Enhanced quantum secret sharing protocol for anonymous secure communication utilizing W states.

Quantum secret sharing (QSS) represents the fusion of quantum mechanics principles with secret information sharing, allowing a sender to distribute a secret among receivers for collective recovery. This paper introduces the concept of quantum anonymous secret sharing (QASS) to enhance the practicality of such protocols. We propose a QASS protocol leveraging W states, ensuring both recover-security and anonymity of shared secrets. Our protocol undergoes rigorous evaluation verifying their accuracy and fortifying their security against scenarios involving the active adversary. Additionally, acknowledging the imperfections inherent in real-world communication channels, we conduct a comprehensive analysis of protocol security and efficacy in noisy quantum networks. Our investigations reveal that W states exhibit good performance in mitigating noise interference, making them apt for practical applications.

FAM83B promotes cell proliferation via regulating the expression of CDK4/CDK6/CCND1 complex in laryngeal squamous cell carcinoma.

FAM83B, as one of the FAM83 family members, has been closely involved in cell transformation, and a growing number of scholars have been studied its role in tumours over the years. Whereas the effect and potential mechanism of FAM83B in laryngeal squamous cell carcinoma (LSCC) have not been investigated. In this research, we discovered that the expression quantity of FAM83B was remarkably higher in LSCC tissues (79.65 ± 35.98) than in matched adjacent tissues (59.34 ± 32.59) by tissue microarrays and immunohistochemistry. Furthermore, expression of FAM83B was knocked down in HEP-2 and TU177 cell lines via lentivirus, and in the course of intracorporal and extracorporeal experiments, FAM83B knockdown showed the inhibition of tumour growth, migration, and invasion ability. Moreover, cell cycle assay showed that FAM83B knockdown leads to an apparent accumulation of cells in the G1 phase, indicating that FAM83B knockdown can inhibit cell proliferation. Meanwhile, western blotting (WB) demonstrated that FAM83B knockdown led to a significant reduction in CDK4/CDK6/CCND1 protein expression, which may have decelerated cell cycle progression. Collectively, this study demonstrates that FAM83B serves as an oncogene in LSCC, promoting cell proliferation by controlling the protein expression of CDK4, CDK6, and CCND1, thus inducing a transference of the G1 stage to S stage in cell-cycle of LSCC cells. These results provide an academic foundation for elucidating the mechanism of LSCC occurrence and evolution and for developing treatment strategies for LSCC.

Shexiang Tongxin Dropping Pill Promotes Angiogenesis through VEGF/eNOS Signaling Pathway on Diabetic Coronary Microcirculation Dysfunction.

OBJECTIVE: To study the effect of Shexiang Tongxin Dropping Pill (STDP) on angiogenesis in diabetic cardiomyopathy mice with coronary microcirculation dysfunction (CMD). METHODS: According to a random number table, 6 of 36 SPF male C57BL/6 mice were randomly selected as the control group, and the remaining 30 mice were injected with streptozotocin intraperitoneally to replicate the type 1 diabetes model. Mice successfully copied the diabetes model were randomly divided into the model group, STDP low-dose group [15 mg/(kg·d)], medium-dose group [30 mg/(kg·d)], high-dose group [60 mg/(kg·d)], and nicorandil group [15 mg/(kg·d)], 6 in each group. The drug was given by continuous gavage for 12 weeks. The cardiac function of mice in each group was detected at the end of the experiment, and coronary flow reserve (CFR) was detected by chest Doppler technique. Pathological changes of myocardium were observed by hematoxylin-eosin staining, collagen fiber deposition was detected by masson staining, the number of myocardial capillaries was detected by platelet endothelial cell adhesion molecule-1 staining, and the degree of myocardial hypertrophy was detected by wheat germ agglutinin staining. The expression of the vascular endothlial growth factor (VEGF)/endothelial nitric oxide synthase (eNOS) signaling pathway-related proteins in myocardial tissue was detected by Western blot. RESULTS: Compared with the model group, medium- and high-dose STDP significantly increased the left ventricular ejection fraction and left ventricular fraction shortening (P<0.01), obviously repaired the disordered cardiac muscle structure, reduced myocardial fibrosis, reduced myocardial cell area, increased capillary density, and increased CFR level (all P<0.01). Western blot showed that high-dose STDP could significantly increase the expression of VEGF and promote the phosphorylation of vascular endothelial growth factor receptor 2, phosphoinositide 3-kinase, protein kinase B, and eNOS (P<0.05 or P<0.01). CONCLUSION: STDP has a definite therapeutic effect on diabetic CMD, and its mechanism may be related to promoting angiogenesis through the VEGF/eNOS signaling pathway.

