Co-expression of immune checkpoints in glioblastoma revealed by single-nucleus RNA sequencing and spatial transcriptomics.

Glioblastoma (GBM) is one of the most malignant tumors of the central nervous system. The pattern of immune checkpoint expression in GBM remains largely unknown. We performed snRNA-Seq and spatial transcriptomic (ST) analyses on untreated GBM samples. 8 major cell types were found in both tumor and adjacent normal tissues, with variations in infiltration grade. Neoplastic cells_6 was identified in malignant cells with high expression of invasion and proliferator-related genes, and analyzed its interactions with microglia, MDM cells and T cells. Significant alterations in ligand-receptor interactions were observed, particularly between Neoplastic cells_6 and microglia, and found prominent expression of VISTA/VSIG3, suggesting a potential mechanism for evading immune system attacks. High expression of TIM-3, VISTA, PSGL-1 and VSIG-3 with similar expression patterns in GBM, may have potential as therapeutic targets. The prognostic value of VISTA expression was cross-validated in 180 glioma patients, and it was observed that patients with high VISTA expression had a poorer prognosis. In addition, multimodal cross analysis integrated SnRNA-seq and ST, revealing complex intracellular communication and mapping the GBM tumor microenvironment. This study reveals novel molecular characteristics of GBM, co-expression of immune checkpoints, and potential therapeutic targets, contributing to improving the understanding and treatment of GBM.

DECIDE: A decoupled semantic and boundary learning network for precise osteosarcoma segmentation by integrating multi-modality MRI.

Automated Osteosarcoma Segmentation in Multi-modality MRI (AOSMM) holds clinical significance for effective tumor evaluation and treatment planning. However, the precision of AOSMM is challenged by the diverse characteristics of multi-modality MRI and the inherent heterogeneity and boundary ambiguity of osteosarcoma. While numerous methods have made significant strides in automated osteosarcoma segmentation, they primarily focused on the use of a single MRI modality and overlooked the potential benefits of integrating complementary information from other MRI modalities. Furthermore, they did not adequately model the long-range dependencies of complex tumor features, which may lead to insufficiently discriminative feature representations. To this end, we propose a decoupled semantic and boundary learning network (DECIDE) to achieve precise AOSMM with three functional modules. The Multi-modality Feature Fusion and Recalibration (MFR) module adaptively fuses and recalibrates multi-modality features by exploiting their channel-wise dependencies to compute low-rank attention weights for effectively aggregating useful information from different MRI modalities, which promotes complementary learning between multi-modality MRI and enables a more comprehensive tumor characterization. The Lesion Attention Enhancement (LAE) module employs spatial and channel attention mechanisms to capture global contextual dependencies over local features, significantly enhancing the discriminability and representational capacity of intricate tumor features. The Boundary Context Aggregation (BCA) module further enhances semantic representations by utilizing boundary information for effective context aggregation while also ensuring intra-class consistency in cases of boundary ambiguity. Substantial experiments demonstrate that DECIDE achieves exceptional performance in osteosarcoma segmentation, surpassing state-of-the-art methods in terms of accuracy and stability.

Repositioning baloxavir marboxil as VISTA agonist that ameliorates experimental asthma.

