Clinicopathological features as prognostic predictors of poor outcome in papillary thyroid carcinoma

Papillary thyroid cancer (PTC) has an indolent nature and usually excellent prognosis. Some PTC clinicopathological features may contribute to the development of aggressive metastatic disease. In this work, we want to evaluate PTC clinicopathological features that are presurgical prognostic predictors of patients’ outcomes and find which indicators are more adequate for tailoring surgical procedures and follow-up. We studied a series of 241 PTC patients submitted to surgery. All patients’ files and histological tumor samples were reviewed. The 8th edition AJCC/UICC (American Joint Committee on Cancer/Union for International Cancer) Controlstaging system and the 2015 American Thyroid Association risk stratification system were used. Total thyroidectomy was performed in 228 patients, lymphadenectomy in 28 patients. Gross extrathyroidal extension (ETE) was present in 10 patients and 31 tumor resection margins were incomplete. Cervical lymph node metastases (LNMs) were present in 34 patients and distant metastases at diagnosis in four patients. In multivariate analysis, male gender (OR = 15.4, p = 0.015), venous invasion (OR = 16.7, p = 0.022), and lateral compartment LNM (OR = 26.7, p = 0.004) were predictors of mortality; psammoma bodies (PBs) (OR = 4.5, p = 0.008), lymph vessel invasion (OR = 6.9, p < 0.001), and gross ETE (OR = 16.1, p = 0.001) were predictors of structural disease status; male gender (OR = 2.9, p = 0.011), lymph vessel invasion (OR = 2.8, p = 0.006), and incomplete resection margins (OR = 4.6, p < 0.001) were predictors of recurrent/persistent disease. Our study supports that the factors helping to tailor patient’s surgery are male gender, presence of PBs, gross ETE, and lateral compartment LNM. Together with pathological factors, lymph vessel invasion, venous invasion, necrosis, and incomplete surgical resection, should be taken into consideration regarding treatment and follow-up of patients.This study was supported by FCT, the Portuguese Foundation for Science and Technology through a PhD grant to E.T. SFRH/BD/143458/2019. This work was financed by FEDER—Fundo Europeu de Desenvolvimento Regional funds through the COMPETE 2020—Operacional Programme for Competitiveness and Internationalization (POCI), Portugal 2020. Additional funding by the European Regional Development Fund (ERDF) through the Operational Programme for Competitiveness and Internationalization— COMPETE2020, and Portuguese national funds via FCT, under project POCI-01-0145-FEDER-016390: CANCEL STEM and from the FCT under the project POCI-01-0145-FEDER-031438: The other faces of telomerase: Looking beyond tumor immortalization (PDTC/MED_ONC/31438/2017). Additional funding through the Sociedade Portuguesa de Endocrinologia, Diabetes e Metabolismo-BOLSA SPEDM PARA PROJECTO DE INVESTIGAÇÃO-2017

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Use of the industrial property system in Colombia (2018): A supervised learning application

The purpose of this paper is to establish ways to predict the spatial distribution of the use of the intellectual property system from information on industrial property applications and grants (distinctive signs and new creations) and copyright registrations in 2018. This will be done using supervised learning algorithms applied to information on industrial property applications and grants (trademarks and new creations) and copyright registrations in 2018. Within the findings, 4 algorithms were identified with a level of explanation higher than 80%: (i) Linear Regression, with an elastic network regularization; (ii) Stochastic Gradient Descent, with Hinge loss function, Ringe regularization (L2) and a constant learning rate; (iii) Neural Networks, with 1,000 layers, with Adam’s solution algorithm and 2,000 iterations; (iv) Random Forest, with 10 tree

cDNA cloning and functional expression of the α-d-galactose-binding lectin frutalin in escherichia coli

cDNA clones encoding frutalin, the α-d-galactose-binding lectin expressed in breadfruit seeds (Artocarpus incisa), were isolated and sequenced. The deduced amino acid sequences indicated that frutalin may be encoded by a family of genes. The NCBI database searches revealed that the frutalin sequence is highly homologous with jacalin and mornigaG sequences. Frutalin cDNA was re-amplified and cloned into the commercial expression vector pET-25b(+) for frutalin production in Escherichia coli. An experimental factorial design was employed to maximise the soluble expression of the recombinant lectin. The results indicated that temperature, time of induction, concentration of IPTG and the interaction between the concentration of IPTG and the time of induction had the most significant effects on the soluble expression level of recombinant frutalin. The optimal culture conditions were as follows: induction with 1 mM IPTG at 22°C for 20 h, yielding 16 mg/l of soluble recombinant frutalin. SDS-PAGE and Western blot analysis revealed that recombinant frutalin was successfully expressed by bacteria with the expected molecular weight (17 kDa). These analyses also showed that recombinant frutalin was mainly produced as insoluble protein. Recombinant frutalin produced by bacteria revealed agglutination properties and carbohydrate-binding specificity similar to the native breadfruit lectin.Fundação para a Ciência e a Tecnologia (FCT