Nanocavity in hollow sandwiched catalysts as substrate regulator for boosting hydrodeoxygenation of biomass-derived carbonyl compounds.

Hydrodeoxygenation of oxygen-rich molecules toward hydrocarbons is attractive yet challenging in the sustainable biomass upgrading. The typical supported metal catalysts often display unstable catalytic performances owing to the migration and aggregation of metal nanoparticles (NPs) into large sizes under harsh conditions. Here, we develop a crystal growth and post-synthetic etching method to construct hollow chromium terephthalate MIL-101 (named as HoMIL-101) with one layer of sandwiched Ru NPs as robust catalysts. Impressively, HoMIL-101@Ru@MIL-101 exhibits the excellent activity and stability for hydrodeoxygenation of biomass-derived levulinic acid to gamma-valerolactone under 50°C and 1-megapascal H2, and its activity is about six times of solid sandwich counterparts, outperforming the state-of-the-art heterogeneous catalysts. Control experiments and theoretical simulation clearly indicate that the enrichment of levulinic acid and H2 by nanocavity as substrate regulator enables self-regulating the backwash of both substrates toward Ru NPs sandwiched in MIL-101 shells for promoting reaction with respect to solid counterparts, thus leading to the substantially enhanced performance.

Application of machine learning combined with population pharmacokinetics to improve individual prediction of vancomycin clearance in simulated adult patients.

Background and aim: Vancomycin, a glycopeptide antimicrobial drug. PPK has problems such as difficulty in accurately reflecting inter-individual differences, and the PPK model may not be accurate enough to predict individual pharmacokinetic parameters. Therefore, the aim of this study is to investigate whether the application of machine learning combined with the PPK method can improve the prediction of vancomycin CL in adult Chinese patients. Methods: In the first step, a vancomycin CL prediction model for Chinese adult patients is given by PPK and Hamilton Monte Carlo sampling is used to obtain the reference CL of 1,000 patients; the second step is to obtain the final prediction model by machine learning using an appropriate model for the predictive factor and the reference CL; and the third step is to randomly select, in the simulated data, a total of 250 patients for prediction effect evaluation. Results: XGBoost model is selected as final machine learning model. More than four-fifths of the subjects' predictive values regarding vancomycin CL are improved by machine learning combined with PPK. Machine learning combined with PPK models is more stable in performance than the PPK method alone for predicting models. Conclusion: The first combination of PPK and machine learning for predictive modeling of vancomycin clearance in adult patients. It provides a reference for clinical pharmacists or clinicians to optimize the initial dosage given to ensure the effectiveness and safety of drug therapy for each patient.

Motif-Aware miRNA-Disease Association Prediction Via Hierarchical Attention Network.

As post-transcriptional regulators of gene expression, micro-ribonucleic acids (miRNAs) are regarded as potential biomarkers for a variety of diseases. Hence, the prediction of miRNA-disease associations (MDAs) is of great significance for an in-depth understanding of disease pathogenesis and progression. Existing prediction models are mainly concentrated on incorporating different sources of biological information to perform the MDA prediction task while failing to consider the fully potential utility of MDA network information at the motif-level. To overcome this problem, we propose a novel motif-aware MDA prediction model, namely MotifMDA, by fusing a variety of high- and low-order structural information. In particular, we first design several motifs of interest considering their ability to characterize how miRNAs are associated with diseases through different network structural patterns. Then, MotifMDA adopts a two-layer hierarchical attention to identify novel MDAs. Specifically, the first attention layer learns high-order motif preferences based on their occurrences in the given MDA network, while the second one learns the final embeddings of miRNAs and diseases through coupling high- and low-order preferences. Experimental results on two benchmark datasets have demonstrated the superior performance of MotifMDA over several state-of-the-art prediction models. This strongly indicates that accurate MDA prediction can be achieved by relying solely on MDA network information. Furthermore, our case studies indicate that the incorporation of motif-level structure information allows MotifMDA to discover novel MDAs from different perspectives. The data and codes are available at https://github.com/stevejobws/MotifMDA.

