Comprehensive analysis and experimental verification of the mechanism of anoikis related genes in pancreatic cancer.

Background: Pancreatic cancer (PC), characterized by its aggressive nature and low patient survival rate, remains a challenging malignancy. Anoikis, a process inhibiting the spread of metastatic cancer cells, is closely linked to cancer progression and metastasis through anoikis-related genes. Nonetheless, the precise mechanism of action of these genes in PC remains unclear. Methods: Study data were acquired from the Cancer Genome Atlas (TCGA) database, with validation data accessed at the Gene Expression Omnibus (GEO) database. Differential expression analysis and univariate Cox analysis were performed to determine prognostically relevant differentially expressed genes (DEGs) associated with anoikis. Unsupervised cluster analysis was then employed to categorize cancer samples. Subsequently, a least absolute shrinkage and selection operator (LASSO) Cox regression analysis was conducted on the identified DEGs to establish a clinical prognostic gene signature. Using risk scores derived from this signature, patients with cancer were stratified into high-risk and low-risk groups, with further assessment conducted via survival analysis, immune infiltration analysis, and mutation analysis. External validation data were employed to confirm the findings, and Western blot and immunohistochemistry were utilized to validate risk genes for the clinical prognostic gene signature. Results: A total of 20 prognostic-related DEGs associated with anoikis were obtained. The TCGA dataset revealed two distinct subgroups: cluster 1 and cluster 2. Utilizing the 20 DEGs, a clinical prognostic gene signature comprising two risk genes (CDKN3 and LAMA3) was constructed. Patients with pancreatic adenocarcinoma (PAAD) were classified into high-risk and low-risk groups per their risk scores, with the latter exhibiting a superior survival rate. Statistically significant variation was noted across immune infiltration and mutation levels between the two groups. Validation cohort results were consistent with the initial findings. Additionally, experimental verification confirmed the high expression of CDKN3 and LAMA3 in tumor samples. Conclusion: Our study addresses the gap in understanding the involvement of genes linked to anoikis in PAAD. The clinical prognostic gene signature developed herein accurately stratifies patients with PAAD, contributing to the advancement of precision medicine for these patients.

Polystyrene microplastics and di-2-ethylhexyl phthalate co-exposure: Implications for female reproductive health.

Microplastics and phthalates are prevalent and emerging pollutants that pose a potential impact on human health. Previous studies suggest that both microplastics and phthalates can adversely affect the reproductive systems of humans and mammals. However, the combined impact of these pollutants on the female reproductive system remains unclear. Here we show the impacts of exposure to polystyrene microplastics (PS-MPs) and di-2-ethylhexyl phthalate (DEHP) on female Sprague-Dawley rats' reproductive systems. We find that co-exposure to PS-MPs and DEHP results in a marked increase in cystic and atretic follicles, oxidative stress, fibrosis, and dysregulation of serum sex hormone homeostasis in the ovaries of the rats. Proteomic analysis identified differentially expressed proteins that were predominantly enriched in signaling pathways related to fatty acid metabolism and tight junctions, regulated by transforming growth factor ß1 (TGF-ß1). We further confirm that co-exposure to DEHP and PS-MPs activates the TGF-ß1/Smad3 signaling pathway, and inhibiting this pathway alleviates oxidative stress, hormonal dysregulation, and ovarian fibrosis. These results indicate that exposure to the combination of microplastics and phthalates leads to a significant increase in atretic follicles and may increase the risk of polycystic ovary syndrome (PCOS). Our study provides new insights into the reproductive toxicity effects of microplastics and DEHP exposure on female mammals, highlighting the potential link between environmental pollutants and the occurrence of PCOS. These findings highlight the need for comprehensive assessments of the reproductive health risks posed by microplastic pollution to women and contribute to the scientific basis for evaluating such risks.

Comprehensive Analysis of the Mechanism of Anoikis in Hepatocellular Carcinoma.

