Rapid intracellular acidification is a plant defense response countered by the brown planthopper.

The brown planthopper (BPH) is the most destructive insect pest in rice. Through a stylet, BPH secretes a plethora of salivary proteins into rice phloem cells as a crucial step of infestation. However, how various salivary proteins function in rice cells to promote insect infestation is poorly understood. Among them, one of the salivary proteins is predicted to be a carbonic anhydrase (Nilaparvata lugens carbonic anhydrase [NlCA]). The survival rate of the NlCA-RNA interference (RNAi) BPH insects was extremely low on rice, indicating a vital role of this salivary protein in BPH infestation. We generated NlCA transgenic rice plants and found that NlCA expressed in rice plants could restore the ability of NlCA-RNAi BPH to survive on rice. Next, we produced rice plants expressing the ratiometric pH sensor pHusion and found that NlCA-RNAi BPH induced rapid intracellular acidification of rice cells during feeding. Further analysis revealed that both NlCA-RNAi BPH feeding and artificial lowering of intracellular pH activated plant defense responses and that NlCA-mediated intracellular pH stabilization is linked to diminished defense responses, including reduced callose deposition at the phloem sieve plates and suppressed defense gene expression. Given the importance of pH homeostasis across the kingdoms of life, discovery of NlCA-mediated intracellular pH modulation uncovered a new dimension in the interaction between plants and piercing/sucking insect pests. The crucial role of NlCA for BPH infestation of rice suggests that NlCA is a promising target for chemical or trans-kingdom RNAi-based inactivation for BPH control strategies in plants.

Metastatic prostate cancer presenting as generalized lymphadenopathy and progressing with inferior vena cava syndrome: A case report and literature review.

The present study describes the case of a 71-year-old male patient that presented with generalized lymphadenopathy and a pelvic mass, but no signs of bone and visceral metastasis. Their total prostate-specific antigen level was >100 ng/ml. A biopsy of the pelvic mass, situated near the left iliac vessels, confirmed the existence of an adenocarcinoma originating from the prostate and a subsequent prostate biopsy indicated a Gleason score of 4+5. Endocrine treatment with bicalutamide and goserelin (androgen deprivation therapy) resulted in only a partial response of the left iliac metastatic lesions to the treatment. The subsequent treatment plan of androgen deprivation therapy and abiraterone plus docetaxel did not change the progression of the disease. The patient finally developed inferior vena cava syndrome. Subsequently, the patient declined both a re-biopsy of the prostate and enlarged cervical lymph nodes, and interventions by a vascular surgeon. To the best of our knowledge, the present study is the first documented case of a natural progression of metastatic prostate cancer with inferior vena cava syndrome.

Ring-extended carbazole modification to activate efficient phosphorescent OLED performance of traditional host materials.

A novel "Ring-expansion" strategy is proposed to optimize traditional host molecular structures, featuring a rigid molecular skeleton and excellent transport of carriers. Consequently, the two novel host materials facilitate the fabrication of efficient phosphorescent OLEDs with suppressed efficiency roll-off compared to OLEDs based on the conventional host material (mCP).

Inhibition of acid-sensing receptor GPR4 attenuates neuronal ferroptosis via RhoA/YAP signaling in a rat model of subarachnoid hemorrhage.