V-type immunoglobulin domain-containing suppressor of T-cell activation (VISTA), a novel negative checkpoint regulator, plays an essential role in allergic pulmonary inflammation in mice. Treatment with a VISTA agonistic antibody could significantly improve asthma symptoms. Thus, for allergic asthma treatment, VISTA targeting may be a compelling approach. In this study, we examined the functional mechanism of VISTA in allergic pulmonary inflammation and screened the FDA-approved drugs for VISTA agonists. By using mass cytometry (CyTOF), we found that VISTA deficiency primarily increased lung macrophage infiltration in the OVA-induced asthma model, accompanied by an increased proportion of M1 macrophages (CD11b+F4/80+CD86+) and a decreased proportion of M2 macrophages (CD11b+F4/80+CD206+). Further in vitro studies showed that VISTA deficiency promoted M1 polarization and inhibited M2 polarization of bone marrow-derived macrophages (BMDMs). Importantly, we discovered baloxavir marboxil (BXM) as a VISTA agonist by virtual screening of FDA-approved drugs. The surface plasmon resonance (SPR) assays revealed that BXM (KD = 1.07 µM) as well as its active form, baloxavir acid (BXA) (KD = 0.21 µM), could directly bind to VISTA with high affinity. Notably, treatment with BXM significantly ameliorated asthma symptoms, including less lung inflammation, mucus secretion, and the generation of Th2 cytokines (IL-5, IL-13, and IL-4), which were dramatically attenuated by anti-VISTA monoclonal antibody treatment. BXM administration also reduced the pulmonary infiltration of M1 macrophages and raised M2 macrophages. Collectively, our study indicates that VISTA regulates pulmonary inflammation in allergic asthma by regulating macrophage polarization and baloxavir marboxil, and an old drug might be a new treatment for allergic asthma through targeting VISTA.

How does full-cost insurance for wheat affect pesticide use? From the perspective of the differentiation of farmers' production scale.

Theoretically, agricultural insurance influences farmers' use of pesticides by changing the expected income of agricultural production. Full-cost insurance, with high guarantee and high compensation characteristics, may significantly affect farmers' pesticide use. First, this paper constructs a production function to characterize and compare the marginal incomes of insured and uninsured farmers under risk uncertainty and analyses how insured farmers can increase marginal income by increasing or reducing factor inputs. Considering scale differentiation, it discusses pesticide use strategies different types of farmers may adopt to maximize household utility. Second, using survey data of the pilot counties of full-cost insurance for wheat in Henan Province, China, the simultaneous equation model is used for empirical testing. The results reveal the following: (i) Farmers' insurance participation and pesticide application behaviour are not mutually independent. (ii) For the whole sample, full-cost insurance for wheat has a significant pesticide reduction effect. (iii) However, considering scale differentiation, pesticide application decreases significantly among insured ordinary farmers but does not change significantly among insured large-scale farmers. Third, policy measures are proposed to activate the green development function of agricultural insurance.

Transcriptome profiling reveals transcriptional regulation of VISTA in T cell activation.

PURPOSE: V-domain immunoglobulin suppressor of T-cell activation (VISTA) is a novel type of immune checkpoint. This study was performed to explore the potential mechanism by which different domains of VISTA affect T-cell activation and search for potential interacting proteins. METHODS: Stably transfected Jurkat cell lines were constructed to overexpress human VISTA (VISTA-FL), cytoplasmic domain deletion mutants (VISTA-ΔECD) and extracellular domain deletion mutants (VISTA- ΔCD). Empty vector (EV) control cell lines were constructed. Four stable cell lines were subjected to transcriptome sequencing after stimulation with PMA and PHA. The differentially expressed genes (DEGs) were analysed to explore the potential pathway by which VISTA inhibits T-cell activation. Proteinprotein interaction (PPI) network analysis was used to search for potential interacting proteins of VISTA. RESULTS: In this study, 1256 DEGs were identified in Jurkat-VISTA-FL cells, 740 DEGs in Jurkat-VISTA-ΔCD cells, and 5605 DEGs in Jurkat-VISTA-ΔECD cells compared with Jurkat-EV cells. DEGs were mainly enriched in pathways related to T-cell differentiation, T-cell receptor signalling pathway and T-cell migration in Jurkat-VISTA-ΔECD cells; with cholesterol biosynthesis in Jurkat-VISTA-ΔCD cells; and with the inflammatory response in Jurkat-VISTA-FL cells. HHLA2 and CTH were identified as potential partners that interact directly with VISTA. The results also show an indirect interaction between VISTA and PSGL-1. CONCLUSIONS: This study revealed the pathways by which VISTA is involved in T-cell activation and identified the potential binding partners of VISTA through RNA-seq, providing valuable resources for developing in-depth studies of the action mechanisms of VISTA as a potential target for cancer and inflammatory diseases.

