Pancreatic neuroendocrine tumors:Are tumors smaller than 2 cm truly indolent?

BACKGROUND Pancreatic neuroendocrine tumors(PNETs)are relatively rare but rank as the second most common pancreatic neoplasm.They can be functional,causing early metabolic disturbances due to hormone secretion,or non-functional and diagnosed later based on tumor size-related symptoms.Recent diagnoses of PNETs under 2 cm in size have sparked debates about their management;some practitioners advocate for surgical removal and others suggest observation due to the tumors’lower potential for malignancy.However,it is unclear whether managing these small tumors expectantly is truly safe.AIM To evaluate poor prognostic factors in PNETs based on tumor size(>2 cm or<2 cm)in surgically treated patients.METHODS This cohort study included 64 patients with PNETs who underwent surgical resection between 2006 and 2019 at a high-complexity reference hospital in Medellín,Colombia.To assess patient survival,quarterly follow-ups were conducted during the first year after surgery,followed by semi-annual con-sultations at the hospital's hepatobiliary surgery department.Qualitative variables were described using absolute and relative frequencies,and quantitative variables were expressed using measures of central tendency and their corresponding measures of dispersion.RESULTS The presence of lymph node involvement,neural involvement,and lymphovascular invasion were all associated with an increased risk of mortality,with hazard ratios of 5.68(95%CI:1.26–25.61,P=0.024),6.44(95%CI:1.43–28.93,P=0.015),and 24.87(95%CI:2.98–207.19,P=0.003),respectively.Neural involvement and lymphovascular invasion were present in tumors smaller than 2 cm in diameter and those larger than 2 cm in diameter.The recurrence rates between the two tumor groups were furthermore similar:18.2%for tumors smaller than 2 cm and 21.4%for tumors larger than 2 cm.Patient survival was additionally comparable between the two tumor groups.CONCLUSION Tumor size does not dictate prognosis;lymph node and lymphovascular involvement affect mortality,which high-lights that histopathological factors-rather than tumor size-may play a role in management.

Predicting intensive care unit-acquired weakness:A multilayer perceptron neural network approach

In this editorial,we comment on the article by Wang and Long,published in a recent issue of the World Journal of Clinical Cases.The article addresses the challenge of predicting intensive care unit-acquired weakness(ICUAW),a neuromuscular disorder affecting critically ill patients,by employing a novel processing strategy based on repeated machine learning.The editorial presents a dataset comprising clinical,demographic,and laboratory variables from intensive care unit(ICU)patients and employs a multilayer perceptron neural network model to predict ICUAW.The authors also performed a feature importance analysis to identify the most relevant risk factors for ICUAW.This editorial contributes to the growing body of literature on predictive modeling in critical care,offering insights into the potential of machine learning approaches to improve patient outcomes and guide clinical decision-making in the ICU setting.

Design and Robust Performance Evaluation of a Fractional Order PID Controller Applied to a DC Motor

This paper proposes a methodology for the quantitative robustness evaluation of PID controllers employed in a DC motor. The robustness analysis is performed employing a 2~3 factorial experimental design for a fractional order proportional integral and derivative controller(FOPID), integer order proportional integral and derivative controller(IOPID)and the Skogestad internal model control controller(SIMC). The factors assumed in experiment are the presence of random noise,external disturbances in the system input and variable load. As output variables, the experimental design employs the system step response and the controller action. Practical implementation of FOPID and IOPID controllers uses the MATLAB stateflow toolbox and a NI data acquisition system. Results of the robustness analysis show that the FOPID controller has a better performance and robust stability against the experiment factors.

TREFACE: A New Computerized Test of Emotional Stroop with Facial Expressions

Using the conflict principle of the Stroop task, “effect of interference in color naming”, the present study proposes to create a computational version of the emotional Stroop task, called TREFACE, for its acronyms in Portuguese “Teste de Reconhecimento de Expressões Faciais com Conflito Emocional” (Facial Expression Recognition Test with Emotional Conflict). In this protocol, four fixed styles of presentation were generated according to the condition: Congruent Word Reading, Incongruent Word Reading, Congruent Recognition of Face Expression and Incongruent Recognition of Face Expression, counterbalanced in terms of each facial expression, word and gender of the photo character. Forty-two healthy volunteers completed the task. Results revealed that a task associated with word reading allows better performance than a task associated with face recognition. It was also identified that in the congruent condition, there is an advantage in terms of the correct responses. Additionally, the data regarding recognition of face expression showed greater difficulty when the image was not congruent with the word. In general, the results suggest that the emotional attribute can compromise the ability to recognize the faces, reaching the functioning of mechanisms such as cognitive control and regulation of emotions. Thus, the TREFACE paradigm can be considered a good assessment tool for monitoring emotional conflict, in addition to presenting itself as a new instrument in Portuguese language for assessing emotional working memory in healthy individuals and, eventually, in different pathologies that affect the functioning of cortical areas related to executive functions.