Background: Hepatocellular carcinoma (HCC), ranking as the second-leading cause of global mortality among malignancies, poses a substantial burden on public health worldwide. Anoikis, a type of programmed cell death, serves as a barrier against the dissemination of cancer cells to distant organs, thereby constraining the progression of cancer. Nevertheless, the mechanism of genes related to anoikis in HCC is yet to be elucidated. Methods: This paper's data (TCGA-HCC) were retrieved from the database of the Cancer Genome Atlas (TCGA). Differential gene expression with prognostic implications for anoikis was identified by performing both the univariate Cox and differential expression analyses. Through unsupervised cluster analysis, we clustered the samples according to these DEGs. By employing the least absolute shrinkage and selection operator Cox regression analysis (CRA), a clinical predictive gene signature was generated from the DEGs. The Cell-Type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT) algorithm was used to determine the proportions of immune cell types. The external validation data (GSE76427) were procured from Gene Expression Omnibus (GEO) to verify the performance of the clinical prognosis gene signature. Western blotting and immunohistochemistry (IHC) analysis confirmed the expression of risk genes. Results: In total, 23 prognostic DEGs were identified. Based on these 23 DEGs, the samples were categorized into four distinct subgroups (clusters 1, 2, 3, and 4). In addition, a clinical predictive gene signature was constructed utilizing ETV4, PBK, and SLC2A1. The gene signature efficiently distinguished individuals into two risk groups, specifically low and high, demonstrating markedly higher survival rates in the former group. Significant correlations were observed between the expression of these risk genes and a variety of immune cells. Moreover, the outcomes from the validation cohort analysis aligned consistently with those obtained from the training cohort analysis. The results of Western blotting and IHC showed that ETV4, PBK, and SLC2A1 were upregulated in HCC samples. Conclusion: The outcomes of this paper underscore the effectiveness of the clinical prognostic gene signature, established utilizing anoikis-related genes, in accurately stratifying patients. This signature holds promise in advancing the development of personalized therapy for HCC.

Target Fishing Reveals a Novel Mechanism of N-Acylamino Saccharin Derivatives Targeting Glyceraldehyde-3-Phosphate Dehydrogenase toward Cyanobacterial Blooms Control.

Based on current challenges of poor targeting and limited choices in chemical control methods of cyanobacterial blooms (CBs), identifying new targets is an urgent and formidable task in the quest for target-based algaecides. This study discovered N-acylamino saccharin derivatives exhibiting potent algicidal activity. Thus, using N-acylamino saccharin as the probes, glyceraldehyde-3-phosphate dehydrogenase from cyanobacterial (CyGAPDH) was identified as a new target of algaecides through the activity-based protein profiling (ABPP) strategy for the first time. Building upon the structure of Probe2, a series of derivatives were designed and synthesized, with compound b6 demonstrating the most potent inhibitory activity against CyGAPDH and Synechocystis sp. PCC6803 (IC50 = 1.67 µM and EC50 = 1.15 µM). Furthermore, the potential covalent binding model of b6 to the cysteine residue C154 was explored through covalent possibility prediction, LC-MS experiments, substrate competitive inhibition experiments, and molecular docking. Especially, the results revealed C154 as a crucial covalent binding site, with residues T184 and R11 forming robust hydrophobic interactions and H181 establishing significant hydrogen-bonding interactions with b6, highlighting their potential as essential pharmacophores. In summary, this study not only identifies a novel target of algaecides for the control of CB but also lays the solid foundation for the development of targeted covalent algaecides.

OGG1: An emerging multifunctional therapeutic target for the treatment of diseases caused by oxidative DNA damage.

Oxidative DNA damage-related diseases, such as incurable inflammation, malignant tumors, and age-related disorders, present significant challenges in modern medicine due to their complex molecular mechanisms and limitations in identifying effective treatment targets. Recently, 8-oxoguanine DNA glycosylase 1 (OGG1) has emerged as a promising multifunctional therapeutic target for the treatment of these challenging diseases. In this review, we systematically summarize the multiple functions and mechanisms of OGG1, including pro-inflammatory, tumorigenic, and aging regulatory mechanisms. We also highlight the potential of OGG1 inhibitors and activators as potent therapeutic agents for the aforementioned life-limiting diseases. We conclude that OGG1 serves as a multifunctional hub; the inhibition of OGG1 may provide a novel approach for preventing and treating inflammation and cancer, and the activation of OGG1 could be a strategy for preventing age-related disorders. Furthermore, we provide an extensive overview of successful applications of OGG1 regulation in treating inflammatory, cancerous, and aging-related diseases. Finally, we discuss the current challenges and future directions of OGG1 as an emerging multifunctional therapeutic marker for the aforementioned challenging diseases. The aim of this review is to provide a robust reference for scientific researchers and clinical drug developers in the development of novel clinical targeted drugs for life-limiting diseases, especially for incurable inflammation, malignant tumors, and age-related disorders.

