Application of organoids in otolaryngology: head and neck surgery.

PURPOSE: The purpose of this review is to systematically summarize the application of organoids in the field of otolaryngology and head and neck surgery. It aims to shed light on the current advancements and future potential of organoid technology in these areas, particularly in addressing challenges like hearing loss, cancer research, and organ regeneration. METHODS: Review of current literature regrading organoids in the field of otolaryngology and head and neck surgery. RESULTS: The review highlights several advancements in the field. In otology, the development of organoid replacement therapies offers new avenues for treating hearing loss. In nasal science, the creation of specific organoid models aids in studying nasopharyngeal carcinoma and respiratory viruses. In head and neck surgery, innovative approaches for squamous cell carcinoma prediction and thyroid regeneration using organoids have been developed. CONCLUSION: Organoid research in otolaryngology-head and neck surgery is still at an early stage. This review underscores the potential of this technology in advancing our understanding and treatment of various conditions, predicting a transformative impact on future medical practices in these fields.

Research progress and application of single-cell sequencing in head and neck malignant tumors.

Single-cell sequencing (SCS) is a technology that separates thousands of cells from the organism and accurately analyzes the genetic material expressed in each cell using high-throughput sequencing technology. Unlike the traditional bulk sequencing approach, which can only provide the average value of a cell population and cannot obtain specific single-cell data, single-cell sequencing can identify the gene sequence and expression changes of a single cell, and reflects the differences between genetic material and protein between cells, and ultimately the role played by the tumor microenvironment. single-cell sequencing can further explore the pathogenesis of head and neck malignancies from the single-cell biological level and provides a theoretical basis for the clinical diagnosis and treatment of head and neck malignancies. This article will systematically introduce the latest progress and application of single-cell sequencing in malignant head and neck tumors.

Mechanism and treatment of olfactory dysfunction caused by coronavirus disease 2019.

Coronavirus disease 2019 (COVID-19) is an infectious disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Since the start of the pandemic, olfactory dysfunction (OD) has been reported as a common symptom of COVID-19. In some asymptomatic carriers, OD is often the first and even the only symptom. At the same time, persistent OD is also a long-term sequela seen after COVID-19 that can have a serious impact on the quality of life of patients. However, the pathogenesis of post-COVID-19 OD is still unclear, and there is no specific treatment for its patients. The aim of this paper was to review the research on OD caused by SARS-CoV-2 infection and to summarize the mechanism of action, the pathogenesis, and current treatments.

T cell effects and mechanisms in immunotherapy of head and neck tumors.

Head and neck tumors (HNCs) are a common tumor in otorhinolaryngology head and neck surgery, accounting for 5% of all malignant tumors in the body and are the sixth most common malignant tumor worldwide. In the body, immune cells can recognize, kill, and remove HNCs. T cell-mediated antitumor immune activity is the most important antitumor response in the body. T cells have different effects on tumor cells, among which cytotoxic T cells and helper T cells play a major killing and regulating role. T cells recognize tumor cells, activate themselves, differentiate into effector cells, and activate other mechanisms to induce antitumor effects. In this review, the immune effects and antitumor mechanisms mediated by T cells are systematically described from the perspective of immunology, and the application of new immunotherapy methods related to T cells are discussed, with the objective of providing a theoretical basis for exploring and forming new antitumor treatment strategies. Video Abstract.

The role and mechanism of action of tRNA-derived fragments in the diagnosis and treatment of malignant tumors.

Cancer is a leading cause of morbidity and death worldwide. While various factors are established as causing malignant tumors, the mechanisms underlying cancer development remain poorly understood. Early diagnosis and the development of effective treatments for cancer are important research topics. Transfer RNA (tRNA), the most abundant class of RNA molecules in the human transcriptome, participates in both protein synthesis and cellular metabolic processes. tRNA-derived fragments (tRFs) are produced by specific cleavage of pre-tRNA and mature tRNA molecules, which are highly conserved and occur widely in various organisms. tRFs were initially thought to be random products with no physiological function, but have been redefined as novel functional small non-coding RNA molecules that help to regulate RNA stability, modulate translation, and influence target gene expression, as well as other biological processes. There is increasing evidence supporting roles for tRFs in tumorigenesis and cancer development, including the regulation of tumor cell proliferation, invasion, migration, and drug resistance. Understanding the regulatory mechanisms by which tRFs impact these processes has potential to inform malignant tumor diagnosis and treatment. Further, tRFs are expected to become new biological markers for early diagnosis and prognosis prediction in patients with tumors, as well as a targets for precision cancer therapies. Video abstract.

Role of exosomal competitive endogenous RNA (ceRNA) in diagnosis and treatment of malignant tumors.