Adverse events in critical care: Search and active detection through the Trigger Tool

AIM To investigate the incidence of disadvantageous events by using the Global Trigger Tool in an intensive care unit(ICU).METHODS A retrospective descriptive study was performed in a 12-bed university ICU in the city of Medellin, Colombia. Clinical charts of hospitalized patients were reviewed, between January 1 and December 31, 2016, with the following inclusion criteria: subjects aged over 18 years, with at least 24 h of hospitalization and who had a complete medical history that could be accessed. Interventions: Trained reviewers conducted a retros pective examination of medical charts searching for clue events that elicit investigation, in order to detect an unfavorable event. Measurements: Information was processed through SPSS softwareversion 21; for numerical variables, the mean was reported with standard deviation(SD). Percentages were calculated for qualitative variables. RESULTS Two hundred and forty-four triggers occurred, with 82.4% of subjects having presented with at least one and an average of 3.37 (SD 3.47). A total of 178 adverse events (AEs) took place in 48 individuals, with an incidence of 52.1%. On average, four events per patient were recorded, and for each unfortunate event, 1.98 triggers were presented. The most frequent displeasing issues were: pressure ulcers(17.6%), followed by complications or reactions to medical devices(4.3%), and lacerations or skin defects(3.7%); the least frequent was delayed diagnosis or treatment (0.56%). Thirty-eight point four percent of mishap events caused temporary damage that required intervention, and 48.9% of AEs were preventable. Comparison between AEs and admission diagnoses found that hypertension and sepsis were the only diagnoses that had statistical significance (P = 0.042 and 0.022, respectively).CONCLUSION Almost half of the unfavorable issues were classified as avoidable, which leaves a very wide field of work in terms of preventative activities.

Electronic Tongue and Neural Networks, Biologically Inspired Systems Applied to Classifying Coffee Samples

In this paper, the possibility to use an electronic tongue based on a polypyrrole sensor array in classifying coffee samples has been studied. Each sensor shows a distinguished electrochemical response when exposed to the studied solutions, providing signals with a high degree of cross-selectivity. The sensor array electrochemical response is related to the interaction of the ionic and non-ionic solution compounds and to the surface of the sensors polymeric matrix. Furthermore, the electronic tongue was used to perform an analysis on coffee samples. In this case, each sensor showed a particular response to each coffee sample. Data obtained from the registered signals were used to perform a discrimination of the samples. The analysis with neural networks of the principal components (NNPC) done on the electronic tongue response to five types of commercial coffee, allows to achieve a clear differentiation of samples.

EEG Mapping of Cortical Activation Related to Emotional Stroop with Facial Expressions: A TREFACE Study

TREFACE (Test for Recognition of Facial Expressions with Emotional Conflict) is a computerized model for investigating the emotional factor in executive functions based on the Stroop paradigm, for the recognition of emotional expressions in human faces. To investigate the influence of the emotional component at the cortical level, the electroencephalographic (EEG) recording technique was used to measure the involvement of cortical areas during the execution of certain tasks. Thirty Brazilian native Portuguese-speaking graduate students were evaluated on their anxiety and depression levels and on their well-being at the time of the session. The EEG recording was performed in 19 channels during the execution of the TREFACE test in the 3 stages established by the model-guided training, reading, and recognition—both with congruent conditions, when the image corresponds to the word shown, and incongruent condition, when there is no correspondence. The results showed better performance in the reading stage and in congruent conditions, while greater intensity of cortical activation in the recognition stage and in incongruent conditions. In a complementary way, specific frontal activations were observed: intense theta frequency activation in the left extension representing the frontal recruitment of posterior regions in information processing;also, activation in alpha frequency in the right frontotemporal line, illustrating the executive processing in the control of attention, in addition to the dorsal manifestation of the prefrontal side, for emotional performance. Activations in beta and gamma frequencies were displayed in a more intensely distributed way in the recognition stage. The results of this mapping of cortical activity in our study can help to understand how words and images of faces can be regulated in everyday life and in clinical contexts, suggesting an integrated model that includes the neural bases of the regulation strategy.