Exploring Carbonization Temperature to Create Closed Pores for Hard Carbon as High-Performance Sodium-Ion Battery Anodes.

Biomass-derived porous carbon materials are meaningful to employ as a hard carbon precursor for anode materials of sodium-ion batteries (SIBs) from a sustainability perspective. Here, a straightforward approach is proposed to develop rich closed pores in pinenut-derived carbon, with the aim of improving Na+ plateau storage by adjusting the pyrolysis temperature. The optimized sample, namely the pinenut-derived carbon at 1300 °C, demonstrates remarkable reversible specific capacity of 278 mAh g-1, along with a high initial Coulomb efficiency of 85% and robust cycling stability (with a capacity retention of 89% after 800 cycles at 0.2 A g-1). In situ and ex situ analyses unveil that the developed closed pores play a significant role in enhancing the plateau capacity, providing compelling evidence for the "adsorption-filling" mechanism. Moreover, the corresponding full-cell achieves a high energy density of 245.7 Wh kg-1 (based on the total weight of both electrode active materials) and exhibits outstanding rate capability (191.4 mAh g-1 at 3 A g-1).

Deformation and Failure Mechanisms of Element-Substituted Thermoelectric Type-I and Type-VIII Clathrates.

Clathrates are potential "phonon-glass, electron-crystal" thermoelectric semiconductors, whose structure of polyhedron stacks is very attractive. However, their mechanical properties have not yet met the requirements of industrial applications. Here, we report the ideal strength of element-substituted type-I and type-VIII clathrates and the shear deformation mechanism by using density functional theory. The results show that the framework element is the determinant of the intrinsic mechanical properties of the clathrates and is affected by sequential weakening of Si-Ge-Sn. The highest ideal shear strength is 8.71 GPa for I-Ba8Au6Si40 along the (110)/[001] slip system, which is attributed to the formation of higher-energy Si-Si covalent bonds. Meanwhile, the ideal shear strength of Ba-filled I/VIII clathrates (4.51/2.65 GPa) is higher than that of Sr-filled clathrates (3.64 GPa/1.91 GPa). In addition, the strength and ultimate strain of VIII-Ba8Ga16Sn30 can be significantly increased by the structural coordination accommodating with the stiffness of the Ga-Ge bond to achieve simultaneous bond breaking. Our findings demonstrate that the element substitution strategy is an effective approach for designing highly robust clathrates.

Molecular subtyping and the construction of a predictive model of colorectal cancer based on ion channel genes.

PURPOSE: Colorectal cancer (CRC) is a highly heterogeneous malignancy with an unfavorable prognosis. The purpose of this study was to address the heterogeneity of CRC by categorizing it into ion channel subtypes, and to develop a predictive modeling based on ion channel genes to predict the survival and immunological states of patients with CRC. The model will provide guidance for personalized immunotherapy and drug treatment. METHODS: A consistent clustering method was used to classify 619 CRC samples based on the expression of 279 ion channel genes. Such a method was allowed to investigate the relationship between molecular subtypes, prognosis, and immune infiltration. Furthermore, a predictive modeling was constructed for ion channels to evaluate the ion channel properties of individual tumors using the least absolute shrinkage and selection operator. The expression patterns of the characteristic genes were validated through molecular biology experiments. The effect of potassium channel tetramerization domain containing 9 (KCTD9) on CRC was verified by cellular functional experiments. RESULTS: Four distinct ion channel subtypes were identified in CRC, each characterized by unique prognosis and immune infiltration patterns. Notably, Ion Cluster3 exhibited high levels of immune infiltration and a favorable prognosis, while Ion Cluster4 showed relatively lower levels of immune infiltration and a poorer prognosis. The ion channel score could predict overall survival, with lower scores correlated with longer survival. This score served as an independent prognostic factor and presented an excellent predictive efficacy in the nomogram. In addition, the score was closely related to immune infiltration, immunotherapy response, and chemotherapy sensitivity. Experimental evidence further confirmed that low expression of KCTD9 in tumor tissues was associated with an unfavorable prognosis in patients with CRC. The cellular functional experiments demonstrated that KCTD9 inhibited the proliferation, migration and invasion capabilities of LOVO cells. CONCLUSIONS: Ion channel subtyping and scoring can effectively predict the prognosis and evaluate the immune microenvironment, immunotherapy response, and drug sensitivity in patients with CRC.

