Synthesis and structural optimization of oncolytic peptide LTX-315.

Oncolytic peptides represented potential novel candidates for anticancer treatments especially drug-resistant cancer cell lines. One of the most promising and extensively studied is LTX-315, which is considered as the first in class oncolytic peptide and has entered phase I/II clinical trials. Nevertheless, the shortcomings including poor proteolytic stability, moderate anticancer durability and high synthesis costs may hinder the widespread clinical applications of LTX-315. In order to reduce the synthesis costs, as well as develop derivatives possessing both high protease-stability and durable anticancer efficiency, twenty LTX-315-based derived-peptides were designed and efficiently synthesized. Especially, through solid-phase S-alkylation, as well as the optimized peptide cleavage condition, the derived peptides could be prepared with drastically reduced synthesis cost. The in vitro anticancer efficiency, serum stability, anticancer durability, anti-migration activity, and hemolysis effect were systematically investigated. It was found that derived peptide MS-13 exhibited comparable anticancer efficiency and durability to those of LTX-315. Strikingly, the D-type peptide MS-20, which is the enantiomer of MS-13, was demonstrated to possess significantly high proteolytic stability and sustained anticancer durability. In general, the cost-effective synthesis and stability-guided structural optimizations were conducted on LTX-315, affording the highly hydrolysis resistant MS-20 which possessed durable anticancer activity. Meanwhile, this study also provided a reliable reference for the future optimization of anticancer peptides through the solid-phase S-alkylation and L-type to D-type amino acid substitutions.

Construction of an enzyme-constrained metabolic network model for Myceliophthora thermophila using machine learning-based kcat data.

BACKGROUND: Genome-scale metabolic models (GEMs) serve as effective tools for understanding cellular phenotypes and predicting engineering targets in the development of industrial strain. Enzyme-constrained genome-scale metabolic models (ecGEMs) have emerged as a valuable advancement, providing more accurate predictions and unveiling new engineering targets compared to models lacking enzyme constraints. In 2022, a stoichiometric GEM, iDL1450, was reconstructed for the industrially significant fungus Myceliophthora thermophila. To enhance the GEM's performance, an ecGEM was developed for M. thermophila in this study. RESULTS: Initially, the model iDL1450 underwent refinement and updates, resulting in a new version named iYW1475. These updates included adjustments to biomass components, correction of gene-protein-reaction (GPR) rules, and a consensus on metabolites. Subsequently, the first ecGEM for M. thermophila was constructed using machine learning-based kcat data predicted by TurNuP within the ECMpy framework. During the construction, three versions of ecGEMs were developed based on three distinct kcat collection methods, namely AutoPACMEN, DLKcat and TurNuP. After comparison, the ecGEM constructed using TurNuP-predicted kcat values performed better in several aspects and was selected as the definitive version of ecGEM for M. thermophila (ecMTM). Comparing ecMTM to iYW1475, the solution space was reduced and the growth simulation results more closely resembled realistic cellular phenotypes. Metabolic adjustment simulated by ecMTM revealed a trade-off between biomass yield and enzyme usage efficiency at varying glucose uptake rates. Notably, hierarchical utilization of five carbon sources derived from plant biomass hydrolysis was accurately captured and explained by ecMTM. Furthermore, based on enzyme cost considerations, ecMTM successfully predicted reported targets for metabolic engineering modification and introduced some new potential targets for chemicals produced in M. thermophila. CONCLUSIONS: In this study, the incorporation of enzyme constraint to iYW1475 not only improved prediction accuracy but also broadened the model's applicability. This research demonstrates the effectiveness of integrating of machine learning-based kcat data in the construction of ecGEMs especially in situations where there is limited measured enzyme kinetic parameters for a specific organism.

Degradation of FAK-targeting by proteolytic targeting chimera technology to inhibit the metastasis of hepatocellular carcinoma.