An approach for full space inverse materials design by combining universal machine learning potential, universal property model, and optimization algorithm.

We present a full space inverse materials design (FSIMD) approach that fully automates the materials design for target physical properties without the need to provide the atomic composition, chemical stoichiometry, and crystal structure in advance. Here, we used density functional theory reference data to train a universal machine learning potential (UPot) and transfer learning to train a universal bulk modulus model (UBmod). Both UPot and UBmod were able to cover materials systems composed of any element among 42 elements. Interfaced with optimization algorithm and enhanced sampling, the FSIMD approach is applied to find the materials with the largest cohesive energy and the largest bulk modulus, respectively. NaCl-type ZrC was found to be the material with the largest cohesive energy. For bulk modulus, diamond was identified to have the largest value. The FSIMD approach is also applied to design materials with other multi-objective properties with accuracy limited principally by the amount, reliability, and diversity of the training data. The FSIMD approach provides a new way for inverse materials design with other functional properties for practical applications.

Chemical Isotope Labeling and Dual-Filtering Strategy for Comprehensive Profiling of Urinary Glucuronide Conjugates.

Glucuronidation, a crucial process in phase II metabolism, plays a vital role in the detoxification and elimination of endogenous substances and xenobiotics. A comprehensive and confident profiling of glucuronate-conjugated metabolites is imperative to understanding their roles in physiological and pathological processes. In this study, a chemical isotope labeling and dual-filtering strategy was developed for global profiling of glucuronide metabolites in biological samples. N,N-Dimethyl ethylenediamine (DMED-d0) and its deuterated counterpart DMED-d6 were used to label carboxylic acids through an amidation reaction. First, carboxyl-containing compounds were extracted based on a characteristic mass difference (Δm/z, 6.037 Da) observed in MS between light- and heavy-labeled metabolites (filter I). Subsequently, within the pool of carboxyl-containing compounds, glucuronides were identified using two pairs of diagnostic ions (m/z 247.1294/253.1665 and 229.1188/235.1559 for DMED-d0/DMED-d6-labeled glucuronides) originating from the fragmentation of the derivatized glucuronic acid group in MS/MS (filter II). Compared with non-derivatization, DEMD labeling significantly enhanced the detection sensitivity of glucuronides, as evidenced by a 3- to 55-fold decrease in limits of detection for representative standards. The strategy was applied to profiling glucuronide metabolites in urine samples from colorectal cancer (CRC) patients. A total of 685 features were screened as potential glucuronides, among which 181 were annotated, mainly including glucuronides derived from lipids, organic oxygen, and phenylpropanoids. Enzymatic biosynthesis was employed to accurately identify unknown glucuronides without standards, demonstrating the reliability of the dual-filtering strategy. Our strategy exhibits great potential for profiling the glucuronide metabolome with high coverage and confidence to reveal changes in CRC and other diseases.

MSE-VGG: A Novel Deep Learning Approach Based on EEG for Rapid Ischemic Stroke Detection.

