncover lung adenocarcinoma progression and prognostic biomarkers.

The progression of lung adenocarcinoma (LUAD) from atypical adenomatous hyperplasia (AAH) to invasive adenocarcinoma (IAC) involves a complex evolution of tumour cell clusters, the mechanisms of which remain largely unknown. By integrating single-cell datasets and using inferCNV, we identified and analysed tumour cell clusters to explore their heterogeneity and changes in abundance throughout LUAD progression. We applied gene set variation analysis (GSVA), pseudotime analysis, scMetabolism, and Cytotrace scores to study biological functions, metabolic profiles and stemness traits. A predictive model for prognosis, based on key cluster marker genes, was developed using CoxBoost and plsRcox (CPM), and validated across multiple cohorts for its prognostic prediction capabilities, tumour microenvironment characterization, mutation landscape and immunotherapy response. We identified nine distinct tumour cell clusters, with Cluster 6 indicating an early developmental stage, high stemness and proliferative potential. The abundance of Clusters 0 and 6 increased from AAH to IAC, correlating with prognosis. The CPM model effectively distinguished prognosis in immunotherapy cohorts and predicted genomic alterations, chemotherapy drug sensitivity, and immunotherapy responsiveness. Key gene S100A16 in the CPM model was validated as an oncogene, enhancing LUAD cell proliferation, invasion and migration. The CPM model emerges as a novel biomarker for predicting prognosis and immunotherapy response in LUAD patients, with S100A16 identified as a potential therapeutic target.

Data describing the effects of Induced knockout of Heterogeneous nuclear ribonucleoprotein K in mouse skeletal muscle satellite cells.

HnRNPK, a prominent member of the heterogeneous nuclear ribonucleoprotein (hnRNP) family, is widely expressed in mammalian tissues and plays a crucial role in animal development. Despite its well-established functions, limited information is available regarding its role in skeletal muscle development and regeneration. To elucidate the functional role of hnRNPK in skeletal muscle, we utilized Pax7CreER; HnrnpkLoxP/LoxP (Hnrnpk pKO) mice as a model, isolated primary mouse skeletal muscle satellite cells (MuSCs), and induced hnRNPK knockout using 4-OTH. Transcriptome sequencing was performed on four distinct groups: Hnrnpk pKO MuSCs undergoing proliferation for 24 h (ethanol 24 h) and 48 h (ethanol 48 h) after treatment with ethanol as the control, as well as Hnrnpk pKO MuSCs undergoing proliferation for 24 h (4-OHT 24 h) and 48 h (4-OHT 48 h) after treatment with 4-OHT as the hnRNPK-induced knockout group. The RNA sequencing data was generated using the Illumina HiSeq 2000/2500 sequencing platform. The raw data files have been archived in the Sequence Read Archive at the China National Center for Bioinformation (CNCB) under the accession number CRA015864. This data article is related to the research paper "Deletion of heterogeneous nuclear ribonucleoprotein K in satellite cells leads to inhibited skeletal muscle regeneration in mice, Genes & Diseases 11: 101,062, DOI: 10.1016/j.gendis.2023.06.031".

Unravelling the metabolic landscape of cutaneous melanoma: Insights from single-cell sequencing analysis and machine learning for prognostic assessment of lactate metabolism.

This manuscript presents a comprehensive investigation into the role of lactate metabolism-related genes as potential prognostic markers in skin cutaneous melanoma (SKCM). Bulk-transcriptome data from The Cancer Genome Atlas (TCGA) and GSE19234, GSE22153, and GSE65904 cohorts from GEO database were processed and harmonized to mitigate batch effects. Lactate metabolism scores were assigned to individual cells using the 'AUCell' package. Weighted Co-expression Network Analysis (WGCNA) was employed to identify gene modules correlated with lactate metabolism. Machine learning algorithms were applied to construct a prognostic model, and its performance was evaluated in multiple cohorts. Immune correlation, mutation analysis, and enrichment analysis were conducted to further characterize the prognostic model's biological implications. Finally, the function of key gene NDUFS7 was verified by cell experiments. Machine learning resulted in an optimal prognostic model, demonstrating significant prognostic value across various cohorts. In the different cohorts, the high-risk group showed a poor prognosis. Immune analysis indicated differences in immune cell infiltration and checkpoint gene expression between risk groups. Mutation analysis identified genes with high mutation loads in SKCM. Enrichment analysis unveiled enriched pathways and biological processes in high-risk SKCM patients. NDUFS7 was found to be a hub gene in the protein-protein interaction network. After the expression of NDUFS7 was reduced by siRNA knockdown, CCK-8, colony formation, transwell and wound healing tests showed that the activity, proliferation and migration of A375 and WM115 cell lines were significantly decreased. This study offers insights into the prognostic significance of lactate metabolism-related genes in SKCM.

