ABSTRACT The aim of this study was to develop visible and near-infrared spectroscopy (Vis-NIRS) calibration models for predicting the content of organic carbon (OC), total nitrogen (N), clay + silt, and pH values in soils from Argentina, employing different mathematical preprocessing techniques for spectral data. A total of 154 soil samples with contrasting physicochemical characteristics was selected, dried, and sieved to 2 mm prior to the analysis of OC, N, pH, and clay + silt using reference methods. Subsequently, the Vis-NIR spectrum (400 to 2500 nm) of each sample was obtained in reflectance mode. The sample set was randomly divided into two groups: one for calibration model development (80%) and the other for model validation (20%). Eight preprocessing techniques for spectral information were employed, and the best one for each parameter studied was selected based on the criteria of achieving the minimum standard error of cross-validation (EECV), maximum coefficient of determination of cross-validation (R2cv), and maximum residual predictive deviation (RPD). Calibration models were obtained using modified partial least squares regression (MPLS) and five-fold cross-validation. The best models for predicting OC and N were obtained with the raw spectra (RPD=4.69 and 3.65 respectively); for pH, the best model was obtained using the standard normal variate preprocessing technique with the second derivative (RPD=2.27), and for clay + silt, the best model was obtained with multiple scattering correction and second derivative (RPD=2.83). The performance of the models applied to the calibration and testing groups was similar. The results indicate that the appropriate choice of spectral data preprocessing technique can optimize calibration for the prediction. Vis-NIRS is a valuable tool for soil monitoring in Argentina, complementing traditional analysis methods.

RESUMEN El objetivo de este estudio fue desarrollar modelos de calibración por espectroscopía visible e infrarrojo cercano (Vis-NIRS) para la predicción del contenido de carbono orgánico (CO), nitrógeno total (N), arcilla+li-mo, y pH en suelos de Argentina, aplicando diferentes técnicas de pretratamiento matemático de los datos espectrales. Se seleccionaron 154 muestras de suelo con características físico químicas contrastantes, se secaron y tamizaron a 2 mm previo al análisis de CO, N, pH y arcilla+limo mediante métodos de referencia. Luego se obtuvo el espectro Vis-NIR (400 a 2500 nm) de cada muestra en modo reflectancia. El conjunto de muestras fue dividido aleatoriamente en dos grupos: uno para obtener el modelo de calibración (80 %) y el otro para la validación del modelo (20 %). Se utilizaron ocho técnicas de pretratamiento de la información espectral y luego se seleccionó la mejor para cada parámetro, con el criterio de obtener el mínimo error estándar de la validación cruzada (EEVC), máximo coeficiente de determinación de la validación cruzada (R2cv) y máxima desviación predictiva residual (RPD). Los modelos de calibración se obtuvieron utilizando regresión de cuadrados mínimos parciales modificada (MPLS) y validación cruzada con cinco etapas. Los mejores modelos para la predicción de CO y N se obtuvieron con los espectros sin procesar (RPD=4,69 y 3,65 respectivamente); para pH se obtuvo con la técnica variación normal estándar con segunda derivada (RPD=2,27) y para arcilla+limo con corrección de dispersión múltiple y segunda derivada (RPD=2,83). El desempeño de los modelos aplicados sobre el grupo de testeo y calibración fue similar. Los resultados indican que la elección apropiada de la técnica de pretratamiento de datos espectrales puede optimizar la calibración. Vis-NIRS es una herramienta valiosa para el monitoreo de suelos en Argentina, como comple-mento de los métodos tradicionales de análisis.

Intracranial hemorrhage (ICH) is a serious medical condition that can lead to significant morbidity and mortality if not diagnosed and treated promptly. Early detection and treatment are essential for improving the outcome in patients with ICH. Near-infrared spectroscopy (NIRS) is a non-invasive imaging technique that has been used to detect changes in brain tissue oxygenation and blood flow in various conditions. The aim of this study was to investigate the predictive potential of NIRS for early diagnosis of ICH in patients presenting to the Emergency Department (ED) triage with headache. A total of 378 patients were included in the study. According to the final diagnosis of the patients, 4 groups were formed: migraine, tension-cluster headache, intracranial hemorrhage and intracranial mass, and control group. Cerebral NIRS values “rSO2” were measured at the first professional medical contact with the patient. The right and left rSO2 (RrSO2, LrSO2) were significantly lower and the rSO2 difference was significantly higher in the intracranial hemorrhage group compared to all other patient groups (P<0.001). The cut-off values determined in the receiver operating characteristics (ROC) analysis were RrSO2 ≤67, LrSO2 ≤67, and ΔrSO2 ≥9. This study found that a difference of more than 9 in cerebral right-left NIRS values can be a non-invasive, easy-to-administer, rapid, and reliable diagnostic test for early detection of intracranial bleeding. NIRS holds promise as an objective method in ED triage for patients with intracranial hemorrhage. However, further research is needed to fully understand the potential benefits and limitations of this method. (ICH promptly Nearinfrared Near infrared (NIRS noninvasive non invasive conditions (ED headache 37 formed migraine tensioncluster tension cluster mass rSO “rSO2 RrSO2, RrSO (RrSO2 LrSO P<0.001. P0001 P P<0.001 . 0 001 (P<0.001) cutoff cut off ROC (ROC 67 ≤67 ΔrSO ≥9 rightleft noninvasive, invasive, easytoadminister, easytoadminister easy administer, administer easy-to-administer rapid bleeding However 3 “rSO (RrSO P000 P<0.00 00 (P<0.001 6 ≤6 ≥ P00 P<0.0 (P<0.00 ≤ P0 P<0. (P<0.0 P<0 (P<0. P< (P<0 (P< (P

