Bubble-Guidance Breaking Gas Shield for Highly Efficient Overall Water Splitting.

Overall water splitting is a promising technology for sustainable hydrogen production, but the primary challenge is removing bubbles from the electrode surface quickly to increase hydrogen production. Inspired by the directional fluid transport properties of natural biological surfaces like Nepenthes peristome and Morpho butterfly's wings, here a strategy is demonstrated to achieve highly efficient overall water splitting by a bubble-guidance electrode, that is, an anisotropic groove-micro/nanostructured porous electrode (GMPE). Gradient groove micro/nanostructures on the GMPE serve as high-speed bubble transmission channels and exhibit superior bubble-guidance capabilities. The synergistic effect of the asymmetric Laplace pressure generated between microscale porous structure and groove patterns and the buoyancy along the groove patterns pushes the produced bubbles directionally to spread, transport, and detach from the electrode surface in time. Moreover, the low adhesive nanosheet arrays are beneficial to reduce bubble size and increase bubble release frequency, which cooperatively improve mass transfer with the microscale structure. Notably, GMPE outperforms planar-micro/nanostructured porous electrode (PMPE) in hydrogen/oxygen evolution reactions, with GMPE||GMPE showing better water splitting performance than commercially available RuO2||20 wt.% Pt/C. This work improves electrodes for better mass transfer and kinetics in electrochemical reactions at solid-liquid-gas interfaces, offering insight for designing and preparing gas-involved photoelectrochemical electrodes.

Destabilized reporters for background-subtracted, chemically-gated, and multiplexed deep-tissue imaging.

Tracking gene expression in deep tissues requires genetic reporters that can be unambiguously detected using tissue penetrant techniques. Magnetic resonance imaging (MRI) is uniquely suited for this purpose; however, there is a dearth of reporters that can be reliably linked to gene expression with minimal interference from background tissue signals. Here, we present a conceptually new method for generating background-subtracted, drug-gated, multiplex images of gene expression using MRI. Specifically, we engineered chemically erasable reporters consisting of a water channel, aquaporin-1, fused to destabilizing domains, which are stabilized by binding to cell-permeable small-molecule ligands. We showed that this approach allows for highly specific detection of gene expression through differential imaging. In addition, by engineering destabilized aquaporin-1 variants with orthogonal ligand requirements, it is possible to distinguish distinct subpopulations of cells in mixed cultures. Finally, we demonstrated this approach in a mouse tumor model through differential imaging of gene expression with minimal background.

Effect of modified opioid sparing anaesthesia on postoperative quality of recovery in patients undergoing laparoscopic bariatric surgery: protocol for a monocentre, double-blind randomised controlled trial - the MOSA study.

INTRODUCTION: Obesity patients undergoing laparoscopic bariatric surgery (LBS) are frequently encountered perioperative adverse events related to opioids-based anaesthesia (OBA) or opioids-free anaesthesia (OFA). While modified opioid-sparing anaesthesia (MOSA) has been shown to lower the occurrence of adverse events related to OBA and OFA. This study is to assess the efficacy of MOSA in enhancing the recovery quality among individuals undergoing LBS. METHODS AND ANALYSIS: A single-centre, prospective, double-blind, randomised controlled trial is conducted at a tertiary hospital. A total of 74 eligible participants undergoing elective LBS will be recruited and randomly allocated. Patients in the MOSA group will receive a combination of low-dose opioids, minimal dexmedetomidine, esketamine and lidocaine, while in the OBA group will receive standard general anaesthesia with opioids. Patients in both groups will receive standard perioperative care. The primary outcome is the quality of recovery-15 score assessed at 24 hours after surgery. Secondary outcomes include pain levels, anxiety and depression assessments, gastrointestinal function recovery, perioperative complication rates, opioid consumption and length of hospital stay. ETHICS AND DISSEMINATION: Ethical approval has been provided by the Ethical Committee of Yan'an Hospital of Kunming City (approval No. 2023-240-01). Eligible patients will provide written informed consent to the investigator. The outcomes of this trial will be disseminated in a peer-reviewed scholarly journal. TRIAL REGISTRATION NUMBER: The study protocol is registered at https://www.chictr.org.cn/ on 19 December 2023. (identifier: ChiCTR2300078806). The trial was conducted using V.1.0.

Learning interpretable causal networks from very large datasets, application to 400,000 medical records of breast cancer patients.

