Caffeine (CAF) and nicotine (NIC) are emerging contaminants and are among the most consumed substances in the world, making it crucial to monitor these contaminants. In this work, an alternative electrolyte, 2-hydroxyethylammonium acetate (2HEAA) was used for the development of an electroanalytical method for determination and quantification of CAF and NIC, simultaneously, using differential pulse voltammetry (DPV). The system with the 2HEAA electrolyte was characterized by cyclic voltammetry and electrochemical impedance spectroscopy, and the DPV parameters were optimized for the best conditions. The method was validated from a calibration curve obtained which showed limit of detection (LOD) of 0.82 and 6.26 μmol L 1 and limit of quantification (LOQ) of 2.73 and 20.8 μmol L-1 for CAF and NIC, respectively. In the precision analyses, values lower than 10% of relative standard deviation were obtained. In the presence of concomitant inorganic and organic species, the system proved to be selective in the determination of analytes. The method was used to determine the analytes in fortified samples (river water, synthetic urine and commercial milk), obtaining recoveries between 87.25 and 111.40%. The 2HEAA demonstrated high efficiency as an alternative electrolyte with good signal-to-noise ratio, increased analytical sensitivity of the method, in addition to presenting low cost and fast electrolyte preparation. (CAF NIC (NIC world work 2hydroxyethylammonium hydroxyethylammonium 2 HEAA (2HEAA simultaneously DPV. . (DPV) spectroscopy conditions LOD (LOD 082 0 82 0.8 626 6 26 6.2 LOQ (LOQ 273 73 2.7 208 20 8 20. L1 L- respectively analyses 10 species river water milk, milk , milk) 8725 87 25 87.2 11140 111 40 111.40% signaltonoise signal noise ratio preparation (DPV 08 0. 62 6. 27 7 2. 872 87. 1114 11 4 111.40 111.4 111.

This paper presents an analytical multiresidue method for the quantification of 7 nitroimidazoles, 19 anthelmintics, 3 amphenicols, and 4 dyes in poultry, pork, beef, horse, shrimp, and fish samples by isotope dilution ultra-high performance liquid chromatography coupled with tandem mass spectrometry (UHPLC-MS/MS) in a single 6 min run. Samples were prepared using a modified quick, easy, cheap, effective, rugged and safe (QuEChERS)-type extraction with ethyl acetate and Na2SO4-NaCl (2:1), concentration into dimethyl sulfoxide (DMSO), and defatting by liquid-liquid extraction (LLE) with n-hexane. No clean-up using solid-phase extraction (SPE) cartridges or dispersive solid-phase extraction (DSPE) was necessary. The linearity ranges (in μg kg-1) were 0.10-0.60 for chloramphenicol, 0.50-3.0 for dyes, 1.5-9.0 for nitroimidazoles, and 5.0-30.0 for the other drugs. The limits of quantitation (LOQ) were established at the lowest calibration curve levels. Except for chloramphenicol in the horse matrix, analyte recovery and reproducibility were satisfactory (recovery (fREC): 75.0 to 116.6%; coefficient of variation (CV): 1.2 to 29.9%). For the unapproved substances and the substances with a maximum residue level (MRL), respectively, the decision limits (CCα) were 0.14-4.10 and 5.28-1003.60 μg kg-1, while the detection capabilities (CCβ) were 0.13-3.33 and 5.46-11.56 μg kg-1. nitroimidazoles 1 anthelmintics amphenicols poultry pork beef shrimp ultrahigh ultra high UHPLCMS/MS UHPLCMSMS UHPLC MS/MS MS (UHPLC-MS/MS run quick easy cheap effective QuEChERStype QuEChERS type Na2SO4NaCl NaSONaCl Na2SO4 NaCl Na SO 21, 21 2 , (2:1) DMSO, DMSO (DMSO) liquidliquid LLE (LLE nhexane. nhexane n hexane. hexane n-hexane cleanup clean up solidphase solid phase SPE (SPE DSPE (DSPE necessary kg1 kg kg-1 0.100.60 010060 0.10 0.60 0 10 60 0.10-0.6 0.503.0 05030 0.50 3.0 50 0.50-3. 1.59.0 1590 1.5 9.0 5 9 1.5-9. 5.030.0 50300 5.0 30.0 30 5.0-30. drugs LOQ (LOQ levels matrix fREC (fREC) 750 75 75. 116.6% 1166 116 CV (CV) 12 1. 29.9%. 299 29.9% . 29 29.9%) MRL, MRL (MRL) respectively CCα (CCα 0.144.10 014410 0.14 4.10 14 0.14-4.1 5.281003.60 528100360 5.28 1003.60 28 1003 5.28-1003.6 kg1, 1, CCβ (CCβ 0.133.33 013333 0.13 3.33 13 33 0.13-3.3 5.4611.56 5461156 5.46 11.56 46 11 56 5.46-11.5 kg1. UHPLCMS MSMS NaSO Na2SO (2:1 (DMSO kg- 100 0.100.6 01006 010 0.1 060 0.6 0.10-0. 503 0.503. 0503 050 0.5 3. 0.50-3 59 1.59. 159 15 90 9. 1.5-9 030 5.030. 5030 5. 300 30. 5.0-30 (fREC 116.6 (CV 29.9 (MRL 144 0.144.1 01441 014 410 4.1 0.14-4. 281003 5.281003.6 52810036 528 5.2 100360 1003.6 5.28-1003. 133 0.133.3 01333 013 333 3.3 0.13-3. 4611 5.4611.5 546115 546 5.4 1156 11.5 5.46-11. (2: 0.100. 0100 01 0. 06 0.10-0 0.503 05 0.50- 1.59 1.5- 03 5.030 5.0-3 116. 29. 0.144. 0144 41 4. 0.14-4 28100 5.281003. 5281003 52 10036 1003. 5.28-1003 0.133. 0133 0.13-3 461 5.4611. 54611 54 115 11. 5.46-11 (2 0.100 0.10- 5.03 5.0- 0.144 0.14- 2810 5.281003 528100 5.28-100 0.133 0.13- 5.4611 5461 5.46-1 ( 281 5.28100 52810 5.28-10 5.461 5.46- 5.2810 5281 5.28-1 5.281 5.28-