快速培养法对结核病诊断的评价:拉丁美洲的一个多中心研究

地点:拉丁美洲的结核病(TB)诊断实验室。目的:薄层琼脂(thin-layer agar,TLA)和罗氏培养(Lowenstein-Jensen,LJ)对结核病诊断的对比评价。设计:6个实验室Ⅱ期前瞻性研究。临床诊断的TB病人样本包括痰标本和肺外结核的标本。呼吸道标本用NaOH／NALC去污;根据推荐的操作程序对所有标本进行离心,萋尼氏法进行抗酸菌(AFB)染色,用LJ和TLA法培养检查。计算两种培养基的敏感度和似然比、生长检测时间和污染率。结果:总共研究了1118份临床标本。所有AFB阳性标本培养后均检出结核分枝杆菌,AFB阴性标本中,LJ检出率为3．2％,TLA为4．4％。TLA和LJ的敏感性分别为92．6％(95％CI:87．9-95．9)和84．7％(95％CI:78．8-89．0)。阳性和阴性LR相似。TLA和LJ的污染率分别为5．1％和3．0％。TLA和LJ对培养阳性的检出平均时间分别为11．5天(95％CI: 9．3-15．0)和30．5天(95％CI:26．9-39．0)(P<0．0001)。结论:参加研究实验室的不同特点、疾病流行情况和标本处理的不同并不影响TLA和LJ的总体效果,建议不同实验室使用这种方法,因它具有可靠性和可行性。

A rare pigmented keratitis caused by Aspergillus fumigatus

【正】Dear Sir,I am Mauricio Vélez,from the Department of Ophthalmology,Cornea Service Director,Universidad Pontificia Bolivariana in Medellín,Colombia.Below,I would like to share an interesting case I managed recently,which I’ve entitled"A rare pigmented keratitis caused by Aspergillus fumigatus".Fungi are a relatively uncommon cause of microbial keratitis

Different Interaction Mechanisms of Evaporated Porphyrin Films Exposed to NO₂

In this work, metal free and zinc tetraphenylporphyrin films were employed as nitrogen dioxide (NO2) gas sensors. The films were vacuum evaporated and the sensor response was evaluated as changes in the optical absorption spectra, hydrophobic properties and conductivity at different gas concentrations. From UV-Vis results, important changes in the absorption peaks were observed after gas exposure. The morphology of the films before and after gas interaction was obtained by using scanning electron and atomic force microscopy. The films morphology showed a degradation after gas adsorption for the metal free system but gas entrapment for the zinc porphyrin film. In order to elucidate the gas adsorption phenomena, density functional theory calculations were also performed. Here, it was observed that the porphyrin chemical structure not only affects the gas coordination sites which affect the porphyrin electronic distribution and packing arrangement, but also, determines the gas detection mechanism for sensing applications.

Description of New Bioelectromechanical Properties in Alginate: An Insight with a Computer Simulation

Alginate biopolymer from Tropicalgin C302245 was studied by means of piezoresponse force microscopy imaging, scanning electron microscopy, powder X-rays, infrared spectroscopy and computer simulations. Local piezoresponse force microscopy images show possible ferroelectric domains detected in the out of plane mode and these results are confirmed by the second harmonic generation analysis. Alginate powder is composed by diatom frustules containing a cristobalite-like compound, amorphous silica and chitin. The experimental results are explained by MM+ and PM3 computer simulations that establish that the self-assembly of the alginate molecules enhance the polarization increasing the molecular collective dipole moment. Alginate molecular properties might open interesting possibilities for organic technological applications.

Statistical Approach to Regulation of Nanotechnology:Need,Advantages and Disadvantages

The need to have an express regulation covering nanotechnology has been the subject of debate in the scientific literature and identified as one of the main subsets of nanotechnology field research. However, most countries still do not have regulatory framework in order to guarantee consumer safety. This is the case of Costa Rica, one of the most promising countries in Latin America in terms of biotechnology and nanotechnology. This article presents a statistical study about the position of industry, academia and government institutions on the need to expressly regulate nanotechnology in Costa Rica. A qualitative study consisting of a survey of 79 forms was done to individuals representing the community involved with nanotechnology and institutions responsible for ensuring the safety of the citizen’s health, to conclude that the nanotechnology regulation should be created to protect the consumer in Costa Rica. The research also proposes aspects that should be taken into account in its drafting as well as the variables on which decisions should be made to authorize the commercialization of nanomaterials based on the findings of the literature.

An unsupervised pattern recognition methodology based on factor analysis and a genetic-DBSCAN algorithm to infer operational conditions from strain measurements in structural applications

Structural Health Monitoring(SHM) suggests the use of machine learning algorithms with the aim of understanding specific behaviors in a structural system. This work introduces a pattern recognition methodology for operational condition clustering in a structure sample using the well known Density Based Spatial Clustering of Applications with Noise(DBSCAN) algorithm.The methodology was validated using a data set from an experiment with 32 Fiber Bragg Gratings bonded to an aluminum beam placed in cantilever and submitted to cyclic bending loads under 13 different operational conditions(pitch angles). Further, the computational cost and precision of the machine learning pipeline called FA + GA-DBSCAN(which employs a combination of machine learning techniques including factor analysis for dimensionality reduction and a genetic algorithm for the automatic selection of initial parameters of DBSCAN) was measured. The obtained results have shown a good performance, detecting 12 of 13 operational conditions, with an overall precision over 90%.

