Sort Of Mechanism Research Articles

Quantification of elastic modulus variations during zebrafish embryo development using a 3D-printed microfluidic platform

Reliable indicators to assess embryo quality are critical for the in vitro fertilization. Increasing evidence suggests that elasticity is emerging as a potential marker to evaluate the early development of embryos. This paper introduces a 3D-printed microfluidic device to measure the elastic modulus of zebrafish embryos deformed in a circular constriction channel. Firstly, numerical simulation was performed to analyze the impact of inlet pressure, embryo size and constriction channel diameter on the maximum protrusion length of the embryo. Subsequently, the zebrafish embryos were deformed using the device to record the protrusion length which was automatically measured using U-net, before the power-law rheological model was employed to calculate the elastic modulus. Experiments showed the power-law exponent and embryo elasticity were stable as the inlet pressure was not less than 250 mbar. Embryo culturing after squeezes revealed that embryos could maintain normal development even after multiple squeezes at 150 mbar while higher pressure may be fatal. Afterward, the deformation of the yolk was found to increase elasticity by 60.4% compared to cases where only the chorion envelope was deformed. Finally, the elasticity variation of zebrafish embryos was measured for 17hours. It revealed that the elasticity initially increased from hour 1 to hour 7-10 and then returned to approximately the original value during culture from the cleavage to the segmentation stages. The system with the ability of precise and long-term assessment of embryo elasticity may find valuable application potentials in the mechanical evaluation and sorting of embryos.

Applications of Machine Learning: Classifying Wheat Seeds through Computer Neural Networks

In the past few decades, the incompetent processes of traditional mechanical seed sorting have given rise to new, innovative methods, along with the integration of smart technology in agriculture. The present study created a multi-classification machine learning model that classifies wheat seeds based on given characteristics by giving highly accurate predictions for future samples based on given data. Due to various uses of different types of seeds, effective sorting is an integral preparatory stage for food processing. The dataset used in the study included seven features (directly measured characteristics of seeds), three labels (types of seeds), and around two hundred examples. The seven features include area, perimeter, compactness, kernel length, kernel width, asymmetry coefficient, and kernel groove. The first model was created through neural networks trained on all seven characteristics, reaching an overall accuracy of 0.94. Implementing a decision tree method, feature selection was applied to the data, which distinguished kernel groove, kernel width, and asymmetry coefficient as the three most important features. A new model was constructed with only the three selected features, which reduced the risk of overfitting, eliminated noise, and yielded a higher accuracy (0.96) than the previous model. Both multi-classification models used the softmax activation function and results were compared; feature selection noticeably reduced any inaccuracies, including categorical cross entropy loss. The main incentive of the study was to develop an effective model to sort wheat seeds (to replace traditional mechanical sorting) and provide reasonable recommendations for practical use through an analysis of feature selection.

Identifying defects and varieties of Malting Barley Kernels

This study introduces a comprehensive approach for classifying individual malting barley kernels, involving dual-sided kernel imaging, a specifically designed image processing algorithm, an optimized deep neural network architecture, and a mechanical sorting system. The proposed method achieves precise classification into multiple classes, aligning with quality standards for malting material assessment. Throughout the study, various image analysis techniques were assessed, including traditional feature engineering, established transfer learning deep neural network architectures, and our custom-designed convolutional neural network tailored for barley kernel image analysis. Comparative analysis underscores the superior performance of our network model. The study reveals that our proposed deep learning network achieves a 94% accuracy in classifying barley kernel defects and varieties, outperforming well-established transfer learning models to complex architectures that attain 93% accuracy. Additionally, it surpasses the traditional machine learning approach involving feature extraction and support vector machine classifiers, which achieve accuracy below 90% in detecting defective kernels and below 70% in varietal classification. However, we also noted the traditional approach’s advantage in morphological feature recognition. This observation guides new research toward integrating morphological feature extraction techniques with modern convolutional networks. This paper presents a deep neural network designed specifically for the analysis of cereal kernel images in two applications: defect and variety classification. It emphasizes the importance of standardizing kernel orientation and merging images from both sides of the kernel, and introduces a device for image acquisition that fulfills this need.

