Search

Medullary thyroid carcinoma (MTC) is a rare thyroid malignancy, which is more aggressive with high metastasis and recurrence rate. Surgical treatment is the preferred treatment option for MTC. Targeted therapy and immunotherapy have gradually become new treatment strategy for MTC. The pathology of MTC was updated in the 5th edition WHO classification of endocrine and neuroendocrine tumor in 2022. This review summarized the update of MTC pathology focusing on the histologic grading schemes, gene screening and genetic counseling.

The modification mechanism of low-molecular-weight organic acids on a single-chain silicate mineral (wollastonite) was investigated through a leaching method. Solid and liquid samples were analyzed using atomic absorption spectrophotometer (AAS), X-ray diffraction (XRD), scanning electron microscope (SEM), and Fourier-transform infrared spectroscopy (FTIR). After 720 h of reaction, the results revealed that the dissolution concentration of Si (2200 μmol/L) in citric acid solution is more than that (1950 μmol/L) in oxalic acid. In the composite acids (citric acid and oxalic acid), the dissolution concentration of Si release from wollastonite reached the maximum value of 3304 μmol/L. The dissolution data of Si in wollastonite were fittingly described by the parabolic equation (Ct = a + bt1/2), with the highest correlation coefficients (R2 > 0.993), in the presence of the low-molecular-weight organic acids. The dissolution data suggested that the dissolution reaction process of Si was consistent with the diffusion-controlled model. Citric acid exhibited a higher affinity for attacking the (200) surface, while oxalic acid was prone to dissolve the (002) crystal face. The synergistic effects of oxalic acid and citric acid led to the weakening of the XRD diffraction peak intensity of wollastonite. When exposed to composite acids, the surface of wollastonite was covered with insoluble reactants that restricted the substance diffusion and hindered the reaction. This study offers valuable theoretical insights into the modification or activation of wollastonite by composite low-molecular-weight organic acids. [ABSTRACT FROM AUTHOR]

Background: Sleep apnea is highly prevalent after acute ischemic stroke (AIS) and has increased stroke-related mortality and morbidity. The conventional sleep apnea treatment is continuous positive airway pressure (CPAP) ventilation. However, it is poorly tolerated by patients and is not used in all stroke patients. This protocol describes the impact of high-flow nasal cannula (HFNC) oxygen therapy compared to nasal continuous positive airway pressure (nCPAP) ventilation or usual care on the early prognosis of patients with sleep apnea after AIS. Methods: This randomised controlled study will be conducted in the intensive care unit of the Department of Neurology at the Wuhan Union Hospital. According to the study plan, 150 patients with sleep apnea after AIS will be recruited. All patients are randomly allocated in a 1:1:1 ratio to one of three groups: the nasal catheter group (standard oxygen group), the HFNC group, and the nCPAP group. Patients receive different types of ventilation after admission to the group, and their tolerance while using the different ventilation is recorded. Patients will be followed up by telephone three months after discharge, and stroke recovery is recorded. The primary outcomes were 28-day mortality, the incidence of pulmonary infection and endotracheal intubation. Discussion: This study analyses different ventilation modalities for early interventions in patients with sleep apnea after AIS. We will investigate whether nCPAP and HFNC reduce early mortality and endotracheal intubation rates and improve distant neurological recovery in patients. Trial registration: This trial was registered at ClinicalTrials.gov (NCT05323266; 25 March 2022). [ABSTRACT FROM AUTHOR]

At present, the study on the pathogenesis of Alzheimer's disease (AD) by multimodal data fusion analysis has been attracted wide attention. It often has the problems of small sample size and high dimension with the multimodal medical data. In view of the characteristics of multimodal medical data, the existing genetic evolution random neural network cluster (GERNNC) model combine genetic evolution algorithm and neural network for the classification of AD patients and the extraction of pathogenic factors. However, the model does not take into account the non-linear relationship between brain regions and genes and the problem that the genetic evolution algorithm can fall into local optimal solutions, which leads to the overall performance of the model is not satisfactory. In order to solve the above two problems, this paper made some improvements on the construction of fusion features and genetic evolution algorithm in GERNNC model, and proposed an improved genetic evolution random neural network cluster (IGERNNC) model. The IGERNNC model uses mutual information correlation analysis method to combine resting-state functional magnetic resonance imaging data with single nucleotide polymorphism data for the construction of fusion features. Based on the traditional genetic evolution algorithm, elite retention strategy and large variation genetic algorithm are added to avoid the model falling into the local optimal solution. Through multiple independent experimental comparisons, the IGERNNC model can more effectively identify AD patients and extract relevant pathogenic factors, which is expected to become an effective tool in the field of AD research. [ABSTRACT FROM AUTHOR]