RESUMO: Um experimento foi conduzido para avaliar a produtividade, a composição nutricional e a contaminação por micotoxinas em diferentes híbridos de milho. Essas medidas também foram correlacionadas com o impacto do custo do milho na formulação de ração inicial para frangos de corte. Um total de 150 amostras de 50 híbridos de milho foram obtidas em experimento de campo. As variáveis nutricionais foram preditas via NIRS e as micotoxinas foram analisadas por HPLC-MS/MS. Os dados foram submetidos à análise de variância e os híbridos agrupados pelo teste de Scott-Knott a 5% de significância. Correlação de Pearson foi realizada entre as principais variáveis. A maioria das variáveis foi diferente entre os híbridos de milho (P < 0,05), com exceção de fósforo disponível, grãos avariados e contaminações por DON e ZEA (P > 0,05). A produtividade teve correlação positiva (P < 0,05) com o custo de formulação da ração (r = 0,35) e correlação negativa (P < 0,05) com proteína bruta (-0,42), Tre digestível (dig.) (-0,42) e Met+Cis dig. (-0,42). O custo da formulação de rações apresentou correlação positiva (P < 0,05) com FUM (0,33) e ZEA (0,29), e negativa (P < 0,05) com proteína bruta (-0,74). Diferentes híbridos de milho variam em produtividade, conteúdo nutricional e contaminação por micotoxinas. Foi demonstrado que um aumento no rendimento à campo pode estar relacionado com redução no conteúdo nutricional e na qualidade do milho, resultando em um aumento no custo da formulação de ração. RESUMO corte 15 5 HPLCMS/MS. HPLCMSMS HPLC MS/MS. MS HPLC-MS/MS ScottKnott Scott Knott significância P 0,05, 005 0,05 , 0 05 disponível 0,05. . r 0,35 035 35 0,42, 042 0,42 42 dig (dig. (-0,42 MetCis Met Cis 0,42. 0,33 033 33 (0,33 0,29, 029 0,29 29 (0,29) 0,74. 074 0,74 74 (-0,74) 1 HPLCMS HPLCMS/MS MSMS MS/MS 00 0,0 0,3 03 3 04 0,4 4 (dig (-0,4 (0,3 02 0,2 2 (0,29 07 0,7 7 (-0,74 0, (-0, (0, (0,2 (-0,7 (-0 (0 (- (

ABSTRACT: An experiment was conducted to assess the crop yield, nutritional composition, and mycotoxin contamination in different corn hybrids. The impact of these variables on the feed formulation cost of starter diets for broilers was also evaluated. A total of 150 samples from 50 corn hybrids was obtained from a field experiment. Nutrients were predicted by NIRS and mycotoxins were analyzed by HPLC-MS/MS. Data were submitted to analysis of variance and corn hybrids were grouped using Scott-Knott test at 5% significance. Pearson correlation analysis was performed among the main variables. Most of the variables were different among corn hybrids (P < 0.05), with exception of available phosphorus (Av. P), damaged grains, and DON and ZEA contaminations (P > 0.05). Crop yield had a positive correlation (P < 0.05) with feed formulation cost (r = 0.35) and a negative correlation (P < 0.05) with crude protein (-0.42), digestible (dig.) Thr (-0.42), and dig. Met+Cys (-0.42). The feed cost correlated positively (P < 0.05) with FUM (0.33) and ZEA (0.29), and negatively (P < 0.05) with crude protein (-0.74). Different corn hybrids vary in their productivity, nutritional content and mycotoxins contamination. It was demonstrated that an increase in the crop yield might be related to a reduction in corn nutritional content and quality, resulting in an increase in feed formulation cost. ABSTRACT composition evaluated 15 5 HPLCMS/MS. HPLCMSMS HPLC MS/MS. MS HPLC-MS/MS ScottKnott Scott Knott significance P 0.05, 005 0.05 , 0 05 Av. Av (Av P, P) grains 0.05. . r 0.35 035 35 0.42, 042 0.42 42 (-0.42) dig (dig. MetCys Met Cys 0.42. 0.33 033 33 (0.33 0.29, 029 0.29 29 (0.29) 0.74. 074 0.74 74 (-0.74) productivity quality 1 HPLCMS HPLCMS/MS MSMS MS/MS 00 0.0 0.3 03 3 04 0.4 4 (-0.42 (dig (0.3 02 0.2 2 (0.29 07 0.7 7 (-0.74 0. (-0.4 (0. (0.2 (-0.7 (-0. (0 (-0 ( (-