ABSTRACT Water application to cultivated soil is often done without careful consideration in irrigated agriculture, leading to inefficient or suboptimal water usage. In many instances, the intricate relationship between soil, water, and plants, as well as the potential and limitations of irrigation systems, is overlooked. Sustainable irrigated agriculture necessitates the development of a soil moisture monitoring system that curtails water loss and enhances overall efficiency. This study aimed to develop and assess the efficiency of an intelligent system for monitoring soil moisture. The system comprises two stations: the first collects data on apparent soil moisture parameters using sensors, while the second transmits this data to a central processing station. The system precisely determines current soil moisture values, enabling estimation of the required irrigation water volume to meet the crop’s water demand based on field capacity. Results from the calibration curve of the sensors indicate that the system can measure current soil moisture precisely, aiding in irrigation management. For irrigated areas under unsaturated soil conditions, it is recommended to use tensiometers due to their higher reliability between field capacity and permanent wilting point, ensuring more accurate irrigation practices. usage instances plants systems overlooked stations station values crops crop s management conditions point practices

RESUMO Na agricultura irrigada, é comum a aplicação de água no solo cultivado sem critério, resultando em uso ineficiente ou não otimizado da água. Em muitos casos, a relação solo-água-planta, bem como as potencialidades e limitações dos sistemas de irrigação são ignoradas. A agricultura irrigada sustentável requer o desenvolvimento de um sistema de monitoramento da umidade do solo que evite a perda de água e melhore a eficiência do uso. O objetivo deste estudo foi desenvolver e avaliar a eficiência de um sistema inteligente de monitoramento da umidade do solo. O sistema é composto por duas estações: a primeira coleta os dados sobre parâmetros de umidade aparente do solo usando sensores, enquanto a segunda transmite esses dados para uma estação de processamento central. O sistema determina precisamente os valores atuais de umidade do solo, permitindo estimar o volume de água de irrigação necessário para atender à demanda hídrica da cultura com base na capacidade de campo. Os resultados da curva de calibração dos sensores indicam que o sistema pode medir com precisão a umidade do solo atual, auxiliando no manejo da irrigação. Para áreas irrigadas em condições de solo não saturado, recomenda-se o uso de tensiômetros devido à sua maior confiabilidade entre a capacidade de campo e o ponto de murcha permanente, garantindo práticas de irrigação mais precisas. critério casos soloáguaplanta, soloáguaplanta planta, planta solo-água-planta ignoradas estações central atual saturado recomendase recomenda se permanente precisas

The increase in the average temperature of the Earth due to excess CO2 and other greenhouse gases has caused glaciers to melt and sea levels to rise. The burning of fossil fuels is one of the main causes of this problem, so the use of biofuels is important for mitigating this environmental impact. In Brazil, biodiesel is mixed with mineral; however, irregularities have been detected, reducing the expected positive effects. Therefore, this study proposes the use of multivariate curve resolution with alternating least squares (MCR ALS) to quantify the content of methyl palm oil biodiesel in diesel blends and determine the concentration of the adulterant automotive lubricating oil in the blend. The model for quantifying biodiesel in diesel obtained R2 = 0.9997, root mean square error of calibration (RMSEC) = 0.56% (v v-1) and prediction (RMSEP) = 0.65% (v v-1), while the determination of adulteration in the biodiesel-diesel blend showed RMSEC = 0.67% (v v-1), RMSEP = 0.81% (v v-1) and R2 = 0.9992. These results demonstrate the ability of the models developed to predict both the content and quantity of possible adulterants in blends of palm oil biodiesel and mineral diesel, contributing to the quality control of this fuel. CO rise problem impact Brazil however detected effects Therefore MCR ALS R 09997 0 9997 0.9997 (RMSEC 056 56 0.56 v v1 1 v-1 (RMSEP 065 65 0.65 v1, , biodieseldiesel 067 67 0.67 081 81 0.81 09992 9992 0.9992 fuel 0999 999 0.999 05 5 0.5 v- 06 6 0.6 08 8 0.8 099 99 0.99 0. 09 9 0.9