Discovering causal effects is at the core of scientific investigation but remains challenging when only observational data are available. In practice, causal networks are difficult to learn and interpret, and limited to relatively small datasets. We report a more reliable and scalable causal discovery method (iMIIC), based on a general mutual information supremum principle, which greatly improves the precision of inferred causal relations while distinguishing genuine causes from putative and latent causal effects. We showcase iMIIC on synthetic and real-world healthcare data from 396,179 breast cancer patients from the US Surveillance, Epidemiology, and End Results program. More than 90% of predicted causal effects appear correct, while the remaining unexpected direct and indirect causal effects can be interpreted in terms of diagnostic procedures, therapeutic timing, patient preference or socio-economic disparity. iMIIC's unique capabilities open up new avenues to discover reliable and interpretable causal networks across a range of research fields.

A novel curdlan/methyl cellulose/walnut green husk polyphenol edible composite film for walnut packaging.

In this study, polyphenols were extracted from walnut green husk, an agricultural waste, and were incorporated into curdlan (CD) and methyl cellulose (MC) to create a novel edible composite film. For structural character, the film matrix was tightly bound primarily by non-covalent bonds and the addition of walnut green husk polyphenols (WGHP) significantly reduced the surface roughness of the composite film. For mechanical properties, the addition of WGHP improve the flexibility of films, and it significantly improved the barrier ability of ultraviolet rays and water-vapor. Furthermore, the incorporation of WGHP to the CD-MC film resulted in enhanced antioxidant and antibacterial effects, which effectively retards lipid oxidation in fried walnuts. Consequently, the fabricated CD-MC-WGHP composite film bears immense potential for use in food preservation applications, particularly in extending the shelf life of fried walnuts.

Integrating somatic mutation profiles with structural deep clustering network for metabolic stratification in pancreatic cancer: a comprehensive analysis of prognostic and genomic landscapes.

Pancreatic cancer is a globally recognized highly aggressive malignancy, posing a significant threat to human health and characterized by pronounced heterogeneity. In recent years, researchers have uncovered that the development and progression of cancer are often attributed to the accumulation of somatic mutations within cells. However, cancer somatic mutation data exhibit characteristics such as high dimensionality and sparsity, which pose new challenges in utilizing these data effectively. In this study, we propagated the discrete somatic mutation data of pancreatic cancer through a network propagation model based on protein-protein interaction networks. This resulted in smoothed somatic mutation profile data that incorporate protein network information. Based on this smoothed mutation profile data, we obtained the activity levels of different metabolic pathways in pancreatic cancer patients. Subsequently, using the activity levels of various metabolic pathways in cancer patients, we employed a deep clustering algorithm to establish biologically and clinically relevant metabolic subtypes of pancreatic cancer. Our study holds scientific significance in classifying pancreatic cancer based on somatic mutation data and may provide a crucial theoretical basis for the diagnosis and immunotherapy of pancreatic cancer patients.

MYL3 protects chondrocytes from senescence by inhibiting clathrin-mediated endocytosis and activating of Notch signaling.

As the unique cell type in articular cartilage, chondrocyte senescence is a crucial cellular event contributing to osteoarthritis development. Here we show that clathrin-mediated endocytosis and activation of Notch signaling promotes chondrocyte senescence and osteoarthritis development, which is negatively regulated by myosin light chain 3. Myosin light chain 3 (MYL3) protein levels decline sharply in senescent chondrocytes of cartilages from model mice and osteoarthritis (OA) patients. Conditional deletion of Myl3 in chondrocytes significantly promoted, whereas intra-articular injection of adeno-associated virus overexpressing MYL3 delayed, OA progression in male mice. MYL3 deficiency led to enhanced clathrin-mediated endocytosis by promoting the interaction between myosin VI and clathrin, further inducing the internalization of Notch and resulting in activation of Notch signaling in chondrocytes. Pharmacologic blockade of clathrin-mediated endocytosis-Notch signaling prevented MYL3 loss-induced chondrocyte senescence and alleviated OA progression in male mice. Our results establish a previously unknown mechanism essential for cellular senescence and provide a potential therapeutic direction for OA.

Structural deep clustering network for stratification of breast cancer patients through integration of somatic mutation profiles.

