Genomic profiling for clinical decision making in myeloid neoplasms and acute leukemia

Myeloid neoplasms and acute leukemias derive from the clonal expansion of hematopoietic cells driven by somatic gene mutations. Although assessment of morphology plays a crucial role in the diagnostic evaluation of patients with these malignancies, genomic characterization has become increasingly important for accurate diagnosis, risk assessment, and therapeutic decision making. Conventional cytogenetics, a comprehensive and unbiased method for assessing chromosomal abnormalities, has been the mainstay of genomic testing over the past several decades and remains relevant today. However, more recent advances in sequencing technology have increased our ability to detect somatic mutations through the use of targeted gene panels, whole-exome sequencing, whole-genome sequencing, and whole-transcriptome sequencing or RNA sequencing. In patients with myeloid neoplasms, whole-genome sequencing represents a potential replacement for both conventional cytogenetic and sequencing approaches, providing rapid and accurate comprehensive genomic profiling. DNA sequencing methods are used not only for detecting somatically acquired gene mutations but also for identifying germline gene mutations associated with inherited predisposition to hematologic neoplasms. The 2022 International Consensus Classification of myeloid neoplasms and acute leukemias makes extensive use of genomic data. The aim of this report is to help physicians and laboratorians implement genomic testing for diagnosis, risk stratification, and clinical decision making and illustrates the potential of genomic profiling for enabling personalized medicine in patients with hematologic neoplasms

The 5th edition of the World Health Organization classification of haematolymphoid tumours: myeloid and histiocytic/dendritic neoplasms

The upcoming 5th edition of the World Health Organization (WHO) Classification of Haematolymphoid Tumours is part of an effort to hierarchically catalogue human cancers arising in various organ systems within a single relational database. This paper summarizes the new WHO classification scheme for myeloid and histiocytic/dendritic neoplasms and provides an overview of the principles and rationale underpinning changes from the prior edition. The definition and diagnosis of disease types continues to be based on multiple clinicopathologic parameters, but with refinement of diagnostic criteria and emphasis on therapeutically and/or prognostically actionable biomarkers. While a genetic basis for defining diseases is sought where possible, the classification strives to keep practical worldwide applicability in perspective. The result is an enhanced, contemporary, evidence-based classification of myeloid and histiocytic/dendritic neoplasms, rooted in molecular biology and an organizational structure that permits future scalability as new discoveries continue to inexorably inform future editions

On the neurocomputing based intelligent simulation of tractor fuel efficiency parameters

Tractor fuel efficiency parameters (TFEPs) (fuel consumption per working hour (FCWH), fuel consumption per tilled area (FCTA) and specific volumetric fuel consumption (SVFC)) were intelligently simulated. A neurocomputing based simulation strategy (adaptive neuro-fuzzy inference system (ANFIS)) was used to simulate the TFEPs. A comparison was also made between results of the best ANFIS environment and those of another neurocomputing based simulation strategy, artificial neural network (ANN). Field experiments were conducted at plowing depths of 10, 20 and 30 (cm) and forward speeds of 2, 4 and 6 (km/h) using a disk plow implement. Statistical descriptor parameters applied to evaluate simulation environments indicated that the best simulation environment of both ANFIS and ANN were able to perfectly predict the TFEPs. However, the best comprehensive ANN simulation environment with a simple architecture of 2-6-3 was easier to use than three individual ANFIS simulation environments. The ANN results revealed that simultaneous increase of forward speed from 2 to 6 (km/h) and plowing depth from 10 to 30 (cm) led to nonlinear increment of the FCWH from 5.29 to 14.89 (L/h) and nonlinear decrement of the SVFC from 2.95 to 0.67 (L/h kW). Meanwhile, forward speed increment along with plowing depth decrement resulted in nonlinear decrement of the FCTA from 28.13 to 12.24 (L/ha). Interaction of forward speed and plowing depth on the FCWH and SVFC was congruent, while it was incongruent for the FCTA. It is suggested to employ the ANN environment in developing future fuel planning schemes of tractor during tillage operations. Keywords: Adaptive neuro-fuzzy inference system, Artificial neural network, Fuel consumption per working hour, Fuel consumption per tilled area, Specific volumetric fuel consumptio

Prognostication of energy indices of tractor-implement utilizing soft computing techniques