Liver cancer is a prevalent malignant cancer, ranking third in terms of mortality rate. Metastasis and recurrence primarily contribute to the high mortality rate of liver cancer. Hepatocellular carcinoma (HCC) has low expression of focal adhesion kinase (FAK), which increases the risk of metastasis and recurrence. Nevertheless, the efficacy of FAK phosphorylation inhibitors is currently limited. Thus, investigating the mechanisms by which FAK affects HCC metastasis to develop targeted therapies for FAK may present a novel strategy to inhibit HCC metastasis. This study examined the correlation between FAK expression and the prognosis of HCC. Additionally, we explored the impact of FAK degradation on HCC metastasis through wound healing experiments, transwell invasion experiments, and a xenograft tumor model. The expression of proteins related to epithelial-mesenchymal transition (EMT) was measured to elucidate the underlying mechanisms. The results showed that FAK PROTAC can degrade FAK, inhibit the migration and invasion of HCC cells in vitro, and notably decrease the lung metastasis of HCC in vivo. Increased expression of E-cadherin and decreased expression of vimentin indicated that EMT was inhibited. Consequently, degradation of FAK through FAK PROTAC effectively suppressed liver cancer metastasis, holding significant clinical implications for treating liver cancer and developing innovative anti-neoplastic drugs.

Arabidopsis transcription factor TCP4 controls the identity of the apical gynoecium.

The style and stigma at the apical gynoecium are crucial for flowering plant reproduction. However, the mechanisms underlying specification of the apical gynoecium remain unclear. Here, we demonstrate that Class II TEOSINTE BRANCHED 1/CYCLOIDEA/PCF (TCP) transcription factors are critical for apical gynoecium specification in Arabidopsis (Arabidopsis thaliana). The septuple tcp2 tcp3 tcp4 tcp5 tcp10 tcp13 tcp17 (tcpSEP) and duodecuple tcp2 tcp3 tcp4 tcp5 tcp10 tcp13 tcp17 tcp24 tcp1 tcp12 tcp18 tcp16 (tcpDUO) mutants produce narrower and longer styles, while disruption of TCPs and CRABS CLAW (CRC) or NGATHAs (NGAs) in tcpDUO crc or tcpDUO nga1 nga2 nga4 causes the apical gynoecium to be replaced by lamellar structures with indeterminate growth. TCPs are predominantly expressed in the apex of the gynoecium. TCP4 interacts with CRC to synergistically up-regulate the expression level of NGAs, and NGAs further form high-order complexes to control the expression of auxin-related genes in the apical gynoecium by directly interacting with TCP4. Our findings demonstrate that TCP4 physically associates with CRC and NGAs to control auxin biosynthesis in forming fine structures of the apical gynoecium.

Prediction of microbial activity and abundance using interpretable machine learning models in the hyporheic zone of effluent-dominated receiving rivers.

Serving as a vital linkage between surface water and groundwater, the hyporheic zone (HZ) plays a fundamental role in improving water quality and maintaining ecological security. In arid or semi-arid areas, effluent discharge from wastewater treatment facilities could occupy a predominant proportion of the total base flow of receiving rivers. Nonetheless the relationship between microbial activity, abundance and environmental factors in the HZ of effluent-receiving rivers appear to be rarely addressed. In this study, a spatiotemporal field study was performed in two representative effluent-dominated receiving rivers in Xi'an, China. Land use data, physical and chemical water quality parameters of surface and subsurface water were used as predictive variables, while the microbial respiratory electron transport system activity (ETSA), the Chao1 and Shannon index of total microbial community, as well as the Chao1 and Shannon index of denitrifying bacteria community were used as response variables, while ETSA was used as response variables indicating ecological processes and Shannon and Chao1 were utilized as parameters indicating microbial diversity. Two machine learning models were utilized to provide evidence-based information on how environmental factors interact and drive microbial activity and abundance in the HZ at variable depths. The models with Chao1 and Shannon as response variables exhibited excellent predictive performances (R2: 0.754-0.81 and 0.783-0.839). Dissolved organic nitrogen (DON) was the most important factor affecting the microbial functions, and an obvious threshold value of ∼2 mg/L was observed. Credible predictions of models with Chao1 and Shannon index of denitrifying bacteria community as response variables were detected (R2: 0.484-0.624 and 0.567-0.638), with soluble reactive phosphorus (SRP) being the key influencing factor. Fe (Ⅱ) was favorable in predicting denitrifying bacteria community. The ESTA model highlighted the importance of total nitrogen in the ecological health monitoring in HZ. These findings provide novel insights in predicting microbial activity and abundance in highly-impacted areas such as the HZ of effluent-dominated receiving rivers.

Nanomaterials in crossroad of autophagy control in human cancers: Amplification of cell death mechanisms.

