Identifying an immunogenic cell death-related gene signature contributes to predicting prognosis, immunotherapy efficacy, and tumor microenvironment of lung adenocarcinoma.

BACKGROUND: Immunogenic cell death (ICD) is a regulated form of cell death that triggers an adaptive immune response. The objective of this study was to investigate the correlation between ICD-related genes (ICDGs) and the prognosis and the immune microenvironment of patients with lung adenocarcinoma (LUAD). METHODS: ICD-associated molecular subtypes were identified through consensus clustering. Subsequently, a prognostic risk model comprising 5 ICDGs was constructed using Lasso-Cox regression in the TCGA training cohort and further tested in the GEO cohort. Enriched pathways among the subtypes were analyzed using GO, KEGG, and GSVA. Furthermore, the immune microenvironment was assessed using ESTIMATE, CIBERSORT, and ssGSEA analyses. RESULTS: Consensus clustering divided LUAD patients into three ICDG subtypes with significant differences in prognosis and the immune microenvironment. A prognostic risk model was constructed based on 5 ICDGs and it was used to classify the patients into two risk groups; the high-risk group had poorer prognosis and an immunosuppressive microenvironment characterized by low immune score, low immune status, high abundance of immunosuppressive cells, and high expression of tumor purity. Cox regression, ROC curve analysis, and a nomogram indicated that the risk model was an independent prognostic factor. The five hub genes were verified by TCGA database, cell sublocalization immunofluorescence analysis, IHC images and qRT-PCR, which were consistent with bioinformatics analysis. CONCLUSIONS: The molecular subtypes and a risk model based on ICDGs proposed in our study are both promising prognostic classifications in LUAD, which may provide novel insights for developing accurate targeted cancer therapies.

Dopamine Sulfonate Ligand-Assisted TiO2 Deposition Enabling Highly Efficient and Stable Perovskite Solar Cells.

The metal oxide electron transport layers (ETLs) with flat morphology and high electrical quality are essential to manufacture highly efficient perovskite solar cells (PSCs), in which the regulation of the metal oxide deposition process plays a crucial role. Herein, a judiciously designed dopamine sulfonate (DS) ligand-assisted deposition of titanium dioxide (TiO2) films approach is implemented based on electrostatic repulsion and steric hindrance of assembled ligands to improve colloidal nanoparticles dispersity in precursor and effectively inhibit their aggregation, which could enable obtaining smooth topography of TiO2 films and initiating growth of top high-quality perovskite films. Furthermore, sulfonate bridges bonded on the perovskite buried layer that is beneficial to form better buried interface contact and accelerate electron extraction. As a result, the PSCs employing DS/TiO2 ETLs exhibit the best power conversion efficiency of 24.53% with impressive storage stability and operation stability, i.e., remaining more than 88% of their initial efficiency upon storage N2 glovebox without encapsulation over 4000 h, and the efficiency does not attenuate significantly under maximum power point for 60 h.

Exploring the relationship between Treg-mediated risk in COPD and lung cancer through Mendelian randomization analysis and scRNA-seq data integration.

BACKGROUND: Evidence from observational studies suggests an association between chronic obstructive pulmonary disease (COPD) and lung cancer. The potential interactions between the immune system and the lungs may play a causative role in COPD and lung cancer and offer therapeutic prospects. However, the causal association and the immune-mediated mechanisms between COPD and lung cancer remain to be determined. METHODS: We employed a two-sample Mendelian randomization (MR) approach to investigate the causal association between COPD and lung cancer. Additionally, we examined whether immune cell signals were causally related to lung cancer, as well as whether COPD was causally associated with immune cell signals. Furthermore, through two-step Mendelian randomization, we investigated the mediating effects of immune cell signals in the causal association between COPD and lung cancer. Leveraging publicly available genetic data, our analysis included 468,475 individuals of European ancestry with COPD, 492,803 individuals of European ancestry with lung cancer, and 731 immune cell signatures of European ancestry. Additionally, we conducted single-cell transcriptome sequencing analysis on COPD, lung cancer, and control samples to validate our findings. FINDINGS: We found a causal association between COPD and lung cancer (odds ratio [OR] = 1.63, 95% confidence interval [CI] = 1.31-2.02, P-value < 0.001). We also observed a causal association between COPD and regulatory T cells (odds ratio [OR] = 1.19, 95% confidence interval [CI] = 1.01-1.40, P-value < 0.05), as well as a causal association between regulatory T cells and lung cancer (odds ratio [OR] = 1.02, 95% confidence interval [CI] = 1.002-1.045, P-value < 0.05). Furthermore, our two-step Mendelian randomization analysis demonstrated that COPD is associated with lung cancer through the mediation of regulatory T cells. These findings were further validated through single-cell sequencing analysis, confirming the mediating role of regulatory T cells in the association between COPD and lung cancer. INTERPRETATION: As far as we are aware, we are the first to combine single-celled immune cell data with two-sample Mendelian randomization. Our analysis indicates a causal association between COPD and lung cancer, with regulatory T cells playing an intermediary role.