Characterization, recyclability, and significance of plastic packaging in mixed municipal solid waste for achieving recycling targets in a Swedish city

About 60% of plastic packaging in Sweden ends up in mixed municipal solid waste (MSW), which is incinerated with energy recovery. This status quo presents a missed opportunity to meet ambitious recycling targets. This study aims to provide a detailed characterization of plastic packaging in mixed MSW to assess its potential for recycling and its significance in improving the overall recycling rate. A case study involving a Swedish city was conducted wherein a sample of 5500 kg of mixed MSW from 920 households was characterized. From the 31% recycling rate, improvement of up to 59% can be achieved by diverting this misplaced plastic packaging into the existing recycling system. An additional 9% increase remains challenging to achieve due to the occurrence of non-recyclable attributes like black and multilayer packaging. The highlighted key enabler is the combination of correct household waste separation behavior and the establishment of mechanical sorting facilities to recover plastic waste from mixed MSW. These recycling potentials and associated challenges are discussed in the context of Sweden's ongoing efforts across the plastic packaging value chain. Furthermore, the importance of extended waste characterization is emphasized as a tool for identifying recycling potentials and monitoring the effectiveness of measures in enhancing circularity and resource-efficiency.

Origin of high-Mg# orthopyroxene-rich cratonic mantle: Insights from the Mogok peridotites (Myanmar)

Cratonic peridotites are typically depleted but have overall higher modal orthopyroxene than young oceanic and continental peridotites. The origin of this enrichment remains debatable. Here we focus on a spinel harzburgite block from the Mogok metamorphic belt, Myanmar, presenting major and trace element data for 27 harzburgite samples. Twelve samples are clinopyroxene-free but have high modal orthopyroxene (mostly 25.3–30.4%); The remaining fifteen are clinopyroxene-bearing (<4%), with only 10.8–22.7% orthopyroxene. The clinopyroxene-free samples display higher Mg# (91.8–92.5) than those with clinopyroxene (91.1–92.1). All samples yield a positive correlation between modal orthopyroxene and bulk Mg#, overlapping with the trend defined by refractory cratonic peridotite xenoliths. This correlation is unlikely explained by post-melting metasomatism, mechanical sorting, or serpentinization. Instead, it is consistent with non-pyrolitic, silica-rich mantle melting. Thermodynamic modeling shows that high-pressure melting (∼15–35 kbar) of the silica-rich mantle proceeds through an orthopyroxene-forming peritectic reaction, leaving residues with higher Mg# compared to those produced at lower pressures. Our harzburgite samples are compatible with this model, with high-Mg# orthopyroxene-rich samples formed at higher pressures (∼20–40 kbar) than the orthopyroxene-poor ones (∼10–20 kbar). We suggest that high-Mg# orthopyroxene-rich cratonic peridotites are likely an important component of the primordial cratonic mantle. Their formation might occur through anhydrous extensive melting of the silica-rich mantle at relatively high pressures, corresponding to the elevated potential temperatures characteristic of the Archean mantle. Progressive mantle cooling from the Archean to the present can account for the rarity of young analogues of high-Mg# orthopyroxene-rich cratonic mantle.

How far does culture go?

Abstract Focusing on the late prehistoric southern Levant, we recently suggested that the diffused low-frequency distribution of large predator bones (lion, leopard and bear) coalesces into a coherent temporal pattern when observed at a sufficiently long timescale. While in the previous research we sought to determine what sort of sociocultural mechanism might explain this pattern, effectively drawing it into the orbit of the familiar, in this brief provocation, we push in the other direction, towards the unfamiliar: how can a process or phenomenon be culturally significant yet meaningless at the human and societal levels? How is a phenomenon substantial in the long term and insubstantial in the short term?

Legal and Historical Perspective of Plant Breeders Rights Act of Pakistan

Pakistan is an agricultural country and numerous plant varieties have been developed indigenously by local scientists. There was a long felt need to introduce any sort of protection mechanism for these novel plant varieties to protect the research and development (R&amp;D). Being a World Trade Organization (WTO) member, Pakistan acceded to the Trade-Related Aspects of Intellectual Property Rights (TRIPS) agreement in 1995, and since then, legislation was due to protect the rights of breeders of new plant varieties. In 2016, the Government of Pakistan passed the Plant Breeder’s Rights Act (PBRA), in alignment with the International Union for the Protection of New Varieties of Plants Convention of 1991 (UPOV), balancing the interests of biotechnology companies and traditional plant breeders. The current study highlights Pakistan's strengths and areas that still require improvement to meet the nation's demands for plant variety protection.