ABSTRACT With the increasing soybean production in Brazil, and the demand for soybeans with high protein and oil content, it is essential to conduct an in-depth study of the constituents of this grain, which can vary according to genotypes and growing conditions. Therefore, the objective of this study was to classify soybean genotypes, cultivated in different environments and sowing seasons, according to their chemical composition and the spectrum generated by near-infrared spectroscopy (NIRS). For this purpose, artificial intelligence and its machine learning technique were employed. 10 soybean genotypes were used, sown in two sowing seasons and cultivated 7 cities in Rio Grande do Sul. The chemical composition of the samples was analyzed using the FOSS NIRS DS2500 equipment, selecting the band between 807 and 817 nm. The applied algorithms were J48, Random Forest, CVR, lBk, MLP, using the Resample filter. The Weka software, version 3.8.6, was employed for data mining. The IBk algorithm achieved the best performance, reaching 89% correct classification of attributes. From the Confusion Matrix, it was observed that all genotypes obtained results above 60/70 for correctly predicted values, highlighting the algorithms’ good performance. In the metrics, IBk achieved 0.89 Precision, Recall, and F-Measure, and 0.94 ROC Area. Thus, it was possible to classify the genotypes according to their chemical composition related to the data obtained in the spectral curve, sowing season, and environment, using artificial intelligence and machine learning. Brazil content indepth depth grain conditions Therefore nearinfrared near infrared NIRS. . (NIRS) purpose 1 used Sul DS DS250 equipment 80 81 nm J48 J Forest CVR lBk MLP filter software 386 3 8 6 3.8.6 mining performance 89 attributes Matrix 6070 60 70 60/7 values metrics 089 0 0.8 Precision Recall FMeasure, FMeasure F Measure, Measure F-Measure 094 94 0.9 Area Thus curve season environment (NIRS DS25 J4 38 3.8. 607 60/ 08 0. 09 9 DS2 3.8 3.

RESUMO Com a crescente produção de soja no Brasil e a demanda por grãos de soja com alto teor de proteína e óleo, é fundamental o estudo aprofundado dos constituintes desse grão, os quais podem variar de acordo com os genótipos e as condições de cultivo. Com isso, o objetivo desse estudo foi realizar a classificação de genótipos de soja, cultivados em diferentes ambientes e épocas de semeadura, de acordo com a composição química e o espectro gerado por infravermelho próximo (NIRs). Para isso, foi empregada a inteligência artificial e sua técnica de aprendizado de máquina. Foram utilizados 10 genótipos de soja, semeados em duas épocas de semeadura e em 7 cidades do Rio Grande do Sul. A composição química das amostras foi analisada através do equipamento FOSS NIRS DS2500, selecionando a banda entre 807 e 817nm. Os algoritmos aplicados foram J48, Random Forest, CVR, lBk, MLP, utilizando o filtro Resample. Foi empregado o software Weka, versão 3.8.6, para mineração de dados. O algoritmo IBk conseguiu o melhor desempenho, alcançando 89% de classificação correta dos atributos. A partir da Matriz de Confusão, observou-se que todos os genótipos obtiveram resultados superiores a 60/70 para os valores preditos corretamente, destacando o bom desempenho dos algoritmos. Nas métricas, o IBk obteve 0,89 de Precisão, Recall e F-Measure, e 0,94 de ROC Area. Foi possível classificar os genótipos, de acordo com a sua composição química relacionada aos dados obtidos na curva espectral, época e ambiente de semeadura, a partir da inteligência artificial e aprendizado de máquina. óleo grão cultivo isso NIRs. NIRs . (NIRs) máquina 1 Sul DS2500 DS 80 817nm nm J48 J Forest CVR lBk MLP Resample Weka 386 3 8 6 3.8.6 89 atributos Confusão observouse observou se 6070 60 70 60/7 corretamente métricas 089 0 0,8 Precisão FMeasure, FMeasure F Measure, Measure F-Measure 094 94 0,9 Area espectral (NIRs DS250 J4 38 3.8. 607 60/ 08 0, 09 9 DS25 3.8 DS2 3.

Resumen La espectroscopia de reflectancia en el infrarrojo cercano (NIRS) permite estimar la composición química de diversas muestras, (ingredientes, productos de origen animal, etc.); sin embargo, existe poca información de su uso con muestras de digesta ileal (DI) o heces (H) de cerdo; por lo que el objetivo fue desarrollar ecuaciones de predicción basadas en el método de cuadrados mínimos parciales para predecir la composición química de DI y H a través de un NIRS. Se utilizaron 110 muestras de DI y 202 de H de experimentos de digestibilidad, obteniéndose su espectro y mediante un modelo multivariado se desarrolló el método de predicción. Las variables analizadas en la DI fueron: proteína cruda (PC), Leucina (Leu), lisina (Lys) y treonina (Thr) y en las H: materia seca (MS), PC y energía (E). Los valores en DI fueron: PC: R2 0.98, error estándar de calibración (SEC) 0.330, error estándar de predicción (SEP) 0.640; Leu: R2 0.95, SEC 0.040, SEP 0.102; Lys: R2 0.93, SEC 0.077, SEP 0.143; Thr: R2 0.67, SEC 0.209, SEP 0.187. En H fueron PC: R2 0.98, SEC 0.95, SEP 1.19; E (kcal/kg): R2 0.94, SEC 60.8, SEP 95.3; MS: R2 0.87, SEC 0.83, SEP 1.15. Los resultados muestran que la robustez de la calibración (DE/SEP) fue buena para PC, 3.34, Leu 2.07 y Lys 2.48 y regular para Thr 1.94, la predicción (RPD) fue buena para PC 2.11 en la DI. En H las R2 fueron altas para PC 0.98 y E 0.94. La mayor robustez fue para PC 5.59 y su predicción fue excelente 4.16 y buena para E 2.53. Se concluye que el NIRS puede predecir la PC en la DI y la PC y E en H. Para mejorar la estimación de aminoácidos en DI deben explorarse las causas que afectan la robustez de las calibraciones.