Comprehensive single-cell transcriptomic profiling reveals molecular subtypes and prognostic biomarkers with implications for targeted therapy in esophageal squamous cell carcinoma.

BACKGROUND: Esophageal squamous cell carcinoma (ESCC) is a genetically heterogeneous disease with poor clinical outcomes. Identification of biomarkers linked to DNA replication stress may enable improved prognostic risk stratification and guide therapeutic decision making. We performed integrated single-cell RNA sequencing and computational analyses to define the molecular determinants and subtypes underlying ESCC heterogeneity. METHODS: Single-cell RNA sequencing was performed on ESCC samples and analyzed using Seurat. Differential gene expression analysis was used to identify esophageal cell phenotypes. DNA replication stress-related genes were intersected with single-cell differential expression data to identify potential prognostic genes, which were used to generate a DNA replication stress (DRS) score. This score and associated genes were evaluated in survival analysis. Putative prognostic biomarkers were evaluated by Cox regression and consensus clustering. Mendelian randomization analyses assessed the causal role of PRKCB. RESULTS: High DRS score associated with poor survival. Four genes (CDKN2A, NUP155, PPP2R2A, PRKCB) displayed prognostic utility. Three molecular subtypes were identified with discrete survival and immune properties. A 12-gene signature displayed robust prognostic performance. PRKCB was overexpressed in ESCC, while PRKCB knockdown reduced ESCC cell migration. CONCLUSIONS: This integrated single-cell sequencing analysis provides new insights into the molecular heterogeneity and prognostic determinants underlying ESCC. The findings identify potential prognostic biomarkers and a gene expression signature that may enable improved patient risk stratification in ESCC. Experimental validation of the role of PRKCB substantiates the potential clinical utility of our results.

MoViT: Memorizing Vision Transformers for Medical Image Analysis.

The synergy of long-range dependencies from transformers and local representations of image content from convolutional neural networks (CNNs) has led to advanced architectures and increased performance for various medical image analysis tasks due to their complementary benefits. However, compared with CNNs, transformers require considerably more training data, due to a larger number of parameters and an absence of inductive bias. The need for increasingly large datasets continues to be problematic, particularly in the context of medical imaging, where both annotation efforts and data protection result in limited data availability. In this work, inspired by the human decision-making process of correlating new "evidence" with previously memorized "experience", we propose a Memorizing Vision Transformer (MoViT) to alleviate the need for large-scale datasets to successfully train and deploy transformer-based architectures. MoViT leverages an external memory structure to cache history attention snapshots during the training stage. To prevent overfitting, we incorporate an innovative memory update scheme, attention temporal moving average, to update the stored external memories with the historical moving average. For inference speedup, we design a prototypical attention learning method to distill the external memory into smaller representative subsets. We evaluate our method on a public histology image dataset and an in-house MRI dataset, demonstrating that MoViT applied to varied medical image analysis tasks, can outperform vanilla transformer models across varied data regimes, especially in cases where only a small amount of annotated data is available. More importantly, MoViT can reach a competitive performance of ViT with only 3.0% of the training data. In conclusion, MoViT provides a simple plug-in for transformer architectures which may contribute to reducing the training data needed to achieve acceptable models for a broad range of medical image analysis tasks.