Malignant tumors are a threat to human health, thus it is critical to better understand the mechanism of tumor occurrence and development and to find key therapeutic targets. Competitive endogenous RNA (ceRNA) is a type of RNA molecule that includes mRNA of coding-protein, pseudogenes, long non-coding RNA (lncRNA), and circular RNA (circRNA) etc. It is created through a competitive combination of common small RNA (miRNA) and has an inhibitory effect on mRNA translation. ceRNA regulate the post transcriptional expression of genes by competitively binding to common microRNAs (miRNAs).Studies have shown that cernas are involved in tumor cell proliferation, invasion and migration, drug resistance, angiogenesis, as well as tumor immunity, and so on, affecting the progression of tumor development. This article reviews the reported roles of exosomal ceRNA in the diagnosis and treatment of malignant tumors and the mechanisms underlying these.

Roles and clinical application of exosomal circRNAs in the diagnosis and treatment of malignant tumors.

Exosomes are microvesicles secreted by cells. They contain a variety of bioactive substances with important roles in intercellular communication. Circular RNA (circRNA), a type of nucleic acid molecule found in exosomes, forms a covalently bonded closed loop without 5' caps or 3' poly(A) tails. It is structurally stable, widely distributed, and tissue specific. CircRNAs mainly act as microRNA sponges and have important regulatory roles in gene expression; they are superior to other non-coding RNAs as molecular diagnostic markers and drug treatment targets. Exosomal-derived circRNAs in the body fluids of tumor patients can modulate tumor proliferation, invasion, metastasis, and drug resistance. They can be used as effective biomarkers for early non-invasive diagnosis and prognostic evaluation of tumors, and also represent ideal targets for early precision therapeutic intervention. This review provides a theoretical basis for exploring the applications of exosomal circRNAs in malignant tumor diagnosis and treatment. We describe the biological functions of exosomal circRNAs in the occurrence and development of malignant tumors, their potential utility in diagnosis and treatment, and possible mechanisms.

Research Progress of Olfactory Nerve Regeneration Mechanism and Olfactory Training.

The olfactory nerve (ON) is the only cranial nerve exposed to the external environment. Hence, it is susceptible to damage from head trauma, viral infection, inflammatory stimulation, and chemical toxins, which can lead to olfactory dysfunction. However, compared with all other cranial nerves, the ON is unique due to its inherent ability to regenerate. This characteristic provides a theoretical basis for treatment of olfactory dysfunction. Olfactory training (OT) is one of the main treatments for olfactory dysfunction. It is easy to apply and has few side-effects, and has been shown to be efficacious for patients with olfactory dysfunction of various causes. To further understand the application value of ON regeneration and OT on olfactory dysfunction, we review the research progress on the mechanism of ON regeneration and OT.

Identification of violent patients with schizophrenia using a hybrid machine learning approach at the individual level.

Despite numerous risk factors associated with violence in patients with schizophrenia, predicting and preventing violent behavior is still a challenge. At present, machine learning (ML) has become a promising strategy for guiding individualized assessment. To build an effective model to predict the risk of violence in patients with schizophrenia, we proposed a hybrid ML method to improve the prediction capability in 42 violent offenders with schizophrenia and 33 non-violent patients with schizophrenia. The results revealed that the final model, which combined multimodal data, achieved the highest prediction performance with an accuracy of 90.67%. Specifically, the model, which fused three modalities of neuroimaging data, achieved a better accuracy than other fused models. In addition, the msot discriminative neuroimaging features involved in the prefrontal-temporal cognitive circuit and striatum reward system, indicating that dysfunction in cortical-subcortical circuits might be associated with high risk of violence in patients with schizophrenia. This study provides the first evidence supporting that the combination of specific multimodal neuroimaging and clinical data in ML analysis can effectively identify violent patients with schizophrenia. Furthermore, this work is crucial for the development of neuro-prediction models that could facilitate individualized treatment and interventions for violent behaviors in patients with schizophrenia.

Schizophrenia Identification Using Multi-View Graph Measures of Functional Brain Networks.

Schizophrenia (SZ) is a functional mental disorder that seriously affects the social life of patients. Therefore, accurate diagnosis of SZ has raised extensive attention of researchers. At present, study of brain network based on resting-state functional magnetic resonance imaging (rs-fMRI) has provided promising results for SZ identification by studying functional network alteration. However, previous studies based on brain network analysis are not very effective for SZ identification. Therefore, we propose an improved SZ identification method using multi-view graph measures of functional brain networks. Firstly, we construct an individual functional connectivity network based on Brainnetome atlas for each subject. Then, multi-view graph measures are calculated by the brain network analysis method as feature representations. Next, in order to consider the relationships between measures within the same brain region in feature selection, multi-view measures are grouped according to the corresponding regions and Sparse Group Lasso is applied to identify discriminative features based on this feature grouping structure. Finally, a support vector machine (SVM) classifier is employed to perform SZ identification task. To evaluate our proposed method, computational experiments are conducted on 145 subjects (71 schizophrenic patients and 74 healthy controls) using a leave-one-out cross-validation (LOOCV) scheme. The results show that our proposed method can obtain an accuracy of 93.10% for SZ identification. By comparison, our method is more effective for SZ identification than some existing methods.