Essential role of lattice oxygen in hydrogen sensing reaction.

Understanding the sensing mechanism of metal oxide semiconductors is imperative to the development of high-performance sensors. The traditional sensing mechanism only recognizes the effect of surface chemisorbed oxygen from the air but ignores surface lattice oxygen. Herein, using in-situ characterizations, we provide direct experimental evidence that the surface chemisorbed oxygen participated in the sensing process can come from lattice oxygen of the oxides. Further density functional theory (DFT) calculations prove that the p-band center of O serves as a state of art for regulating the participation of lattice oxygen in gas-sensing reactions. Based on our experimental data and theoretical calculations, we discuss mechanisms that are fundamentally different from the conventional mechanism and show that the easily participation of lattice oxygen is helpful for the high response value of the materials.

Incidence and risk factors for pulmonary hemorrhage after percutaneous CT-guided pulmonary nodule biopsy: an observational study.

To evaluate the current incidence of pulmonary hemorrhage and the potential factors contributing to its increased risk after percutaneous CT-guided pulmonary nodule biopsy and to summarize the technical recommendations for its treatment. In this observational study, patient data were collected from ten medical centers from April 2021 to April 2022. The incidence of pulmonary hemorrhage was as follows: grade 0, 36.1% (214/593); grade 1, 36.8% (218/593); grade 2, 18.9% (112/593); grade 3, 3.5% (21/593); and grade 4, 4.7% (28/593). High-grade hemorrhage (HGH) occurred in 27.2% (161/593) of the patients. The use of preoperative breathing exercises (PBE, p =0.000), semiautomatic cutting needles (SCN, p = 0.004), immediate contrast enhancement (ICE, p =0.021), and the coaxial technique (CoT, p = 0.000) were found to be protective factors for HGH. A greater length of puncture (p =0.021), the presence of hilar nodules (p = 0.001), the presence of intermediate nodules (p = 0.026), a main pulmonary artery diameter (mPAD) larger than 29 mm (p = 0.015), and a small nodule size (p = 0.014) were risk factors for high-grade hemorrhage. The area under the curve (AUC) was 0.783. These findings contribute to a deeper understanding of the risks associated with percutaneous CT-guided pulmonary nodule biopsy and provide valuable insights for developing strategies to minimize pulmonary hemorrhage.

Effects of Glutamine Synthetase on Neovascularization in Glioma: In Vivo MR Vessel Size Imaging and Histology.