Abstract Aldehydes are compounds in the atmosphere formed by the photochemical degradation of other organic compounds in the troposphere and can be emitted by natural or anthropogenic sources. (Objective) An analytical method was implemented to quantify aldehyde samples in matrices such as air and rainwater. (Methodology) Aldehyde sampling and analysis were conducted using method TO-11 from the United tates Environmental Protection Agency (EPA). Sampling was carried out by using adsorption cartridges coated with a 2,4-DNPH solution, forming a hydrazone with the aldehydes present in the rainwater and the air, which were tested using a liquid chromatograph coupled to a UV-visible detector (HPLC-UV/Vis). To validate the analysis technique and the analytical quality of the results, the following was determined: linearity, sensitivity, quantification limits, detection limits, repeatability, reproducibility, and recovery percentage. In the case of repeatability, the comparison of the Horwitz coefficient of variation was used with the percentages of relative standard deviation% RSD) of the samples. (Results) The detection and quantification limits obtained range between 0.18 μg/m3 and 3.20 μg/m3 for acetaldehyde and acrolein, respectively, while quantification limits are between 0.62 μg/m3 for acetaldehyde and 4.70 μg/m3 for heptanal, data that characterizes the method’s analytical quality. (Conclusions) In general, the analysis method for aldehydes showed linearity, with R2 values equal to or greater than 0.9991 for each calibration curve, and relative deviation percentage values less than 2.25 %, indicating good precision in the analysis.

Resumo Os aldeídos são compostos presentes na atmosfera que são formados pela degradação fotoquímica de outros compostos orgânicos na troposfera, estes podem ser emitidos por fontes naturais ou antrópicas. (Objetivo) no presente trabalho, foi implementado um método analítico para a quantificação de amostras de aldeído em matrizes como ar e água da chuva. (Metodologia) A amostragem e a análise de aldeído usaram a metodologia TO-11 da Agência de Proteção Ambiental dos Estados Unidos (EPA). As amostragens foram realizadas utilizando cartuchos de adsorção revestidos com uma solução de 2,4-DNFH, formando uma hidrazona com os aldeídos presentes na água da chuva e no ar. Elas foram analisadas usando um cromatógrafo líquido acoplado a um detector UV-Visível (HPLC-UV/Vis). Para a validação da técnica de análise e da qualidade analítica dos resultados, foram determinados: linearidade, sensibilidade, limites de quantificação, limites de detecção, repetibilidade, reprodutibilidade e porcentagem de recuperação. No caso da repetibilidade, foi utilizada a comparação do coeficiente de variação de Horwitz com os percentuais de desvio padrão relativo (% DER) das amostras. (Resultados) Os limites de detecção obtidos variam de 0,18 μg/m3 para acetaldeído e 3,20 μg/m3 no caso da acroleína, enquanto os limites de quantificação estão entre 0,62 μg/m3 para acetaldeído e 4,70 μg/m3 para o heptanal; dados que garantem a qualidade analítica do método. (Conclusões) De forma geral, o método de análise para aldeídos apresentou uma boa correlação linear, com valores de R2 igual ou superior a 0,9991 para cada curva de calibração, e valores percentuais de desvio relativo inferiores a 2,25%, o que indica boa acurácia na análise.

Resumen Los aldehídos son compuestos presentes en la atmósfera que se forman por la degradación fotoquímica de otros compuestos orgánicos en la tropósfera, estos pueden ser emitidos por fuentes naturales o antropogénicas. (Objetivo) En el presente trabajo se implementó un método analítico para la cuantificación de muestras de aldehídos en matrices como aire y agua de lluvia. (Metodología) El muestreo y el análisis de los aldehídos utilizó la metodología TO-11 de la Agencia de Protección Ambiental de los Estados Unidos (EPA). El muestreo se realizó mediante el uso de cartuchos de adsorción recubiertos con una disolución de 2,4-DNFH, formando una hidrazona con los aldehídos presentes en el agua de lluvia y en el aire. Estos fueron analizados mediante un cromatógrafo de líquido acoplado a un detector UV-Visible (HPLC-UV/Vis). Para la validación de la técnica de análisis y la calidad analítica de los resultados se determinaron: linealidad, sensibilidad, límites de cuantificación, límites de detección, repetibilidad, reproducibilidad y porcentaje de recuperación. En el caso de la repetibilidad, se utilizó la comparación del coeficiente de variación de Horwitz con los porcentajes de desviación estándar relativo (% DER) de las muestras. (Resultados) Los límites de detección obtenidos oscilan entre 0,18 μg/m3 para el acetaldehído y 3,20 μg/m3 en el caso de la acroleína, mientras que los límites de cuantificación están entre 0,62 μg/m3 para el acetaldehído y 4,70 μg/m3 para el heptanal; datos que garantizan la calidad analítica del método. (Conclusiones) En general, el método de análisis para los aldehídos mostró una buena correlación lineal, con valores de R2 igual o mayores a 0,9991 para cada curva de calibración, y valores de porcentajes de desvío relativo menores al 2,25 %, lo cual indica una buena precisión en el análisis.