Abstract Near-infrared reflectance spectroscopy (NIRS) allows the estimation of the chemical composition of various samples (ingredients, animal products, etc.); however, there is little information on its use with samples of swine ileal digesta (ID) or feces (F). Therefore, the objective was to develop prediction equations based on the partial least squares method to predict the chemical composition of the ID and F through NIRS. 110 ID and 202 F samples from digestibility experiments were used, their spectra were obtained and a multivariate model was used to develop the prediction method. The variables analyzed in ID were: crude protein (CP), leucine (Leu), lysine (Lys) and threonine (Thr) and in F: dry matter (DM), CP and energy (E). The DI values were: PC: R2 0.98, standard error of calibration (SEC) 0.330, standard error of prediction (SEP) 0.640; Leu: R2 0.95, SEC 0.040, SEP 0.102; Lys: R2 0.93, SEC 0.077, SEP 0.143; Thr: R2 0.67, SEC 0.209, SEP 0.187. F values were: PC: R2 0.98, SEC 0.95, SEP 1.19; E (kcal/kg): R2 0.94, SEC 60.8, SEP 95.3; MS: R2 0.87, SEC 0.83, SEP 1.15. The results show that the calibration robustness (SD/SEP) was good for PC, 3.34, Leu 2.07 and Lys 2.48 and fair for Thr 1.94, the prediction (RPD) was good for PC 2.11 in ID. In F the R2 were high for PC 0.98 and E 0.94. The highest robustness was for PC 5.59 and its prediction was excellent 4.16 and good for E 2.53. It is concluded that NIRS can predict PC in ID and PC and E in F. In order to improve the estimation of amino acids in ID, the causes affecting the robustness of the calibrations should be explored.

Resumen: La estenosis carotídea (EC) ocurre en 13% de los pacientes con estenosis valvular aórtica (EVA). El riesgo de evento vascular cerebral (EVC), en los pacientes con EC significativa sometidos a cirugía valvular cardíaca, puede aumentar hasta 11%. Someter a un paciente con EVA crítica y fracción de eyección del ventrículo izquierdo (FEVI) disminuida a endarterectomía carotídea es todo un reto anestésico, cuyo principal objetivo es evitar la hipotensión y el bajo gasto cardíaco. La anestesia regional es una opción para estos pacientes. Presentamos el caso de un hombre de 70 años con diagnóstico de EC significativa y EVA crítica con disfunción ventricular izquierda, al que se realizó endarterectomía carotídea con bloqueo del plexo cervical superficial por alto riesgo de colapso circulatorio. Dicha estrategia anestésica permitió mantener al paciente despierto durante la cirugía, al valorar continuamente su estado neurológico. Asimismo, se documentaron los cambios transoperatorios en el NIRS (Near-infrared spectroscopy) cerebral y Doppler transcraneal (DTC), los cuales se correlacionaron con el estado clínico del paciente. En un segundo tiempo se hizo cambio valvular aórtico sin complicaciones. En este caso destaca la importancia de la anestesia regional y el monitoreo neurológico con Doppler transcraneal, en pacientes sometidos a endarterectomía carotídea con alto riesgo quirúrgico por EVA crítica.

Abstract: Carotid stenosis occurs in 13% of patients with aortic valve stenosis. The risk of stroke in patients with significant carotid stenosis undergoing heart valve surgery may increase to 11%. Proposing a patient with critical aortic valve stenosis and left ventricular dysfunction to carotid endarterectomy is an anesthetic challenge, where the objective is to avoid hypotension and low cardiac output. Regional anesthesia is an option for these patients. Due to the high incidence of intraoperative stroke during carotid endarterectomy, continuous neurological monitoring is of relevance. We present the case of a 70-year-old man diagnosed with significant carotid stenosis and critical aortic valve stenosis and left ventricular dysfunction who underwent carotid endarterectomy with superficial cervical plexus block due to a high risk of circulatory collapse. In addition, this anesthetic strategy made it possible to keep the patient awake during surgery, and to continuously assess their neurological status. Likewise, transoperative changes in brain NIRS and transcranial Doppler were documented, which correlated with the patient’s clinical status. In a second time, aortic valve replacement was performed without complications. This case highlights the importance of regional anesthesia and neurological monitoring in patients undergoing carotid endarterectomy with high surgical risk due to critical aortic valve stenosis.