Cancer is the result of genetic abnormalities that cause normal cells to grow into neoplastic cells. Cancer is characterized by several distinct features, such as uncontrolled cell growth, extensive spreading to other parts of the body, and the ability to resist treatment. The scientists have stressed the development of nanostructures as novel therapeutic options in suppressing cancer, in response to the emergence of resistance to standard medicines. One of the specific mechanisms with dysregulation during cancer is autophagy. Nanomaterials have the ability to specifically carry medications and genes, and they can also enhance the responsiveness of tumor cells to standard therapy while promoting drug sensitivity. The primary mechanism in this process relies on autophagosomes and their fusion with lysosomes to break down the components of the cytoplasm. While autophagy was initially described as a form of cellular demise, it has been demonstrated to play a crucial role in controlling metastasis, proliferation, and treatment resistance in human malignancies. The pharmacokinetic profile of autophagy modulators is poor, despite their development for use in cancer therapy. Consequently, nanoparticles have been developed for the purpose of delivering medications and autophagy modulators selectively and specifically to the cancer process. Furthermore, several categories of nanoparticles have demonstrated the ability to regulate autophagy, which plays a crucial role in defining the biological characteristics and response to therapy of tumor cells.

The quality evaluation of 30 Asparagus officinalis L. varieties.

Asparagus, a vital economic contributor, is a well-liked vegetable grown around the globe, and some secondary metabolites in its spear are beneficial to human health. Asparagus spears possess a significant quantity of nutrients and phytochemicals; however, the difference in these chemical compositions among various varieties has not been sufficiently studied. This work aimed to detect the chemical compositions of 30 varieties of asparagus and to assess them by principal component analysis (PCA). The results showed that the contents of these chemical compositions varied in varieties. Selenium (Se, 1.12-2.9 µg/100 g dry-weight [DW]) was abundant in asparagus, with an average dry matter content of 8.25%. Free amino acids (5.60-9.98 g/100 g DW) and polyphenols (6.34-8.67 mg/g DW) were both present in high amounts, along with flavonoids (4.218-8.22 mg/g DW) and protodioscin (0.44-1.96 mg/g DW). Correlation analysis, PCA, and hierarchical cluster analysis were used to conduct a comprehensive evaluation of asparagus. Atlas, Appolo, Jinggang 111, Jingke 2, and WS-1 were the top five varieties with comprehensive scores. This study provided valuable data for the breeding, quality improvement, processing, and utilization of asparagus varieties in the future.

Investigating the effects of Laggera pterodonta on H3N2-Induced inflammatory and immune responses through network pharmacology, molecular docking, and experimental validation in a mice model.

For centuries, Laggera pterodonta (LP), a Chinese herbal medicine, has been widely employed for treating respiratory infectious diseases; however, the mechanism underlying LP's effectiveness against the influenza A/Aichi/2/1968 virus (H3N2) remains elusive. This study aims to shed light on the mechanism by which LP combats influenza in H3N2-infected mice. First, we conducted quasi-targeted metabolomics analysis using liquid chromatography-mass spectrometry to identify LP components. Subsequently, network pharmacology, molecular docking, and simulation were conducted to screen candidate targets associated with AKT and NF-κB. In addition, we conducted a series of experiments including qPCR, hematoxylin-eosin staining, flow cytometry, immunohistochemistry, and enzyme-linked immunosorbent assay to provide evidence that LP treatment in H3N2-infected mice can reduce pro-inflammatory cytokine levels (TNF-α, IL-6, IL-1ß, and MCP-1) while increasing T cells (CD3+, CD4+, and CD8+) and syndecan-1 and secretory IgA expression. This, in turn, aids in the prevention of excessive inflammation and the fortification of immunity, both of which are compromised by H3N2. Finally, we utilized a Western blot assay to confirm that LP indeed inhibits the AKT/NF-κB signaling cascade. Thus, the efficacy of LP serves as a cornerstone in establishing a theoretical foundation for influenza treatment.

Monitoring Changes in Biochemical and Metabolite Profiles in Garlic Cloves during Storage.