Ischemic stroke is a type of brain dysfunction caused by pathological changes in the blood vessels of the brain which leads to brain tissue ischemia and hypoxia and ultimately results in cell necrosis. Without timely and effective treatment in the early time window, ischemic stroke can lead to long-term disability and even death. Therefore, rapid detection is crucial in patients with ischemic stroke. In this study, we developed a deep learning model based on fusion features extracted from electroencephalography (EEG) signals for the fast detection of ischemic stroke. Specifically, we recruited 20 ischemic stroke patients who underwent EEG examination during the acute phase of stroke and collected EEG signals from 19 adults with no history of stroke as a control group. Afterwards, we constructed correlation-weighted Phase Lag Index (cwPLI), a novel feature, to explore the synchronization information and functional connectivity between EEG channels. Moreover, the spatio-temporal information from functional connectivity and the nonlinear information from complexity were fused by combining the cwPLI matrix and Sample Entropy (SaEn) together to further improve the discriminative ability of the model. Finally, the novel MSE-VGG network was employed as a classifier to distinguish ischemic stroke from non-ischemic stroke data. Five-fold cross-validation experiments demonstrated that the proposed model possesses excellent performance, with accuracy, sensitivity, and specificity reaching 90.17%, 89.86%, and 90.44%, respectively. Experiments on time consumption verified that the proposed method is superior to other state-of-the-art examinations. This study contributes to the advancement of the rapid detection of ischemic stroke, shedding light on the untapped potential of EEG and demonstrating the efficacy of deep learning in ischemic stroke identification.

Natural course of ulcerative colitis in China: Differences from the West?

BACKGROUND AND AIMS: Whether the natural course of ulcerative colitis (UC) in mainland China is similar or different from that in Western countries is unknown, and data on it is limited. We aimed to provide a comprehensive description of the natural course of UC in China and compare it with Western UC patients. METHODS: Based on a prospective Chinese nationwide registry of consecutive patients with inflammatory bowel diseases, the medical treatments and natural history of UC were described in detail, including disease extension, surgery, and neoplasia. The Cox regression model was used to identify factors associated with poor outcomes. RESULTS: A total of 1081 UC patients were included with a median follow-up duration of 5.3 years. The overall cumulative exposure was 99.1% to 5-aminosalicylic acids, 52.1% to corticosteroids, 25.6% to immunomodulators, and 15.4% to biologics. Disease extent at diagnosis was proctitis in 26.9%, left-sided colitis in 34.8%, and extensive colitis in 38.3%. Of 667 patients with proctitis and left-sided colitis, 380 (57.0%) experienced disease extent progression. A total of 58 (5.4%) UC patients underwent colectomy, demonstrating cumulative proportions of surgery at 1, 5, and 10 years after diagnosis of 0.6%, 3.4%, and 8.2%, respectively. In addition, 23 (2.1%) UC patients were diagnosed with neoplasia, demonstrating cumulative proportions of neoplasia at 1, 5, and 10 years after diagnosis of 0.5%, 1.0%, and 3.5%, respectively. CONCLUSIONS: Chinese UC patients had similar cumulative proportions of exposure to IBD-specific treatments but a lower surgical rate than patients in Western countries, indicating a different natural course, and close monitoring needs for UC in China. However, these results must be confirmed in population-based studies because the hospital-based cohort in our study might lead to selection bias.

Endothelial Cells Promote Pseudo-islet Function Through BTC-EGFR-JAK/STAT Signaling Pathways.

Interactions between cells are of fundamental importance in affecting cell function. In vivo, endothelial cells and islet cells are close to each other, which makes endothelial cells essential for islet cell development and maintenance of islet cell function. We used endothelial cells to construct 3D pseudo-islets, which demonstrated better glucose regulation and greater insulin secretion compared to conventional pseudo-islets in both in vivo and in vitro trials. However, the underlying mechanism of how endothelial cells promote beta cell function localized within islets is still unknown. We performed transcriptomic sequencing, differential gene analysis, and enrichment analysis on two types of pseudo-islets to show that endothelial cells can promote the function of internal beta cells in pseudo-islets through the BTC-EGFR-JAK/STAT signaling pathway. Min6 cells secreted additional BTC after co-culture of endothelial cells with MIN6 cells outside the body. After BTC knockout in vitro, we found that beta cells functioned differently: insulin secretion levels decreased significantly, while the expression of key proteins in the EGFR-mediated JAK/STAT signaling pathway simultaneously decreased, further confirming our results. Through our experiments, we elucidate the molecular mechanisms by which endothelial cells maintain islet function in vitro, which provides a theoretical basis for the construction of pseudo-islets and islet cell transplants for the treatment of diabetes mellitus.

A DNA-Modularized STING Agonist with Macrophage-Selectivity and Programmability for Enhanced Anti-Tumor Immunotherapy.