Molecular subtypes of ischemic heart disease based on circadian rhythm.

Coronary atherosclerotic heart disease (CAD) is among the most prevalent chronic diseases globally. Circadian rhythm disruption (CRD) is closely associated with the progression of various diseases. However, the precise role of CRD in the development of CAD remains to be elucidated. The Circadian rhythm disruption score (CRDscore) was employed to quantitatively assess the level of CRD in CAD samples. Our investigation revealed a significant association between high CRDscore and adverse prognosis in CAD patients, along with a substantial correlation with CAD progression. Remarkably distinct CRDscore distributions were also identified among various subtypes. In summary, we have pioneered the revelation of the relationship between CRD and CAD at the single-cell level and established reliable markers for the development, treatment, and prognosis of CAD. A deeper understanding of these mechanisms may offer new possibilities for incorporating "the therapy of coronary heart disease based circadian rhythm" into personalized medical treatment regimens.

Strategies and Challenges of Microbiota Regulation in Baijiu Brewing.

The traditional Chinese Baijiu brewing process utilizes natural inoculation and open fermentation. The microbial composition and abundance in the microecology of Baijiu brewing often exhibit unstable characteristics, which directly results in fluctuations in Baijiu quality. The microbiota plays a crucial role in determining the quality of Baijiu. Analyzing the driving effect of technology and raw materials on microorganisms. Elucidating the source of core microorganisms and interactions between microorganisms, and finally utilizing single or multiple microorganisms to regulate and intensify the Baijiu fermentation process is an important way to achieve high efficiency and stability in the production of Baijiu. This paper provides a systematic review of the composition and sources of microbiota at different brewing stages. It also analyzes the relationship between raw materials, brewing processes, and brewing microbiota, as well as the steps involved in the implementation of brewing microbiota regulation strategies. In addition, this paper considers the feasibility of using Baijiu flavor as a guide for Baijiu brewing regulation by synthesizing the microbiota, and the challenges involved. This paper is a guide for flavor regulation and quality assurance of Baijiu and also suggests new research directions for regulatory strategies for other fermented foods.

Photo-Assisted Rechargeable Metal Batteries: Principles, Progress, and Perspectives.

The utilization of diverse energy storage devices is imperative in the contemporary society. Taking advantage of solar power, a significant environmentally friendly and sustainable energy resource, holds great appeal for future storage of energy because it can solve the dilemma of fossil energy depletion and the resulting environmental problems once and for all. Recently, photo-assisted energy storage devices, especially photo-assisted rechargeable metal batteries, are rapidly developed owing to the ability to efficiently convert and store solar energy and the simple configuration, as well as the fact that conventional Li/Zn-ion batteries are widely commercialized. Considering many puzzles arising from the rapid development of photo-assisted rechargeable metal batteries, this review commences by introducing the fundamental concepts of batteries and photo-electrochemistry, followed by an exploration of the current advancements in photo-assisted rechargeable metal batteries. Specifically, it delves into the elucidation of device components, operating principles, types, and practical applications. Furthermore, this paper categorizes, specifies, and summarizes several detailed examples of photo-assisted energy storage devices. Lastly, it addresses the challenges and bottlenecks faced by these energy storage systems while providing future perspectives to facilitate their transition from laboratory research to industrial implementation.

Freeform robotic optical coherence tomography beyond the optical field-of-view limit.