BACKGROUND AND PURPOSE: Subarachnoid hemorrhage (SAH) is a devastating stroke, in which acidosis is one of detrimental complications. The extracellular pH reduction can activate G protein-coupled receptor 4 (GPR4) in the brain. Yet, the extent to which proton-activated GPR4 contributes to the early brain injury (EBI) post-SAH remains largely unexplored. Ferroptosis, iron-dependent programmed cell death, has recently been shown to contribute to EBI. We aimed to investigate the effects of GPR4 inhibition on neurological deficits and neuronal ferroptosis after SAH in rats. METHODS: A total 253 Sprague Dawley (SD) male rats (weighing 275-330g) were utilized in this study. SAH was induced by endovascular perforation. NE-52-QQ57 (NE), a selective antagonist of GPR4 was administered intraperitoneally 1-h post-SAH. To explore the mechanisms, RhoA activator U-46619 and YAP activator PY-60 were delivered intracerebroventricularly. Short- and long-term neurobehavior, SAH grading, Western blot assay, ELISA assay, immunofluorescence staining, and transmission electron microscopy was performed post-SAH. RESULTS: Following SAH, there was an upregulation of GPR4 expression in neurons. GPR4 inhibition by NE improved both short-term and long-term neurological outcomes post-SAH. NE also reduced neuronal ferroptosis, as evidenced by decreased lipid peroxidation products 4HNE and MDA levels in brain tissues, and reduced mitochondrial shrinkage, increased mitochondria crista and decreased membrane density. The application of either U-46619 or PY-60 partially offset the neuroprotective effects of NE on neuronal ferroptosis in SAH rats. CONCLUSIONS: This study demonstrated that acid-sensing receptor GPR4 contributed to neuronal ferroptosis after SAH via RhoA/YAP pathway, and NE may be a potential therapeutic strategy to attenuate GPR4 mediated neuronal ferroptosis and EBI after SAH.

NPRL2 promotes TRIM16-mediated ubiquitination degradation of Galectin-3 to prevent CD8+T lymphocyte cuproptosis in glioma.

BACKGROUND: Our previous study found that tumor suppressor nitrogen permease regulator like-2(NPRL2) is frequently downregulated in glioma, leading to malignant growth. However, NPRL2-mediated crosstalk between tumor cells and immune cells remains unclear. METHODS: The regulatory effects of NPRL2 on tripartite motif-containing protein 16(TRIM16) dependent ubiquitination degradation of Galectin-3(Gal-3) were explored. The effects of Gal-3 on copper uptake, immunocompetence and cuproptosis were investigated in CD8+T lymphocytes(CD8+T cells). The ability of NPRL2 to protect CD8+T cells from Gal-3 damage was evaluated. Furthermore, the correlations among NPRL2, TRIM16, Gal-3 and CD8+T cell accumulation were analyzed in glioma clinical specimens. RESULTS: NPRL2 increased the TRIM16 expression via inactivation of ERK1/2, which in turn promoted the ubiquitination-mediated degradation of Gal-3 and diminished Gal-3 release from glioma cells. Moreover, Gal-3 accelerated copper uptake and triggered cuproptosis in CD8+T cells, whereas NPRL2 increased CD8+T cell recruitment and prevented impairment of CD8+T cells by Gal-3. Clinical samples revealed that NPRL2 expression was positively associated with TRIM16 expression and negatively correlated with Gal-3, but Gal-3 expression was negatively associated with CD8+T cell accumulation. CONCLUSION: Glioma-derived NPRL2/TRIM16/Gal-3 axis participates in the regulation of CD8+T cell cuproptosis, which provides a promising strategy to rescue the immune activity of CD8+T cells and reverse immunosuppression in glioma.

MiR-126 accelerates renal injury induced by UUO via inhibition PI3K/ IRS-1/ FAK signaling induced M2 polarization and endocytosis in macrophages.

To investigate the role and molecular mechanism of miR-126 in unilateral ureteral occlusion (UUO). We used bioinformatics to analyse miRNAs specifically expressed in UUO. The mouse model of UUO was established using RAW264.7 cells cultured in vitro and in vivo. The mice were divided into control group, miR-126-NC (negative control) group and miR-126-KD (knockdown) group. Then the relative expression of miR-126 was detected by quantitative reverse transcription-polymerase chain reaction (qRT-PCR), the renal fibrosis was detected by Masson staining, and the protein expression of CD68, collagen I and collagen III in the kidney was detected by immunofluorescence assay. Immunohistochemistry detects α-SMA expression. Moreover, Western blotting was performed to measure the expressions of p-PI3K, CD163, CD206, CD86, iNOS, IL-1ß, p-FAK, p-Rac-1, p-IRS-1 and MMP9. The relative fluorescence intensity of F-actin and p-FAK was detected by immunofluorescence assay, and the phagocytosis ability of macrophages was determined by phagocytosis assay with fluorescent microspheres. Bioinformatics analysis reveals miR-126-specific overexpression in UUO. Successful transfection of miR-126-NC and miR-126-KD was confirmed by RT-PCR. The selective reduction of miR-126 was validated by Masson, immunohistochemistry and immunofluorescence staining to decrease the area of UUO-induced renal fibrosis and to lower the expression of CD68, α-SMA, collagen I, and collagen III. The reduction of iNOS expression may also be achieved with selective knockdown of miR-126, as verified by cell tests. enhances the phagocytic ability of macrophages and the expression of p-PI3K, CD206, p-FAK, F-actin, p-Rac-1, p-IRS-1 and MMP9. MiR-126 can inhibit the PI3K signaling pathway, promote M1 macrophage polarization, and suppress the activation of FAK and Rac-1, thus accelerating the progression of UUO.