The activation of cyclic GMP-AMP (cGAMP) synthase (cGAS) and its adaptor, stimulator of interferon genes (STING), is known to reprogram the immunosuppressive tumor microenvironment for promoting antitumor immunity. To enhance the efficiency of cGAS-STING pathway activation, macrophage-selective uptake, and programmable cytosolic release are crucial for the delivery of STING agonists. However, existing polymer- or lipid-based delivery systems encounter difficulty in integrating multiple functions meanwhile maintaining precise control and simple procedures. Herein, inspired by cGAS being a natural DNA sensor, a modularized DNA nanodevice agonist (DNDA) is designed that enable macrophage-selective uptake and programmable activation of the cGAS-STING pathway through precise self-assembly. The resulting DNA nanodevice acts as both a nanocarrier and agonist. Upon local administration, it demonstrates the ability of macrophage-selective uptake, endosomal escape, and cytosolic release of the cGAS-recognizing DNA segment, leading to robust activation of the cGAS-STING pathway and enhanced antitumor efficacy. Moreover, DNDA elicits a synergistic therapeutic effect when combined with immune checkpoint blockade. The study broadens the application of DNA nanotechnology as an immune stimulator for cGAS-STING activation.

scCRT: a contrastive-based dimensionality reduction model for scRNA-seq trajectory inference.

Trajectory inference is a crucial task in single-cell RNA-sequencing downstream analysis, which can reveal the dynamic processes of biological development, including cell differentiation. Dimensionality reduction is an important step in the trajectory inference process. However, most existing trajectory methods rely on cell features derived from traditional dimensionality reduction methods, such as principal component analysis and uniform manifold approximation and projection. These methods are not specifically designed for trajectory inference and fail to fully leverage prior information from upstream analysis, limiting their performance. Here, we introduce scCRT, a novel dimensionality reduction model for trajectory inference. In order to utilize prior information to learn accurate cells representation, scCRT integrates two feature learning components: a cell-level pairwise module and a cluster-level contrastive module. The cell-level module focuses on learning accurate cell representations in a reduced-dimensionality space while maintaining the cell-cell positional relationships in the original space. The cluster-level contrastive module uses prior cell state information to aggregate similar cells, preventing excessive dispersion in the low-dimensional space. Experimental findings from 54 real and 81 synthetic datasets, totaling 135 datasets, highlighted the superior performance of scCRT compared with commonly used trajectory inference methods. Additionally, an ablation study revealed that both cell-level and cluster-level modules enhance the model's ability to learn accurate cell features, facilitating cell lineage inference. The source code of scCRT is available at https://github.com/yuchen21-web/scCRT-for-scRNA-seq.

[Determination of 12 prohibited veterinary drug residues in pig urine by ultra high performance liquid chromatography-tandem mass spectrometry].

A method was established for the simultaneous detection of 12 prohibited veterinary drugs, including ß2-receptor agonists, nitrofuran metabolites, nitroimidazoles, chlorpromazine, and chloramphenicol, in pig urine. The sample was pretreated by enzymolysis, acid hydrolysis/derivatization, and liquid-liquid extraction combined with solid-phase extraction. Detection was performed using ultra high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS). Ammonium acetate solution (0.2 mol/L, 4.5 mL) and ß-glucuronidase/aryl sulfatase (40 µL) were added to the sample, which was subsequently enzymolized at 37 ℃ for 2 h. Then, 1.5 mL of 1.0 mol/L hydrochloric acid solution and 100 µL of 0.1 mol/L o-nitrobenzaldehyde solution were added to the sample. The mixture was incubated at 37 ℃ for 16 h, and the analytes were extracted with 8 mL of ethyl acetate by liquid-liquid extraction. The lower aqueous phase obtained after extraction was extracted and purified using a mixed cation-exchange solid-phase extraction column. The extracts were combined, the extraction solution was blow-dried with nitrogen, and the residue was redissolved for determination. The samples were analyzed under multiple-reaction monitoring mode with both positive and negative electrospray ionization, and quantified using an isotope internal standard method. The correlation coefficients (r) of the 12 compounds were >0.99. The limits of detection (LODs) and quantification (LOQs) of chloramphenicol were 0.05 and 0.1 µg/L, respectively, and the LODs and LOQs of the other compounds were 0.25 and 0.5 µg/L, respectively. The mean recoveries and RSDs at 1, 2, and 10 times the LOQ were 83.6%-115.3% and 2.20%-12.34%, respectively. The proposed method has the advantages of high sensitivity, good stability, and accurate quantification; thus, it is suitable for the simultaneous determination of the 12 prohibited veterinary drug residues in pig urine.

