Transient flow responses of viscoelastic fluids to different external body forces are studied. As a non-Newtonian fluid, the viscoelastic fluid exhibits significant elastic response which does not raise in Newtonian fluid. Here, we investigate the transient response of a viscoelastic Poiseuille flow in a two-dimensional channel driven by external body forces in different forms. The velocity response is derived using the Oldroyd-B constitutive model in OpenFOAM. Responses in various forms like damped harmonic oscillation and periodic oscillation are induced and modulated depending on the fluid intrinsic properties like the viscosity and the elasticity. The external body forces like constant force, step force and square wave force are applied at the inlet of the channel. Through both time domain and frequency domain analysis on the fluid velocity response, it is revealed that the oscillation damping originates from the fluid viscosity while the oscillation frequency is dependent on the fluid elasticity. The velocity response of the applied square waves with different periods shows more flexible modulation signal types than constant force and step force. An innovative way is also developed to characterize the relaxation time of the viscoelastic fluid by modulating the frequency of the square wave force. Much attention has been paid to the fluid logic component due to its advantages of no extra mechanical structure, low cost and high reliability. Its resistance to extreme conditions of shock, vibration or radiation is also desired for many applications.Fluid has been widely used as the medium for energy and force transmission in control systems named as fluidic devices. Such devices has been developed into functional dynamic elements like amplifiers and triodes, and exhibit logical operations similar as electronic componentsRe) number flows by taking the advantage of the nonlinear property of Newtonian fluid6. While in microfluidic component, the logical function usually relies on the formation of droplets7, bubbles8 or circuits with valve switches9. For real application, these methods usually require complex control systems. On the other hand, realizing nonlinear behavior of Newtonian fluid for microfluidic components remains large challenging as extremely high pressure is required to achieve high Re number condition10. However, other studies14 show that viscoelastic fluid can induce nonlinear characteristic from its elastic property even at extremely low Re conditions17. Therefore, by using a viscoelastic fluid, a nonlinear microfluidic circuit can be obtained.Traditionally, fluidic logical functions are implemented in macro-scale devices at high Reynolds  limited linear models including Maxwell model, Jeffreys model and Generalized Maxwell model35, etc.; (2) nonlinear differential models including Convected Maxwell model, Convected Jeffreys model, Oldroyd 8-Constant model, White-Metzner Model, FENE (FENE-P) model and Giesekus model36, etc. In this study, we adopt the Oldroyd-B model, which is one of the Oldroyd 8-Constant models due to its simplicity. Based on the Oldroyd-B model, we build a new solver for viscoelastic fluid flow in OpenFOAM.Firstly, we need to choose suitable constitutive models to represent the flow properties of viscoelastic fluids. There are various constitutive models being developed, among which two models are often usedu is the velocity vector normalized by the maximum velocity Umax; p is the pressure in the fluid and normalized by ρUmax2, where ρ is density of the fluid; Ts is the viscous stress, and Tp is the elastic stress. Ts is described as ηs to the total of solvent viscosity and solute viscosity ηp. F0 corresponds to the external body force and i represents the unit vector in the x-direction. H is the characteristic length of the flow and equals to the half width of the channel. In the Newtonian fluid flow, there is no elastic component and Tp = 0. For the viscoelastic fluid described in the Oldroyd-B model, the elastic stress term in the constitutive equation is described asC is the conformation tensor; I (Kronecker symbol) is the unit tensor; ηP is the dynamic viscosity of the solute, and The dimensionless governing equations for incompressible viscoelastic fluid flow are expressed as::The conformation tensor transport equation is:Wi number typically break down due to the computational instability. The instability may arise from the nonlinear term in Eq. 10) into 39.The dominant nonlinear term of original conformation tensor in Eq.  turns in40 with the dimensionless time step δt being 10−3. In spatial discretization, the QUICK scheme41 is adopted for the convective term in Eq.  of two