Research hotspots and frontiers of machine learning in renal medicine: a bibliometric and visual analysis from 2013 to 2024.

BACKGROUND: The kidney, an essential organ of the human body, can suffer pathological damage that can potentially have serious adverse consequences on the human body and even affect life. Furthermore, the majority of kidney-induced illnesses are frequently not readily identifiable in their early stages. Once they have progressed to a more advanced stage, they impact the individual's quality of life and burden the family and broader society. In recent years, to solve this challenge well, the application of machine learning techniques in renal medicine has received much attention from researchers, and many results have been achieved in disease diagnosis and prediction. Nevertheless, studies that have conducted a comprehensive bibliometric analysis of the field have yet to be identified. OBJECTIVES: This study employs bibliometric and visualization analyses to assess the progress of the application of machine learning in the renal field and to explore research trends and hotspots in the field. METHODS: A search was conducted using the Web of Science Core Collection database, which yielded articles and review articles published from the database's inception to May 12, 2024. The data extracted from these articles and review articles were then analyzed. A bibliometric and visualization analysis was conducted using the VOSviewer, CiteSpace, and Bibliometric (R-Tool of R-Studio) software. RESULTS: 2,358 papers were retrieved and analyzed for this topic. From 2013 to 2024, the number of publications and the frequency of citations in the relevant research areas have exhibited a consistent and notable increase annually. The data set comprises 3734 institutions in 91 countries and territories, with 799 journals publishing the results. The total number of authors contributing to the data set is 14,396. China and the United States have the highest number of published papers, with 721 and 525 papers, respectively. Harvard University and the University of California System exert the most significant influence at the institutional level. Regarding authors, Cheungpasitporn, Wisit, and Thongprayoon Charat of the Mayo Clinic organization were the most prolific researchers, with 23 publications each. It is noteworthy that researcher Breiman I had the highest co-citation frequency. The journal with the most published papers was "Scientific Reports," while "PLoS One" had the highest co-citation frequency. In this field of machine learning applied to renal medicine, the article "A Clinically Applicable Approach to Continuous Prediction of Future Acute Kidney Injury" by Tomasev N et al., published in NATURE in 2019, emerged as the most influential article with the highest co-citation frequency. A keyword and reference co-occurrence analysis reveals that current research trends and frontiers in nephrology are the management of patients with renal disease, prediction and diagnosis of renal disease, imaging of renal disease, and development of personalized treatment plans for patients with renal disease. "Acute kidney injury," "chronic kidney disease," and "kidney tumors" are the most discussed diseases in medical research. CONCLUSIONS: The field of renal medicine is witnessing a surge in the application of machine learning. On one hand, this study offers a novel perspective on applying machine learning techniques to kidney-related diseases based on bibliometric analysis. This analysis provides a comprehensive overview of the current status and emerging research areas in the field, as well as future trends and frontiers. Conversely, this study furnishes data on collaboration and exchange between countries, regions, institutions, journals, authors, keywords, and reference co-citations. This information can facilitate the advancement of future research endeavors, which aim to enhance interdisciplinary collaboration, optimize data sharing and quality, and further advance the application of machine learning in the renal field.