Smart-sight: Video-based waste characterization for RDF-3 production

A material recovery facility (MRF) can transform municipal solid waste (MSW) into a valued commodity called refuse-derived fuel (RDF) as a promising solution to waste-to-energy conversion. The quality of the produced RDF significantly relies on the composition of in-feed waste and waste characterization method applied for auditing purposes, a process that is both time-consuming and fraught with potential hazards. This study focuses to enhance the workflow of the waste characterization process at an MRF. A solution named Smart Sight is proposed to detect and classify waste based on videos recorded after processing MSW through a mechanical sorting line consisting of bag breakers and trommel screens. A comprehensive dataset is created encompassing thirteen mixed waste classes from single and multi-family streams. The dataset is preprocessed with motion compensation techniques and frame differencing methods to extract and refine valuable frames. A one-stage YOLO detector model is then trained over the dataset. The experimental results show that the proposed method works efficiently at detecting and classifying waste objects in indoor MRF environments. Accuracy, precision, recall, and F1 score related to the proposed solution are found to be 0.70, 0.762, 0.69 and 0.72, respectively, with a mAP@0.5 of 0.716. The proposed approach is validated using data collected from local MRF by comparing the estimated waste composition values of the proposed solution with laboratory results obtained through current standardized industrial practices. Comparison reveals that waste characterization estimation obtained is consistent with the laboratory results, inferring that Smart-Sight is a viable tool for estimating waste composition.

On the cutting-edge of non-recyclable plastic waste valorization: From pyrolysis char to nitrogen-enriched activated carbon for landfill biogas upgrading

The rejected fraction of post-consumer plastics collected by mechanical sorting is a source of chemical recycling by processes such as pyrolysis, promoting the circular economy. The char residue produced in this process has been valorized, reinforcing the introduction in the consumption chain, as an adsorbent aimed at the upgrading of a biogas stream. The char was activated with KOH (496 m2 g−1) and the surface of the material was enriched with nitrogen groups (6% wt. by XPS) to raise the CO2 uptake. KOH and urea were used following different strategies, demonstrating that sequential activation and modification is the most efficient approach. Although the surface area was decreased after N insertion, i.e. from 497 to 389 m2 g−1, the CO2 uptake was raised. Specifically, comparing the CO2 uptake per micropore surface was considerably improved after urea functionalization (0.351 vs 0.235 mg m−2). The selectivity was not considerably modified, but the isosteric adsorption heat of the urea-modified sample was higher than the bare one. The behavior in the dynamic tests was studied in fixed-bed column, assessing the effect of temperature, and inlet CO2/CH4 concentration, individually and in mixtures. There was no appreciated loss of performance in the adsorption-desorption cycles. The urea-modification in a two-pot synthesis process proved a better performance in dynamic tests if compared to the non-modified activated char. This work sheds insights into the feasibility of the recycling of plastic residues giving to new added-value materials such as functionalized carbonaceous adsorbents, promoting a circular economy basis.

Spectral Characterization of Battery Components from Li-Ion Battery Recycling Processes

Considering the increasing demand for Li-ion batteries, there is a need for sophisticated recycling strategies with both high recovery rates and low costs. Applying optical sensors for automating component detection is a very promising approach because of the non-contact, real-time process monitoring and the potential for complete digitization of mechanical sorting processes. In this work, mm-scale particles from shredded end-of-life Li-ion batteries are investigated by five different reflectance sensors, and a range from the visible to long-wave infrared is covered to determine the ideal detection window for major component identification as relevant input signals to sorting technologies. Based on the characterization, a spectral library including Al, Cu, separator foil, inlay foil, and plastic splinters was created, and the visible to near-infrared range (400–1000 nm) was identified as the most suitable spectral range to reliably discriminate between Al, Cu, and other battery components in the recycling material stream of interest. The evaluation of the different sensor types outlines that only imaging sensors meet the requirements of recycling stream monitoring and can deliver sufficient signal quality for subsequent mechanical sorting controls. Requirements for the setup parameters were discussed leading to the setup recommendation of a fast snapshot camera with a sufficiently high spectral resolution and signal-to-noise ratio.

Design of an IoT ultrasonic-vision based system for automatic fruit sorting utilizing size and color

While integrating mechanical conveyor chains and object sorting automation with an Internet of Things (IoT) system can present exciting and challenging opportunities, the potential benefits of increased efficiency, real-time tracking, and predictive maintenance make it valuable. Machine learning techniques, precise computer vision, and ultrasonic technology have proven to be powerful tools for accurately detecting and differentiating fruits based on color and size. In light of this, a proposed solution is developing an automatic IoT system comprising a mechanical conveyor chain, wooden sorting trays, ultrasonic sensors, a fisheye camera, Raspberry Pi, and other necessary components. This system can detect and sort fruits such as apples, oranges, lemons, tangerines, bananas, and avocados into four customizable trays, with a sorting accuracy of 90%. Moreover, the system can be easily adapted and expanded to support more sorting trays and a more comprehensive range of agricultural products.