Sono-responsive smart nanoliposomes for precise and rapid hemostasis application.

Massive hemorrhage caused by injuries and surgical procedures is a major challenge in emergency medical scenarios. Conventional means of hemostasis often fail to rapidly and efficiently control bleeding, especially in inaccessible locations. Herein, a type of smart nanoliposome with ultrasonic responsiveness, loaded with thrombin (thrombin@liposome, named TNL) was developed to serve as an efficient and rapid hemostatic agent. Firstly, the hydrophilic cavities of the liposomes were loaded onto the sono-sensitive agent protoporphyrin. Secondly, a singlet oxygen-sensitive chemical bond was connected with the hydrophobic and hydrophilic ends of liposomes in a chemical bond manner. Finally, based on the host guest effect between ultrasound and the sono-sensitizer, singlet oxygen is continuously generated, which breaks the hydrophobic and hydrophilic ends of liposome fragments, causing spatial collapse of the TNL structure, swiftly releases thrombin loaded in the hydrophilic capsule cavity, thereby achieving accurate and rapid local hemostasis (resulted in a reduction of approximately 67% in bleeding in the rat hemorrhage model). More importantly, after thorough assessments of biocompatibility and biodegradability, it has been confirmed that TNL possesses excellent biosafety, providing a new avenue for efficient and precise hemostasis.

Voice Changes of Patients With Nasopharyngeal Carcinoma in Eleven Years After Radiotherapy: A Cross-Sectional Study.

OBJECTIVES: The objective of this study was to assess voice changes in patients with nasopharyngeal carcinoma (NPC) using subjective and objective assessment tools and to make inferences regarding the underlying pathological causes for different phases of radiotherapy (RT). METHODS: A total of 187 (123 males and 64 females) patients with post-RT NPC with no recurrence of malignancy or other voice diseases and 17 (11 males and 6 females) healthy individuals were included in this study. The patients were equally divided into 11 groups according to the number of years after RT. The acoustic analyses, GRBAS (grade, roughness, breathiness, asthenia, and strain) scales, and Voice Handicap Index (VHI)-10 scores were collected and analyzed. RESULTS: The fundamental frequency (F0) parameters in years 1 and 2 and year 11 were significantly lower in patients with NPC than in healthy individuals. The maximum phonation times in years 1 and 11 were significantly shorter than those in healthy individuals. The jitter parameters were significantly different between year 1 and from years 8 to 11 and the healthy individuals. The shimmer parameters were significantly different between years 1, from years 9 to 11, and healthy individuals. Hoarseness was the most prominent problem compared to other items of the GRBAS. The VHI-10 scores were significantly different between years 1 and 2 and year 11 after RT in patients with NPC. CONCLUSIONS: Voice quality was worse in the first 2 years and from years 8 to 11 but remained relatively normal from years 3 to 7 after RT. Patient-reported voice handicaps began during year 3 after RT. The most prominent problem was perceived hoarseness, which was evident in the first 2 years and from years 9 to 11 after RT. The radiation-induced mucous edema, laryngeal intrinsic muscle fibrosis, nerve injuries, upper respiratory tract changes, and decreased lung capacity might be the pathological reasons for voice changes in post-RT patients with NPC.

Comparative transcriptomic analysis reveals the molecular changes of acute pancreatitis in experimental models.