Effects of male hepatitis B virus infection and serostatus on sperm quality, pregnancy outcomes, and neonatal outcomes following intrauterine insemination.

OBJECTIVE: To evaluate the impact of male hepatitis B virus (HBV) infection and serostatus on sperm quality, pregnancy outcomes, and neonatal outcomes following intrauterine insemination for infertility. DESIGN AND METHODS: We retrospectively analyzed data from 962 infertile couples undergoing intrauterine insemination treatment at a single center. The case group comprised 212 infertile couples with male HBV infection, and the control group comprised 750 noninfected infertile couples. The couples were further divided into subgroups according to their hepatitis B e antigen (HBeAg)/anti-HBe status: hepatitis B surface antigen (HBsAg)+HBeAg- (group A), HBsAg+HBeAg+ (group B), and HBsAg-HBeAg- (control group). The main outcome parameters, including the seminal parameters, clinical pregnancy rate, miscarriage rate, live birth rate, preterm delivery rate, multiple pregnancy rate, delivery type, birth weight, and sex ratio, were compared. RESULTS: A lower sperm acrosin activity, higher cesarean rate, and newborn sex ratio were observed in the HBV-infected group and group A in comparison with the control group (P < 0.05). However, the standard sperm parameters, clinical pregnancy rate, miscarriage rate, live birth rate, preterm delivery, and birth weight showed no statistically significant differences among the groups. CONCLUSION: Male HBV infection does not adversely impact standard sperm parameters or pregnancy outcomes but can influence sperm acrosin activity and some neonatal outcomes. Moreover, the effect may vary among different HBV serostatuses.

Cu(II)-Loaded Polydopamine-Coated Urchin-like Titanate Microspheres as a High-Performance IMAC Adsorbent for Hemoglobin Separation.

Immobilized metal ion affinity chromatography (IMAC) adsorbents generally have excellent affinity for histidine-rich proteins. However, the leaching of metal ions from the adsorbent usually affects its adsorption performance, which greatly affects the reusable performance of the adsorbent, resulting in many limitations in practical applications. Herein, a novel IMAC adsorbent, i.e., Cu(II)-loaded polydopamine-coated urchin-like titanate microspheres (Cu-PDA-UTMS), was prepared via metal coordination to make Cu ions uniformly decorate polydopamine-coated titanate microspheres. The as-synthesized microspheres exhibit an urchin-like structure, providing more binding sites for hemoglobin. Cu-PDA-UTMS exhibit favorable selectivity for hemoglobin adsorption and have a desirable adsorption capacity towards hemoglobin up to 2704.6 mg g-1. Using 0.1% CTAB as eluent, the adsorbed hemoglobin was easily eluted with a recovery rate of 86.8%. In addition, Cu-PDA-UTMS shows good reusability up to six cycles. In the end, the adsorption properties by Cu-PDA-UTMS towards hemoglobin from human blood samples were analyzed by SDS-PAGE. The results showed that Cu-PDA-UTMS are a high-performance IMAC adsorbent for hemoglobin separation, which provides a new method for the effective separation and purification of hemoglobin from complex biological samples.

Workshop AGV path planning based on improved A* algorithm.

This article proposes an improved A* algorithm aimed at improving the logistics path quality of automated guided vehicles (AGVs) in digital production workshops, solving the problems of excessive path turns and long transportation time. The traditional A* algorithm is improved internally and externally. In the internal improvement process, we propose an improved node search method within the A* algorithm to avoid generating invalid paths; offer a heuristic function which uses diagonal distance instead of traditional heuristic functions to reduce the number of turns in the path; and add turning weights in the A* algorithm formula, further reducing the number of turns in the path and reducing the number of node searches. In the process of external improvement, the output path of the internally improved A* algorithm is further optimized externally by the improved forward search optimization algorithm and the Bessel curve method, which reduces path length and turns and creates a path with fewer turns and a shorter distance. The experimental results demonstrate that the internally modified A* algorithm suggested in this research performs better when compared to six conventional path planning methods. Based on the internally improved A* algorithm path, the full improved A* algorithm reduces the turning angle by approximately 69% and shortens the path by approximately 10%; based on the simulation results, the improved A* algorithm in this paper can reduce the running time of AGV and improve the logistics efficiency in the workshop. Specifically, the walking time of AGV on the improved A* algorithm path is reduced by 12s compared to the traditional A* algorithm.