BACKGROUND AND OBJECTIVE: Breast cancer is among of the most malignant tumor that occurs in women and is one of the leading causes of death from gynecologic malignancy worldwide. The high degree of heterogeneity that characterizes breast cancer makes it challenging to devise effective therapeutic strategies. Accumulating evidence highlights the crucial role of stratifying breast cancer patients into clinically significant subtypes to achieve better prognoses and treatments. The structural deep clustering network is a graph convolutional network-based clustering algorithm that integrates structural information and has achieved state-of-the-art performance in various applications. METHODS: In this study, we employed structural deep clustering network to integrate somatic mutation profiles for stratifying 2526 breast cancer patients from the Memorial Sloan Kettering Cancer Center into two clinically differentiable subtypes. RESULTS: Breast cancer patients in cluster 1 exhibited better prognosis than breast cancer patients in cluster 2, and the difference between them was statistically significant. The immunogenomic landscape further demonstrated that cluster 1 was associated with remarkable infiltration of the tumor infiltrating lymphocytes. The clustering subtype could be used to evaluate the therapeutic benefit of immunotherapy and chemotherapy in breast cancer patients. Furthermore, our approach effectively classified patients from eight different cancer types, demonstrating its generalizability. CONCLUSIONS: Our study represents a step towards a generic methodology for classifying cancer patients using only somatic mutation data and structural deep clustering network approaches. Employing structural deep clustering network to identify breast cancer subtypes is promising and can inform the development of more accurate and personalized therapies.

Engineering ligand stabilized aquaporin reporters for magnetic resonance imaging.

Imaging transgene expression in live tissues requires reporters that are detectable with deeply penetrant modalities, such as magnetic resonance imaging (MRI). Here, we show that LSAqp1, a water channel engineered from aquaporin-1, can be used to create background-free, drug-gated, and multiplex images of gene expression using MRI. LSAqp1 is a fusion protein composed of aquaporin-1 and a degradation tag that is sensitive to a cell-permeable ligand, which allows for dynamic small molecule modulation of MRI signals. LSAqp1 improves specificity for imaging gene expression by allowing reporter signals to be conditionally activated and distinguished from the tissue background by difference imaging. In addition, by engineering destabilized aquaporin-1 variants with different ligand requirements, it is possible to image distinct cell types simultaneously. Finally, we expressed LSAqp1 in a tumor model and showed successful in vivo imaging of gene expression without background activity. LSAqp1 provides a conceptually unique approach to accurately measure gene expression in living organisms by combining the physics of water diffusion and biotechnology tools to control protein stability.

More efficient and inclusive time-to-event trials with covariate adjustment: a simulation study.

Adjustment for prognostic covariates increases the statistical power of randomized trials. The factors influencing the increase of power are well-known for trials with continuous outcomes. Here, we study which factors influence power and sample size requirements in time-to-event trials. We consider both parametric simulations and simulations derived from the Cancer Genome Atlas (TCGA) cohort of hepatocellular carcinoma (HCC) patients to assess how sample size requirements are reduced with covariate adjustment. Simulations demonstrate that the benefit of covariate adjustment increases with the prognostic performance of the adjustment covariate (C-index) and with the cumulative incidence of the event in the trial. For a covariate that has an intermediate prognostic performance (C-index=0.65), the reduction of sample size varies from 3.1% when cumulative incidence is of 10% to 29.1% when the cumulative incidence is of 90%. Broadening eligibility criteria usually reduces statistical power while our simulations show that it can be maintained with adequate covariate adjustment. In a simulation of adjuvant trials in HCC, we find that the number of patients screened for eligibility can be divided by 2.4 when broadening eligibility criteria. Last, we find that the Cox-Snell [Formula: see text] is a conservative estimation of the reduction in sample size requirements provided by covariate adjustment. Overall, more systematic adjustment for prognostic covariates leads to more efficient and inclusive clinical trials especially when cumulative incidence is large as in metastatic and advanced cancers. Code and results are available at https://github.com/owkin/CovadjustSim .

Novel antiosteoporotic peptides purified from protein hydrolysates of taihe black-boned silky fowl: By larval zebrafish model and molecular docking.