Impacts of visitors on female pheasants in pheasantry, Haripur, Pakistan.

Background: The interaction between visitors and captive birds is complex, with a potential impact on bird's behavior and welfare. Understanding this interaction is essential for effective conservation and management. Methods: We conducted a study at the University of Haripur's pheasantry in Khyber Pakhtunkhwa, Pakistan to investigate the effects of visitor numbers, duration of visitor presence, and climatic factors on the behavior of female pheasants. We observed the state and events of feeding, hiding, and moving behaviors of 16 randomly selected individuals from five species. Results: The mixed-effects modeling results show that visitors (VT), visitors' presence duration (VPD), and temperature (TP), significantly influence feeding events (p < 0.001), feeding duration (p < 0.001), hiding events (p < 0.001) and hiding duration of female pheasants (p < 0.001). The moving events of pheasants were also significantly affected by both VT and VPD (VT: p = 0.002, VPD: p < 0.001). Moreover, under high visitor conditions, the impact of VPD on the behavior of female pheasants was more pronounced (p < 0.001). Additionally, our result reveals that different species of pheasants exhibit varying sensitivities to human factors and climatic factors. For instance, the two species of female pheasants with the highest feeding and hiding events were the Green pheasant (Phasianus versicolor) and the Ring-necked pheasant (Phasianus colchicus). While hiding duration of female Green pheasants, female Golden pheasants (Chrysolophus pictus), and female Silver pheasants (Lophura nycthemera) was longer than those of others. The mean number of moving events was highest in females of Ring-necked, followed by Golden pheasants. The female Indian peafowl (Pavo cristatus) and female Silver pheasants were the birds with the longest moving duration. Conclusion: Our findings highlight the necessity for customized management strategies, to lessen the effects of human disturbances in pheasantries. For a thorough understanding of these interactions, more studies involving larger sample sizes and a wider variety of species are advised.

Dual active site-mediated Ir single-atom-doped RuO2 catalysts for highly efficient and stable water splitting.

The electronic structure modulation through heterogeneous single-atom doping is an effective strategy to improve electrocatalysis performance of catalysts. Here, Ir single-atom doped RuO2 (IrSA/RuO2) is constructed by substituting Ru sites with mono-disperse Ir atoms in RuO2 crystals. The IrSA/RuO2-850 catalyst shows excellent activity for the hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) in alkaline media, with overpotentials of only 37 and 234 mV respectively, at a current density of 10 mA cm-2, lower than that of commercial Pt/C (39 mV-HER) and RuO2 (295 mV-OER). Notably, no significant degradation occurs during the 1000 h HER stability test at 500 mA cm-2. Furthermore, IrSA/RuO2-850 also demonstrates superior catalytic activity and stability in acidic media. Theoretical calculations show that the interaction between Ir and RuO2 modulates the electronic structure of both Ru and Ir sites, resulting in the lowest reaction energy barriers of Ru and Ir sites for the HER and OER, respectively, which thermodynamically explains the enhancement of the catalytic activity. Besides, the introduction of Ir atoms also enhances the demetallation energy of Ru atoms and strengthens the structural stability of the crystal, leading to the improved stability of the catalyst. This work provides an effective strategy for construction of high-performing catalysts by precisely controlling the electronic structure and active sites of polymetal atoms.

Research progress and application strategies of sugar transport mechanisms in rice.

In plants, carbohydrates are central products of photosynthesis. Rice is a staple that contributes to the daily calorie intake for over half of the world's population. Hence, the primary objective of rice cultivation is to maximize carbohydrate production. The "source-sink" theory is proposed as a valuable principle for guiding crop breeding. However, the "flow" research lag, especially in sugar transport, has hindered high-yield rice breeding progress. This review concentrates on the genetic and molecular foundations of sugar transport and its regulation, enhancing the fundamental understanding of sugar transport processes in plants. We illustrate that the apoplastic pathway is predominant over the symplastic pathway during phloem loading in rice. Sugar transport proteins, such as SUTs and SWEETs, are essential carriers for sugar transportation in the apoplastic pathway. Additionally, we have summarized a regulatory pathway for sugar transport genes in rice, highlighting the roles of transcription factors (OsDOF11, OsNF-YB1, OsNF-YC12, OsbZIP72, Nhd1), OsRRM (RNA Recognition Motif containing protein), and GFD1 (Grain Filling Duration 1). Recognizing that the research shortfall in this area stems from a lack of advanced research methods, we discuss cutting-edge analytical techniques such as Mass Spectrometry Imaging and single-cell RNA sequencing, which could provide profound insights into the dynamics of sugar distribution and the associated regulatory mechanisms. In summary, this comprehensive review serves as a valuable guide, directing researchers toward a deep understanding and future study of the intricate mechanisms governing sugar transport.