Storage is important for the garlic cloves industry because it is critical to enabling a year-round supply. This study aimed to investigate the changes in biochemical and metabolic profiles in garlic cloves in terms of different temperatures and cultivars during storage using nontargeted and targeted metabolomics. The results showed that the storage temperatures and times were important factors affecting the composition and metabolite content of garlic cloves. In detail, the metabolic profiling of garlic cloves changed significantly at 22 °C, which was mainly related to sprouting. Furthermore, γ-glutamyl peptide was converted into the corresponding flavor precursors or free amino acids, leading to the fluctuation in the amount of nutrients in garlic cloves. In contrast, the quality of garlic cloves remained stable for 290 days at 0 °C though metabolism still occurred, which indicated that the slight chemical changes did not impact the quality significantly and low temperature could prolong their dormancy.

Silencing gram-negative bacteria binding protein 1 decreases the immunity of Tribolium castaneum against bacteria.

Gram-negative bacteria binding proteins (GNBPs) have the ability to recognize molecular patterns associated with microbial pathogens (PAMPs), leading to the activation of immune responses downstream. In the genome of Tribolium castaneum, three GNBP genes have been identified; however, their immunological roles remain unexplored. In our study, a GNBP1, designated as TcGNBP1, were identified from the cDNA library of T. castaneum. The coding sequence of TcGNBP1 consisted of 1137 bps and resulted in the synthesis of a protein comprising 378 amino acids. This protein encompasses a signal peptide, a low-complexity region, and a glycoside hydrolase 16 domain. TcGNBP1 was strongly expressed in early adult stages, and mainly distributed in hemolymph and gut. Upon being challenged with Escherichia coli or Staphylococcus aureus, the transcript levels of TcGNBP1 were significantly changed at different time points. Through molecular docking and ELISA analysis, it was observed that TcGNBP1 has the ability to interact with lipopolysaccharides, peptidoglycan, and ß-1, 3-glucan. Based on these findings, it was further discovered that recombinant TcGNBP1 can directly bind to five different bacteria in a Ca2+-dependent manner. After knockdown of TcGNBP1 with RNA interference, expression of antimicrobial peptide genes and prophenoloxidase (proPO) activity were suppressed, the susceptibility of T. castaneum to E. coli or S. aureus infection was enhanced, leading to low survival rate. These results suggest a regulatory mechanism of TcGNBP1 in innate immunity of T. castaneum and provide a potential molecular target for dsRNA-based insect pest management.

Utilizing network pharmacology and experimental validation to investigate the underlying mechanism of Denglao Qingguan decoction against HCoV-229E.

Background: Denglao Qingguan decoction (DLQGD) has been extensively utilized for the treatment of colds, demonstrating significant therapeutic efficacy. Human Coronavirus 229E (HCoV-229E) is considered a crucial etiological agent of influenza. However, the specific impact and underlying mechanisms of DLQGD on HCoV-229E remain poorly understood. Methods: Active ingredients and targets information of DLQGD were collected from Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), literature search, and Swiss ADEM database. The Genecard database was used to collect HCoV-229E related targets. We built an "ingredient-target network" through Cytoscape. Protein - Protein interaction (PPI) networks were mapped using the String database. The Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) were enriched using the DAVID database. Then, we used molecular docking techniques to verify the binding activity between the core compounds and the core gene targets. Finally, in vitro experiments were conducted to validate DLQGD's antiviral activity against HCoV-229E and assess its anti-inflammatory effects. Results: In total, we identified 227 active components in DLQGD. 18 key targets involved in its activity against HCoV-229E. Notably, the core active ingredients including quercetin, luteolin, kaempferol, ß-sitosterol, and apigenin, and the core therapeutic targets were CXCL8, RELA, MAPK14, NFKB1, and CXCL10, all associated with HCoV-229E. KEGG enrichment results included IL-17 signaling pathway, Toll-like receptor signaling pathway, RIG-I-like receptor signaling pathway and so on. The core active ingredients and the core therapeutic targets and Human Aminopeptidase N (ANPEP) all showed good binding activity by molecular docking verification. In vitro, DLQGD exhibited anti-HCoV-229E activity and anti-inflammatory effects. Conclusion: Our study suggests that DLQGD has both effects of anti-HCoV-229E and anti-inflammatory. The core active ingredients (quercetin, luteolin, kaempferol, ß-sitosterol, apigenin) and the core therapeutic targets (CXCL8, RELA, MAPK14, NFKB1, CXCL10) may play key roles in the pharmacological action of DLQGD against HCoV-229E.