The Effect of N6-Methyladenosine Regulators and m6A Reader YTHDC1-Mediated N6-Methyladenosine Modification Is Involved in Oxidative Stress in Human Aortic Dissection.

Aortic dissection (AD) develops pathological changes in the separation of the true and false aortic lumen, with high lethality. m6A methylation and oxidative stress have also been shown to be involved in the onset of AD. Through bioinformatics methods, three differentially expressed m6A regulators (YTHDC1, YTHDC2, and RBM15) were excavated from the GSE52093 dataset in the Gene Expression Omnibus (GEO) database, and functional enrichment analysis of the differentially expressed genes (DEGs) regulated by m6A regulators was performed. Then, the genes with oxidative stress-related functions among these genes were found. The protein interaction network of the oxidative stress-related genes and the competing endogenous RNA- (ceRNA-) miRNA-mRNA network were constructed. Among them, DHCR24, P4HB, and PDGFRA, which have m6A differences in AD samples, were selected as key genes. We also performed immune infiltration analysis, as well as cell-gene correlation analysis, on samples from the dataset. The results showed that YTHDC1 was positively correlated with macrophage M1 and negatively correlated with macrophage M2. Finally, we extracted AD and healthy aorta RNA and protein from human tissues that were taken from AD patients and patients who received heart transplants, performed quantitative real-time PCR (qRT-PCR) on YTHDC2 and RBM15, and performed qRT-PCR and western blot (WB) detection on YTHDC1 to verify their differences in AD. The mRNA and protein levels of YTHDC1 were consistent with the results of bioinformatics analysis and were downregulated in AD. Immunofluorescence (IF) was used to colocalize YTHDC1 and endothelial cell marker CD31. After knocking down YTHDC1 in human umbilical vein endothelial cells (HUVECs), reactive oxygen species (ROS) levels had a tendency to increase and the expression of peroxide dismutase SOD2 was decreased. This study provides assistance in discovering the role of m6A regulator YTHDC1 in AD. In particular, m6A modification participates in oxidative stress and jointly affects AD.

Single-Cell RNA Sequencing Reveals the Immune Cell Profiling in IMQ Induced Psoriasis-Like Model.

Purpose: Psoriasis is a chronic systemic inflammatory skin disease with a high recurrence rate. The immune response plays an important role in psoriasis. However, the subsets of immune cells involved in inflammation in psoriatic mice have not been fully studied. This study showed the immune environment characteristics of psoriasis in mice. Methods: We used single-cell RNA sequencing (10× Genomics) as an unbiased analytical strategy to investigate the heterogeneity of skin immune cells in imiquimod-induced psoriasis mice systematically. Results: We identified 10 major clusters and their marker genes among 14,439 cells. The proportions of macrophages, NK/T cells, conventional dendritic cells (cDCs) and plasmacytoid dendritic cells (pDCs) were increased in psoriatic mice. Macrophages were the largest group and were further divided into 7 subgroups, and all macrophage clusters were increased in psoriatic mice. Differentially expressed genes in control versus psoriatic mice skin lesions showed that Fcgr4, Saa3 and Acp5 in macrophages, Acp5, Fcgr4 and Ms4a6d in NK/T cells, Saa3 in cDCs, and Ifitm1 in pDCs were upregulated in psoriasis mice. Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathway enrichment analysis emphasized the role of oxidative phosphorylation signals and antigen processing and presentation signals in murine psoriasis-like models. Conclusion: Our study reveals the immune environment characteristics of the commonly used IMQ induced psoriasis-like models and provides a systematic insight into the immune response of mice with psoriasis, which is conducive to comparing the similarities and differences between the mouse model and human psoriasis.

Skin Cancer Classification With Deep Learning: A Systematic Review.