Resumen: La espectroscopia cercana al infrarrojo (NIRS, por sus siglas en inglés) es un método óptico de diagnóstico no invasivo, útil como guía para tomar medidas correctivas y prevenir así la lesión cerebral en prematuros. El objetivo es evaluar la eficacia de la NIRS en la detección de la oxigenación cerebral y su impacto en la prevención de lesiones cerebrales y la mortalidad en prematuros. Se realizó una búsqueda sistemática de la literatura en PubMed y Cochrane con las palabras clave spectroscopy, near-infrared, preterm newborn, infant, neonates, Clinical Trial, Meta-Analysis, systematic para encontrar estudios que evalúen el uso de la NIRS en la oxigenación cerebral en recién nacidos pretérmino. Se incluyó un ensayo clínico fase II, uno fase III y una revisión sistemática. En estos estudios el uso de la NIRS redujo de manera significativa la carga de hipoxia cerebral. La NIRS mostró tendencias en reducir la mortalidad y la lesión cerebral, pero sin diferencia estadísticamente significativa.

Abstract: Near-infrared spectroscopy (NIRS) is a non-invasive optical diagnostic method as a guide to taking corrective measures to prevent brain injury in premature infants. This review aims to evaluate the efficacy of NIRS in detecting cerebral oxygenation and its impact on preventing brain injury and mortality in preterm. A systematic search of the literature was carried out in PubMed and Cochrane with the keywords spectroscopy, near-infrared, preterm newborn, infant, neonates, Clinical Trial, Meta-Analysis, and systematic to find studies that evaluate the use of the NIRS in cerebral oxygenation in preterm newborns. A phase II clinical trial, a phase III clinical trial, and a systematic review were included. NIRS significantly reduced the burden of cerebral hypoxia. The NIRS showed trends in reducing mortality and brain injury but did not show a statistically significant difference.

ABSTRACT Biochar soil amendments are attracting attention as one strategy to improve soil microbially ecological environment and regulate the soil nitrogen cycle. This study aimed to evaluate the effects of biochar application on agricultural soil improvement, nitrogen (N) mineralization and nitrification. The experiment was carried out on a typical farmland containing black soil and saline-alkaline soil in Northeast China. Four treatments were undertaken, including the control-treated black soil farmland (CS), the biochar-treated black soil farmland (BCS), the control-treated saline-alkali soil farmland (SAS), and the biochar-treated saline-alkaline soil farmland (BSAS). Basic physical and chemical properties, enzyme activity, and the contents of ammonium-nitrogen (NH4+-N) and nitrate-nitrogen (NO3--N) in the soil were subsequently determined. The co-occurrence networks of bacterial communities of the biochar and control treatment groups were constructed based on high-throughput sequencing data of the 16S rRNA genes. The results showed that the BCS and BSAS treatments significantly increased the contents of soil organic matter, total nitrogen, total phosphorus, and available phosphorus. The application of biochar significantly increased the NH4+-N contents in the black soil and saline-alkaline soil by 81.78 and 80.08 %, respectively, while significantly reducing the soil NH4+-N/NO3--N content, which promoted the transformation of NH4+-N into NO3--N. Subsequently, the released NH4+-N was transformed into NO3--N through nitrification. After the biochar application, the NO3--N contents in the black and saline-alkaline soils could be fixed. The biochar application significantly increased the abundance of gdh, AOA-amoA, AOB-amoA, nirK, nirS, nosZ, and nifH genes, with no significant difference in the abundance of napA genes being found among different treatments. Microbes playing a key role in the co-occurrence network were Proteobateria, Acidobacteria, Bacteroidetes, Actinobacteria, and Chloroflexi. As compared with the CS and SAS treatments, under the BCS+BSAS treatment, the connectors, module hubs, connectedness, and clustering coefficient showed larger parameters, and the networks were more complex. The application of biochar gradually increased the nodes, edges, and average degree of the bacterial co-occurrence network, thus indicating that the interaction between microbial groups in the black and saline-alkaline soils post biochar application may be important in the biogeochemical cycle process in farmland soil. improvement N (N nitrification salinealkaline saline alkaline China undertaken controltreated treated CS, , (CS) biochartreated BCS, (BCS) salinealkali alkali SAS, (SAS) BSAS. . (BSAS) properties activity ammoniumnitrogen ammonium NH4+N NH4N NHN NH4+ NH4 NH (NH4+-N nitratenitrogen nitrate NO3N NON NO3 NO (NO3--N determined cooccurrence co occurrence highthroughput high throughput S matter phosphorus 8178 81 78 81.7 8008 80 08 80.0 % respectively NH4+N/NO3N NH4NNO3N NHNNON N/NO3 content NO3N. N. Subsequently fixed gdh AOAamoA, AOAamoA AOA amoA, amoA AOA-amoA AOBamoA, AOBamoA AOB AOB-amoA nirK nirS nosZ Proteobateria Acidobacteria Bacteroidetes Actinobacteria Chloroflexi BCSBSAS connectors hubs connectedness parameters complex nodes edges (CS (BCS (SAS (BSAS 817 8 7 81. 800 0 80. NNO NNO3 N/NO