Energy indices (energy requirement for tillage implement (ERTI) and tractor overall energy efficiency (TOEE)) of tractor-implement during tillage operations were aimed to be investigated in this study. To generate a new comprehensive model, the effects of forward speed at three levels (2, 4 and 6 km/h) and plowing depth at three levels (10, 20 and 30 cm) on energy indices were experimentally evaluated. Two soft computing techniques, artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS), were employed to prognosticate energy indices. Comparison between the best developed structure of each soft computing technique demonstrated that one comprehensive ANN model was preferred than two individual ANFIS models. According to the ANN prognostication results, simultaneous increase of forward speed from 2 to 6 km/h along with plowing depth increment from 10 to 30 cm led to nonlinear increment of the ERTI and TOEE from 33.87 to 122.66 MJ/ha and 4.65 to 17.85%, respectively. Moreover, interaction of forward speed and plowing depth on energy indices was congruent. Development of comprehensive ANN model now makes it possible to answer fundamental questions in domain of the effect of plowing depth and forward speed on energy indices of tractor-implement that were previously intractable. Hence, to properly manage energy indices and reduce energy dissipation of tractor-implement, application of the new developed ANN model is strongly recommended. Keywords: Artificial neural network, Energy requirement for tillage implement, Tractor overall energy efficiency, Adaptive neuro-fuzzy inference syste

Feasibility of implementation of intelligent simulation configurations based on data mining methodologies for prediction of tractor wheel slip

This paper deals with implementation of intelligent simulation configurations for prediction of tractor wheel slip in tillage operations. The effects of numeral variables of forward speed (2, 4, and 6 km/h) and plowing depth (10, 20, and 30 cm), and nominal variable of tractor driving mode (two-wheel drive (2WD) and four-wheel drive (4WD)) on tractor rear wheel slip were intelligently simulated utilizing data mining methodologies of artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS). Neuro-fuzzy potential of the ANFIS simulation framework against neural ability of the ANN simulation framework was apprised. Results confirmed higher efficiency of the best configuration of the ANFIS simulation framework with satisfactory statistical performance criteria of coefficient of determination (0.981), root mean square error (1.124%), mean absolute percentage error (1.515%), and mean of absolute values of prediction residual errors (1.135%) than that of the ANN simulation framework. Physical perception obtained from the ANFIS simulation results demonstrated that the wheel slip increased nonlinearly with increment of forward speed and plowing depth, while it decreased as tractor driving mode changed from the 2WD to 4WD. Therefore, the best configuration of the ANFIS based intelligent simulation framework implemented in this study can be used for further relevant studies of tractor rear wheel slip as a reference. Keywords: Forward speed, Plowing depth, Tractor driving mode, Tillage operations, Tractor tractive efficienc

Determining the most suitable frequency and shaking time for olive harvesting by a pneumatic branch shaker

Introduction Olive (Oleo europaea) includes about 20 species of small trees from Oleaceae family. This point should be considered that Iran has allocated only a small universal market to its olive products in spite of having high production potentials; so that about 23 provinces of this country can produce olive products. Therefore mechanizing of olive production and encouraging to develop olive trade are among the effective methods for development of this market. On the basis of IOOC report, the production of olive oil in 2008-2009 in Iran and all over the world has been 3 and 2866.5 thousand tons, respectively. Currently, harvesting olive product is done by hand in Iran. The expensiveness of work force and providing the needed workers are considered as the biggest problem in olive harvesting. While harvesting the tall trees, the workers use beating method by wood sticks which causes the fruits to be damaged and their quality to be decreased. The harvesting method which the quality and quantity of the olive final products is under its effect and also high expenses of harvesting by hand are considered as the two important factors in developing the mechanical harvesting of olive. For this purpose, the mechanized harvesting of olive should be considered for producing olive conserve and olive oil and decreasing expenses of harvesting. Considering the conducted studies on one hand and shortage of informational resources in the country on the other hand, a research was designed and performed with the following purposes: Designing and fabricating of a portable pneumatic branch shaking system. Determining the best frequency and oscillation duration for harvesting olive by the constructed system. Materials and Methods The branch shaking system is made of two general parts: (a) The set of branch shaker driving unit. (b) The portable vibration arm. For constructing the set of vibrating arm, two experiments “elasticity and inflectionˮ of tree branches were conducted and the maximum force of 362.40 N was registered and it was considered as the base of computations. Then a double-action pneumatic jack with the internal diameter of 32 mm and the rod diameter of 12mm with the stroke length of 200 mm was selected. An electronic circuit was designed and developed for ordering the solenoid valve to control the flow. The system was transferred to one of the olive garden’s located in kilometer 5 of Sarvestan – Fasa road in Fars province in order to be evaluated. The effects of three oscillation frequencies of 12, 16 and 20 Hz and three oscillation durations of 5, 10 and 15 seconds at constant amplitude of 5 cm on detachment percentage of olive fruit was investigated through a factorial 3×3 experiment based on completely randomized design with four replications. Then the most suitable frequency and vibration duration was selected for harvesting olive by this system. For measuring the static detachment force of the fruits, a tensile force dynamometer system model FG-5100 made by Lutron Company was used with the accuracy of 0.1 N and a maximum capacity of 980 N. Results and Discussion The variance analysis of the investigated features on the basis of the factorial experiment based on completely randomized designs was conducted through using SPSS software. The results showed that both frequency of vibration and oscillation duration had significant effect on the shaker performance; with no significant interaction effects which implies the independence of the debated variables. Comparing the means by using Duncan test at 1% significance level for features of oscillation frequency and duration of shaking showed that at any constant duration of oscillation, increasing of oscillation frequency significantly increases the percentage of the olive fruit detachment. This increase is due to the increase of dynamic force with the second power of oscillation frequency compared to the static separating force (Murphy, 1950). It was observed that the calculated dynamic force is larger than the static force for separating the fruit in frequencies of 16 and 20 Hz, but since the dynamic force is variable at each point of the branch, 84.50 percent of fruits are separated from branches at frequency of 16 Hz and 87.25 percent of the fruits are separated from branches at frequency of 20 Hz. Conclusions At the end, the frequency of 20 Hz with 5 second duration of oscillation was selected as the most suitable treatment for this branch– shaker in harvesting oil-type olives