Abstract Objective: Periventricular-intraventricular hemorrhage is the most common type of intracranial bleeding in newborns, especially in the first 3 days after birth. Severe periventricular-intraventricular hemorrhage is considered a progression from mild periventricular-intraventricular hemorrhage and is often closely associated with severe neurological sequelae. However, no specific indicators are available to predict the progression from mild to severe periventricular-intraventricular in early admission. This study aims to establish an early diagnostic prediction model for severe PIVH. Method: This study was a retrospective cohort study with data collected from the MIMIC-III (v1.4) database. Laboratory and clinical data collected within the first 24 h of NICU admission have been used as variables for both univariate and multivariate logistic regression analyses to construct a nomogram-based early prediction model for severe periventricular-intraventricular hemorrhage and subsequently validated. Results: A predictive model was established and represented by a nomogram, it comprised three variables: output, lowest platelet count and use of vasoactive drugs within 24 h of NICU admission. The model’s predictive performance showed by the calculated area under the curve was 0.792, indicating good discriminatory power. The calibration plot demonstrated good calibration between observed and predicted outcomes, and the Hosmer-Lemeshow test showed high consistency (p = 0.990). Internal validation showed the calculated area under a curve of 0.788. Conclusions: This severe PIVH predictive model, established by three easily obtainable indicators within the NICU, demonstrated good predictive ability. It offered a more user-friendly and convenient option for neonatologists. Objective Periventricularintraventricular Periventricular intraventricular newborns birth periventricularintraventricular periventricular sequelae However Method MIMICIII MIMIC III v1.4 v14 v v1 4 (v1.4 database 2 nomogrambased nomogram based validated Results output models s 0792 0 792 0.792 power outcomes HosmerLemeshow Hosmer Lemeshow p 0.990. 0990 0.990 . 990 0.990) 0788 788 0.788 Conclusions ability userfriendly user friendly neonatologists v1. (v1. 079 79 0.79 099 0.99 99 078 78 0.78 (v1 07 7 0.7 09 0.9 9 (v 0.

Abstract Objective: Reliably prediction models for coronary artery abnormalities (CAA) in children aged > 5 years with Kawasaki disease (KD) are still lacking. This study aimed to develop a nomogram model for predicting CAA at 4 to 8 weeks of illness in children with KD older than 5 years. Methods: A total of 644 eligible children were randomly assigned to a training cohort (n = 450) and a validation cohort (n = 194). The least absolute shrinkage and selection operator (LASSO) analysis was used for optimal predictors selection, and multivariate logistic regression was used to develop a nomogram model based on the selected predictors. Area under the receiver operating characteristic curve (AUC), calibration curves, Hosmer-Lemeshow test, Brier score, and decision curve analysis (DCA) were used to assess model performance. Results: Neutrophil to lymphocyte ratio, intravenous immunoglobulin resistance, and maximum baseline z-score ≥ 2.5 were identified by LASSO as significant predictors. The model incorporating these variables showed good discrimination and calibration capacities in both training and validation cohorts. The AUC of the training cohort and validation cohort were 0.854 and 0.850, respectively. The DCA confirmed the clinical usefulness of the nomogram model. Conclusions: A novel nomogram model was established to accurately assess the risk of CAA at 4–8 weeks of onset among KD children older than 5 years, which may aid clinical decisionmaking. Objective (CAA (KD lacking Methods 64 n 450 194. 194 . 194) (LASSO AUC, , (AUC) curves HosmerLemeshow Hosmer Lemeshow test score (DCA performance Results ratio resistance zscore z 25 2 2. cohorts 0854 0 854 0.85 0850 850 0.850 respectively Conclusions 48 4– decisionmaking 6 45 19 (AUC 085 85 0.8 1 08 0.

Abstract: This study attempts to obtain the approximate fatigue vulnerability of a steel arch bridge from the Colombian national road network. It establishes the interaction between the demand and the available capacity through the Weibull probability equation, and an AASHTO remaining-time equation indicated in (FHWA, 2015). However, the available capacity in terms of the S-N curve obtained from available international references was modified to account for the effects of corrosion present in elements and/or joints in the bridge. The load demand was modeled as the controlled action of the fatigue truck reported in AASHTO, which was systematically located on a structural model represented by Shell and Frame type finite elements, which represented the information available in drawings (in the current Colombian bridge management system), and the one obtained from structural survey activities. The structural model was further calibrated by a parametric study on the modulus of elasticity of steel, which included the minimization of the error difference in the vertical deflections of a bridge load test, keeping the magnitude within the expected ranges established in a protocol. Such reports of actual deflections were achieved using distance meters at important points of the bridge. This model allowed for estimating the magnitude of stresses in the structural elements of the bridge, especially in an area of interest for the study where chemical and physical elements of structural deficiency were determined. The results show an inverse relationship between the probability of failure and remaining service life. The effect of corrosion on the remaining capacity and the probability of failure of the structural elements is clear.

Resumen: El presente estudio busca obtener la vulnerabilidad aproximada a fatiga de un Puente de acero en arco que pertenece a la red de vías nacionales de Colombia. Se establece la interacción entre la demanda y la capacidad disponible de resistencia através de la ecuación de probabilidad de Weibull y la ecuación indicada en ela norma AASHTO para vida remanente en fatiga (FHWA, 2015). Sin embargo, la capacidad disponible con base en las curvas S-N de capacidad disponible, se modificaron para poder tener en cuenta los efectos de corrosión presentes en elementos y/o conexiones del puente. La carga se modeló mediante el camion de fatiga especificado en la AASHTO, el cual fue localizado de manera sistemática sobre los nudos de un modelo hecho en elementos finitos tipo Shell and Frame. Este modelo se construyó basado en planos disponibles y de algunas actividades de levantamiento estructural en campo. El modelo estructural fue calibrado mediante un proceso paramétrico en el modulo de elasticidad del acero, el cual minimizó el error entre las deflexiones verticales modealdas y las determinadas mediante una prueba de carga sobre el puente real. Las deflexiones reales fueron reportadas mediane el uso de distanciómetros localizados en puntos seleccionados del puente. El modelo calibrado sirvió para estimar la magnitud de los rangos de esfuerzo en los elementos modelados del Puente, especialmente en la zona de estudio, donde se determinó la presencia de corrosión. Los resultados presentan una relación inversa entre la probabilidad de falla por fatiga, y la vida remanente estimada por efectos de fatiga. Se pudo determinar con claridad el efecto de la corrosión en la capacidad del puente y la probabilidad de falla asociada.