Influence of a biodegradable contaminant on the mechanical recycling of a low‐density polyethylene sample

AbstractMechanical recycling of oil‐derived polymers is certainly our best option to reduce pollution, save raw materials, and protect ourselves and the environment from the adverse effects of waste disposal. However, the presence of contaminants, including other types of plastics, that are mixed in during the recycling collection process or during the mechanical waste sorting stage could adversely affect the quality of the recycled product, leading to the recycling of a poor‐quality secondary material. In this work, the influence of a biodegradable contaminant on the mechanical recycling of a low‐density polyethylene (LDPE) sample was investigated by rheological (shear and non‐isothermal elongation) and mechanical analyses. The results showed that 2% of the contaminant is able to influence the rheological, shear, and isothermal elongation properties of recycled LDPE, while the results of the mechanical tests showed that after one extrusion cycle, the main tensile properties were not significantly affected by the presence of the contaminant, but after only two cycles of extrusions, some significant reduction in the final properties began to appear. In short, the presence of 2% of a biodegradable co‐polyester in a LDPE matrix gives rise to a more pronounced decay of the rheological and mechanical properties, but, after two extrusion steps, both rheological and mechanical properties seem still useful for the production of film.Highlights To what extent the contaminant affects the quality and usability of the recycled LDPE; The effects of contamination on the LDPE sample during the recycling process; Reduction in properties, compromising product quality; Compromised product quality after only two additional processing steps; Important implications for the recycling industry.

Effect of 2 sex-sorting time schedules on SIT facility management.

Improvements are needed in mosquito mass-rearing to effectively implement the sterile insect technique (SIT). However, managing this technique is challenging and resource intensive. SIT relies on mass rearing, sterilization, and release of adult males to reduce field populations. Maintaining an acceptable level of female presence, who can transmit viruses through biting, is crucial. Females are also essential for facility sustainability. Sex sorting plays a vital role in the production process, and our current mechanical sorting approach aims to obtain a high number of adult males with minimal female contamination within 24 h of pupation. Utilizing protandry helps control female contamination. While the 24-h sorting period achieves desired contamination levels, it may not yield enough females to sustain breeding lines, leading to increased labor costs that impact project sustainability. By delaying the sorting procedure to 48 h, we obtained sufficient females to sustain breeding lines, achieving a balance between male production and female contamination using the automatic version of the Fay-Morlan device as the sorting tool.

FTIR study of H2O in silicate minerals and mineral inclusions in chromite from the peridotite zone of the Stillwater complex (Montana, USA): Evidence for chromitite formation in an H2O-rich environment

Although the involvement of hydrous fluids has been frequently invoked in the formation of stratiform chromitites in layered intrusions, there is a lack of natural evidence to signify their presence and mechanism. Here, Fourier-transform infrared spectroscopy (FTIR) of H2O in silicate minerals in the lowermost layer and G chromitite layer of the Stillwater complex, Montana, USA, shows that olivine grains have 20−55 ppm H2O, orthopyroxene has 30−45 ppm H2O, and clinopyroxene has 144−489 ppm H2O. The jointly increasing H2O contents of olivine and orthopyroxene in silicate cumulates along with magma differentiation record a negative correlation in chromitites. On the basis of poikilitic clinopyroxene, we calculated that the interstitial melts had averages of 1.3 wt% and 2.3 wt% H2O in dunite and chromitite, respectively, showing significant differences between chromitites and silicate cumulates. More than 10% of the chromite grains contained polymineralic inclusions up to 100 μm in size that were composed mainly of orthopyroxene, hornblende, plagioclase, and phlogopite. Most of these minerals were characterized by higher MgO and fluid-mobile element contents, such as Na and K, than minerals in associated silicates. Based on the mineral modes of the hydrous phases and their compositions, the trapped fluids contained ∼2.6 wt% H2O, consistent with the FTIR estimates, indicating the inclusion compositions represent interstitial melts instead of parental magmas. These observations indicate that the chromite microlites collected fluids during early crystallization, leading to a heterogeneous fluid redistribution in the melt. The fluids were collected on the surface of chromite grains during crystallization and then dissolved into poikilitic pyroxene. Chromite grains could also be efficiently floated by these fluids, causing them to migrate away from the silicate minerals in the magma channel and leading to the formation of nearly monomineralic chromitite seams. This process serves as a kinetic model indicating that chromite could be completely separated from silicates during mechanical sorting in layered intrusions.