Formation Characteristics of Pt-Ni Alloy Nanoparticles Fabricated by Nanolamination of Atomic Layer Deposition in Hydrogen.

Forced-flow atomic layer deposition nanolamination is employed to fabricate Pt-Ni nanoparticles on XC-72, with the compositions ranging from Pt94Ni6 to Pt67Ni33. Hydrogen is used as a co-reactant for depositing Pt and Ni. The growth rate of Pt is slower than that using oxygen reactant, and the growth exhibits preferred orientation along the (111) plane. Ni shows much slower growth rate than Pt, and it is only selectively deposited on Pt, not on the substrate. Higher ratios of Ni would hinder subsequent stacking of Pt atoms, resulting in lower overall growth rate and smaller particles (1.3-2.1 nm). Alloying of Pt with Ni causes shifted lattice that leads to larger lattice parameter and d-spacing as Ni fraction increases. From the electronic state analysis, Pt 4f peaks are shifted to lower binding energies with increasing the Ni content, suggesting charge transfer from Ni to Pt. Schematic of the growth behavior is proposed. Most of the alloy nanoparticles exhibit higher electrochemical surface area and oxygen reduction reaction activity than those of commercial Pt. Especially, Pt83Ni17 and Pt87Ni13 show excellent mass activities of 0.76 and 0.59 A mgPt -1, respectively, higher than the DOE target of 2025, 0.44 A mgPt -1.

Fe-S dually modulated adsorbate evolution and lattice oxygen compatible mechanism for water oxidation.

Simultaneously activating metal and lattice oxygen sites to construct a compatible multi-mechanism catalysis is expected for the oxygen evolution reaction (OER) by providing highly available active sites and mediate catalytic activity/stability, but significant challenges remain. Herein, Fe and S dually modulated NiFe oxyhydroxide (R-NiFeOOH@SO4) is conceived by complete reconstruction of NiMoO4·xH2O@Fe,S during OER, and achieves compatible adsorbate evolution mechanism and lattice oxygen oxidation mechanism with simultaneously optimized metal/oxygen sites, as substantiated by in situ spectroscopy/mass spectrometry and chemical probe. Further theoretical analyses reveal that Fe promotes the OER kinetics under adsorbate evolution mechanism, while S excites the lattice oxygen activity under lattice oxygen oxidation mechanism, featuring upshifted O 2p band centers, enlarged d-d Coulomb interaction, weakened metal-oxygen bond and optimized intermediate adsorption free energy. Benefiting from the compatible multi-mechanism, R-NiFeOOH@SO4 only requires overpotentials of 251 ± 5/291 ± 1 mV to drive current densities of 100/500 mA cm-2 in alkaline media, with robust stability for over 300 h. This work provides insights in understanding the OER mechanism to better design high-performance OER catalysts.

Radical-triggered translocation of C-C double bond and functional group.

Multi-site functionalization of molecules provides a potent approach to accessing intricate compounds. However, simultaneous functionalization of the reactive site and the inert remote C(sp3)-H poses a formidable challenge, as chemical reactions conventionally occur at the most active site. In addition, achieving precise control over site selectivity for remote C(sp3)-H activation presents an additional hurdle. Here we report an alternative modular method for alkene difunctionalization, encompassing radical-triggered translocation of functional groups and remote C(sp3)-H desaturation via photo/cobalt dual catalysis. By systematically combining radical addition, functional group migration and cobalt-promoted hydrogen atom transfer, we successfully effectuate the translocation of the carbon-carbon double bond and another functional group with precise site selectivity and remarkable E/Z selectivity. This redox-neutral approach shows good compatibility with diverse fluoroalkyl and sulfonyl radical precursors, enabling the migration of benzoyloxy, acetoxy, formyl, cyano and heteroaryl groups. This protocol offers a resolution for the simultaneous transformation of manifold sites.