Abstract Objective We aimed to assess the significance of rENE and creat a predictive tool (nomogram) for estimating Overall Survival (OS) in locoregionally advanced Nasopharyngeal Carcinoma (NPC) patients with Lymph Node Metastasis (LNM) based on their clinical characteristics and Radiologic Extranodal Extension (rENE). Methods Five hundred and sixty-nine NPC patients with LNM were randomly divided into training and validation groups. Significant factors were identified using univariate and multivariate analyses in the training cohort. Then, the nomogram based on the screening results was established to predict the Overall Survival (OS). Calibration curves and the Concordance index (C-index) gauged predictive accuracy and discrimination. Receiver Operating Characteristic (ROC) analysis assessed risk stratification, and clinical utility was measured using Decision Curve Analysis (DCA). The nomogram's performance was validated for discrimination and calibration in an independent validation cohort. Results A total of 360 (63.2%) patients were present with radiologic extranodal extension at initial diagnosis. Patients with rENE had significantly lower OS than other patients. Multivariate analysis identified the five factors, including rENE, for the nomogram model. The C-index was 0.75 (0.71-0.78) in the training cohort and 0.76 (0.69-0.83) in the validation cohort. Notably, the nomogram outperformed the 8th TNM staging system, as evident from the higher AUC values (0.77 vs. 0.60 for 2 year and 0.75 vs. 0.65 for 3 year) and well-calibrated calibration curves. Decision curve analysis indicated improved Net Benefit (NB) with the nomogram for predicting OS. The log-rank test confirmed significant survival distinctions between risk groups in both training and validation cohorts. Conclusions We demonstrated the prognostic value of rENE in nasopharyngeal carcinoma and developed a nomogram based on rENE and other factors to provide individual prediction of OS for locoregionally advanced nasopharyngeal carcinoma with lymph node metastasis. Level of evidence: III. (nomogram (OS (NPC (LNM rENE. . (rENE) sixtynine sixty nine Then Cindex C (C-index ROC (ROC stratification DCA. DCA (DCA) nomograms s 36 63.2% 632 63 (63.2% diagnosis model 075 0 75 0.7 0.710.78 071078 0.71 0.78 71 78 (0.71-0.78 076 76 0.690.83 069083 0.69 0.83 69 83 (0.69-0.83 Notably th system 0.77 077 77 (0.7 vs 060 60 0.6 065 65 wellcalibrated well calibrated NB (NB logrank log rank cohorts metastasis evidence III (rENE (DCA 63.2 6 (63.2 07 7 0. 710 0.710.7 07107 071 078 (0.71-0.7 690 0.690.8 06908 069 083 0.8 8 (0.69-0.8 (0. 06 63. (63. 0.710. 0710 (0.71-0. 0.690. 0690 08 (0.69-0. (0 (63 0.710 (0.71-0 0.690 (0.69-0 ( (6 (0.71- (0.69- (0.71 (0.69 (0.6

ABSTRACT The performance of colorimetric methods for P quantification has been overlooked by researchers for decades. We investigated the performance of two blue colorimetric methods for P quantification, Braga and Defelipo (B&D) and Murphy and Riley (M&R), using two commonly soil P extractants, Mehlich-1 (M1) and Mehlich-3 (M3). Specifically, we evaluated the color development time and its stability in different soil extractant solution proportions (1:1 or 1:4 v/v), the optimum wavelength, limits of detection, and element quantification. Our results indicate that M3 leads to lower limits of detection and quantification for both colorimetric methods, particularly for B&D. For M1, the volumetric ratio (1:1 or 1:4) did not influence color development and both B&D and M&R methods showed a fast color development. However, B&D showed greater color stability (from 5 to 600 min) and an optimum wavelength of 711 nm, while M&R was stable from 27 to 600 min an optimum wavelength of 889 nm. For M3 soil extractant, there are important issues, such as M&R being unstable and B&D presenting slow color development. In addition, the spectral profile obtained from soil extractant was different from the one obtained by the calibration curve without soil for both M&R and B&D. Therefore, the adoption of original methods on P quantification in M3 extracting solution represents a potential source of error, leading to wrong P fertilizer recommendations. Thus, the best option for P quantification in M3 extracts seems to be the use of Inductively Coupled Plasma Atomic Emission Spectrometry (ICP-AES). decades BD B D (B&D M&R, MR , M R (M&R) extractants Mehlich1 Mehlich 1 Mehlich- M1 (M1 Mehlich3 3 M3. . (M3) Specifically 11 (1: 14 4 1: v/v, vv v/v v v/v) However 60 71 nm 2 88 issues addition Therefore error recommendations Thus ICPAES. ICPAES ICP AES (ICP-AES) (M&R (M (M3 (1 6 7 8 (ICP-AES (