Taurohyocholic acid acts as a potential predictor of the efficacy of tyrosine kinase inhibitors combined with programmed cell death-1 inhibitors in hepatocellular carcinoma.

Background and aims: Tyrosine kinase inhibitors (TKIs) combined with programmed cell death protein-1 (PD-1) have significantly improved survival in patients with unresectable hepatocellular carcinoma (uHCC), but effective biomarkers to predict treatment efficacy are lacking. Peripheral blood bile acids (BAs) are associated with tumor response to therapy, but their roles in HCC remain unclear. Methods: This retrospective study included HCC patients who received first-line TKIs combined with PD-1 inhibitors treatment (combination therapy) in our clinical center from November 2020 to June 2022. The aim of this study was to analyze the changes in plasma BA profiles before and after treatment in both the responding group (Res group) and the non-responding group (Non-Res group). We aimed to explore the potential role of BAs in predicting the response to combination therapy in HCC patients. Results: Fifty-six patients with HCC who underwent combination therapy were included in this study, with 28 designated as responders (Res group) and 28 as non-responders (Non-Res group). There were differences in plasma BA concentrations between the two groups before systemic therapy. Plasma taurohyocholic acid (THCA) levels in the Res group were significantly lower than those in the Non-Res group. Patients with low levels of THCA exhibited superior median progression-free survival (7.6 vs. 4.9 months, p = 0.027) and median overall survival (23.7 vs. 11.6 months, p = 0.006) compared to those of patients with high levels of THCA. Conclusion: Peripheral blood BA metabolism is significantly correlated with combination therapy response and survival in patients with HCC. Our findings emphasize the potential of plasma BAs as biomarkers for predicting combination therapy outcomes and offering novel therapeutic targets for modulating responses to systemic cancer therapy.

Remnant cholesterol traits and risk of stroke: A multivariable Mendelian randomization study.

Observational epidemiological studies have reported a relationship between remnant cholesterol and stroke. However, the results are inconclusive, and causality remains unclear due to confounding or reverse causality. Our objective in this study was to investigate the causal relevance of remnant cholesterol and the risk of stroke and its subtypes using the Mendelian randomization (MR) approach. Genome-wide association studies (GWASs) including 115,082 European individuals (UK Biobank) were used to identify instruments for remnant cholesterol, including intermediate-density lipoprotein (IDL) cholesterol and very-low-density lipoprotein (VLDL) cholesterol. Summary-level data for total stroke, intracerebral hemorrhage, subarachnoid hemorrhage, ischemic stroke (IS), and IS subtypes were obtained from GWAS meta-analyses conducted by the MEGASTROKE consortium. Univariable and multivariable MR analyses were performed. The GWAS identified multiple single-nucleotide polymorphisms after clumping for remnant cholesterol (n = 52), IDL cholesterol (n = 62), and VLDL cholesterol (n = 67). Assessed individually using MR, remnant cholesterol (weighted median: odds ratio [OR] 1.32 per 1-SD higher trait; 95% CI: 1.04-1.67; P = 0.024) had effect estimates consistent with a higher risk of LAS-IS, driven by IDL cholesterol (OR 1.32; 95% CI: 1.04-1.68; P = 0.022). In multivariable MR, IDL cholesterol (OR 1.46; 95% CI: 1.10-1.93; P = 0.009) retained a robust effect on LAS-IS after controlling for VLDL cholesterol and high-density lipoprotein cholesterol. The MR analysis did not indicate causal associations between remnant cholesterol and other stroke subtypes. This study suggests that remnant cholesterol is causally associated with the risk of LAS-IS driven by IDL cholesterol.

Preparation of Yeast Extract from Brewer's Yeast Waste and Its Potential Application as a Medium Constituent.

Yeast extract serves as a source of nutritional components essential for human dietary requirements, feed formulations, and the vital growth factors and nutrients necessary for microorganisms. However, the production cost of yeast extract using cultivated active dry yeast is relatively high. This study aims to utilize the autolysis of discarded yeast post beer brewing to produce yeast extract. The concentration, temperature, pH, and time conditions are systematically optimized. It reveals that the yield of amino nitrogen and solids in the extract was increased by 3.3% and 20.9% under the optimized conditions (1.2% wall-breaking enzyme, 1% yeast extract enzyme, and a hydrolysis time of 24 h) than that of the documented 4.03% and 69.05%. Additionally, a comparative analysis with commercially available yeast powder demonstrates that the yeast extract derived from this study adequately fulfills the nutritional requirements for microbial growth. Hence, the utilization of discarded beer yeast presents an opportunity for the valuable reclamation of waste yeast, showcasing promising potential applications.