Abstract Near infrared spectroscopy (NIRS) combined with multiple algorithms was used to determinate the tea polyphenols content in Chongzhou new loquat tea lines quickly and nondestructively. Samples of 26 Chongzhou new loquat tea lines were collected, then scanning NIRS, pretreating spectral noise information, screening characteristic spectral intervals by backward interval partial least squares, proceeding principal component analysis. Finally, the artificial neural network (BP-ANN) method with three kinds of transfer functions was applied to establish models. The best pretreated method was the combination of standard normal variation (SNV) and first derivative, and the characteristic spectral regions selected were 4381.5-4755.6 cm–1, 4759.5-5133.6 cm–1, 6266.6-6637.8 cm–1 and 7389.9-7760.2 cm–1, respectively. The cumulative contribution rate of the first three principal components of the selected characteristic spectra was 95.24%. When the BP-ANN calibration set model was established with the logistic function, NIRS model had the best results, whose root mean square error and determination coefficient of the cross validation were 0.975 and 0.372%, respectively. The root mean square error and the determination coefficient of the prediction set model were 0.962 and 0.400%, respectively. The results showed NIRS can predict the tea polyphenols content in Chongzhou new loquat tea lines quickly and accurately. (NIRS nondestructively 2 collected information squares analysis Finally BPANN BP ANN (BP-ANN models SNV (SNV derivative 4381.54755.6 4381547556 4381.5 4755.6 4381 5 4755 6 4381.5-4755. cm1 cm 1 4759.55133.6 4759551336 4759.5 5133.6 4759 5133 4759.5-5133. 6266.66637.8 6266666378 6266.6 6637.8 6266 6637 8 6266.6-6637. cm– 7389.97760.2 7389977602 7389.9 7760.2 7389 9 7760 7389.9-7760. respectively 9524 95 24 95.24% function 0975 0 975 0.97 0372 372 0.372% 0962 962 0.96 0400 400 0.400% accurately 54755 4381.54755. 438154755 43815 4381. 47556 4755. 438 475 4381.5-4755 55133 4759.55133. 475955133 47595 4759. 51336 5133. 513 4759.5-5133 66637 6266.66637. 626666637 62666 6266. 66378 6637. 626 663 6266.6-6637 97760 7389.97760. 738997760 73899 7389. 77602 7760. 738 776 7389.9-7760 952 95.24 097 97 0.9 037 37 0.372 096 96 040 40 0.400 5475 4381.54755 43815475 43 47 4381.5-475 5513 4759.55133 47595513 51 4759.5-513 6663 6266.66637 62666663 62 66 6266.6-663 9776 7389.97760 73899776 73 77 7389.9-776 95.2 09 0. 03 3 0.37 04 4 0.40 547 4381.5475 4381547 4381.5-47 551 4759.5513 4759551 4759.5-51 666 6266.6663 6266666 6266.6-66 977 7389.9776 7389977 7 7389.9-77 95. 0.3 0.4 54 4381.547 438154 4381.5-4 55 4759.551 475955 4759.5-5 6266.666 626666 6266.6-6 7389.977 738997 7389.9-7 4381.54 4381.5- 4759.55 4759.5- 6266.66 6266.6- 7389.97 7389.9-

ABSTRACT Purpose: In this study, the aim to assess the combined effects of prone-positioning (PP) and minimal-flow (MF) general anesthesia on regional cerebral oxygenation (RCO) and systemic hemodynamics. Methods: This is a randomized prospective study aiming to evaluate changes in cerebral oxygenation and hemodynamic parameters in MF systemic anesthesia in patients undergoing surgery in PP. Patients were randomized to MF or normal-flow (NF) anesthesia. In the operating room, pulse rate, mean arterial pressure (MAP), peripheral hemoglobin oxygen saturation (spO2), and right- and left-side RCO (assessed by near-infrared spectroscopy, NIRS) were measured perioperatively. Results: Overall, 46 patients were included (24 in the MF group and 22 in the NF group). The amount of anesthetic gas consumption was significantly lower in the low-flow (LF) group. In both groups, the mean pulse rate showed a decrease after PP. Before induction, RCO was significantly higher both at the right- and left-sides in the LF group compared to the NF group. This difference continued throughout the operation on the left-side and disappeared 10 min after intubation on the right-side. On the left side, mean RCO decreased after PP in both groups. Conclusions: MF anesthesia in PP did not reduce cerebral oxygenation compared to NF and was safe in terms of systemic hemodynamics and cerebral oxygenation. Purpose pronepositioning prone positioning (PP minimalflow minimal flow (MF (RCO Methods normalflow normal (NF room MAP, MAP , (MAP) spO2, spO2 spO (spO2) right leftside side assessed nearinfrared near infrared spectroscopy NIRS perioperatively Results Overall 4 24 (2 2 . group) lowflow low (LF groups induction leftsides sides 1 rightside. rightside side. right-side Conclusions (MAP (spO2 ( (spO