The GM-JMNS-CPHD Filtering Algorithm for Nonlinear Systems Based on a Generalized Covariance Intersection.

Some fusion criteria in multisensor and multitarget motion tracking cannot be directly applied to nonlinear motion models, as the fusion accuracy applied in nonlinear systems is relatively low. In response to the above issue, this study proposes a distributed Gaussian mixture cardinality jumping Markov-cardinalized probability hypothesis density (GM-JMNS-CPHD) filter based on a generalized inverse covariance intersection. The state estimation of the JMNS-CPHD filter combines the state evaluation of traditional CPHD filters with the state estimation of jump Markov systems, estimating the target state of multiple motion models without knowing the current motion models. The performances of the generalized covariance intersection (GCI)GCI-GM-JMNS-CPHD and generalized inverse covariance intersection (GICI)GICI-GM-JMNS-CPHD methods are evaluated via simulation results. The simulation results show that, compared with algorithms such as Sensor1, Sensor2, GCI-GM-CPHD, and GICI-GM-CPHD, this algorithm has smaller optimal subpattern assignment (OSPA) errors and a higher fusion accuracy.

Metabolic responses to the occurrence and chemotherapy of pancreatic cancer: biomarker identification and prognosis prediction.

As the most malignant tumor, the prognosis of pancreatic cancer is not ideal even in the small number of patients who can undergo radical surgery. As a highly heterogeneous tumor, chemotherapy resistance is a major factor leading to decreased efficacy and postoperative recurrence of pancreatic cancer. In this study, nuclear magnetic resonance (NMR)-based metabolomics was applied to identify serum metabolic characteristics of pancreatic ductal adenocarcinoma (PDAC) and screen the potential biomarkers for its diagnosis. Metabolic changes of patients with different CA19-9 levels during postoperative chemotherapy were also monitored and compared to identify the differential metabolites that may affect the efficacy of chemotherapy. Finally, 19 potential serum biomarkers were screened to serve the diagnosis of PDAC, and significant metabolic differences between the two CA19-9 stratifications of PDAC were involved in energy metabolism, lipid metabolism, amino acid metabolism, and citric acid metabolism. Enrichment analysis of metabolic pathways revealed six shared pathways by PDAC and chemotherapy such as alanine, aspartate and glutamate metabolism, arginine biosynthesis, glutamine and glutamate metabolism, citrate cycle, pyruvate metabolism, and glycogolysis/gluconeogeneis. The similarity between the metabolic characteristics of PDAC and the metabolic responses to chemotherapy provided a reference for clinical prediction of benefits of postoperative chemotherapy in PDAC patients.

Illuminating Shared Genetic Associations Between Oesophageal Carcinoma and Pulmonary Carcinoma Risk.

Background: Lung cancer and oesophageal cancer are prevalent malignancies with rising incidence and mortality worldwide. While some environmental and behavioural risk factors for these cancers are established, the contribution of genetic factors to their pathogenesis remains incompletely defined. This study aimed to interrogate the intricate genetic relationship between lung cancer and oesophageal cancer and their potential comorbidity. Methods: We utilised linkage disequilibrium score regression (LDSC) to analyse the genetic correlation between oesophageal carcinoma and lung carcinoma. We then employed several approaches, including pleiotropic analysis under the composite null hypothesis (PLACO), multi-marker analysis of genomic annotation (MAGMA), cis-expression quantitative trait loci (eQTL) analysis, and a pan-cancer assessment to identify pleiotropic loci and genes. Finally, we performed bidirectional Mendelian randomisation (MR) to evaluate the causal relationship between these malignancies. Results: LDSC revealed a significant genetic correlation between oesophageal carcinoma and lung carcinoma. Further analysis identified shared gene loci including PGBD1, ZNF323, and WNK1 using PLACO. MAGMA identified enriched pathways and 9 pleiotropic genes including HIST1H1B, HIST1H4L, and HIST1H2BL. eQTL analysis integrating oesophageal, lung, and blood tissues revealed 26 shared genes including TERT, NKAPL, RAD52, BTN3A2, GABBR1, CLPTM1L, and TRIM27. A pan-cancer exploration of the identified genes was undertaken. MR analysis showed no evidence for a bidirectional causal relationship between oesophageal carcinoma and lung carcinoma. Conclusions: This study provides salient insights into the intricate genetic links between lung carcinoma and oesophageal carcinoma. Utilising multiple approaches for genetic correlation, locus and gene analysis, and causal assessment, we identify shared genetic susceptibilities and regulatory mechanisms. These findings reveal new leads and targets to further elucidate the genetic basis of lung and oesophageal carcinoma, aiding development of preventive and therapeutic strategies.