Abstract Objective The aim of the study was to create two consensus nomograms for predicting Overall Survival (OS) and Cancer-Specific Survival (CSS) in adults with papillary Renal Cell Carcinoma (pRCC). Methods Using the Surveillance, Epidemiology, and End Results databases, a retrospective analysis of 1,074 adults with pRCC from 2004 to 2015 was performed. These patients were then randomly divided into two independent cohorts with a ratio of 7:3 (training cohort: 752; validation cohort: 322). In a retrospective analysis of 752 patients from the training cohort, independent prognostic variables affecting OS and CSS were found. R software was used to create prognostic nomograms based on the findings of Cox regression analysis. The performance of the nomograms was assessed using the Concordance Index (C-index), the Area Under Curve (AUC), a calibration curve, and Decision Curve Analysis (DCA). Data from the 107 postoperative pRCC patients at the Affiliated Hospital of Xuzhou Medical University were used for external validation of the nomogram. Results For OS and CSS, the C-indices and AUCs of the training cohort and the validation cohort indicated that the model had excellent discrimination. The DCA demonstrated that the model was clinically applicable, and the calibration curves in the internal and external validations showed that the model's accuracy was high. Conclusion The authors developed and validated a prognostic nomogram that accurately predicted the 3-, 5-, and 8-year OS and CSS of adults with pRCC. Clinicians can use this knowledge to direct the clinical management and counseling of patients with pRCC. (OS CancerSpecific Cancer Specific (CSS . (pRCC) Surveillance Epidemiology databases 1074 1 074 1,07 200 201 performed 73 7 3 7: 322. 322 322) 75 found Cindex, Cindex C index , (C-index) AUC, AUC (AUC) curve DCA. (DCA) 10 Cindices indices discrimination applicable models s high 3, 3- 5, 5 5- 8year year 8 (pRCC 07 1,0 20 32 (C-index (AUC (DCA 0 1, 2

Abstract Background To explore the correlation of pre-treatment Hemoglobin-Albumin-Lymphocyte-Platelet (HALP) score with the prognosis of patients with advanced Non-Small Cell Lung Cancer (NSCLC) undergoing first-line conventional platinum-based chemotherapy. Methods In this retrospective cohort study, 203 patients with advanced NSCLC were recruited from January 2017 to December 2021. The cut-off value for the HALP score was determined by Receiver Operating Characteristic (ROC) curve analysis. The baseline characteristics and blood parameters were recorded, and the Log-rank test and Kaplan-Meier curves were applied for the survival analysis. In the univariate and multivariate analyses, the Cox regression analysis was carried out. The predictive accuracy and discriminative ability of the nomogram were determined by the Concordance index (C-index) and calibration curve and compared with a single HALP score by ROC curve analysis. Results The optimal cut-off value for the HALP score was 28.02. The lower HALP score was closely associated with poorer Progression-Free Survival (PFS) and Overall Survival (OS). The male gender and other pathological types were associated with shorter OS. Disease progression and low HALP were correlated with shorter OS and PFS. In addition, nomograms were established based on HALP scores, gender, pathology type and efficacy rating, and used to predict OS. The C-index for OS prediction was 0.7036 (95% CI 0.643 to 0.7643), which was significantly higher than the C-index of HALP at 6-, 12-, and 24-months. Conclusion The HALP score is associated with the prognosis of advanced NSCLC patients receiving conventional platinum-based chemotherapy, and the nomogram established based on the HALP score has a better predictive capability for OS. pretreatment pre treatment HemoglobinAlbuminLymphocytePlatelet Hemoglobin Albumin Lymphocyte Platelet (HALP NonSmall Non Small (NSCLC firstline first line platinumbased platinum chemotherapy study 20 201 2021 cutoff cut off (ROC recorded Logrank Log rank KaplanMeier Kaplan Meier analyses out Cindex C (C-index 2802 28 02 28.02 ProgressionFree Progression Free PFS (PFS . (OS) addition scores rating 07036 0 7036 0.703 95% 95 (95 0643 643 0.64 0.7643, 07643 0.7643 , 7643 0.7643) 6, 6 6- 12, 12 12- 24months. 24months months 24 months. 24-months 2 202 280 28.0 (OS 0703 703 0.70 9 (9 064 64 0.6 0764 0.764 764 1 28. 070 70 0.7 ( 06 0. 076 0.76 76 07 7

Abstract Background Atrial fibrillation (AF) is a risk factor for cerebral ischemia. Identifying the presence of AF, especially in paroxysmal cases, may take time and lacks clear support in the literature regarding the optimal investigative approach; in resource-limited settings, identifying a higher-risk group for AF can assist in planning further investigation. Objective To develop a scoring tool to predict the risk of incident AF in the poststroke follow-up. Methods A retrospective longitudinal study with data collected from electronic medical records of patients hospitalized and followed up for cerebral ischemia from 2014 to 2021 at a tertiary stroke center. Demographic, clinical, laboratory, electrocardiogram, and echocardiogram data, as well as neuroimaging data, were collected. Stepwise logistic regression was employed to identify associated variables. A score with integer numbers was created based on beta coefficients. Calibration and validation were performed to evaluate accuracy. Results We included 872 patients in the final analysis. The score was created with left atrial diameter ≥ 42 mm (2 points), age ≥ 70 years (1 point), presence of septal aneurysm (2 points), and score ≥ 6 points at admission on the National Institutes of Health Stroke Scale (NIHSS; 1 point). The score ranges from 0 to 6. Patients with a score ≥ 2 points had a fivefold increased risk of having AF detected in the follow-up. The area under the curve (AUC) was of 0.77 (0.72–0.85). Conclusion We were able structure an accurate risk score tool for incident AF, which could be validated in multicenter samples in future studies. (AF cases approach resourcelimited resource limited settings higherrisk higher investigation followup. followup follow up. follow-up 201 202 center Demographic clinical laboratory electrocardiogram variables coefficients accuracy 87 analysis 4 ( points, , points) 7 point, point point) NIHSS (NIHSS point. . AUC (AUC 077 77 0.7 0.72–0.85. 072085 0.72–0.85 72 85 (0.72–0.85) studies 20 8 07 0. 07208 0.72–0.8 (0.72–0.85 0720 0.72–0. (0.72–0.8 072 0.72–0 (0.72–0. 0.72– (0.72–0 0.72 (0.72– (0.72 (0.7 (0. (0