ABSTRACT Objective: In this study, we aimed to evaluate the factors affecting major adverse event (MAE) development after full-term neonatal cardiac surgery. Methods: This study was conducted retrospectively on newborns who underwent congenital heart surgery between June 1, 2020, and June 1, 2022. MAE was defined as the presence of at least one of the following: cardiac arrest, unplanned reoperation, emergency chest opening, admission to the advanced life support system, and death. The role of blood lactate level, vasoactive inotropic score (VIS), and cerebral near-infrared spectroscopy (NIRS) changes in predicting MAE was investigated. Results: A total of 240 patients (50% male) were operated during the study period. The median age of patients was seven days (interquartile range 3-10 days). MAE was detected in 19.5% of the cases. Peak blood lactate levels >7 mmol/liter (area under the curve [AUC] 0.72, 95% confidence interval [CI] [0.62-0.82], P<0.001, sensitivity 76%, specificity 82%, positive predictive value [PPV] 88%) was an independent risk factor for MAE (odds ratio [OR] 2.7 [95% CI 1.3-6]). More than 30% change in NIRS value during the operative period (AUC 0.84, 95% CI [0.80-0.88], P<0.001, sensitivity 65%, specificity 85%, PPV 90%) was a strong predictor of MAE. VIS > 10 was an independent risk factor (AUC 0.75, 95% CI [0.70-0.84], P<0.001, sensitivity 86%, specificity 80%, PPV 84%) and strongly predicted MAE (OR 1.4 [95% CI 0.9-5]). Conclusion: Cerebral NIRS changes > 30%, high blood lactate levels, and VIS score within the 48 hours may help to predict the development of MAE in the postoperative period. Objective (MAE fullterm full term Methods 1 2020 2022 following arrest reoperation opening system death level VIS, , (VIS) nearinfrared near infrared (NIRS investigated Results 24 50% 50 (50 male interquartile 310 3 3-1 days. . days) 195 19 5 19.5 cases 7 mmolliter mmol liter area AUC [AUC 072 0 72 0.72 95 [CI 0.620.82, 062082 0.62 0.82 62 82 [0.62-0.82] P0001 P 001 P<0.001 76 76% 82% [PPV 88% 88 odds OR [OR 27 2 2. [95 1.36. 136 1.3 6 1.3-6]) 30 084 84 0.84 0.800.88, 080088 0.80 0.88 80 [0.80-0.88] 65 65% 85 85% 90% 90 075 75 0.75 0.700.84, 070084 0.70 70 [0.70-0.84] 86 86% 80% 84% 14 4 1. 0.95. 095 0.9 9 0.9-5]) Conclusion 202 (VIS (5 31 3- 19. 07 0.7 620 0.620.82 06208 062 0.6 082 0.8 8 [0.62-0.82 P000 00 P<0.00 [9 36 1.36 13 1.3-6] 08 800 0.800.88 08008 080 088 [0.80-0.88 700 0.700.84 07008 070 [0.70-0.84 0.95 09 0. 0.9-5] 20 ( 0.620.8 0620 06 [0.62-0.8 P00 P<0.0 [ 1.3-6 0.800.8 0800 [0.80-0.8 0.700.8 0700 [0.70-0.8 0.9-5 0.620. [0.62-0. P0 P<0. 1.3- 0.800. [0.80-0. 0.700. [0.70-0. 0.9- 0.620 [0.62-0 P<0 0.800 [0.80-0 0.700 [0.70-0 [0.62- P< [0.80- [0.70- [0.62 [0.80 [0.70 [0.6 [0.8 [0.7 [0. [0

Abstract Background: Temporomandibular disorder (TMD) is an umbrella term encompassing various clinical complaints involving the temporomandibular joints, masticatory muscles, and/or associated orofacial structures. Myogenous TMDs are the most frequent cause of chronic orofacial pain. Musculoskeletal pain is commonly associated with myofascial trigger points (MTPs), for which dry needling (DN) is a routine treatment. Objective: To investigate muscle oxygenation and pain immediately after DN application on an MTP in the masseter muscle of patients with myogenous TMDs. Methodology: Masseter muscle oxygen tissue saturation indices (TSI%) were assessed by near-infrared spectroscopy (NIRS) pre- and post-interventions by a randomized, controlled, double-blind, crossover DN/Sham clinical trial (primary outcome). Pain was investigated by the visual analog scale (VAS). In total, 32 individuals aged from 18 to 37 years who were diagnosed with myogenous TMD and myofascial trigger points in their masseter muscles participated in this study. Relative deltas for the studied variables were calculated. Data normality was tested using the Shapiro-Wilk test. According to their distribution, data were analyzed by two-way ANOVA and the Student's t-, and Mann-Whitney tests. Statistical analyses were performed using Prism® 5.0 (GraphPad, USA). Results: We found a significant difference (2,108% vs. 0,142%) between masseter muscle TSI% deltas after the DN and Sham interventions, respectively (n=24). We only evaluated women since men refused to follow NIRS procedures. Pain increased immediately after DN (n=32, 8 men), in comparison to Sham delta VAS. Conclusion: These findings show an increase in tissue oxygen saturation in the evaluated sample immediately after the DN intervention on the MTP of patients’ masseter muscle. Pain may have increased immediately after DN due to the needling procedure. Background (TMD joints andor or structures MTPs, MTPs , (MTPs) (DN treatment Objective Methodology TSI (TSI% nearinfrared near infrared (NIRS pre postinterventions post interventions randomized controlled doubleblind, doubleblind double blind, blind double-blind DNSham primary outcome. outcome . outcome) VAS (VAS) total 3 1 study calculated ShapiroWilk Shapiro Wilk test distribution twoway two way Students Student s t, t t- MannWhitney Mann Whitney tests Prism 50 5 0 5. GraphPad, GraphPad (GraphPad USA. USA USA) Results 2,108% 2108 2 108 (2,108 vs 0,142% 0142 142 n=24. n24 n n=24 24 (n=24) procedures n=32, n32 (n=32 men, men) Conclusion procedure (MTPs (TSI (VAS 2,108 210 10 (2,10 0,142 014 14 n2 n=2 (n=24 n=32 n3 (n=3 2,10 21 (2,1 0,14 01 n= (n=2 n=3 (n= 2,1 (2, 0,1 (n 2, (2 0, (