Integrative analysis of single-cell and bulk RNA-sequencing data revealed disulfidptosis genes-based molecular subtypes and a prognostic signature in lung adenocarcinoma.

BACKGROUND: Disulfidoptosis is an unconventional form of programmed cell death that distinguishes itself from well-established cell death pathways like ferroptosis, pyroptosis, and necroptosis. METHODS: Initially, we conducted a single-cell analysis of the GSE131907 dataset from the GEO database to identify disulfidoptosis-related genes (DRGs). We utilized differentially expressed DRGs to classify TCGA samples with an unsupervised clustering algorithm. Prognostic models were built using Cox regression and LASSO regression. RESULTS: Two DRG-related clusters (C1 and C2) were identified based on the DEGs from single-cell sequencing data analysis. In comparison to C1, C2 exhibited significantly worse overall prognosis, along with lower expression levels of immune checkpoint genes (ICGs) and chemoradiotherapy sensitivity-related genes (CRSGs). Furthermore, C2 displayed a notable enrichment in metabolic pathways and cell cycle-associated mechanisms. C2 was also linked to the development and spread of tumors. We created a prognostic risk model known as the DRG score, which relies on the expression levels of five DRGs. Patients were categorized into high-risk and low-risk groups depending on their DRG score, with the former group being linked to a poorer prognosis and higher TMB score. Moreover, the DRG score displayed significant correlations with CRSGs, ICGs, the tumor immune dysfunction and exclusion (TIDE) score, and chemotherapeutic sensitivity. Subsequently, we identified a significant correlation between the DRG score and monocyte macrophages. Additionally, crucial DRGs were additionally validated using qRT-PCR. CONCLUSIONS: Our new DRG score can predict the immune landscape and prognosis of LUAD, serving as a reference for immunotherapy and chemotherapy.

Occurrence and Prognosis of Mixed Subtype Adenocarcinoma and Adeno-Squamous Carcinoma in Esophageal Cancer.

Purpose: To gain a deeper understanding of the incidence and survival rates of rare esophageal mixed adenoacanthoma (EAM) and esophageal mixed adeno-squamous carcinoma (EASC) to promote a more comprehensive understanding of these two subtypes. Background: EAM and EASC are rare subtypes of esophageal cancer with limited literature available. Extensive research has been conducted on the clinical and pathological characteristics of gastric and colorectal mixed adenoacanthomas, but there is relatively little literature on esophageal mixed adenoacanthomas. Therefore, this study aims to investigate the incidence and survival rates of these two subtypes in depth. Methods: Patients diagnosed with EAM and EASC between 2000 and 2019 were selected from the SEER database for the study. Joinpoint software was used to calculate the incidence rates of esophageal AM and ASC patients, and differences in cancer overall survival (OS) and cancer-specific survival (CSS) based on Kaplan-Meier curves were compared. Multivariate Cox regression analysis was employed to identify independent prognostic factors for OS and CSS, and a prognostic model was established and validated for accuracy. Results: The study found that the incidence of EAM increased until 2014, followed by a decline, while the incidence of EASC decreased until 2017, followed by an increase. Both of these subtypes were more common in male patients and those over the age of 65. For EAM patients, preoperative chemoradiotherapy was associated with better survival rates, while for EASC patients, preoperative radiotherapy combined with adjuvant chemotherapy improved survival. Finally, we constructed nomograms for predicting the overall survival of EAM and EASC patients by incorporating identified risk factors, which demonstrated good sensitivity and specificity. Conclusion: EAM and EASC are rare subtypes of esophageal cancer, and an in-depth exploration of their incidence and survival rates provides valuable data and insights for understanding these rare esophageal cancer subtypes. This information can assist clinical decision-making for healthcare professionals.

