Objective To determine the prognostic biomarkers and new therapeutic targets of the lung adenocarcinoma (LUAD), based on which to establish a prediction model for the survival of LUAD patients. Methods An integrative analysis was conducted on gene expression and clinicopathologic data of LUAD, which were obtained from the UCSC database. Subsequently, various methods, including screening of differentially expressed genes (DEGs), Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis and Gene Set Enrichment Analysis (GSEA), were employed to analyze the data. Cox regression and least absolute shrinkage and selection operator (LASSO) regression were used to establish an assessment model. Based on this model, we constructed a nomogram to predict the probable survival of LUAD patients at different time points (1-year, 2-year, 3-year, 5-year, and 10-year). Finally, we evaluated the predictive ability of our model using Kaplan-Meier survival curves, receiver operating characteristic (ROC) curves, and time-dependent ROC curves. The validation group further verified the prognostic value of the model. Results The different-grade pathological subtypes' DEGs were mainly enriched in biological processes such as metabolism of xenobiotics by cytochrome P450, natural killer cell-mediated cytotoxicity, antigen processing and presentation, and regulation of enzyme activity, which were closely related to tumor development. Through Cox regression and LASSO regression, we constructed a reliable prediction model consisting of a five-gene panel (MELTF, MAGEA1, FGF19, DKK4, C14ORF105). The model demonstrated excellent specificity and sensitivity in ROC curves, with an area under the curve (AUC) of 0.675. The time-dependent ROC analysis revealed AUC values of 0.893, 0.713, and 0.632 for 1-year, 3-year, and 5-year survival, respectively. The advantage of the model was also verified in the validation group. Additionally, we developed a nomogram that accurately predicted survival, as demonstrated by calibration curves and C-index. Conclusion We have developed a prognostic prediction model for LUAD consisting of five genes. This novel approach offers clinical practitioners a personalized tool for making informed decisions regarding the prognosis of their patients.

BACKGROUND:Primary cortical neurons and microglial cells play a crucial role in exploring cell therapies for neurological disorders,and most of the current methods for obtaining the two types of cells are cumbersome and require separate extraction.It is therefore crucial to find a convenient and rapid method to extract both types of cells simultaneously. OBJECTIVE:To explore a novel method for simultaneous extraction of primary cortical neurons and microglial cells. METHODS:Newborn suckling SD rats were taken within 24 hours.The brain was removed and placed in a dish with DMEM,and the pia mater was removed for later use.Primary neurons were extracted from the same brain tissue,and then the remaining brain tissue was used to extract microglial cells.The whole process was performed on ice.Extraction and culture steps of primary cortical neurons:The cerebral cortex was taken 2.0-3.0 mm with forceps,and the tissue was digested with papain for 20 minutes.After aborting digestion,the blown tissue presented an adherent tissue suspension.The supernatant cell suspension was obtained,filtered,and dispensed into 15 mL centrifuge tubes.After centrifugation and re-suspension,the cells were inoculated onto 6-well plate crawls coated with L-polylysine.Neuronal morphology was observed at 1-day intervals,and staining could be performed for identification using immunofluorescence staining of MAP2 and β-Tubulin by day 7.Microglia extraction and culture steps:The remaining brain tissue at 8-10 mm thick was subjected to microglial cell extraction,digested by trypsin for 20 minutes.After digestion was stopped,the tissue was blown to a homogenate,and then the homogenate was transferred to the culture bottle for culture.On day 14,the culture flasks were sealed and subjected to constant temperature horizontal shaking for 2 hours.Microglial cells were shed in the supernatant.Purified microglial cells were taken and continued to be cultured for 3 days for identification by Iba1 immunofluorescence staining. RESULTS AND CONCLUSION:(1)After 24 hours of culture,the neurons were adherent to the wall,the cytosol was enlarged,and some neurons developed synapses.After 3 and 5 days of culture,the cytosol was further enlarged,and most of the neurons were in the form of synapses,and some neurons were growing in clusters.On day 7,neuronal synapses were prolonged and thickened,and they were connected with each other to form a network.The neurons were identified by β-Tubulin and MAP2 immunofluorescence staining.(2)The cells grew close to the wall on day 1 of culture.On days 3,5,and 7,the density of microglial cells was small,and the cell morphology was bright oval or round,but the cells basically grew in clumps on the upper layer of other cells.On day 10,the density of microglial cells increased significantly.On day 14,microglial cells grew in dense clumps on the upper layer of other cells,and then they could be isolated and purified.The isolated and purified cells were taken and re-cultured to day 3 and identified as microglial cells by Iba1 immunofluorescence;their purity was greater than 95%.(3)The results show that primary cortical neurons and microglial cells obtained by this method after extraction and culture are of high purity,good morphology,and high viability.