Resumo Antecedentes Fibrilação atrial (FA) é um fator de risco para isquemia cerebral. Identificar a presença de FA, especialmente em casos paroxísticos, pode demandar tempo, e não há fundamentos claros na literatura quanto ao melhor método de proceder à investigação; em locais de parcos recursos, identificar um grupo de mais alto risco de FA pode auxiliar no planejamento da investigação complementar. Objetivo Desenvolver uma ferramenta de escore para prever o risco de FA no acompanhamento após acidente vascular cerebral (AVC). Métodos Estudo longitudinal retrospectivo, com dados coletados dos prontuários eletrônicos de pacientes hospitalizados e acompanhados ambulatorialmente por isquemia cerebral, de 2014 a 2021, em um centro de AVC terciário. Foram coleados dados demográficos, clínicos, laboratoriais, de eletrocardiograma e ecocardiograma, além de dados de neuroimagem. Mediante uma regressão logística por stepwise, foram identificadas variáveis associadas. Um escore com números inteiros foi criado com base nos coeficientes beta. Calibração e validação foram realizadas para avaliar a precisão. Resultados Foram incluídos 872 pacientes na análise final. O escore foi criado com diâmetro de átrio esquerdo ≥ 42 mm (2 pontos), idade ≥ 70 anos (1 ponto), presença de aneurisma septal (2 pontos) e pontuação à admissão ≥ 6 na escala de AVC dos National Institutes of Health (National Institutes of Health Stroke Scale, NIHSS, em inglês; 1 ponto). O escore tem pontuação que varia de 0 a 6. Pacientes com escore ≥ 2 pontos tiveram cinco vezes mais risco de terem FA detectada no acompanhamento. A área sob a curva (area under curve, AUC, em inglês) foi de 0.77 (0.72–0.85). Conclusão Pudemos estruturar uma ferramenta precisa de escore de risco de FA, a qual poderá ser validada em amostras multicêntricas em estudos futuros. (FA paroxísticos tempo recursos complementar AVC. . (AVC) retrospectivo 201 2021 terciário demográficos clínicos laboratoriais ecocardiograma neuroimagem stepwise associadas beta precisão 87 final 4 ( pontos, , 7 ponto, ponto ponto) Scale NIHSS inglês ponto. area curve AUC 077 77 0.7 0.72–0.85. 072085 0.72–0.85 72 85 (0.72–0.85) futuros (AVC 20 202 8 07 0. 07208 0.72–0.8 (0.72–0.85 0720 0.72–0. (0.72–0.8 072 0.72–0 (0.72–0. 0.72– (0.72–0 0.72 (0.72– (0.72 (0.7 (0. (0

Transarterial chemoembolization (TACE) is an established therapeutic strategy for intermediate stage Barcelona Clinic Liver Cancer (BCLC) hepatocellular carcinoma (HCC). However, patients who are early refractory to TACE may not benefit from repeated TACE treatment. Our primary objective was to assess the diagnostic value of inflammatory markers in identifying early TACE refractory for patients with early (BCLC 0 and A) or intermediate (BCLC B) stage HCC. We retrospectively reviewed the HCC patients who underwent TACE as the initial treatment in two hospitals. Patients with early TACE refractoriness had significantly poorer median overall survival (OS) (16 vs 40 months, P<0.001) and progression-free survival (PFS) (7 vs 23 months, P<0.001) compared to TACE non-refractory patients. In the multivariate regression analysis, tumor size (P<0.001), bilobular invasion (P=0.007), high aspartate aminotransferase-to-platelet ratio index (APRI) (P=0.007), and high alpha fetoprotein (AFP) level (P=0.035) were independent risk factors for early TACE refractoriness. The predictive model showcasing these factors exhibited high ability proficiency, with an area under curve (AUC) of 0.833 (95%CI=0.774-0.892) in the training cohort, 0.750 (95%CI: 0.640-0.861) in the internal-validation cohort, and 0.733 (95%CI: 0.594-0.872) in the external-validation cohort. Calibration curve analysis revealed good agreement between the actual and predicted probabilities of early TACE refractoriness. Our preliminary study estimated the potential value of inflammatory markers in predicting early TACE refractoriness and provides a predictive model to assist in identifying patients who may not benefit from repeat TACE treatment. (TACE BCLC . (HCC) However A B hospitals OS (OS 16 (1 4 months P<0.001 P0001 P 001 progressionfree progression free PFS (PFS 7 ( 2 nonrefractory non P<0.001, , (P<0.001) P=0.007, P0007 P=0.007 007 (P=0.007) aminotransferasetoplatelet aminotransferase platelet APRI (APRI AFP (AFP P=0.035 P0035 035 (P=0.035 proficiency AUC (AUC 0833 833 0.83 95%CI=0.7740.892 95CI07740892 CI 95%CI=0.774 0.892 95 774 892 (95%CI=0.774-0.892 cohort 0750 750 0.75 95%CI 95CI (95%CI 0.6400.861 06400861 0.640 0.861 640 861 0.640-0.861 internalvalidation internal validation 0733 733 0.73 0.5940.872 05940872 0.594 0.872 594 872 0.594-0.872 externalvalidation external (HCC 1 P<0.00 P000 00 (P<0.001 P=0.00 (P=0.007 P=0.03 P003 03 (P=0.03 083 83 0.8 7740 95%CI=0.7740.89 95CI0774089 95CI0774 95%CI=0.77 0892 0.89 9 77 89 (95%CI=0.774-0.89 075 75 0.7 6400 0.6400.86 0640086 0640 0.64 0861 0.86 64 86 0.640-0.86 073 73 5940 0.5940.87 0594087 0594 0.59 0872 0.87 59 87 0.594-0.87 P<0.0 P00 (P<0.00 P=0.0 (P=0.00 (P=0.0 08 8 0. 95%CI=0.7740.8 95CI077408 95CI077 95%CI=0.7 089 (95%CI=0.774-0.8 07 0.6400.8 064008 064 0.6 086 6 0.640-0.8 0.5940.8 059408 059 0.5 087 5 0.594-0.8 P<0. P0 (P<0.0 P=0. (P=0. 95%CI=0.7740. 95CI07740 95CI07 95%CI=0. (95%CI=0.774-0. 0.6400. 06400 06 0.640-0. 0.5940. 05940 05 0.594-0. P<0 (P<0. P=0 (P=0 95%CI=0.7740 95CI0 95%CI=0 (95%CI=0.774-0 0.6400 0.640-0 0.5940 0.594-0 P< (P<0 P= (P= 95%CI= (95%CI=0.774- 0.640- 0.594- (P< (P (95%CI=0.774 (95%CI=0.77 (95%CI=0.7 (95%CI=0. (95%CI=0 (95%CI=