BACKGROUND: Acute pancreatitis (AP) encompasses a spectrum of pancreatic inflammatory conditions, ranging from mild inflammation to severe pancreatic necrosis and multisystem organ failure. Given the challenges associated with obtaining human pancreatic samples, research on AP predominantly relies on animal models. In this study, we aimed to elucidate the fundamental molecular mechanisms underlying AP using various AP models. AIM: To investigate the shared molecular changes underlying the development of AP across varying severity levels. METHODS: AP was induced in animal models through treatment with caerulein alone or in combination with lipopolysaccharide (LPS). Additionally, using Ptf1α to drive the specific expression of the hM3 promoter in pancreatic acinar cells transgenic C57BL/6J- hM3/Ptf1α(cre) mice were administered Clozapine N-oxide to induce AP. Subsequently, we conducted RNA sequencing of pancreatic tissues and validated the expression of significantly different genes using the Gene Expression Omnibus (GEO) database. RESULTS: Caerulein-induced AP showed severe inflammation and edema, which were exacerbated when combined with LPS and accompanied by partial pancreatic tissue necrosis. Compared with the control group, RNA sequencing analysis revealed 880 significantly differentially expressed genes in the caerulein model and 885 in the caerulein combined with the LPS model. Kyoto Encyclopedia of Genes and Genomes enrichment analysis and Gene Set Enrichment Analysis indicated substantial enrichment of the TLR and NOD-like receptor signaling pathway, TLR signaling pathway, and NF-κB signaling pathway, alongside elevated levels of apoptosis-related pathways, such as apoptosis, P53 pathway, and phagosome pathway. The significantly elevated genes in the TLR and NOD-like receptor signaling pathways, as well as in the apoptosis pathway, were validated through quantitative real-time PCR experiments in animal models. Validation from the GEO database revealed that only MYD88 concurred in both mouse pancreatic tissue and human AP peripheral blood, while TLR1, TLR7, RIPK3, and OAS2 genes exhibited marked elevation in human AP. The genes TUBA1A and GADD45A played significant roles in apoptosis within human AP. The transgenic mouse model hM3/Ptf1α(cre) successfully validated significant differential genes in the TLR and NOD-like receptor signaling pathways as well as the apoptosis pathway, indicating that these pathways represent shared pathological processes in AP across different models. CONCLUSION: The TLR and NOD receptor signaling pathways play crucial roles in the inflammatory progression of AP, notably the MYD88 gene. Apoptosis holds a central position in the necrotic processes of AP, with TUBA1A and GADD45A genes exhibiting prominence in human AP.

Understanding Defects in Perovskite Solar Cells through Computation: Current Knowledge and Future Challenge.

Lead halide perovskites with superior optoelectrical properties are emerging as a class of excellent materials for applications in solar cells and light-emitting devices. However, perovskite films often exhibit abundant intrinsic defects, which can limit the efficiency of perovskite-based optoelectronic devices by acting as carrier recombination centers. Thus, an understanding of defect chemistry in lead halide perovskites assumes a prominent role in further advancing the exploitation of perovskites, which, to a large extent, is performed by relying on first-principles calculations. However, the complex defect structure, strong anharmonicity, and soft lattice of lead halide perovskites pose challenges to defect studies. In this perspective, on the basis of briefly reviewing the current knowledge concerning computational studies on defects, this work concentrates on addressing the unsolved problems and proposing possible research directions in future. This perspective particularly emphasizes the indispensability of developing advanced approaches for deeply understanding the nature of defects and conducting data-driven defect research for designing reasonable strategies to further improve the performance of perovskite applications. Finally, this work highlights that theoretical studies should pay more attention to establishing close and clear links with experimental investigations to provide useful insights to the scientific and industrial communities.

Biomimetic Hydrogels Promote Pseudoislet Formation to Improve Glycemic Control in Diabetic Mice.

Islet or ß-cell transplantation is currently considered to be the ideal treatment for diabetes, and three-dimensional (3D) bioprinting of a bionic pancreas with physiological stiffness is considered to be promising for the encapsulation and transplantation of ß-cells. In this study, a 5%GelMA/2%AlgMA hybrid hydrogel with pancreatic physiological stiffness was constructed and used for ß-cell encapsulation, 3D bioprinting, and in vivo transplantation to evaluate glycemic control in diabetic mice. The hybrid hydrogel had good cytocompatibility and could induce insulin-producing cells (IPCs) to form pseudoislet structures and improve insulin secretion. Furthermore, we validated the importance of betacellulin (BTC) in IPCs differentiation and confirmed that IPCs self-regulation was achieved by altering the nuclear and cytoplasmic distributions of BTC expression. In vivo transplantation of diabetic mice quickly restored blood glucose levels. In the future, 3D bioprinting of ß-cells using biomimetic hydrogels will provide a promising platform for clinical islet transplantation for the treatment of diabetes.