BACKGROUND: Glutamine Synthetase (GS) could induce vascular sprouting through the improvement of endothelial cell migration in inflammatory diseases. MR vessel-size imaging has been proposed as a valuable approach for visualizing the underlying angiogenic processes in the brain. OBJECTIVE: This study aims to investigate the role of GS in the neovascularization of gliomas through the utilization of MR vessel-size imaging and histopathological techniques. METHODS: In this exploratory animal study, we randomly divided the C6 glioma rat models into a control group and an L-methionine sulfoximine (MSO) treatment group. Daily intraperitoneal injections were administered for three consecutive days, starting from day 10 following the implantation of C6 glioma cells in rats. Subsequently, MR vessel size imaging was conducted using a BRUKER 7 T/200 mm MRI scanner, and the MRI results were validated through histopathological examination. RESULTS: A significant decrease in microvessel density was observed in both the tumor periphery and center areas in the MSO treatment group compared to that in the control group. The mean vessel diameter (mVD) and vessel size index (VSI) did not exhibit significant changes compared to the control group. Moreover, the staining intensity of platelet endothelial cell adhesion molecule-1 (CD31) and GS in the tumor periphery was significantly decreased in the MSO treatment group. Additionally, the MSO treatment demonstrated a substantial inhibition of tumor growth. CONCLUSION: GS inhibitors significantly reduced angiogenesis in the periphery area of C6 glioma, exerting an inhibitory effect on tumor progression. Thus, GS inhibitors could be potential therapeutic agents for treating glioma. Additionally, in vivo MR vessel size imaging detects changes in vascularrelated parameters after tumor treatment, making it a promising method for detecting neovascularization in glioma.

Machine Learning Method to Explore the Correlation between Fly Ash Content and Chloride Resistance.

Chloride ion corrosion has been considered to be one of the main reasons for durability deterioration of reinforced concrete structures in marine or chlorine-containing deicing salt environments. This paper studies the relationship between the amount of fly ash and the durability of concrete, especially the resistance to chloride ion erosion. The heat trend map of total chloride ion factor correlation displayed that the ranking of factor correlations was as follows: sampling depth > cement dosage > fly ash dosage. In order to verify the effect of fly ash dosage on chloride ion resistance, three different machine learning algorithms (RF, GBR, DT) are employed to predict the total chloride content of fly ash proportioned concrete with varying admixture ratios, which are evaluated based on R2, MSE, RMSE, and MAE. The results predicted by the RF model show that the threshold of fly ash admixture in chlorinated salt environments is 30-40%. Replacing part of cement with fly ash in the mixture of concrete below this threshold of fly ash, it could change the phase structure and pore structure, which could improve the permeability of fly ash concrete and reduce the content of free chloride ions in the system. Machine learning modeling using sample data can accurately predict concrete properties, which effectively reduce engineering tests. The development of machine learning models is essential for the decarbonization and intelligence of engineering.

Electrocatalytic Hydrogenation Using Palladium Membrane Reactors.

Hydrogenation is a crucial chemical process employed in a myriad of industries, often facilitated by metals such as Pd, Pt, and Ni as catalysts. Traditional thermocatalytic hydrogenation usually necessitates high temperature and elevated pressure, making the process energy intensive. Electrocatalytic hydrogenation offers an alternative but suffers from issues such as competing H2 evolution, electrolyte separation, and limited solvent selection. This Perspective introduces the evolution and advantages of the electrocatalytic Pd membrane reactor (ePMR) as a solution to these challenges. ePMR utilizes a Pd membrane to physically separate the electrochemical chamber from the hydrogenation chamber, permitting the use of water as the hydrogen source and eliminating the need for H2 gas. This setup allows for greater control over reaction conditions, such as solvent and electrolyte selection, while mitigating issues such as low Faradaic efficiency and complex product separation. Several representative hydrogenation reactions (e.g., hydrogenation of C=C, C≡C, C=O, C≡N, and O=O bonds) achieved via ePMR over the past 30 years were concisely discussed to highlight the unique advantages of ePMR. Promising research directions along with the advancement of ePMR for more challenging hydrogenation reactions are also proposed. Finally, we provide a prospect for future development of this distinctive hydrogenation strategy using hydrogen-permeable membrane electrodes.

Depression heightened the association of the systemic immune-inflammation index with all-cause mortality among osteoarthritis patient.

