Effects of light quality and intensity on phycobiliprotein productivity in two Leptolyngbya strains isolated from southern Bahia's Atlantic Forest.

Cyanobacterial phycocyanin and phycoerythrin are gaining commercial interest due to their nutrition and healthcare values. This research analyzed the biomass accumulation and pigment production of two strains of Leptolyngbya under different combinations of light colors and intensities. The results showed that while Leptolyngbya sp.4 B1 (B1) produced all phycobiliproteins, Leptolyngbya sp.5 F2 (F2) only had phycocyanin and allophycocyanin. Both the color of the light and its light intensity affect the biomass accumulation and phycoerythrin concentration in strain B1. Although white light at medium intensity (50 µmol m-2 s-1) causes greater biomass accumulation (1.66 ± 0.13 gDW L-1), low-intensity (25 µmol m-2 s-1) green light induces lower biomass accumulation with twice the pigment content (87.70 ± 2.46 mg gDW -1), culminating in 71% greater productivity. In contrast, for the F2 strain, light intensity positively influenced biomass and pigment accumulation, being observed 2.25 ± 0.10 gDW L-1 under white light at 100 µmol m-2 s-1 and higher phycocyanin concentration (138.38 ± 3.46 mg gDW -1) under red light at 100 µmol m-2 s-1. These findings provide insights into optimizing the growth conditions by altering the intensity and wavelength of light for future production of phycocyanin and phycoerythrin from local cyanobacteria.

Machine Learning Models and Applications for Early Detection.

From the various perspectives of machine learning (ML) and the multiple models used in this discipline, there is an approach aimed at training models for the early detection (ED) of anomalies. The early detection of anomalies is crucial in multiple areas of knowledge since identifying and classifying them allows for early decision making and provides a better response to mitigate the negative effects caused by late detection in any system. This article presents a literature review to examine which machine learning models (MLMs) operate with a focus on ED in a multidisciplinary manner and, specifically, how these models work in the field of fraud detection. A variety of models were found, including Logistic Regression (LR), Support Vector Machines (SVMs), decision trees (DTs), Random Forests (RFs), naive Bayesian classifier (NB), K-Nearest Neighbors (KNNs), artificial neural networks (ANNs), and Extreme Gradient Boosting (XGB), among others. It was identified that MLMs operate as isolated models, categorized in this article as Single Base Models (SBMs) and Stacking Ensemble Models (SEMs). It was identified that MLMs for ED in multiple areas under SBMs' and SEMs' implementation achieved accuracies greater than 80% and 90%, respectively. In fraud detection, accuracies greater than 90% were reported by the authors. The article concludes that MLMs for ED in multiple applications, including fraud, offer a viable way to identify and classify anomalies robustly, with a high degree of accuracy and precision. MLMs for ED in fraud are useful as they can quickly process large amounts of data to detect and classify suspicious transactions or activities, helping to prevent financial losses.

Osteocalcina en el fluido gingival crevicular de pacientes com periodontitis crónica progresiva / Osteocalcin in Gingival Crevicular Fluid of Progressive Chronic Periodontitis Patients

La Osteocalcina, es una pequeña proteína no colágena, fijadora de calcio, muy abundante en los tejidos mineralizados, es sintetizada por los osteoblastos y tiene un importante rol en la regulación de la destrucción y formación ósea, puede inhibir la síntesis de colágeno promoviendo la reabsorción de hueso. Se ha relacionado elevados niveles de osteocalcina con periodos de rápida destrucción ósea como osteoporosis y en la reparación de las fracturas y con activa destrucción ósea en la enfermedad periodontal. El objetivo de este trabajo es determinar los niveles de osteocalcina en el FGC de pacientes con periodontitis crónica progresiva. Material y método: en 14 sitios activos y 14 sitios inactivos determinados de acuerdo con el método de tolerancia se midió los niveles de osteocalcina y se compararon entre si. Los niveles se establecieron utilizando N- MID Osteocalcin ELISA, los resultados se analizaron usando el programa Stata 7.0 y el student-test para muestras no paramétricas. Resultados: se determinó que los niveles de osteocalcina en los sitios activos eran elevados y la diferencia con los sitios inactivos era estadísticamente significativa ( p = 0,001) después del tratamiento los niveles eran muy similares. Conclusiones: los elevados niveles de osteocalcina en los sitios activos permiten sugerir su utilización como predictor de destrucción ósea alveolar.

Osteocalcin is a small protein fixative of calcium, is the most abundant non collagen protein in mineralized tissues, is synthesized primarily by osteoblasts and has an important role in regulating bone formation and destruction. The osteocalcin can inhibit the synthesis of collagen to promote the resorption of bone. It has been shown high levels of osteocalcin during periods of rapid bone loss as osteoporosis and in the repair of fractures also has been associated with active bone loss in periodontal disease. The aim of this study is to determine levels of Osteocalcin in gingival crevicular fluid of progressive chronic periodontitis patients. Material and method in 14 active sites and 14 sites inactive determine by the tolerance method. Osteocalcin levels were measured and compared with each other. The levels were determined by N-MID Osteocalcin ELISA, the statistical data was analyzed by Stata 7.0 using the student-test for unpaired samples. Results: the levels of osteocalcin in active sites were significantly higher than in the inactive sites and difference was statistically significant (p = 0001) after periodontal treatment, levels were ver y similar in both groups. Conclusions: this finding suggest that Osteocalcin could be a good marker for future attachment and alveolar boneloss.

Comportamiento de las neoplasias de glándulas salivales entre 2001 y 2003

Se realizó un estudio descriptivo, retrospectivo y de corte longitudinal de 82 pacientes operados de tumores de glándulas salivales en el Hospital Provincial Clínico Quirúrgico Docente ´´Celia Sánchez Manduley´´en Manzanillo, Granma, en el periodo comprendido de enero de 2001 a diciembre del 2003 . Existió un predominio a partir de la cuarta década de la vida, el sexo femenino fue el más afectado. El aumento de volumen constituyó el signo principal , predominando la neoplasias benignas(adenoma pleomorfo) siendo la parótida la mas afectada. Al contrario de otras series el carcinoma epidermoide y el adenoquistico fueron los más frecuentes. La parotidectomía subtotal resultó la intervención más utilizada(AU)

Gastrectomía total paliative en el tratamiento del cáncer gástrico / Palliative total gastrectomy in the treatment of gastric cancer

Se exponen los resultados obtenidos con la tuilización de la gastrectomíoa total con criterio paliativo en carcinoma avanzados de estómago, en etapa de evasión lesional del órgano. Por tratarse de una casuística reducida, no se realiza un análisis estadístico sino un estudio individual, destacándose que con muy baja orbilidad, se han logrado resultados aceptables sobre todo en cuanto a calidad de sobrevida

Gastrectomía total paliative en el tratamiento del cáncer gástrico / Palliative total gastrectomy in the treatment of gastric cancer

Se exponen los resultados obtenidos con la tuilización de la gastrectomíoa total con criterio paliativo en carcinoma avanzados de estómago, en etapa de evasión lesional del órgano. Por tratarse de una casuística reducida, no se realiza un análisis estadístico sino un estudio individual, destacándose que con muy baja orbilidad, se han logrado resultados aceptables sobre todo en cuanto a calidad de sobrevida (AU)