Skin cancer is one of the most dangerous diseases in the world. Correctly classifying skin lesions at an early stage could aid clinical decision-making by providing an accurate disease diagnosis, potentially increasing the chances of cure before cancer spreads. However, achieving automatic skin cancer classification is difficult because the majority of skin disease images used for training are imbalanced and in short supply; meanwhile, the model's cross-domain adaptability and robustness are also critical challenges. Recently, many deep learning-based methods have been widely used in skin cancer classification to solve the above issues and achieve satisfactory results. Nonetheless, reviews that include the abovementioned frontier problems in skin cancer classification are still scarce. Therefore, in this article, we provide a comprehensive overview of the latest deep learning-based algorithms for skin cancer classification. We begin with an overview of three types of dermatological images, followed by a list of publicly available datasets relating to skin cancers. After that, we review the successful applications of typical convolutional neural networks for skin cancer classification. As a highlight of this paper, we next summarize several frontier problems, including data imbalance, data limitation, domain adaptation, model robustness, and model efficiency, followed by corresponding solutions in the skin cancer classification task. Finally, by summarizing different deep learning-based methods to solve the frontier challenges in skin cancer classification, we can conclude that the general development direction of these approaches is structured, lightweight, and multimodal. Besides, for readers' convenience, we have summarized our findings in figures and tables. Considering the growing popularity of deep learning, there are still many issues to overcome as well as chances to pursue in the future.

The Impact of Environmental Regulation on the Location of Pollution-Intensive Industries in China under Agglomeration Effect.

Pollution-intensive industries (PIIs) have both scale effect and environmental sensitivity. Therefore, this paper studies how environmental regulation (ER) affects the location dynamics of PIIs under the agglomeration effect. Our results show that, ER can increase the production costs of pollution-intensive firms (PIFs) by internalizing the negative impact of pollutant discharge in a region, and thus, directly reduces the region's attractiveness to PIFs. Meanwhile, ER can indirectly reduce the attractiveness of a region to PIFs by reducing the externality of the regional agglomeration effect. Moreover, these influences are regulated by the level of local economic development. Based on the moderated mediating effect model, we find evidence from the site selection activities of newly built chemical firms in cities across China. The empirical test shows that compared with 2014, the proportion of the direct effect of ER to the total effects significantly decreased in 2018, while the proportion of indirect effects under the agglomeration effect increased significantly. Our findings provide reference for the government to design effective environmental policies to guide the location choice of new PIFs.

How Does Environmental Regulation Affect the Location of New Polluting Firms? Exploring the Agglomeration Threshold of Effective Environmental Regulation.

Some scholars have already proved the important role of agglomeration in studying how environmental regulation (ER) affects the location of polluting firms. However, further research is needed on both the mechanism and the empirical evidence. This paper reports the construction of a location database of new chemical plants in China's Yangtze River Economic Belt (YREB), where a fixed-effects panel threshold regression model was used to explore the agglomeration threshold of effective ER. We found a single agglomeration threshold for the whole YREB region that represented the turning point of ER from excluding to attracting new chemical enterprises. Additionally, there were two agglomeration thresholds in the lower reaches. If agglomeration reached the lower threshold, the effect of ER changed from repulsion to nonsignificant attraction. Once above the upper threshold, the attraction effect became large and significant. The results for this region were consistent with the Porter hypothesis. Furthermore, there was a single agglomeration threshold in the middle reaches. When agglomeration level exceeded the threshold, the repellant effect of ER was no longer significant. In the upper reaches, we found no valid threshold and ER always exhibited a small and nonsignificant exclusion effect. The pollution haven hypothesis was more explanatory in the middle and upper reaches. In the end, some suggestions are provided to support the government to formulate differentiated environmental policies.

Benzyl alcohol suppresses seizures in two different animal models.