Polyp segmentation with interference filtering and dynamic uncertainty mining.

Objective.Accurate polyp segmentation from colo-noscopy images plays a crucial role in the early diagnosis and treatment of colorectal cancer. However, existing polyp segmentation methods are inevitably affected by various image noises, such as reflections, motion blur, and feces, which significantly affect the performance and generalization of the model. In addition, coupled with ambiguous boundaries between polyps and surrounding tissue, i.e. small inter-class differences, accurate polyp segmentation remains a challenging problem.Approach.To address these issues, we propose a novel two-stage polyp segmentation method that leverages a preprocessing sub-network (Pre-Net) and a dynamic uncertainty mining network (DUMNet) to improve the accuracy of polyp segmentation. Pre-Net identifies and filters out interference regions before feeding the colonoscopy images to the polyp segmentation network DUMNet. Considering the confusing polyp boundaries, DUMNet employs the uncertainty mining module (UMM) to dynamically focus on foreground, background, and uncertain regions based on different pixel confidences. UMM helps to mine and enhance more detailed context, leading to coarse-to-fine polyp segmentation and precise localization of polyp regions.Main results.We conduct experiments on five popular polyp segmentation benchmarks: ETIS, CVC-ClinicDB, CVC-ColonDB, EndoScene, and Kvasir. Our method achieves state-of-the-art performance. Furthermore, the proposed Pre-Net has strong portability and can improve the accuracy of existing polyp segmentation models.Significance.The proposed method improves polyp segmentation performance by eliminating interference and mining uncertain regions. This aids doctors in making precise and reduces the risk of colorectal cancer. Our code will be released athttps://github.com/zyh5119232/DUMNet.

Upgrading Passenger Vehicle Emission Standard Helps to Reduce China's Air Pollution Risk from Uncertainty in Electrification.

Upgrading to the CHINA 7 standard is crucial for managing air pollution from passenger vehicles in China. Meanwhile, China aims to achieve carbon neutrality by 2060, which necessitates large-scale replacement of gasoline vehicles with electric vehicles in the future. Consequently, the public might view upgrading gasoline vehicles to the CHINA 7 standard as redundant. However, the emission reduction benefits of upgrading standards in the context of uncertain electrification ambitions have not received adequate attention. Here, we show that upgrading standards will compensate for the absence of emissions reductions due to hindered electrification efforts. In the best scenario, China's CO2 emissions can be reduced to 0.047 Gt and NOx to 8.2 × 103 t in 2050. In nonextreme electrification scenarios with CHINA 7 standard, the emission intensity reduction will remain the main driver for emission reductions, outweighing the electrification contribution. In extreme electrification scenarios, upgrading standards will tackle the increased emissions from plug-in hybrid electric vehicles. Our fleet-level results advocate for early standards upgrades to enhance resilience against air pollution risks arising from uncertainties in electrification. Our evidence from China, with one of the most stringent emission standards, can provide a reference point for the world on the upgrading passenger vehicle emission standard issue.

Bladder Cancer: Immunotherapy and Pelvic Lymph Node Dissection.

Bladder cancer, a common malignancy of the urinary system, is routinely treated with radiation, chemotherapy, and surgical excision. However, these strategies have inherent limitations and may also result in various side effects. Immunotherapy has garnered considerable attention in recent years as a novel therapeutic approach. It harnesses and activates the patient's immune system to recognize and eliminate cancer cells, which not only prolongs therapeutic efficacy but also minimizes the toxic side effects. Several immune checkpoint inhibitors and cancer vaccines have been developed for the treatment of bladder cancer. Whereas blocking immune checkpoints on the surface of tumor cells augments the effect of immune cells, immunization with tumor-specific antigens can elicit the production of anti-tumor immune effector cells. However, there are several challenges in applying immunotherapy against bladder cancer. For instance, the efficacy of immunotherapy varies considerably across individual patients, and only a small percentage of cancer patients are responsive. Therefore, it is crucial to identify biomarkers that can predict the efficacy of immunotherapy. Pelvic lymph nodes are routinely dissected from bladder cancer patients during surgical intervention in order to remove any metastatic tumor cells. However, some studies indicate that pelvic lymph node dissection may reduce the efficacy of immunotherapy by damaging the immune cells. Therefore, the decision to undertake pelvic lymph node removal should be incumbent on the clinical characteristics of individual patients. Thus, although immunotherapy has the advantages of lower toxic side effects and long-lasting efficacy, its application in bladder cancer still faces challenges, such as the lack of predictive biomarkers and the effects of pelvic lymph node dissection. Further research is needed to explore these issues in order to improve the efficacy of immunotherapy for bladder cancer.