ObjectiveTo analyze the adverse reactions associated with the clinical use of Banxia （Rhizoma Pinelliae）- Wutou （Aconitum） in the same formula， with the aim of providing a reference for the safety of their clinical application. MethodsLiterature on the clinical application of antagonistic herbs "Banxia-Wutou" used in the same formula， published from January 1st， 2014， to June 30th， 2023， was retrieved from databases including CNKI， VIP， Wanfang， SinoMed， PubMed， Cochrane Library， and Embase. A database was established， and information related to adverse reactions was extracted， including descriptions， classifications， specific manifestations， management and outcomes， patients' primary diseases （western medicine diseases and traditional Chinese medicine diagnoses and syndromes）， and medication information （dosage， ratio， administration routes， and dosage forms）. ResultsA total of 79 researches simultaneously used antagonistic herbs Banxia-Wutou in the same formula and reported associated advers reactions. Gastrointestinal adverse reactions were the most common， with 8 studies reporting management of adverse reactions and 3 studies reporting improvement with no intervention. Among the 11 researches， the adverse reaction relieved to extant， while other 69 researches didn't report the managment of adverse reaction and its prognosis. For the primary disease in western medicine system， chronic bronchitis and chronic obstructive pulmonary disease （COPD） were most common， while gastric pain was the most common symptom in traditional Chinese medicine with spleen and kidney deficiency and spleen stomach cold deficiency being the most frequent syndromes. The most common Banxia dosage was 10 g， while for the Wutou， Fuzi （Radix Aconiti Lateralis Praeparata） was predominant with the highest dose at 15 g. The most frequent herbal combination was Banxia-fuzi， with a 1∶1 ratio. The main administration route was oral， and the primary dosage form was decoction. ConclusionGastrointestinal adverse reactions are the most common in the clinical use of Banxia-Wutou antagonistic herb combinations. Research on the safety of "Banxia-Wutou" combinations should focus on respiratory system diseases and spleen-stomach related conditions.

Digital technologies have become an integral part of complete denture restoration. With advancement in computer-aided design and computer-aided manufacturing (CAD/CAM), tools such as intraoral scanning, facial scanning, 3D printing, and numerical control machining are reshaping the workflow of complete denture restoration. Unlike conventional methods that rely heavily on clinical experience and manual techniques, digital technologies offer greater precision, predictability, and efficacy. They also streamline the process by reducing the number of patient visits and improving overall comfort. Despite these improvements, the clinical application of digital complete denture restoration still faces challenges that require further standardization. The major issues include appropriate case selection, establishing consistent digital workflows, and evaluating long-term outcomes. To address these challenges and provide clinical guidance for practitioners, this expert consensus outlines the principles, advantages, and limitations of digital complete denture technology. The aim of this review was to offer practical recommendations on indications, clinical procedures and precautions, evaluation metrics, and outcome assessment to support digital restoration of complete denture in clinical practice.
Humans ; Denture, Complete ; Computer-Aided Design ; Denture Design/methods* ; Consensus ; Printing, Three-Dimensional

Dysregulated RNA splicing is a well-recognized characteristic of colorectal cancer (CRC); however, its intricacies remain obscure, partly due to challenges in profiling full-length transcript variants at the single-cell level. Here, we employ high-depth long-read scRNA-seq to define the full-length transcriptome of colorectal epithelial cells in 12 CRC patients, revealing extensive isoform diversities and splicing alterations. Cancer cells exhibited increased transcript complexity, with widespread 3'-UTR shortening and reduced intron retention. Distinct splicing regulation patterns were observed between intrinsic-consensus molecular subtypes (iCMS), with iCMS3 displaying even higher splicing factor activities and more pronounced 3'-UTR shortening. Furthermore, we revealed substantial shifts in isoform usage that result in alterations of protein sequences from the same gene with distinct carcinogenic effects during tumorigenesis of CRC. Allele-specific expression analysis revealed dominant mutant allele expression in key oncogenes and tumor suppressors. Moreover, mutated PPIG was linked to widespread splicing dysregulation, and functional validation experiments confirmed its critical role in modulating RNA splicing and tumor-associated processes. Our findings highlight the transcriptomic plasticity in CRC and suggest novel candidate targets for splicing-based therapeutic strategies.
Humans ; Colorectal Neoplasms/metabolism* ; RNA Isoforms/metabolism* ; Single-Cell Analysis ; RNA Splicing ; Gene Expression Regulation, Neoplastic ; RNA, Neoplasm/metabolism* ; Transcriptome

Animal experiments are crucial in evaluating the preclinical safety and efficacy of new dental materials, drugs, instruments, and equipment by identifying and eliminating potential health risks to humans. An international team of several dental experts formulated a guideline named Preferred Reporting Items for Animal Studiesin Endodontology (PRIASE) 2021. Consisting of 11 domains, 43 individual items, and a flowchart. PRIASE provides guidance for animal experiments in dentistry and improves the quality of experiment design and reporting. This work introduces the process and basic content of the guideline and interprets the key items of its checklist with specific examples to provide reference for the reporting of animal experiment in dentistry in China.
Animals ; Animal Experimentation/standards* ; Checklist ; China ; Endodontics ; Guidelines as Topic ; Research Design

Natural components serve the survival instincts of cells that are obtained through long-term evolution, while they often fail to meet the demands of engineered cells for efficiently performing biological functions in special industrial environments. Enzymes, as biological catalysts, play a key role in biosynthetic pathways, significantly enhancing the rate and selectivity of biochemical reactions. However, the catalytic efficiency, stability, substrate specificity, and tolerance of natural enzymes often fall short of industrial production requirements. Therefore, exploring and modifying enzymes to suit specific biomanufacturing processes has become crucial. In recent years, artificial intelligence (AI) has played an increasingly important role in the discovery, evaluation, engineering, and de novo design of proteins. AI can accelerate the discovery and optimization of proteins by analyzing large amounts of bioinformatics data and predicting protein functions and characteristics by machine learning and deep learning algorithms. Moreover, AI can assist researchers in designing new protein structures by simulating and predicting their performance under different conditions, providing guidance for protein design. This paper reviews the latest research advances in protein discovery, evaluation, engineering, and de novo design for biomanufacturing and explores the hot topics, challenges, and emerging technical methods in this field, aiming to provide guidance and inspiration for researchers in related fields.
Protein Engineering/methods* ; Artificial Intelligence ; Proteins/genetics* ; Computational Biology ; Machine Learning ; Data Mining ; Algorithms ; Deep Learning