Imaging complex, non-planar anatomies with optical coherence tomography (OCT) is limited by the optical field of view (FOV) in a single volumetric acquisition. Combining linear mechanical translation with OCT extends the FOV but suffers from inflexibility in imaging non-planar anatomies. We report the freeform robotic OCT to fill this gap. To address challenges in volumetric reconstruction associated with the robotic movement accuracy being two orders of magnitudes worse than OCT imaging resolution, we developed a volumetric registration algorithm based on simultaneous localization and mapping (SLAM) to overcome this limitation. We imaged the entire aqueous humor outflow pathway, whose imaging has the potential to customize glaucoma surgeries but is typically constrained by the FOV, circumferentially in mice as a test. We acquired volumetric OCT data at different robotic poses and reconstructed the entire anterior segment of the eye. The reconstructed volumes showed heterogeneous Schlemm's canal (SC) morphology in the reconstructed anterior segment and revealed a segmental nature in the circumferential distribution of collector channels (CC) with spatial features as small as a few micrometers.

Novel Bifunctional Conjugates Targeting PD-L1/PARP7 as Dual Immunotherapy for Potential Cancer Treatment.

Bifunctional conjugates targeting PD-L1/PARP7 were designed, synthesized, and evaluated for the first time. Compounds B3 and C6 showed potent activity against PD-1/PD-L1 interaction (IC50 = 0.426 and 0.342 µM, respectively) and PARP7 (IC50 = 2.50 and 7.05 nM, respectively). They also displayed excellent binding affinity with hPD-L1, approximately 100-200-fold better than that of hPD-1. Both compounds restored T-cell function, leading to the increase of IFN-γ secretion. In the coculture assay, B3 and C6 enhanced the killing activity of MDA-MB-231 cells by Jurkat T cells in a concentration-dependent manner. Furthermore, B3 and C6 displayed significant in vivo antitumor efficacy in a melanoma B16-F10 tumor mouse model, more than 5.3-fold better than BMS-1 (a PD-L1 inhibitor) and RBN-2397 (a PARP7i clinical candidate) at the dose of 25 mg/kg, without observable side effects. These results provide valuable insight and understanding for developing bifunctional conjugates for potential anticancer therapy.

Deciphering lung adenocarcinoma evolution: Integrative single-cell genomics identifies the prognostic lung progression associated signature.

We employed single-cell analysis techniques, specifically the inferCNV method, to dissect the complex progression of lung adenocarcinoma (LUAD) from adenocarcinoma in situ (AIS) through minimally invasive adenocarcinoma (MIA) to invasive adenocarcinoma (IAC). This approach enabled the identification of Cluster 6, which was significantly associated with LUAD progression. Our comprehensive analysis included intercellular interaction, transcription factor regulatory networks, trajectory analysis, and gene set variation analysis (GSVA), leading to the development of the lung progression associated signature (LPAS). Interestingly, we discovered that the LPAS not only accurately predicts the prognosis of LUAD patients but also forecasts genomic alterations, distinguishes between 'cold' and 'hot' tumours, and identifies potential candidates suitable for immunotherapy. PSMB1, identified within Cluster 6, was experimentally shown to significantly enhance cancer cell invasion and migration, highlighting the clinical relevance of LPAS in predicting LUAD progression and providing a potential target for therapeutic intervention. Our findings suggest that LPAS offers a novel biomarker for LUAD patient stratification, with significant implications for improving prognostic accuracy and guiding treatment decisions.

A Universal Electronic Structure Modulation Strategy: Is Strong Adsorption Always Correlated with High Catalysis?

Unveiling the inherent link between polysulfide adsorption and catalytic activity is key to achieving optimal performance in Lithium-sulfur (Li-S) batteries. Current research on the sulfur reaction process mainly relies on the strong adsorption of catalysts to confine lithium polysulfides (LiPSs) to the cathode side, effectively suppressing the shuttle effect of polysulfides. However, is strong adsorption always correlated with high catalysis? The inherent relationship between adsorption and catalytic activity remains unclear, limiting the in-depth exploration and rational design of catalysts. Herein, the correlation between "d-band center-adsorption strength-catalytic activity" in porous carbon nanofiber catalysts embedded with different transition metals (M-PCNF-3, M = Fe, Co, Ni, Cu) is systematically investigated, combining the d-band center theory and the Sabatier principle. Theoretical calculations and experimental analysis results indicate that Co-PCNF-3 electrocatalyst with appropriate d-band center positions exhibits moderate adsorption capability and the highest catalytic conversion activity for LiPSs, validating the Sabatier relationship in Li-S battery electrocatalysts. These findings provide indispensable guidelines for the rational design of more durable cathode catalysts for Li-S batteries.