The black-boned silky fowl (BSF) muscle protein hydrolysate was gained by alcalase. The hydrolysate could stimulate MC3T3-E1 cell proliferation, as well as enhance alkaline phosphatas (ALP) activity and deposits of minerals. After isolation and purification, 55 peptide sequences with Mascot score over 40 were identified. Combined with molecular docking simulation and molecular dynamics analysis, two novel peptides (PASTGAAK and PGPPGTPF) were identified with the lowest binding energy of -4.99 kcal/mol and -3.07 kcal/mol with receptor BMPR1A of BMP-2/Smad pathway, showing the ability to increase BMPR1A stability. Moreover, both PASTGAAK and PGPPGTPF revealed strong anti-osteoporosis activities in the zebrafish model induced by dexamethasone. Additionally, the identified peptides could be beneficial for the differentiation of MC3T3-E1 cell for upregulating the expression of some osteoblast-related genes and proteins by stimulating BMP-2/Smad pathway. Overall, the two newly identified peptides could be the potential candidate to prevent osteoporosis.

Stratification of ovarian cancer patients from the prospect of drug target-related transcription factor protein activity: the prognostic and genomic landscape analyses.

The expression and activity of transcription factors, which directly mediate gene transcription, are strictly regulated to control numerous normal cellular processes. In cancer, transcription factor activity is often dysregulated, resulting in abnormal expression of genes related to tumorigenesis and development. The carcinogenicity of transcription factors can be reduced through targeted therapy. However, most studies on the pathogenic and drug-resistant mechanisms of ovarian cancer have focused on the expression and signaling pathways of individual transcription factors. To improve the prognosis and treatment of patients with ovarian cancer, multiple transcription factors should be evaluated simultaneously to determine the effects of their protein activity on drug therapies. In this study, the transcription factor activity of ovarian cancer samples was inferred from virtual inference of protein activity by enriched regulon algorithm using mRNA expression data. Patients were clustered according to their transcription factor protein activities to investigate the association of transcription factor activities of different subtypes with prognosis and drug sensitivity for filtering subtype-specific drugs. Meanwhile, master regulator analysis was utilized to identify master regulators of differential protein activity between clustering subtypes, thereby identifying transcription factors associated with prognosis and assessing their potential as therapeutic targets. Master regulator risk scores were then constructed for guiding patients' clinical treatment, providing new insights into the treatment of ovarian cancer at the level of transcriptional regulation.

Discovery of 4-methyl-3-(pyridin-2-ylamino)benzamide derivatives as C-Abl inhibitors with potential neuroprotective effect.

C-Abl is involved in various biological processes and plays an important role in neurodegenerative diseases, especially Parkinson's disease (PD). Previous studies have found that nilotinib shows a neuroprotective effect in cell and animal models of PD by inhibiting the activation of c-Abl. But the low blood-brain barrier permeability and potential toxicity limit the further use of nilotinib in PD. Based on molecular modeling studies, a series of 4-methyl-3-(pyridin-2-ylamino)benzamide derivatives were designed and synthesized. In particular, compound 9a exhibited significant inhibitory activity against c-Abl and a potent neuroprotective effect against MPP+-induced SH-SY5Y cell death. Moreover, 9a not only displayed lower cell toxicity compared with nilotinib, but also showed higher oral bioavailability and proper permeability of the blood-brain barrier. This paper provides 4-methyl-3-(pyridin-2-ylamino)benzamide derivatives as a new scaffold for c-Abl inhibitor with potential neuroprotective effect.

Eculizumab treatment for myasthenia gravis subgroups: 2021 update.

Eculizumab is a recombinant humanized monoclonal antibody that targets the complement protein C5, inhibiting its cleavage into C5a and C5b and ultimately preventing the formation of C5b-9 membrane attack complex (MACs), thereby protecting the neuromuscular junction from the damage of complement activation. In 2017, eculizumab became the second FDA-approved medication for AchR-positive generalized myasthenia gravis (gMG) patients based on the successful results of a randomized, double-blinded, placebo-controlled, phase 2, phase 3 study (the REGAIN trial) and its open-label extension study. Despite the efficacy of eculizumab in treating AchR antibody-positive refractory gMG was demonstrated in the REGAIN study, there is few information on its efficacy in other subgroup of MG patients including seronegative MG, thymoma-associated MG and MG crisis. This narrative review summarizes current clinical studies of eculizumab in these refractory gMG patients, with a focus on the therapeutic efficacy and tolerability in different subgroup of MG.

Metatranscriptomic Analysis Reveals Disordered Alterations in Oropharyngeal Microbiome during the Infection and Clearance Processes of SARS-CoV-2: A Warning for Secondary Infections.