ABSTRACT Purpose: To validate the Barcelona magnetic resonance imaging predictive model (BCN-MRI PM) in men with pre-biopsy multiparametric MRI (mpMRI) reported with the Prostate Imaging Reporting and Data System (PI-RADS) v2.1, followed by transrectal and transperineal prostate biopsies. Materials and Methods: Prospective analysis of 3,264 men with PSA >3.0 ng/mL and/or abnormal digital rectal examination who were referred to ten participant centers in the csPCa early detection program of Catalonia (Spain), between 2021 and 2023. MpMRI was reported with the PI-RADS v2.1, and 2- to 4-core MRI-transrectal ultrasound (TRUS) fusion-targeted biopsy of suspected lesions and/or 12-core systematic biopsy were conducted. 2,295 (70.3%) individuals were referred to six centers for transrectal prostate biopsies, while 969 (39.7%) were referred to four centers for transperineal prostate biopsies. CsPCa was classified whenever the International Society of Urologic Pathology grade group was 2 or higher. Results: CsPCa was detected in 41% of transrectal prostate biopsies and in 45.9% of transperineal prostate biopsies (p <0.016). Both BCN-MRI PM calibration curves were within the ideal correlation between predicted and observed csPCa. Areas under the curve and 95% confidence intervals were 0.847 (0.830-0.857) and 0.830 (0.823-0.855), respectively (p = 0.346). Specificities corresponding to 95% sensitivity were 37.6 and 36.8%, respectively (p = 0.387). The Net benefit of the BCN-MRI PM was similar with both biopsy methods. Conclusions: The BCN-MRI PM has been successfully validated when mpMRI was reported with the PI-RADS v2.1 and prostate biopsies were conducted via the transrectal and transperineal route. Purpose BCNMRI BCN prebiopsy pre (mpMRI PIRADS PI RADS (PI-RADS v21 v v2 1 Methods 3264 3 264 3,26 30 0 >3. ngmL ng mL andor Spain, Spain , (Spain) 202 2023 4core core 4 MRItransrectal TRUS (TRUS fusiontargeted fusion targeted 12core 12 2295 295 2,29 70.3% 703 70 (70.3% 96 39.7% 397 39 7 (39.7% higher Results 41 459 45 9 45.9 p <0.016. 0016 <0.016 . 016 <0.016) 95 0847 847 0.84 0.8300.857 08300857 0.857 830 857 (0.830-0.857 0830 0.83 0.8230.855, 08230855 0.823 0.855 823 855 (0.823-0.855) 0.346. 0346 0.346 346 0.346) 376 37 6 37. 368 36 8 36.8% 0.387. 0387 0.387 387 0.387) methods Conclusions v2. route 326 26 3,2 >3 (Spain 20 229 29 2,2 70.3 (70.3 39.7 (39.7 45. 001 <0.01 01 084 84 0.8 8300 0.8300.85 0830085 0857 0.85 83 85 (0.830-0.85 083 8230 0.8230.855 0823085 0823 0.82 0855 82 (0.823-0.855 034 0.34 34 36.8 038 0.38 38 32 3, > 22 2, 70. (70. 39. (39. 00 <0.0 08 0. 0.8300.8 083008 085 (0.830-0.8 0.8230.85 082308 082 (0.823-0.85 03 0.3 36. (70 (39 <0. 0.8300. 08300 (0.830-0. 0.8230.8 08230 (0.823-0.8 (7 (3 <0 0.8300 (0.830-0 0.8230. (0.823-0. ( < (0.830- 0.8230 (0.823-0 (0.830 (0.823- (0.83 (0.823 (0.8 (0.82 (0. (0