Synthesis, antioxidant and anti-hypoxia activities of 6-hydroxygenistein and its methylated derivatives. / 6-ç¾ŸåŸºæŸ“æ–™æœ¨ç´ åŠå ¶ç”²åŸºåŒ–è¡ç”Ÿç‰©çš„åˆæˆå’ŒæŠ—æ°§åŒ–ä¸ŽæŠ—ç¼ºæ°§æ´»æ€§.

OBJECTIVES: Hypoxia is a common pathological phenomenon, usually caused by insufficient oxygen supply or inability to use oxygen effectively. Hydroxylated and methoxylated flavonoids have significant anti-hypoxia activity. This study aims to explore the synthesis, antioxidant and anti-hypoxia activities of 6-hydroxygenistein (6-OHG) and its methoxylated derivatives. METHODS: The 6-OHG and its methoxylated derivatives, including 4',6,7-trimethoxy-5-hydroxyisoflavone (compound 3), 4',5,6,7-tetramethoxyisoflavone (compound 4), 4',6-imethoxy-5,7-dihydroxyisoflavone (compound 6), and 4'-methoxy-5,6,7-trihydroxyisoflavone (compound 7), were synthesized by methylation, bromination, methoxylation, and demethylation using biochanin A as raw material. The structure of these products were characterized by 1hydrogen-nuclear magnetic resonance spectroscopy (1H-NMR) and mass spectrometry (MS). The purity of these compounds was detected by high pressure chromatography (HPLC). The antioxidant activity in vitro was investigated by 1,1-diphenyl-2-picrylhydrazyl radical (DPPH) free radical scavenging assay. PC12 cells were divided into a normal group, a hypoxia model group, rutin (1×10-9-1×10-5 mol/L) groups, and target compounds (1×10-9-1×10-5 mol/L) groups under normal and hypoxic conditions. Cell viability was detected by cell counting kit-8 (CCK-8) assay, the target compounds with excellent anti-hypoxia activity and the drug concentration at the maximum anti-hypoxia activity were screened. PC12 cells were treated with the optimal concentration of the target compound or rutin with excellent anti-hypoxia activity, and the cell morphology was observed under light microscope. The apoptotic rate was determined by flow cytometry, and the expressions of hypoxia inducible factor-1α (HIF-1α) and vascular endothelial growth factor (VEGF) were detected by Western blotting. RESULTS: The structure of 6-OHG and its 4 methylated derivatives were correct, and the purity was all more than 97%. When the concentration was 4 mmol/L, the DPPH free radical removal rates of chemical compounds 7 and 6-OHG were 81.16% and 86.94%, respectively, which were higher than those of rutin, the positive control. The removal rates of chemical compounds 3, 4, and 6 were all lower than 20%. Compared with the normal group, the cell viability of the hypoxia model group was significantly decreased (P<0.01). Compared with the hypoxia model group, compounds 3, 4, and 6 had no significant effect on cell viability under hypoxic conditions. At all experimental concentrations, the cell viability of the 6-OHG group was significantly higher than that of the hypoxia model group (all P<0.05). The cell viability of compound 7 group at 1×10-7 and 1×10-6 mol/L was significantly higher than that of the hypoxia model group (both P<0.05). The anti-hypoxia activity of 6-OHG and compound 7 was excellent, and the optimal drug concentration was 1×10-6 and 1×10-7 mol/L. After PC12 cells was treated with 6-OHG (1×10-6 mol/L) and compound 7 (1×10-7 mol/L), the cell damage was reduced, the apoptotic rate was significantly decreased (P<0.01), and the protein expression levels of HIF-1α and VEGF were significantly decreased in comparison with the hypoxia model group (both P<0.01). CONCLUSIONS: The optimized synthesis route can increase the yield of 6-OHG and obtain 4 derivatives by methylation and selective demethylation. 6-OHG and compound 7 have excellent antioxidant and anti-hypoxia activities, which are related to the structure of the A-ring ortho-triphenol hydroxyl group in the molecule.