Efficacy of non-invasive brain stimulation for post-stroke dysphagia: a meta-analysis.

BACKGROUND: Given the potential harms of dysphagia after stroke, we noticed the possibility of non-invasive brain stimulation treatments in the management process. METHODS: The meta-analysis search for articles published before May 2023 in databases. We used STATA 12.0 software to compute the standard mean difference (SMD) and 95% confidence intervals (CI). RESULTS: The study showed a greater improvement in swallowing function in post-stroke dysphagia given transcranial direct current stimulation (tDCS) immediately after treatment, compared to those given sham tDCS (SMD = 2.99, 95% CI = 1.86-4.11). The study showed a greater improvement in swallowing function in post-stroke dysphagia given tDCS some days after treatment, compared to those given sham tDCS (SMD = 2.01, 95% CI = 0.87-3.16). The study showed a greater improvement in swallowing function in post-stroke dysphagia given repetitive transcranial magnetic stimulation (rTMS) immediately after treatment, compared to those given sham rTMS (SMD = 4.17, 95% CI = 3.11-5.23). The study showed a greater improvement in swallowing function in post-stroke dysphagia given rTMS some days after treatment, compared to those given sham rTMS (SMD = 1.77, 95% CI = 0.94-2.60). CONCLUSIONS: In conclusion, our study showed the beneficial effects of non-invasive brain stimulation on difficulty swallowing for stroke patients and speculated about the potential application of non-invasive brain stimulation on post-stroke dysphagia improvement.

How does China's big data policy affect the digital economy of cities? Evidence from national big data comprehensive pilot zones.

Based on the panel data of 280 cities in China from 2011 to 2019, this paper examines the effects of big data policies on the digital economy development by using the national big data comprehensive pilot zones as a quasi-natural experiment. The findings of this paper are as follows. First, the big data policy significantly promotes China's digital economy development. Second, cities at a higher administrative level receive higher policy benefits than cities at a lower administrative level. Third, technological innovation and human capital are important ways for the big data policy to improve the development of the digital economy. The conclusions of this paper not only help to assess the effectiveness of big data policies and ensure the efficacy of policy implementation, but also provide policy support for local governments to fully explore the value of data elements and grasp the new opportunities for the digital economy development with the help of the pilot zones.

A methylation-phosphorylation switch controls EZH2 stability and hematopoiesis.

The Polycomb Repressive Complex 2 (PRC2) methylates H3K27 to regulate development and cell fate by transcriptional silencing. Alteration of PRC2 is associated with various cancers. Here, we show that mouse Kdm1a deletion causes a dramatic reduction of PRC2 proteins, whereas mouse null mutation of L3mbtl3 or Dcaf5 results in PRC2 accumulation and increased H3K27 trimethylation. The catalytic subunit of PRC2, EZH2, is methylated at lysine 20 (K20), promoting EZH2 proteolysis by L3MBTL3 and the CLR4DCAF5 ubiquitin ligase. KDM1A (LSD1) demethylates the methylated K20 to stabilize EZH2. K20 methylation is inhibited by AKT-mediated phosphorylation of serine 21 in EZH2. Mouse Ezh2K20R/K20R mutants develop hepatosplenomegaly associated with high GFI1B expression, and Ezh2K20R/K20R mutant bone marrows expand hematopoietic stem cells and downstream hematopoietic populations. Our studies reveal that EZH2 is regulated by methylation-dependent proteolysis, which is negatively controlled by AKT-mediated S21 phosphorylation to establish a methylation-phosphorylation switch to regulate the PRC2 activity and hematopoiesis.