Single-Cell Transcriptome Analysis Identified Core Genes and Transcription Factors in Mesenchymal Cell Differentiation during Liver Cirrhosis.

BACKGROUND: Mesenchymal cells, including hepatic stellate cells (HSCs), fibroblasts (FBs), myofibroblasts (MFBs), and vascular smooth muscle cells (VSMCs), are the main cells that affect liver fibrosis and play crucial roles in maintaining tissue homeostasis. The dynamic evolution of mesenchymal cells is very important but remains to be explored for researching the reversible mechanism of hepatic fibrosis and its evolution mechanism of hepatic fibrosis to cirrhosis. METHODS: Here, we analysed the transcriptomes of more than 50,000 human single cells from three cirrhotic and three healthy liver tissue samples and the mouse hepatic mesenchymal cells of two healthy and two fibrotic livers to reconstruct the evolutionary trajectory of hepatic mesenchymal cells from a healthy to a cirrhotic state, and a subsequent integrative analysis of bulk RNA sequencing (RNA-seq) data of HSCs from quiescent to active (using transforming growth factor ß1 (TGF-ß1) to stimulate LX-2) to inactive states. RESULTS: We identified core genes and transcription factors (TFs) involved in mesenchymal cell differentiation. In healthy human and mouse livers, the expression of NR1H4 and members of the ZEB families (ZEB1 and ZEB2) changed significantly with the differentiation of FB into HSC and VSMC. In cirrhotic human livers, VSMCs transformed into HSCs with downregulation of MYH11, ACTA2, and JUNB and upregulation of PDGFRB, RGS5, IGFBP5, CD36, A2M, SOX5, and MEF2C. Following HSCs differentiation into MFBs with the upregulation of COL1A1, TIMP1, and NR1H4, a small number of MFBs reverted to inactivated HSCs (iHSCs). The differentiation trajectory of mouse hepatic mesenchymal cells was similar to that in humans; however, the evolution trajectory and proportion of cell subpopulations that reverted from MFBs to iHSCs suggest that the mouse model may not accurately reflect disease progression and outcome in humans. CONCLUSIONS: Our analysis elucidates primary genes and TFs involved in mesenchymal cell differentiation during liver fibrosis using scRNA-seq data, and demonstrated the core genes and TFs in process of HSC activation to MFB and MFB reversal to iHSC using bulk RNA-seq data of human fibrosis induced by TGF-ß1. Furthermore, our findings suggest promising targets for the treatment of liver fibrosis and provide valuable insights into the molecular mechanisms underlying its onset and progression.

The mitochondrial quality control system: a new target for exercise therapeutic intervention in the treatment of brain insulin resistance-induced neurodegeneration in obesity.

Obesity is a major global health concern because of its strong association with metabolic and neurodegenerative diseases such as diabetes, dementia, and Alzheimer's disease. Unfortunately, brain insulin resistance in obesity is likely to lead to neuroplasticity deficits. Since the evidence shows that insulin resistance in brain regions abundant in insulin receptors significantly alters mitochondrial efficiency and function, strategies targeting the mitochondrial quality control system may be of therapeutic and practical value in obesity-induced cognitive decline. Exercise is considered as a powerful stimulant of mitochondria that improves insulin sensitivity and enhances neuroplasticity. It has great potential as a non-pharmacological intervention against the onset and progression of obesity associated neurodegeneration. Here, we integrate the current knowledge of the mechanisms of neurodegenration in obesity and focus on brain insulin resistance to explain the relationship between the impairment of neuronal plasticity and mitochondrial dysfunction. This knowledge was synthesised to explore the exercise paradigm as a feasible intervention for obese neurodegenration in terms of improving brain insulin signals and regulating the mitochondrial quality control system.