BACKGROUND: Systemic immune-inflammatory index (SII) has been recognized as a novel inflammatory indicator in numerous diseases. It remains unknown how SII affects all-cause mortality among patients with osteoarthritis (OA). In this prospective cohort study, we intended to examine the relationship of SII with all-cause mortality among OA populations and assess the interaction between depression and SII. METHODS: Data was collected from National Health and Nutrition Examination Survey (NHANES) in 2005-2018. The National Death Index (NDI) provided vital status records. Multivariable Cox regression analyses with cubic spines were applied to estimate the association between SII and all-cause and CVD mortality. Stratified analysis and interaction tests assessed the interaction of SII and depression on all-cause mortality. RESULTS: In total 3174 OA adults were included. The lowest quartile Q1 (HR:1.44, 95%CI:1.02-2.04) and highest quartile Q4 (HR:1.44, 95%CI:1.02-2.04) of SII presented a higher risk of death compared with those in second quartile Q2 (Ref.) and third quartile Q3 (HR:1.23, 95%CI:0.89-1.68. Restricted cubic splines analysis revealed a U-shaped association of SII with all-cause mortality, the inflection points were 412.93 × 109/L. The interaction test observed a more significant relationship of SII with all-cause mortality in depression patients than in non-depression patients, indicating that depression can modify this association. LIMITATIONS: First, the observational study design failed to make causal inferences. Second, the baseline SII cannot reflect the long-term level of inflammation. Finally, there may be potential bias. CONCLUSION: SII was U-shaped associated with all-cause mortality in OA patients, and this association was significantly heightened by depression.

CD63+ cancer-associated fibroblasts confer CDK4/6 inhibitor resistance to breast cancer cells by exosomal miR-20.

Cyclin-dependent kinase 4 (CDK4) and CDK6 inhibitors (CDK4/6i) have rapidly received Food and Drug Administration (FDA) approval as a new type of therapy for patients with advanced hormone receptor-positive breast cancer. However, with the widespread application of CDK4/6i, drug resistance has become a new challenge for clinical practice and has greatly limited the treatment effect. Here, the whole microenvironment landscape of ER+ breast cancer tumors was revealed through single-cell RNA sequencing, and a specific subset of cancer-associated fibroblasts (CD63+ CAFs) was identified as highly enriched in CDK4/6i resistant tumor tissues. Then, we found that CD63+ CAFs can distinctly promote resistance to CDK4/6i in breast cancer cells and tumor xenografts. In addition, it was discovered that miR-20 is markedly enriched in the CD63+ CAFs-derived exosomes, which are used to communicate with ER+ breast cancer cells, leading to CDK4/6i resistance. Furthermore, exosomal miR-20 could directly target the RB1 mRNA 3'UTR and negatively regulate RB1 expression to decrease CDK4/6i sensitivity in breast cancer cells. Most importantly, we designed and synthesized cRGD-miR-20 sponge nanoparticles and found that they can enhance the therapeutic effect of CDK4/6i in breast cancer. In summary, our findings reveal that CD63+ CAFs can promote CDK4/6i resistance via exosomal miR-20, which induces the downregulation of RB1 in breast cancer cells, and suggest that CD63+ CAFs may be a novel therapeutic target to enhance CDK4/6i sensitivity.

LINC00960 affects osteosarcoma treatment and prognosis by regulating the tumor immune microenvironment.

Background: Osteosarcoma (OS), the commonest primary malignant bone tumor, is mainly seen in children and teenagers. LINC00960, a newly discovered long intergenic non-protein coding RNA, has been shown to be important in certain cancers. The objective of this study was to assess LINC00960's prognostic and therapeutic value and analyze its mechanism of action in osteosarcoma. Methods: With the transcriptome information of 85 osteosarcomas from the TARGET database, the Cox regression analyses, K-M curve, and ROC curve, were conducted for survival and prognostic analysis. The functional analysis was conducted using GO, KEGG, GSEA, and GSVA. The ESTIMATE, ssGSEA, MCP-counter, ImmuCellAI algorithms, and immune checkpoint correlation analysis were performed for immune-related analysis. The single-cell RNA sequencing data of 6 osteosarcoma patients was obtained from the Gene Expression Omnibus database. The Tumor Immune Dysfunction and Exclusion algorithm and the "pRRophetic" R package were performed to predict the response to immunotherapy and chemotherapy. Results: LINC00960 overexpression is associated with osteosarcoma metastasis and poor prognosis. Based on the LINC00960 expression, the nomogram prediction model was created, which showed good accuracy and precision to predict the overall survival of osteosarcoma. Single-cell and immune-related analysis showed that LINC00960 is mainly highly expressed in the tumor-exhausted CD8 T cells in osteosarcoma. In osteosarcoma, the expression of LIC00960 was favorably connected with immune checkpoint-related genes and negatively correlated with immune infiltration. TIDE analysis indicated that low LINC00960 expression patients might have a better response to immunotherapy. Drug sensitivity analysis showed that high LINC00960 expression patients might have better responses to Bleomycin and Doxorubicin. Conclusion: LINC00960 has the potential to be a novel biomarker for predicting overall survival in osteosarcoma patients and to guide more individualized treatment and clinical decision-making.