FABP6 serves as a new therapeutic target in esophageal tumor.

BACKGROUND: Esophageal cancer is one of the most common malignant tumors with high incidence and mortality rates. Despite the continuous development of treatment options, the prognosis for esophageal cancer patients remains poor. Therefore, there is an urgent need for new diagnostic and therapeutic targets in clinical practice to improve the survival of patients with esophageal cancer. METHODS: In this study, we conducted a comprehensive scRNA-seq analysis of the tumor microenvironment in primary esophageal tumors to elucidate cell composition and heterogeneity. Using Seurat, we identified eight clusters, encompassing non-immune cells (fibroblasts, myofibroblasts, endothelial cells, and epithelial cells) and immunocytes (myeloid-derived cells, T cells, B cells, and plasma cells). Compared to normal tissues, tumors exhibited an increased proportion of epithelial cells and alterations in immune cell infiltration. Analysis of epithelial cells revealed a cluster (cluster 0) with a high differentiation score and early distribution, suggesting its importance as a precursor cell. RESULTS: Cluster 0 was characterized by high expression of FABP6, indicating a potential role in fatty acid metabolism and tumor growth. T cell analysis revealed shifts in the balance between Treg and CD8+ effector T cells in tumor tissues. Cellular communication analysis identified increased interactions between FABP6+ tumor cells and T cells, with the involvement of the MIF-related pathway and the CD74-CD44 interaction. This study provides insights into the cellular landscape and immune interactions within esophageal tumors, contributing to a better understanding of tumor heterogeneity and potential therapeutic targets.

Changes in the femoral trochlear induced with estradiol exposure, an experimental study on rats.

BACKGROUND: It is well known that estrogen is closely related to bone and joint tissue. Findings indicate that estradiol, injected during pregnancy, passes through the placental barrier and reaches the fetuses in utero where it exerts its action. Since trochlea appears well established in the prenatal period, however, whether trochlear dysplasia is related to estradiol exposure has not been confirmed, and the pathological process of estradiol exposure-induced trochlear dysplasia remains unclear. This study aimed to establish an estradiol exposure animal model in fetuses and to analyze the morphology of the femoral trochlear in neonatal rats. METHODS: 30 pregnant Wistar rats provided by the local Animal Center were assigned randomly into three groups, a high dose estradiol injection group, a low dose estradiol injection group and a blank control group. Gross, cross-sectional observation, histological staining measurement and microcomputed tomography of the rat offspring were conducted to evaluate the morphological changes of the femoral trochlea. RESULTS: The incidence of trochlear dysplasia increased with the concentration of estradiol injection. Gross and cross-sectional observation showed a shallower trochlea groove in two groups with estradiol injection. Histological staining measurement indicated that the trochlear sulcus angle and trochlear sulcus depth were significantly different between the two groups with estradiol injection and the blank control group at 0,5 and 10 days after birth. Subchondral bone loss was observed in the two estradiol injection groups by micro-CT, and the bone loss was found to deteriorate over time. CONCLUSION: In this study, estradiol exposure in fetuses had an adverse effect on intrauterine development and could induce trochlear dysplasia and bone loss in rat offspring. In addition, this study also showed that the higher concentration of estradiol injection in pregnant rats, the more incidence of trochlear dysplasia in rat offspring.

Direct chemical-vapor-deposition growth of alloyed perovskite microcrystals for tunable emissions.

Tunable composition of perovskite micro/nanostructures are perfect candidate for the designing of multifunctional optoelectronic circuits. Especially, integrated polychromatic luminescence based on the perovskite materials along a single substrate or chip is essential to the integrated photonic devices and multicolor displays. Here, we reported a synthesis of composition tunable CsPbI3(1-x)Br3x(X = 0.65-0.9) perovskite microstructures on a single substrate via a magnetic-pulling CVD method. The PL emissions can be changed gradually from green (558 nm, 2.23 eV) to red (610 nm, 2.03 eV) under a focused 375 nm laser illumination. Furthermore, these composition-graded alloyed perovskite microcrystals show stable emissions after six months in air, which may find applications in multicolor display and broad band light sources in the future.