Plant Cover and Soil Biochemical Properties in a Mine Tailing Pond Five Years After Application of Marble Wastes and Organic Amendments

Tailing ponds pose environmental hazards, such as toxic metals which can contaminate the surroundings through wind and water erosions and leaching. Various chemical and biochemical properties, together with extractable and soluble metals were measured five years after reclamation of a polluted soil affected by former mining activities. This abandoned mine site contains large amounts of Fe-oxyhydroxides, sulphates, and heavy metals. As a consequence, soils remain bare and the soil organic matter content is low （〈 3 g kg-1）. Marble waste, pig manure and sewage sludge were applied in 2004. Plant cover and richness, and soil chemical, biochemical and biological parameters were analysed five years later. Results showed that all soil biochemical properties as well as vegetation cover and richness were higher in treated soils than in the untreated contaminated plots （control）, although organic matter, pH values and extractable metals concentrations were similar among treatments. Soluble cadmium and zinc were lower in the amended plots than in control.

Fault diagnosis of spur gearbox based on random forest and wavelet packet decomposition

This paper addresses the development of a random forest classifier for the muki-class fault diagnosis in spur gearboxes. The vibration signal＇s condition parameters are first extracted by applying the wavelet packet decomposition with multiple mother wavelets, and the coefficients＇ energy content for terminal nodes is used as the input feature for the classification problem. Then, a study through the parameters＇ space to find the best values for the number of trees and the number of random features is performed. In this way, the best set of mother wavelets for the application is identified and the best features are selected through the internal ranking of the random forest classifier. The results show that the proposed method reached 98.68% in classification accuracy, and high efficiency and robustness in the models.

Phenomenological Based Soft Sensor for Online Estimation of Slurry Rheological Properties

This work proposes a soft sensor based on a phenomenological model for online estimation of the density and viscosity of a slurry flowing through a pipe-and-fittings assembly(PFA). The model is developed considering the conservation principle applied to mass and momentum transfer and considering frictional energy losses to include the variables directly affecting slurry properties. A reported proposal for state observers with unknown inputs is used to develop the first block of the observer structure. The second block is constructed with two options for evaluating slurry viscosity, generating two possible estimator structures, which are tested using real data. A comparison between them indicates different uses and capabilities according to available process information.

Solving Delay Differential Equations through RBF Collocation

A general and easy-to-code numerical method based on radial basis functions(RBFs)collocation is proposed for the solution of delay differential equations(DDEs).It relies on the interpolation properties of infinitely smooth RBFs,which allow for a large accuracy over a scattered and relatively small discretization support.Hardy’s multiquadric is chosen as RBF and combined with the Residual Subsampling Algorithm of Driscoll and Heryudono for support adaptivity.The performance of the method is very satisfactory,as demonstrated over a cross-section of benchmark DDEs,and by comparison with existing general-purpose and specialized numerical schemes for DDEs.

Evaluation of sources and methods of pectin extraction from fruit and Vegetable wastes:A Systematic Literature Review(SLR)

The potentially commercial sources of pectin are limited.Researchers have studied different extraction methods using a wide variety of fruits and vegetables to obtain pectins with better characteristics.The objective of this work was to identify the methods used in the extraction of pectin,the most used sources and the operation parameters that enable the achievement of higher yields and the final characteristics of the obtained product.These are based on bibliometric methods for exploring the structure of knowledge in this field for the last twelve years.To this end,a Systematic Literature Review(SLR)using the SCOPUS database was carried out,which allowed identifying keywords and formulating search equations to find scientific articles on the topic in question.After selecting the articles,a detailed reading of these works was carried out,and the used extraction methods and the evaluated variables,yields and characteristics were analyzed.This article compares and discusses the effects of conventional and non-conventional pectin extraction techniques,which may provide valuable information on sources and alternatives for pectin extraction to ease decision-making in future research.The acid hydrolysis method remains the most widely used pectin extraction technique since it provides higher yields.It is followed by microwave-assisted extraction,ultrasonic extraction,and the enzymatic method,which have a greater capacity to deliver pectins with high methoxyl content.Finally,non-conventional methods such as radiofrequency,ohmic heating,and aqueous two-phase extraction are presented as promising techniques that offer pectins with a high degree of esterification in addition to good yields.