Abstract Near infrared spectroscopy (NIRS) combined with various chemometrics methods was tried to identify the fresh tea leaves at different altitudes quickly and nondestructively. Three kinds of samples were collected, then scanning NIRS, conducting spectral preprocessing to remove noise information, using backward interval partial least squares to screen characteristic spectral intervals, going on principal component analysis, respectively. Finally, least squares support vector machine method (LS-SVM) was applied to establish NIRS models, whose robustness was tested by prediction set samples. The best pretreated method was the combination of multivariate scattering correction and the first derivative. Six characteristic spectral intervals were screened, and the corresponding spectral wavenumbers were 4821.2-5091.2 cm-1, 5368.9-5638.8 cm-1, 6190.4-6460.4 cm-1, 7011.9-7281.9 cm-1, 8924.9-9191.1 cm-1 and 9734.9-10000 cm-1. The cumulative contribution rate of the first three principal components was 99.92%. The root mean square error of the cross validation and the determination coefficient of the calibration set model were 0.027 and 0.973, respectively. The root mean square error and the determination coefficient of the prediction set model were 0.034 and 0.968, respectively. The discrimination accuracy in prediction set was 100%. The results showed NIRS combined with LS-SVM can realize fast and nondestructive discrimination of fresh tea leaves at different altitudes.

Abstract The current developmental trend is to evaluate the quality of Yongchuan Xiuya tea rapidly. After spectrum pre-processing, near infrared spectroscopy (NIRS) coupled with synergy interval partial least squares (siPLS), principal component analysis (PCA) and back propagation-artificial neural network (BP-ANN) was applied to rapidly and non-destructively predict the quality of Yongchuan Xiuya tea. External Yongchuan Xiuya tea samples were used for the actual application of the proposed model. The best pre-processing method was multiple scattering correction coupled with second derivative, and the characteristic spectral regions selected by siPLS were 4381.5-4755.6 cm-1, 4759.5-5133.6 cm-1, 6266.6-6637.8 cm-1 and 7389.9-7760.2 cm-1. The cumulative contribution rate was 99.05% for the first three principal components of the characteristic spectra regions. The transfer function, root mean square error and determinant coefficient of the best BP-ANN prediction model were the tanh function, 0.384 and 0.977, respectively. The root mean square error and determinant coefficient of the external 10 Yongchuan Xiuya tea samples were 0.406 and 0.969, respectively. These results showed that NIRS combined with BP-ANN algorithm can be used to evaluate the quality of Yongchuan Xiuya tea rapidly and accurately.

RESUMO Objetivou-se comparar os teores dos nutrientes do capim Andropogon gayanus obtidos no equipamento NIRS com os valores obtidos por análises de via úmida, para identificar se os modelos globais de calibração do equipamento NIRS são adequados para predizer a composição químico-bromatológica. As análises de via seca no NIRS foram executadas no Laboratório de Bromatologia e Nutrição Animal (Laban), pertencente à Faculdade de Medicina Veterinária (Famev) da Universidade Federal de Uberlândia (UFU), enquanto as análises de via úmida foram realizadas no Laboratório de Química Analítica de Plantas da Embrapa Cerrados, localizado em Brasília-DF. As amostras utilizadas foram de capim Andropogon gayanus, cultivar Planaltina, as quais, após corte de 20cm acima do solo, foram secas e moídas no tamanho de 1mm. Após a moagem, foram analisadas por via úmida para os teores de matéria seca (MS), matéria mineral (MM), proteína bruta (PB), fibra insolúvel em detergente neutro (FDN) e fibra insolúvel em detergente ácido (FDA), segundo metodologias propostas por Detmann et al. (2012). As amostras moídas foram colocadas em cubetas próprias do equipamento e escaneadas em espectrômetro de refletância no infravermelho próximo (NIRS) NIR, modelo Spectra Star 2600 XT series of Near Infrared Analyzers (Unity Scientific®), em duplicata. Para obtenção dos teores de MS, MM, PB, FDN e FDA, empregaram-se modelos de calibração do próprio equipamento NIRS, utilizando-se a curva de calibração própria do equipamento. As médias dos teores de MS, MM, PB, FDN e FDA obtidas pelas análises de bancada (via úmida) e pelo uso do equipamento NIRS foram comparadas pelo teste T (dados pareados), ao nível de 5% de probabilidade, empregando-se o delineamento em blocos ao acaso. Houve diferença significativa nos nutrientes preditos pelo NIRS e analisados por via úmida (P≤0,05). O NIRS superestimou os teores de matéria seca e matéria mineral, mas subestimou os teores de FDN, FDA e PB. Esse resultado mostra que, quando do uso de modelos globais de calibração, esse equipamento não é capaz de predizer corretamente a composição químico-bromatológica de forrageiras de clima tropical.