Introduction: We have been exploring the effects of dihydroprogesterone in female amygdala-kindled rats. For intraperitoneal (i.p.) time-response studies, we used a vehicle containing the common solvent, benzyl alcohol (BnOH). The vehicle containing BnOH was also tested alone as a control. Method and Results: Unexpectedly, it was found that the vehicle containing BnOH had clear-cut anti-seizure effects in the kindling model, with an ED50 of 100 mg/kg. In a follow-up study, dose- and time-response studies of i.p. BnOH were done in male mice in the maximal pentylenetetrazol (PTZ) model. BnOH suppressed PTZ seizures in a dose-dependent manner, with an ED50 of 300 mg/kg against hindlimb tonic extension. Effects were fully established at 5-min post injection and lasted for an hour. Conclusion: BnOH is not an inert solvent. It has clear-cut anti-seizure effects against both focal and generalized seizures.

Progesterone, 5a-dihydropogesterone and allopregnanolone's effects on seizures: A review of animal and clinical studies.

The anti-seizure effects of progesterone family compounds have long been known. Over the years, however, most studies have focused on progesterone and on its secondary metabolite allopregnanolone (ALLO), with less attention being paid to its primary metabolite 5a-dihydroprogesterone (DHP). Here we review animal and clinical studies related to the anti-seizure effects of progesterone and its 5a neuroactive metabolites, including DHP and ALLO. Progesterone and its reduced metabolites all have demonstrated seizure-suppression effects in animal models - except in models of absence seizures - with the common side effects of sedation and ataxia. Progesterone and ALLO have also shown anti-seizure effects in clinical trials. A large Phase III trial has revealed that female patients with premenstrual exacerbations of seizures benefit most from progesterone therapy. A liquid suspension of ALLO has also been tested in patients with supra-refractory status epilepticus with some success in a small phase II trial. ALLO's C3 methyl analog ganaxolone is under development as an anti-seizure drug. Progesterone's anti-seizure effects are mostly independent of its genomic receptors and are, in large part, due to its active metabolites. ALLO is a potent allosteric modulator of GABA receptors. Other membrane receptors are thought to be involved in the DHP's anti-seizure actions, but their exact nature is not yet known. Potential drawbacks to the development of progesterone family compounds as anti-seizure drug are their endocrine effects. These compounds might form a basis for the future development of novel anti-seizure drugs, however, with hormonal side effects being mitigated through rational drug design.

The anti-seizure effects of IV 5α-dihydroprogesterone on amygdala-kindled seizures in rats.

OBJECTIVE: The present study investigated the anti-seizure effects of 5α-dihydroprogesterone (DHP) in an animal model of human drug-resistant focal seizures with impaired awareness. DHP was administered via the intravenous (IV) route. METHODS: Female Wistar rats were implanted with an electrode in the right basolateral amygdala. They were then kindled to 15 stage 5 seizures, stability tested, and cannulated in the jugular vein. Multiple doses of IV DHP were tested against focal electrographic seizures and secondarily generalized convulsions. The time-course of DHP's action was also examined. RESULTS: The dose-response study, done at 5 min after injection, showed a dose-dependent suppression of both generalized and focal seizures, with an ED50 of 1.69 mg/kg for the generalized convulsive seizures and an ED50 of 3.48 mg/kg for the focal electrographic seizures. Ataxia, as rated by the Löscher ataxia scale, was also seen, with a TD50 of 3.57 mg/kg. The time-response study, done at the ED75 for focal seizure suppression, showed suppression of both generalized and focal seizures from immediately after injection to about 60 min post-injection. SIGNIFICANCE: DHP has demonstrated anti-seizure effects in a drug-resistant model of human focal seizures with impaired awareness. Its analogs might be developed as new anti-seizure drugs.

T7 Peptide-Functionalized PEG-PLGA Micelles Loaded with Carmustine for Targeting Therapy of Glioma.