Integrated deep learning model for automatic detection and classification of stenosis in coronary angiography.

Coronary artery disease poses a significant threat to human health. In clinical settings, coronary angiography remains the gold standard for diagnosing coronary heart disease. A crucial aspect of this diagnosis involves detecting arterial narrowings. Categorizing these narrowings can provide insight into whether patients should receive vascular revascularization treatment. The majority of current deep learning methods for analyzing coronary angiography are mostly confined to the theoretical research domain, with limited studies offering direct practical support to clinical practitioners. This paper proposes an integrated deep-learning model for the localization and classification of narrowings in coronary angiography images. The experimentation employed 1606 coronary angiography images obtained from 132 patients, resulting in an accuracy of 88.9 %, a recall rate of 85.4 %, an F1 score of 0.871, and a MAP value of 0.875 for vascular stenosis detection. Furthermore, we developed the "Hemadostenosis" web platform (http://bioinfor.imu.edu.cn/hemadostenosis) using Django, a highly mature HTTP framework. Users are able to submit coronary angiography image data for assessment via a visual interface. Subsequently, the system sends the images to a trained convolutional neural network model to localize and categorize the narrowings. Finally, the visualized outcomes are displayed to users and are downloadable. Our proposed approach pioneers the recognition and categorization of arterial narrowings in vascular angiography, offering practical support to clinical practitioners in their learning and diagnostic processes.

Bioprinted, spatially defined breast tumor microenvironment models of intratumoral heterogeneity and drug resistance.

Cellular, extracellular matrix (ECM), and spatial heterogeneity of tumor microenvironments (TMEs) regulate disease progression and treatment efficacy. Developing in vitro models that recapitulate the TME promises to accelerate studies of tumor biology and identify new targets for therapy. Here, we used extrusion-based, multi-nozzle 3D bioprinting to spatially pattern triple-negative MDA-MB-231 breast cancer cells, endothelial cells (ECs), and human mammary cancer-associated fibroblasts (HMCAFs) with biomimetic ECM inks. Bioprinted models captured key features of the spatial architecture of human breast tumors, including varying-sized dense regions of cancer cells and surrounding microvessel-rich stroma. Angiogenesis and ECM stiffening occurred in the stromal area but not the cancer cell-rich (CCR) regions, mimicking pathological changes in patient samples. Transcriptomic analyses revealed upregulation of angiogenesis-related and ECM remodeling-related signatures in the stroma region and identified potential ligand-receptor (LR) mediators of these processes. Breast cancer cells in distinct parts of the bioprinted TME showed differing sensitivities to chemotherapy, highlighting environmentally mediated drug resistance. In summary, our 3D-bioprinted tumor model will act as a platform to discover integrated functions of the TME in cancer biology and therapy.

Integrated analysis of patients with bladder cancer from prospective transcription factor activity: Implications for personalized treatment approaches.

Transcription factors are a specialized group of proteins that play important roles in regulating gene expression in human. These proteins control the transcription and translation of genes by binding to specific sites on DNA, thereby regulating key biological processes such as cell differentiation, proliferation, immune response, and neural development. Moreover, transcription factors are also involved in apoptosis and the pathogenesis of various diseases. By investigating transcription factors, researchers can uncover the mechanisms of gene regulation in organisms and develop more effective methods for preventing and treating human diseases. In the present study, the Virtual Inference of Protein-activity by Enriched Regulon algorithm was utilized to calculate the protein activity of transcription factors, and the metabolic-related protein activity were used for classifying bladder cancer patients into different subtype. To identify chemotherapy drugs with clinical benefits, the differences in prognosis and drug sensitivity between two distinct subtypes of bladder cancer patients were investigated. Simultaneously, the master regulators that display varying levels of transcription factor activity between two different bladder cancer subtypes were explored. Additionally, the potential transcriptional regulatory mechanisms and targets of these factors were investigated, thereby generating novel insights into bladder cancer research at the transcriptional regulation level.