This study was conducted to investigate oropharyngeal microbiota alterations during the progression of coronavirus disease 2019 (COVID-19) by analyzing these alterations during the infection and clearance processes of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The diagnosis of COVID-19 was confirmed by using positive SARS-CoV-2 quantitative reverse transcription polymerase chain reaction (RT-qPCR). The alterations in abundance, diversity, and potential function of the oropharyngeal microbiome were identified using metatranscriptomic sequencing analyses of oropharyngeal swab specimens from 47 patients with COVID-19 (within a week after diagnosis and within two months after recovery from COVID-19) and 40 healthy individuals. As a result, in the infection process of SARS-CoV-2, compared to the healthy individuals, the relative abundances of Prevotella, Aspergillus, and Epstein-Barr virus were elevated; the alpha diversity was decreased; the beta diversity was disordered; the relative abundance of Gram-negative bacteria was increased; and the relative abundance of Gram-positive bacteria was decreased. After the clearance of SARS-CoV-2, compared to the healthy individuals and patients with COVID-19, the above disordered alterations persisted in the patients who had recovered from COVID-19 and did not return to the normal level observed in the healthy individuals. Additionally, the expressions of several antibiotic resistance genes (especially multi-drug resistance, glycopeptide, and tetracycline) in the patients with COVID-19 were higher than those in the healthy individuals. After SARS-CoV-2 was cleared, the expressions of these genes in the patients who had recovered from COVID-19 were lower than those in the patients with COVID-19, and they were different from those in the healthy individuals. In conclusion, our findings provide evidence that potential secondary infections with oropharyngeal bacteria, fungi, and viruses in patients who have recovered from COVID-19 should not be ignored; this evidence also highlights the clinical significance of the oropharyngeal microbiome in the early prevention of potential secondary infections of COVID-19 and suggests that it is imperative to choose appropriate antibiotics for subsequent bacterial secondary infection in patients with COVID-19.

ß-Catenin/LEF-1 transcription complex is responsible for the transcriptional activation of LINC01278.

BACKGROUND: Our previous study shows that LINC01278 inhibits the malignant proliferation and invasion of papillary thyroid carcinoma (PTC) cells by regulating the miR-376c-3p/DNM3 axis. However, the regulation mechanism of LINC01278 expression in PTC cells is still unclear. METHODS: The luciferase reporter and ChIP assays were used to confirm the binding of LEF-1 to the putative promoter site of LINC01278 gene. The RNA immunoprecipitation and RNA pulldown were used to determine the enrichment of LINC01278 in ß-catenin protein. The proteasome inhibitors (MG132) was used for detecting the ß-catenin ubiquitination-proteasome degradation. Wnt/ß-catenin specific agonists (LiCI), inhibitors (WiKI4) and TOP/FOP-flash reporter assay were used for detecting the activation of Wnt/ß-catenin signal. Western blot was used to detected the expression of target proteins. RESULTS: The online PROMO algorithm determines a putative LEF-1 binding site on LINC01278 promoter, the LEF-1 binds to the putative promoter site of LINC01278 gene, and ß-catenin enhances the binding of LEF-1 to the LINC01278 gene promoter. Furthermore, LINC01278 negatively regulated the protein accumulation of ß-catenin in the cytoplasm, into nucleus, and ultimately inhibited the transcription of downstream target genes activated by Wnt/ß-catenin signal. The results of RNA immunoprecipitation and RNA pulldown proved the direct binding of LINC01278 to ß-catenin protein. In addition, the combination of LINC01278 and ß-catenin promotes the ß-catenin ubiquitination-proteasome degradation. CONCLUSION: In summary, we found the transcriptional activation of LINC01278 by the ß-catenin/LEF-1 transcription factor, and the negative feedback regulation of LINC01278 onß-catenin signal.

TP53 Mutational Status-Based Genomic Signature for Prognosis and Predicting Therapeutic Response in Pancreatic Cancer.