Food-energy-water nexus optimization brings substantial reduction of urban resource consumption and greenhouse gas emissions.

Urban sustainability is a key to achieving the UN sustainable development goals (SDGs). Secure and efficient provision of food, energy, and water (FEW) resources is a critical strategy for urban sustainability. While there has been extensive discussion on the positive effects of the FEW nexus on resource efficiency and climate impacts, measuring the extent to which such synergy can benefit urban sustainability remains challenging. Here, we have developed a systematic and integrated optimization framework to explore the potential of the FEW nexus in reducing urban resource demand and greenhouse gas (GHG) emissions. Demonstrated using the Metropolis Beijing, we have identified that the optimized FEW nexus can reduce resource consumption and GHG emissions by 21.0 and 29.1%, respectively. These reductions come with increased costs compared to the siloed FEW management, but it still achieved a 16.8% reduction in economic cost compared to the business-as-usual scenario. These findings underscore the significant potential of FEW nexus management in enhancing urban resource efficiency and addressing climate impacts, while also identifying strategies to address trade-offs and increase synergies.

Using blood routine indicators to establish a machine learning model for predicting liver fibrosis in patients with Schistosoma japonicum.

This study intends to use the basic information and blood routine of schistosomiasis patients to establish a machine learning model for predicting liver fibrosis. We collected medical records of Schistosoma japonicum patients admitted to a hospital in China from June 2019 to June 2022. The method was to screen out the key variables and six different machine learning algorithms were used to establish prediction models. Finally, the optimal model was compared based on AUC, specificity, sensitivity and other indicators for further modeling. The interpretation of the model was shown by using the SHAP package. A total of 1049 patients' medical records were collected, and 10 key variables were screened for modeling using lasso method, including red cell distribution width-standard deviation (RDW-SD), Mean corpuscular hemoglobin concentration (MCHC), Mean corpuscular volume (MCV), hematocrit (HCT), Red blood cells, Eosinophils, Monocytes, Lymphocytes, Neutrophils, Age. Among the 6 different machine learning algorithms, LightGBM performed the best, and its AUCs in the training set and validation set were 1 and 0.818, respectively. This study established a machine learning model for predicting liver fibrosis in patients with Schistosoma japonicum. The model could help improve the early diagnosis and provide early intervention for schistosomiasis patients with liver fibrosis.

Integrative single-cell analysis of LUAD: elucidating immune cell dynamics and prognostic modeling based on exhausted CD8+ T cells.

Background: The tumor microenvironment (TME) plays a pivotal role in the progression and metastasis of lung adenocarcinoma (LUAD). However, the detailed characteristics of LUAD and its associated microenvironment are yet to be extensively explored. This study aims to delineate a comprehensive profile of the immune cells within the LUAD microenvironment, including CD8+ T cells, CD4+ T cells, and myeloid cells. Subsequently, based on marker genes of exhausted CD8+ T cells, we aim to establish a prognostic model for LUAD. Method: Utilizing the Seurat and Scanpy packages, we successfully constructed an immune microenvironment atlas for LUAD. The Monocle3 and PAGA algorithms were employed for pseudotime analysis, pySCENIC for transcription factor analysis, and CellChat for analyzing intercellular communication. Following this, a prognostic model for LUAD was developed, based on the marker genes of exhausted CD8+ T cells, enabling effective risk stratification in LUAD patients. Our study included a thorough analysis to identify differences in TME, mutation landscape, and enrichment across varying risk groups. Moreover, by integrating risk scores with clinical features, we developed a new nomogram. The expression of model genes was validated via RT-PCR, and a series of cellular experiments were conducted, elucidating the potential oncogenic mechanisms of GALNT2. Results: Our study developed a single-cell atlas for LUAD from scRNA-seq data of 19 patients, examining crucial immune cells in LUAD's microenvironment. We underscored pDCs' role in antigen processing and established a Cox regression model based on CD8_Tex-LAYN genes for risk assessment. Additionally, we contrasted prognosis and tumor environments across risk groups, constructed a new nomogram integrating clinical features, validated the expression of model genes via RT-PCR, and confirmed GALNT2's function in LUAD through cellular experiments, thereby enhancing our understanding and approach to LUAD treatment. Conclusion: The creation of a LUAD single-cell atlas in our study offered new insights into its tumor microenvironment and immune cell interactions, highlighting the importance of key genes associated with exhausted CD8+ T cells. These discoveries have enabled the development of an effective prognostic model for LUAD and identified GALNT2 as a potential therapeutic target, significantly contributing to the improvement of LUAD diagnosis and treatment strategies.