Management practices for compostable plastic packaging waste: Impacts, challenges and recommendations

The EU Green Deal aims at solving the challenges related to plastic production, (mis-)use, and pollution. While the bioplastic industry is identified as one of the possible avenues to tackle the problem, bioplastic waste collection and management practices are still far from full-development and harmonisation. To inform policy makers on the best practices and their feasibility, this study quantifies environmental and economic impacts of compostable plastic packaging (CPP) waste management schemes by means of Life Cycle Assessment and Costing. Results show that, with respect to climate change and financial costs, the scheme leading to the highest benefits is collecting CPP with conventional plastic waste followed by mechanical sorting and recycling (saving ca. 306 kg CO2eq. t−1 at a net income of 3.7 EUR t−1). The second best option is collecting CPP with bio-waste followed by biological treatment (saving ca. 69 kg CO2eq. t−1 at a cost of 197 EUR t−1). Collecting CPP with conventional plastics followed by sorting and biological treatment is to be avoided. The trend on the other impact categories generally follows climate change. Ideally, closed loop is therefore preferred, but conditioned by (i) having high share of CPP in municipal waste (else sorting is economically unfeasible), (ii) good citizen’s behaviour at source-segregation, and (iii) an established market for secondary material. Currently, overall benefits are limited by the low amounts, suggesting that the management choice could ultimately be based on rather simple technical and economic feasibility criteria while regulatory and management efforts should be focused on other waste streams with greater implications on environment.

Effect of the incorporation of an excavated earth fine grained fraction in cementitious mixes

In the current context of global warming, valorisation of waste materials is becoming a key issue in the cement and concrete industries. This research focuses on the effect of the incorporation of an excavated earth fine-grained fraction (< 63 μm) in cement mixes and its contribution to the cement hydration mechanisms which are mainly coming from the Paris region of France. This fine-grained fraction results from a washing and mechanical sorting of grains process for excavated earth. The omnipresence of gypsum in the subsoil of the Paris region, due to its geological context, is reflected in the fine-grained fraction with the presence of sulphates. Moreover, the fine-grained fraction is also composed of quartz, calcium carbonates and clay phases. The tests have been performed on cement pastes composed of a blast furnace slag cement and the fine-grained fraction as a sludge with its inherent humidity. Pastes with different sludge contents leading to different water-cement ratios (0.5, 0.7 and 0.8) have been studied. The impact of the incorporation of the fine particles and the water contained in the sludge on the rheology and the hydration of the cement pastes has been evaluated using water demand tests, thermogravimetric analysis and isothermal calorimetry. Results indicate that the incorporation of sludge in cementitious mixes increases the water demand, accelerates the hydration reactions and contributes to the formation of additional hydrate phases probably associated with the presence of gypsum in the studied sludge.

Development of flexible tactile sensing arrays for hardness recognition

Hardness sensation is an essential function of human skin, which is significant for enhancing the objects perception ability of intelligent manipulators in various scenarios. Although progress has been made in mimicking this function of human hands, the hardness identification still remains a great challenge. In this study, inspired by the Hertz model and the static pressure response of Merkel cells (SA-I) mechanoreceptors, we develop a membrane-like piezoresistive flexible tactile sensor array (PFTSA) that consists of a flexible electrode array layer and a sensitive material layer with a micropyramidal structure, which can effectively identify the hardness values of different objects. The sensor can be a part of the manipulator’s system due to its conformal ability and large deformation, which shows high pressure response sensitivity (4.432 mA/N in the 0–1 N pressure range) and good cycling stability (2100 cycles at 5 N), enabling the consistent and precise detection of external information. As a proof-of-concept illustration, we integrate the PFTSA on a finger of the manipulator to discriminate six objects with different hardness values. The results demonstrate the great potential of PFTSA in the application of human-machine interactions, paving the way for the development of robotic diagnostics, mechanical sorting operations and virtual reality technology.