TP53 mutation is a critical driver mutation that affects the carcinogenesis and prognosis of patients with pancreatic cancer (PC). Currently, there is no driver mutation-derived signature based on TP53 mutational status for prognosis and predicting therapeutic response in PC. In the present study, we characterized the TP53 mutational phenotypes in multiple patient cohorts and developed a prognostic TP53-associated signature based on differentially expressed genes between PC samples with mutated TP53 and wild-type TP53. Comprehensive investigations were carried out in prognostic stratification, genetic variation, immune cell infiltration, and efficacy prediction of chemotherapy and targeted therapy. We found that TP53 mutation commonly occurred as a survival-related driver mutation in PC. In total, 1,154 differentially expressed genes were found between two distinct TP53 mutational phenotypes. A five-gene TP53-associated signature was constructed in The Cancer Genome Atlas (TCGA) cohort by least absolute shrinkage and selection operator (LASSO)-Cox analysis and proven to be a robust prognostic predictor, which performed well in three independent Gene Expression Omnibus (GEO) validating cohorts. Remarkably, patients in the low-risk group were characterized with decreased tumor mutation burden and activity of immunity, with favorable prognosis. Higher fractions of macrophages M0 and impaired CD8 + T cells were observed in patients in the high-risk group, suggesting immunosuppression with poor survival. Patients in the high-risk group also demonstrated enhanced response to specific chemotherapeutic agents, including gemcitabine and paclitaxel. Several targeted inhibitors, like histamine receptor inhibitor, were screened out as promising drugs for PC treatment. Collectively, the TP53-associated signature is a novel prognostic biomarker and predictive indicator of PC. The signature could contribute to optimizing prognostic stratification and guide effective PC treatments.

Efficacy and safety of bortezomib in rituximab-resistant anti-N-methyl-d-aspartate receptor (anti-NMDAR) encephalitis as well as the clinical characteristics: An observational study.

Treatment resistance leads to physiological, psychological, and economical effects among patients with anti-N-methyl d-aspartate receptor (anti-NMDAR) encephalitis, and the clinical and immune characteristics of these patients remain to be described. According to our clinical experience, bortezomib may be effective due to its plasma-cells depletion ability. Herein, the clinical presentations and immune parameters, including B cell and antibody secreting cell (ASC) abundance, of 5 enrolled treatment-resistant patients are described. When compared with 5 treatment-sensitive cases, the patients had serious clinical presentations but comparable B cells and ASCs. After receiving bortezomib, the ASC count and anti-NMDAR antibody titers decreased effectively. All 5 patients had a favorable prognosis (mRS ≤ 2) with a median follow-up of 31 months without severe side effects or relapse.

S100P as a novel biomarker of microvascular invasion and portal vein tumor thrombus in hepatocellular carcinoma.

BACKGROUND: Portal vein tumor thrombus (PVTT) and microvascular invasion (MVI) are types of intrahepatic vascular metastasis of hepatocellular carcinoma (HCC) and are highly correlated with poor prognosis. However, the underlying biomarkers of PVTT and MVI are unclear. METHODS: We identified a PVTT/MVI-associated gene S100P by cDNA microarray analysis, and assess the potential value of serum S100P measurement in the differential diagnosis of HCC and prediction of MVI status with large retrospective and perspective cohort studies. RESULTS: The mRNA and protein of S100P was increased in HCCs with PVTT or MVI. High S100P immunostaining in tumors was correlated with inferior tumor-free survival. Serum S100P values discriminated patients with HCCs from those with benign liver tumors, and it showed predictive potential of MVI status in both retrospective and perspective cohorts. S100P may regulate HCC tumorigenicity and invasive ability; S100P also was associated with up-regulation of CD44, which may mediate HCC cell adhesion to form PVTT/MVI. CONCLUSIONS: Serum S100P may be a novel differential diagnostic marker for HCC and a potential predictor of MVI status pre-surgery for HCC patients. S100P overexpression in HCC is highly correlated with the formation of PVTT and MVI, which may make S100P as a potential therapeutic target for HCC metastasis.

Expert consensus workshop report: Guidelines for thermal ablation of thyroid tumors (2019 edition).

As a treatment option for cancer, thermal ablation has satisfactory effects on many types of solid tumors (such as liver and renal cancers). However, its clinical applications for the treatment of thyroid nodules and metastatic cervical lymph nodes are still under debate both in China and abroad. In 2015, the "Zhejiang Expert consensus on thermal ablation for thyroid benign nodules, microcarcinoma, and metastatic cervical lymph nodes (2015 edition)," was released by the Thyroid Cancer Committee of Zhejiang Anti-Cancer Association, China. To further standardize the application of thermal ablation for thyroid tumors, the Thyroid Tumor Ablation Experts Group of Chinese Medical Doctor Association has organized many seminars and finally produced a consensus to formulate the "Expert consensus workshop report: Guidelines for thermal ablation of thyroid tumors (2019 edition)."