Rehabilitation exercises for kidney transplant recipients in an organ transplant ward: a best practice implementation project.

INTRODUCTION AND OBJECTIVES: Kidney transplantation is an effective treatment for end-stage kidney disease. Kidney transplant recipients (KTRs) are prone to experiencing reduced physical function, depression, fatigue, and lack of exercise motivation due to their sedentary lifestyle before surgery. Exercise is an effective intervention for KTRs, but it has not been properly implemented in many practice settings. This project aimed to promote evidence-based exercises as part of KTRs' rehabilitation to improve their health outcomes. METHODS: This project was informed by the JBI Evidence Implementation Framework. The project was conducted in the organ transplant ward of a tertiary comprehensive hospital in Changsha, China. Based on a summary of best evidence, 12 audit criteria were developed for the baseline and follow-up audits involving 30 patients and 20 nursing staff. The JBI Practical Application of Clinical Evidence System (PACES) and Getting Research into Practice (GRiP) tool were used to identify barriers and facilitators and develop targeted strategies to improve issues. RESULTS: Compared with the baseline audit, significant improvements were achieved in most of the criteria in the follow-up audit, with 9 of the 12 criteria reaching 100% compliance. Notably, the 6-minute walk distance test results were significantly higher, while the Self-Rating Depression Scale and Self-Rating Anxiety Scale scores were significantly lower (p < 0.05). CONCLUSIONS: This project demonstrates that evidence-based practice can improve the clinical practice of rehabilitation exercises for KTRs. The GRiP strategies proved to be extremely useful, notably, the formulation of a standardized rehabilitation exercise protocol, training, and enhancement of the exercising environment. Head nurses' leadership and decision-making also played an important role in the success of this project. SPANISH ABSTRACT: http://links.lww.com/IJEBH/A180.

Application value of intraoperative electrophysiological monitoring in cerebral eloquent area glioma surgery: a retrospective cohort study.

INTRODUCTION: Surgery for gliomas involving eloquent areas is a very challenging microsurgical procedure. Maximizing both the extent of resection (EOR) and preservation of neurological function have always been the focus of attention. Intraoperative neurophysiological monitoring (IONM) is widely used in this kind of surgery. The purpose of this study was to evaluate the efficacy of IONM in eloquent area glioma surgery. METHODS: Sixty-eight glioma patients who underwent surgical treatment from 2014 to 2019 were included in this retrospective cohort study, which focused on eloquent areas. Clinical indicators and IONM data were analysed preoperatively, two weeks after surgery, and at the final follow-up. Logistic regression, Cox regression, and Kaplan‒Meier analyses were performed, and nomograms were then established for predicting prognosis. The diagnostic value of the IONM indicator was evaluated by the receiver operating characteristic (ROC) curve. RESULTS: IONM had no effect on the postoperative outcomes, including EOR, intraoperative bleeding volume, duration of surgery, length of hospital stay, and neurological function status. However, at the three-month follow-up, the percentage of patients who had deteriorated function in the monitored group was significantly lower than that in the unmonitored group (23.3% vs. 52.6%; P < 0.05). Logistic regression analysis showed that IONM was a significant factor in long-term neurological function (OR = 0.23, 95% CI (0.07-0.70). In the survival analysis, long-term neurological deterioration indicated worsened overall survival (OS) and progression-free survival (PFS). A prognostic nomogram was established through Cox regression model analysis, which could predict the probability 3-year survival rate. The concordance index was 0.761 (95% CI 0.734-0.788). The sensitivity and specificity of IONM evoked potential (SSEP and TCeMEP) were 0.875 and 0.909, respectively. In the ROC curve analysis, the area under the curve (AUC) for the SSEP and TCeMEP curves was 0.892 (P < 0.05). CONCLUSIONS: The application of IONM could improve long-term neurological function, which is closely related to prognosis and can be used as an independent prognostic factor. IONM is practical and widely available for predicting postoperative functional deficits in patients with eloquent area glioma.