Laboratory Study of Standardized Shear Energy of Alfalfa Stem to Estimate Some Nutritional Quality Indices

Introduction Current study tries to find a new simple and practical real-time technique to estimate forage crop nutritional quality indices at field conditions. Estimating these indices help producers to have field quality variation layer to reach the goals of Precision Agriculture. Previous studies have shown that standardized shear characteristics of crop stem would be a good indicator for some nutritional quality indices. In previous studies, laboratory tests were conducted at controlled conditions of crop moisture content, stem diameter and employing standard shear test procedure. Materials and Methods In order to simulate field conditions, a two-stage study was conducted in Iran and United States. In the first stage fresh and naturally sun dried alfalfa stems were used in evaluating four levels of crop growth stage and eight loading conditions (four loading rates and two stem conditions). In order to evaluate the effectiveness of shear technique with respect to the conventional harvest method in Iran, shear tests were conducted using fixed and moving knives of a standard square hay baler (John Deere-348). Special fixtures were constructed to attach these knives to a universal testing machine (SANTAM, STM-20). Since evaluation of the suggested method with regard to other quality related factor indices such as different varieties and seeding rates, was not practically feasible in Iran in the second stage of this research, five different varieties and three seeding rates were tested in United States. In this part of the study, shear tests were conducted using modified Varner-Bratzler shear test with universal testing machine (TESTRESOURCES-311). Based on the results of loading rate and stem condition in the first stage, shear tests were carried out using loading rate of 500 mm/min and multiple stem condition. In both stages Specific Shear Energy (shear energy per stem diameter, J mm-1) were calculated using trapezoidal method. In order to compare the shear energy results with crude fiber nutritional quality indices such as Acid Detergent Fiber (ADF), Neutral Detergent Fiber (NDF) and Relative Feed Value (RFV), all alfalfa samples were analyzed using (Association of Official Agricultural Chemists) AOAC standard analytical laboratory methods. Statistical analyses were consisted of ANOVA mean comparison test at each level of factors and regression analysis to find the correlation between specific shear energy and nutritional quality indices. Results and Discussions Results of ANOVA analysis and mean comparisons showed a significant difference in specific shear energy at different levels of loading rates. The higher loading rates showed lower energy which was related to lower ability of knives to cut alfalfa stem thoroughly and shredding the stems at lower speed levels. Significant differences were found in different levels of annual growing cycle, harvest time and seeding rates. Alfalfa stem in fifth harvest year showed the highest shear energy due to higher lignification in plant stems. In the first year, harvested alfalfa stem did not have the lowest shear energy which might be due to existence of weeds in first year field. Results showed higher values of shear energy in fifth harvest of the season in comparison with the third harvest which was acceptable because of differences in plant received Degree Day in these harvest times. The lowest seeding rate (5 kg h-1) showed the highest shear energy respect to the other seeding rates. The reason for this significant difference could be due to lower competition to receive water and nutritions, also lower plant density helps the canopy to receive more sun light which causes higher lignification. Comparing the shear energy means in different varieties didn’t show significant differences which can be explained because of varieties adoptability to the region specific weather condition. The regression analysis showed good correlations between specific shear energy and crude fiber nutritional indices (ADF, NDF and RFV). The negative trends which were found in regression analyses were also reported in similar studies. Conclusions Two stage laboratory tests were conducted in order to evaluate the effect of alfalfa nutritional feed quality indices related factors on unitized shear energy. Results showed a significant difference of standardized shear energy mean at different levels of harvest time, annual growing cycle and seeding rates. The specific shear energy was not significantly different in different varieties because of varieties environmental adoptability. The unitized shear energy showed a good correlation with crude fiber related indices with similar trends in both stages of research and good agreements with previous studies