A Novel, Controllable, and Efficient Method for Building Highly Hydrophobic Aerogels.

Aerogels prepared using freeze-drying methods have the potential to be insulation materials or absorbents in the fields of industry, architecture, agriculture, etc., for their low heat conductivity, high specific area, low density, degradability, and low cost. However, their native, poor water resistance caused by the hydrophilicity of their polymer matrix limits their practical application. In this work, a novel, controllable, and efficient templating method was utilized to construct a highly hydrophobic surface for freeze-drying aerogels. The influence of templates on the macroscopic morphology and hydrophobic properties of materials was investigated in detail. This method provided the economical and rapid preparation of a water-resistant aerogel made from polyvinyl alcohol (PVA) and montmorillonite (MMT), putting forward a new direction for the research and development of new, environmentally friendly materials.

Edaravone dexborneol alleviates ischemic injury and neuroinflammation by modulating microglial and astrocyte polarization while inhibiting leukocyte infiltration.

Poststroke inflammation is essential in the mechanism of secondary injury, and it is orchestrated by resident microglia, astrocytes, and circulating immune cells. Edaravone dexborneol (EDB) is a combination of edaravone and borneol that has been identified as a clinical protectant for stroke management. In this study, we verified the anti-inflammatory effect of EDB in the mouse model of ischemia and investigated its modulatory action on inflammation-related cells. C57BL/6 male mice, which had the transient middle cerebral artery occlusion (tMCAO), were treated (i.p.) with EDB (15 mg/kg). EDB administration significantly reduced the brain infarction and improved the sensorimotor function after stroke. And EDB alleviated the neuroinflammation by restraining the polarization of microglia/macrophages and astrocyte toward proinflammatory phenotype and inhibiting the production of proinflammatory cytokines (such as IL-1ß, TNF-α, and IL-6) and chemokines (including MCP-1 and CXCL1). Furthermore, EDB ameliorated the MCAO-induced impairment of Blood-brain barrier (BBB) by suppressing the degradation of tight junction protein and attenuated the accumulation of peripheral leukocytes in the ischemic brain. Additionally, systemic EDB administration inhibited the macrophage phenotypic shift toward the M1 phenotype and the macrophage-dependent inflammatory response in the spleen and blood. Collectively, EDB protects against ischemic stroke injury by inhibiting the proinflammatory activation of microglia/macrophages and astrocytes and through reduction by invasion of circulating immune cells, which reduces central and peripheral inflammation following stroke.

Role of the In-Situ-Formed Surface (Pt-S-O)-Ti Active Structure in SO2-Promoted C3H8 Combustion over a Pt/TiO2 Catalyst.

Typically, SO2 unavoidably deactivates catalysts in most heterogeneous catalytic oxidations. However, for Pt-based catalysts, SO2 exhibits an extraordinary boosting effect in propane catalytic oxidation, but the promotive mechanism remains contentious. In this study, an in situ-formed tactful (Pt-S-O)-Ti structure was concluded to be a key factor for Pt/TiO2 catalysts with a substantial SO2 tolerance ability. The experiments and theoretical calculations confirm that the high degree of hybridization and orbital coupling between Pt 5d and S 3p orbitals enable more charge transfer from Pt to S species, thus forming the (Pt-S-O)-Ti structure with the oxygen atom dissociated from the chemisorbed O2 adsorbed on oxygen vacancies. The active oxygen atom in the (Pt-S-O)-Ti active structure is a robust site for C3H8 adsorption, leading to a better C3H8 combustion performance. This work can provide insights into the rational design of chemical bonds for high SO2 tolerance catalysts, thereby improving economic and environmental benefits.