Purine metabolism in lung adenocarcinoma: A single-cell analysis revealing prognostic and immunotherapeutic insights.

Lung adenocarcinoma (LUAD) is a prevalent subtype of lung cancer, yet the contribution of purine metabolism (PM) to its pathogenesis remains poorly elucidated. PM, a critical component of intracellular nucleotide synthesis and energy metabolism, is hypothesized to exert a significant influence on LUAD development. Herein, we employed single-cell analysis to investigate the role of PM within the tumour microenvironment (TME) of LUAD. PM scoring (PMS) across distinct cell types was determined using AUCell, UCell, singscore and AddModuleScore algorithms. Subsequently, we explored communication networks among cells within high- and low-PMS groups, establishing a robust PM-associated signature (PAS) utilizing a comprehensive dataset comprising LUAD samples from TCGA and five GEO datasets. Our findings revealed that the high-PMS group exhibited intensified cell interactions, while the PAS, constructed using PM-related genes, demonstrated precise prognostic predictive capability. Notably, analysis across the TCGA dataset and five GEO datasets indicated that low-PAS patients exhibited a superior prognosis. Furthermore, the low-PAS group displayed increased immune cell infiltration and elevated CD8A expression, coupled with reduced PD-L1 expression. Moreover, data from eight publicly available immunotherapy cohorts suggested enhanced immunotherapy outcomes in the low-PAS group. These results underscore a close association between PAS and tumour immunity, offering predictive insights into genomic alterations, chemotherapy drug sensitivity and immunotherapy responses in LUAD. The newly established PAS holds promise as a valuable tool for selecting LUAD populations likely to benefit from future clinical stratification efforts.

Single-cell and bulk RNA-sequencing reveal SPP1 and CXCL12 as cell-to-cell communication markers to predict prognosis in lung adenocarcinoma.

Lung adenocarcinoma (LUAD) generally presents as an immunosuppressive microenvironment. The characteristics of cell-to-cell communication in the LUAD microenvironment has been unclear. In this study, the LUAD bulk RNA-seq data and single-cell RNA-seq data were retrieved from public dataset. Differential expression genes (DEGs) between LUAD tumor and adjacent non-tumor tissues were calculated by limma algorithm, and then detected by PPI, KEGG, and GO analysis. Cell-cell interactions were explored using the single-cell RNA-seq data. Finally, the first 15 CytoHubba genes were used to establish related pathways and these pathways were used to characterize the immune-related ligands and their receptors in LUAD. Our analyses showed that monocytes or macrophages interact with tissue stem cells and NK cells via SPP1 signaling pathway and tissue stem cells interact with T and B cells via CXCL signaling pathway in different states. Hub genes of SPP1 participated in SPP1 signaling pathway, which was negatively correlated with CD4+ T cell and CD8+ T cell. The expression of SPP1 in LUAD tumor tissues was negatively correlated with the prognosis. While CXCL12 participated in CXCL signaling pathway, which was positively correlated with CD4+ T cell and CD8+ T cell. The role of CXCL12 in LUAD tumor tissues exhibits an opposite effect to that of SPP1. This study reveals that tumor-associated monocytes or macrophages may affect tumor progression. Moreover, the SPP1 and CXCL12 may be the critic genes of cell-to-cell communication in LUAD, and targeting these pathways may provide a new molecular mechanism for the treatment of LUAD.