Towards circular plastics: Density and MFR prediction of PE with IR spectroscopic techniques

The high variety of tailor fitted molecular structures of polyethylene (PE) is very beneficial to fulfill requirements of various applications, however it poses a difficulty in the mechanical recycling of post-consumer PE products. To improve the quality of PE recyclates and increase the amounts of recyclates that can be used in new products, separation of PE waste by density and melt flow rate (MFR) during mechanical sorting is essential. Therefore, 25 virgin PE grades were used to manufacture compression molded plates that were then characterized by means of Attenuated Total Reflection - Fourier transformed IR (ATR-FTIR) and near IR (NIR) spectroscopy, NIR hyperspectral imaging and dual-comb spectroscopy. The results were used to build partial least squares regression (PLS) models to predict MFR and density. ATR-FTIR and laboratory NIR spectroscopy provided sufficient information to predict the density value of PE, whereas the MFR assessments was not possible. The PLS model from the industrial NIR data also only allowed the density-based classification of virgin PE grades. The PLS models built from transmission and reflectance dual comb spectroscopy infrared (DCS-IR) of selected samples clearly showed that density and MFR prediction can be carried out with high accuracy. As DCS-IR could be implemented on plastic sorting systems using a conveyor belt, the addition of this sensor in mechanical sorting line would lead to a significantly higher quality of recycled PE with narrow well-defined density and MFR ranges. Such an improvement would immensely support the targeted recycling rates and amount by the European Union and would make a significant step towards circular plastics.

Optimization of the sustainable production pathways under multiple industries and objectives: A study of China's three energy- and emission-intensive industries

Sustainable production pathways are essential for the greening of the industrial sector. To develop the comprehensive optimal pathway, it is important to consider the interactions between multiple industries and objectives. While previous studies have combined several objectives in this field, the simultaneous optimization of multiple industries is still lacking. This study simulates the system of industrial sustainable production measures, including 184 measures in seven types, and proposes the optimization model in China's iron and steel, cement, and coal-fired power industry as cases. To solve this problem with large-scale variables and high-dimensional objectives, this study develops the solution approach including the objective decomposition mechanism and non-dominated sorting genetic algorithm–II–elimination and choice expressing reality (NSGA–II–ELECTRE-III) algorithm, with final decision schemes selected by the Vague-set based approach. Results show that though the energy and emission objectives within an industry are synergic, but the relationships between different industries are almost irrelevant. By 2035, The three industries are estimated to reach energy conservations and emission reductions of 5.2–66.8% compared to 2017. The optimal solutions can exceed the air pollutant emission reduction targets but take risks of reaching energy conservation and CO2 emission reduction ones. The main contribution measures in the three industries are the integration of production equipment structure upgrade and cleaner production technology promotion, production output limitation, and production equipment structure upgrade, respectively, with 57 measures being prior for promotion. In sum, this study provides new solution methods and several policy suggestions for industrial sustainable production management.

Butyrylcholinesterase in lipid metabolism: A new outlook.

Cholinesterase enzymes acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) are traditionally associated with the termination of acetylcholine mediated neural signaling. The fact that these ubiquitous enzymes are also found in tissues not involved in neurotransmission has led to search for alternative functions for these enzymes. Cholinesterases are reported to be involved in many lipid related disease states. Taking into view that lipases and cholinesterases belong to the same enzyme class and by comparing the catalytic sites, we propose a new outlook on the link between BChE and lipid metabolism. The lipogenic substrates of BChE that have recently emerged in contrast to traditional cholinesterase substrates are explained through the hydrolytic capacity of BChE for ghrelin, 4-methyumbelliferyl (4-mu) palmitate, and arachidonoylcholine and through endogenous lipid mediators such as cannabinoids like anandamide and essential fatty acids. The abundance of BChE in brain, intestine, liver, and plasma, tissues with active lipid metabolism, supports the idea that BChE may be involved in lipid hydrolysis. BChE is also regulated by various lipids such as linoleic acid, alpha-linolenic acid or dioctanoylglycerol, whereas AChE is inhibited. The finding that BChE is able to hydrolyze 4-mu palmitate at a pH where lipases are less efficient points to its role as a backup in lipolysis. In diseases such as Alzheimer, in which elevated BChE and impaired lipid levels are observed, the lipolytic activity of BChE might be involved. It is possible to suggest that fatty acids such as 4-mu palmitate, ghrelin, arachidonoylcholine, essential fatty acids, and other related lipid mediators regulate cholinesterases, which could lead to some sort of compensatory mechanism at high lipid concentrations.