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The diagnosis of oral lichen planus (OLP) poses many challenges due to its nonspecific clinical symptoms and histopathological features. Therefore, the diagnostic process should include a thorough clinical history, immunological tests, and histopathology. Our study aimed to enhance the diagnostic accuracy of OLP by integrating direct immunofluorescence (DIF) results with clinical data to develop a multivariate predictive model based on the Artificial Neural Network. Eighty patients were assessed using DIF for various markers (immunoglobulins of classes G, A, and M; complement 3; fibrinogen type 1 and 2) and clinical characteristics such as age, gender, and lesion location. Statistical analysis was performed using machine learning techniques in Statistica 13. The following variables were assessed: gender, age on the day of lesion onset, results of direct immunofluorescence, location of white patches, locations of erosions, treatment history, medications and dietary supplement intake, dental status, smoking status, flossing, and using mouthwash. Four statistically significant variables were selected for machine learning after the initial assessment. The final predictive model, based on neural networks, achieved 85% in the testing sample and 71% accuracy in the validation sample. Significant predictors included stress at onset, white patches under the tongue, and erosions on the mandibular gingiva. In conclusion, while the model shows promise, larger datasets and more comprehensive variables are needed to improve diagnostic accuracy for OLP, highlighting the need for further research and collaborative data collection efforts. [ABSTRACT FROM AUTHOR]

Y. Li gave a characterization of the class of finite soluble groups in which every subnormal subgroup is normal by means of NE-subgroups: a subgroup H of a group G is called an NE-subgroup of G if NG(H) ∩ HG = H. We obtain a new characterization of these groups related to the local Wielandt subgroup. We also give characterizations of the classes of finite soluble groups in which every subnormal subgroup is permutable or Sylow permutable in terms of NE-subgroups.

P. Hall proved that a finite group G is supersoluble with elementary abelian Sylow sub-groups if and only if every subgroup of G is complemented in G. He called such groups complemented. A. Ballester-Bolinches and X. Guo established the structure of minimal non-complemented groups. We give the classification of finite non-soluble groups all of whose second maximal subgroups are comple-mented groups. We also prove that every finite group with less than 21 non-complemented non-minimal f2; 3; 5g-subgroups is soluble. [ABSTRACT FROM AUTHOR]

The present study highlights the effect of metal precursor types (SO42¯, Cl¯, and NO3¯), their concentration, and the influence of ionic strength of reaction environment on the morphology, surface, and magnetic properties of CoFe2O4 particles. The magnetic nanoparticles were obtained by chemical coprecipitation in alkaline medium at increasing metal concentration in the range of 0.0425 mol·dm-3 to 0.17 mol·dm-3 and calcination temperature from 400°C to 800°C. It was found that the chemistry of precursors can be directly correlated with magnetic properties. The CoFe2O4 particles from metal sulphate precursors showed the highest saturation magnetization and the lowest coercivity. The adjustment of ionic strength in the range of 1.25–5 M was achieved by adding an appropriate quantity of metal sulphates into aqueous solutions at a constant pH or by adding an appropriate quantity of NaClO5 under similar conditions. The average hydrodynamic size of CoFe2O4 increased from 46 nm to 54 nm with increasing metal concentration and ionic strength. An explanation of magnetic properties, caused by ionic strength and metal concentration, is given based mainly on the reduction in repulsive forces at the particle interface and compensation of the double electric layer in the presence of anions. The observed coercivity was lower for the particles obtained in solutions with the highest ionic strength, whereas the concentration of metals and calcination temperature affected the saturation magnetization and morphology of the obtained cobalt ferrite particles. [ABSTRACT FROM AUTHOR]

Mesothelioma is diagnosed in approximately 2,500 patients in the United States every year, most often arising in the pleural space, but also occurring as primary peritoneal mesothelioma. The vast majority of patients with mesothelioma die from their disease within 3 years. We developed a new mouse model of mesothelioma by bladder or intra-peritoneal injection of adenovirus Cre into mice with conditional alleles of each of Tp53 and Tsc1. Such mice began to develop malignant ascites about 6 months after injection, which was due to peritoneal mesothelioma, based on tumor morphology and immunohistochemical staining. Mesothelioma cell lines were established which showed loss of both Tsc1 and Tp53, with mTORC1 activation. Treatment of mice with malignant ascites due to mesothelioma with rapamycin led to a marked reduction in ascites, extended survival, and a 95–99% reduction in mesothelioma tumor volume, in comparison to vehicle-treated mice. To see if TSC1/TSC2 loss was a common genetic event in human mesothelioma, we examined 9 human mesothelioma cell lines, and found that 4 of 9 showed persistent activation of mTORC1 though none had loss of TSC1 or TSC2. A tissue microarray analysis of 198 human mesothelioma specimens showed that 33% of cases had reduced TSC2 expression and 60% showed activation of mTOR, indicating that mTOR activation is common in human mesothelioma and suggesting that it is a potential therapeutic target.