Glioma is regarded as the deadliest and most common brain tumor because of the extremely difficult surgical excision ascribed from its invasive nature. In addition, the natural blood-brain barrier (BBB) greatly restricts the therapeutics' penetration into the central nervous system. Carmustine (BCNU) is a widely used antiglioma drug in clinical applications. However, its serious complications prevent it from being applied in a clinical setting to some extent. Thus, it is urgent to explore novel BCNU delivery systems specially designed for glioma. Development of polymeric nanoparticles offers a favorable alternative to serve this purpose. Particularly, use of poly(lactic-co-glycolic acid) (PLGA) has been shown to be advantageous for its favorable biodegradability and biocompatibility, which ensure safe therapies. In this study, T7 peptide-conjugated, BCNU-loaded micelles were constructed successfully via the emulsion-solvent evaporation method. The micelles were characterized by transmission electron microscopy and dynamic light scattering in detail, and the capacity of BBB crossing was studied. The in vivo detecting results of the targeting effect using the BODIPY probe evidenced that T7-modified micelles showed a more pronounced accumulation and accumulated in the tumor more efficiently than in the unconjugated probe. Meanwhile, the targeting group exhibited the best curative effect accompanied with the lowest loss in body weight, the smallest tumor size, and an obviously prolonged survival time among the groups. In the near future, we believe the targeted delivery system specially designed for BCNU is expected to provide sufficient evidence to proceed to clinical trials.

Dual Functional Peptide-Driven Nanoparticles for Highly Efficient Glioma-Targeting and Drug Codelivery.

Compared with peripheral tumors, glioma is very difficult to treat, not only because it has general features of tumor but also because the therapy has been restricted by the brain-blood barrier (BBB). The two main features of tumor growth are angiogenesis and proliferation of tumor cells. RNA interference (RNAi) can downregulate VEGF overexpression to inhibit tumor neovascularization. Meanwhile, doxorubicin (DOX) has been used for cytotoxic chemotherapy to kill tumor cells. Thus, combining RNAi and chemotherapy has been regarded as a potential strategy for cancer treatment. However, the BBB limits the shVEGF-DOX codelivery system to direct into glioma. Here, a smart drug delivery system modified with a dual functional peptide was established, which could target to transferrin receptor (TfR) overexpressing on both the BBB and glioma. It showed that the dual-targeting delivery system had high tumor targeting efficiency in vitro and in vivo.

The effect of free-standing GaN substrate on carrier localization in ultraviolet InGaN light-emitting diodes.

In this study, we have grown 380-nm ultraviolet light-emitting diodes (UV-LEDs) based on InGaN/AlInGaN multiple quantum well (MQW) structures on free-standing GaN (FS-GaN) substrate by atmospheric pressure metal-organic chemical vapor deposition (AP-MOCVD), and investigated the relationship between carrier localization degree and FS-GaN. The micro-Raman shift peak mapping image shows low standard deviation (STD), indicating that the UV-LED epi-wafer of low curvature and MQWs of weak quantum-confined Stark effect (QCSE) were grown. High-resolution X-ray diffraction (HRXRD) analyses demonstrated high-order satellite peaks and clear fringes between them for the UV-LEDs grown on the FS-GaN substrate, from which the interface roughness (IRN) was estimated. The temperature-dependent photoluminescence (PL) measurement confirmed that the UV-LEDs grown on the FS-GaN substrate exhibited better carrier confinement. Besides, the high-resolution transmission electron microscopy (HRTEM) and energy-dispersive spectrometer (EDS) mapping images verified that the UV-LEDs on FS-GaN have fairly uniform distribution of indium and more ordered InGaN/AlInGaN MQW structure. Clearly, the FS-GaN can not only improve the light output power but also reduce the efficiency droop phenomenon at high injection current. Based on the results mentioned above, the FS-GaN can offer UV-LEDs based on InGaN/AlInGaN MQW structures with benefits, such as high crystal quality and small carrier localization degree, compared with the UV-LEDs on sapphire.

Universal behavior of localization of residue fluctuations in globular proteins.

Localization properties of residue fluctuations in globular proteins are studied theoretically by using a Gaussian network model. Participation ratio for each residue fluctuation mode is calculated. It is found that the relationship between participation ratio and frequency is similar for all globular proteins, indicating a universal behavior in spite of their different size, shape, and architecture.