The effect of a hybrid structured pulmonary rehabilitation education program for patients with lung cancer with a high risk of postoperative pulmonary complications: A quasi-experimental study.

PURPOSE: The absence of standardized protocols and education are the main obstacles to perioperative pulmonary rehabilitation (PR), especially for patients with high-risk factors of postoperative pulmonary complications (PPCs). We aimed to explore the effect of a hybrid structured pulmonary rehabilitation education program (SPREP) on patients with lung cancer at high risk of PPCs. METHODS: A quasi-experimental trial with a pre-post test design was conducted. The control group (n = 53) adopted routine perioperative pulmonary rehabilitation, while the intervention group (n = 53) received SPREP. Respiratory function, 6-min walk distance, Borg dyspnea scale, quality of life, anxiety-depression scores at admission, discharge, 2 weeks and 3 months post-discharge, and incidence of PPCs were compared between the two groups. RESULTS: There were no significant differences on the 6-min walk distance and Borg Dyspnoea Scale at discharge between the two groups (P > 0.05), whereas the intervention group showed improved performance at the remaining time points (P < 0.05). In addition, the intervention group had improved exercise capacity, pulmonary function and quality of life, reduced levels of anxiety and depression at discharge, 2 weeks post-discharge and 3 months post-discharge (P < 0.05). In addition, incidence of PPCs was significantly reduced in the intervention group, especially postoperative pneumonia. CONCLUSIONS: The SPREP could show significant benefits in enhancing exercise capacity, lung function, and quality of life, while diminishing the occurrence of PPCs and mitigating the levels of anxiety and depression, future large RCT need to further explore the efficacy. TRIAL REGISTRATION: This study was registered with the China Clinical Trial Registration Center (ChiCTR) under the Clinical Trial Registration Number [ChiCTR2200066698].

Hybridization of short-range and long-range charge transfer boosts room-temperature phosphorescence performance.

At present, mainstream room-temperature phosphorescence (RTP) emission relies on organic materials with long-range charge-transfer effects; therefore, exploring new forms of charge transfer to generate RTP is worth studying. In this work, indole-carbazole was used as the core to ensure the narrowband fluorescence emission of the material based on its characteristic short-range charge-transfer effect. In addition, halogenated carbazoles were introduced into the periphery to construct long-range charge transfer, resulting in VTCzNL-Cl and VTCzNL-Br. By encapsulating these phosphors into a robust host (TPP), two host-guest crystalline systems were further developed, achieving efficient RTP performance with phosphorescence quantum yields of 26% and phosphorescence lifetimes of 3.2 and 39.2 ms, respectively.

Optimal scheduling model using the IGDT method for park integrated energy systems considering P2G-CCS and cloud energy storage.

To enhance the energy efficiency and financial gains of the park integrated energy system (PIES). This paper constructs a bi-level optimization model of PIES-cloud energy storage (CES) based on source-load uncertainty. Firstly, the scheduling framework of PIES with refined power-to-gas (P2G), carbon capture and storage (CCS) and CES coupling is constructed. Moreover, a bi-level optimization model with the upper tier subject being the PIES operator and the lower tier subject being the CES operator is established under the ladder-type carbon price mechanism with reward and punishment (LCPMRP). Then a proposed entropy weight adaptive information gap decision theory method (EAIGDT) is proposed to eliminate the subjectivity factor and retain its non-probabilistic features while dealing with multiple source-load uncertainties, and according to the operator's risk preference to build risk-averse (RA) and risk-seeking (RS) strategies, respectively. Finally, the measured data in a certain area of Xinjiang verifies the proposed optimal scheduling method. The results show that the method can effectively take into account the interests of various subjects and realise PIES low-carbon economic operation.