Repurposing sodium stibogluconate as an uracil DNA glycosylase inhibitor against prostate cancer using a time-resolved oligonucleotide-based drug screening platform.

Repurposing drugs can significantly reduce the time and costs associated with drug discovery and development. However, many drug compounds possess intrinsic fluorescence, resulting in aberrations such as auto-fluorescence, scattering and quenching, in fluorescent high-throughput screening assays. To overcome these drawbacks, time-resolved technologies have received increasing attention. In this study, we have developed a rapid and efficient screening platform based on time-resolved emission spectroscopy in order to screen for inhibitors of the DNA repair enzyme, uracil-DNA glycosylase (UDG). From a database of 1456 FDA/EMA-approved drugs, sodium stibogluconate was discovered as a potent UDG inhibitor. This compound showed synergistic cytotoxicity against 5-fluorouracil-resistant cancer cells. This work provides a promising future for time-resolved technologies for high-throughput screening (HTS), allowing for the swift identification of bioactive compounds from previously overlooked scaffolds due to their inherent fluorescence properties.

A Catalyst-Like System Enables Efficient Perovskite Solar Cells.

High-quality perovskite films are essential for achieving high performance of optoelectronic devices; However, solution-processed perovskite films are known to suffer from compositional and structural inhomogeneity due to lack of systematic control over the kinetics during the formation. Here, the microscopic homogeneity of perovskite films is successfully enhanced by modulating the conversion reaction kinetics using a catalyst-like system generated by a foaming agent. The chemical and structural evolution during this catalytic conversion is revealed by a multimodal synchrotron toolkit with spatial resolutions spanning many length scales. Combining these insights with computational investigations, a cyclic conversion pathway model is developed that yields exceptional perovskite homogeneity due to enhanced conversion, having a power conversion efficiency of 24.51% for photovoltaic devices. This work establishes a systematic link between processing of precursor and homogeneity of the perovskite films.

Hemin blocks TIGIT/PVR interaction and induces ferroptosis to elicit synergistic effects of cancer immunotherapy.

The immune checkpoint TIGIT/PVR blockade exhibits significant antitumor effects through activation of NK and CD8+ T cell-mediated cytotoxicity. Immune checkpoint blockade (ICB) could induce tumor ferroptosis through IFN-γ released by immune cells, indicating the synergetic effects of ICB with ferroptosis in inhibiting tumor growth. However, the development of TIGIT/PVR inhibitors with ferroptosis-inducing effects has not been explored yet. In this study, the small molecule Hemin that could bind with TIGIT to block TIGIT/PVR interaction was screened by virtual molecular docking and cell-based blocking assay. Hemin could effectively restore the IL-2 secretion from Jurkat-hTIGIT cells. Hemin reinvigorated the function of CD8+ T cells to secrete IFN-γ and the elevated IFN-γ could synergize with Hemin to induce ferroptosis in tumor cells. Hemin inhibited tumor growth by boosting CD8+ T cell immune response and inducing ferroptosis in CT26 tumor model. More importantly, Hemin in combination with PD-1/PD-L1 blockade exhibited more effective antitumor efficacy in anti-PD-1 resistant B16 tumor model. In summary, our finding indicated that Hemin blocked TIGIT/PVR interaction and induced tumor cell ferroptosis, which provided a new therapeutic strategy to combine immunotherapy and ferroptosis for cancer treatment.