fluid flows at the outlet in a dimensionless time t are shown in Fig. uN first increases logarithmically from time 0 to 1 and then saturates at uN = 1 due to the balance between the applied force and the viscous dissipation in the flow. In contrast, the velocity of viscoelastic fluid uV fluctuates as an under-damped vibration function with time: uV first increases to a peak value of 1.9 at t = 1.5, drops to a dip value of 0.7 at t = 4.1, and then continues to oscillate with a damping effect until it finally stabilizes at uV = 1. The oscillation originates from the non-zero elasticity of viscoelastic fluid responding to the constant F0. uV increases at time 0 due to the applied F0. At the same time, the molecular microstructures in viscoelastic fluid are deformed due to its elasticity and elastic potential energy is stored in the molecular microstructures of viscoelastic fluid. The potential energy can be converted to kinetic energy which makes uV continue to increase and exceed the stable velocity of the Newtonian fluid until time t = 1.5. And then, uV starts to drop due to the viscous effect. Meanwhile, the kinetic energy of fluid flow converts to the potential energy, which makes uV continue to drop below the stable velocity of the Newtonian fluid flow until t = 4.1. At this moment, F0 overwhelms the viscous dissipation and uV starts to increase again. The process repeats which leads to an oscillation velocity response of viscoelastic fluid flow to the constant F0. During the oscillation, the total energy decreases due to the viscosity, and therefore the oscillation is damping. The damped oscillation of velocity response in viscoelastic fluid flow reaches a stable state when the viscous resistance balances with the external F0 and the molecular microstructure in viscoelastic fluid remains in a static state. Then, viscoelastic fluid flows at a constant velocity uV = 1 after t = 15. The stable velocities are the same for the Newtonian fluid and viscoelastic fluid flows with the same viscosity under the same constant force. Further investigation on the damped oscillation in the frequency domain reveals a peak resonance at f = 0.27 based on fast Fourier transform, as shown in the inset of Fig. The centerline velocities F0 with different magnitudes are applied to viscoelastic fluid flows, the velocity oscillates with an amplitude proportional to F0 while the oscillation peaks and dips occur at the same time value for all F0, as indicated by open circles in Fig. When the constant forces F0, the oscillation curves of u are shown as solid lines in Fig. F0 as shown in Table A and T are the amplitude and period of harmonic oscillation, respectively; α is the damping coefficient; u0 and tc are the offset values for the amplitude and time, respectively. α and T remain the same when F0 changes because they are intrinsic properties of viscoelastic fluid and only affected by the viscosity and elasticity of viscoelastic fluid. The amplitude of sinusoid functions A, on the other hand, increases proportionally with F0, which is plotted in Fig. tc, which relates to the oscillation phase of velocity, is the same for different F0 because the starting time of force is the same.By fitting parameters in Eq.  to the nAs analyzed above, the damped oscillation depends strongly on the elasticity of viscoelastic fluid. In a fluid with larger elasticity, more potential energy can be stored in the fluid before it is saturated. The potential energy is then converted to the kinetic energy and drives the velocity to increase for much time. For the same reason, with larger elasticity, more time is also needed for the fluid to convert the kinetic energy to the potential energy during the velocity drop period. As a result, the oscillation period should be longer for the fluid with a larger elasticity number. This is numerically confirmed by comparing the transient response of centerline velocities at different elasticity numbers as shown in Fig. T increases from 4.16 to 17.94 as elasticity number E increases from 1 to 20. This proportional relation is explained quantitatively previously. The amplitude A also increases significantly from 1.79 to 7.26, which is because of a viscoelastic fluid with larger elasticity gains and converts more potential energy to the kinetic energy. In addition, the effective damping factor T· α, or the damping in one oscillation period, decreases from 2.20 to 0.66, indicating that the fluid with larger elasticity will experience a relatively lower damping effect under a constant force excitation.The velocity response at different elasticity numbers is then fitted using Eq.  and the f = 0.242, 0.110, 0.078, 0.064 and 0.055 are obtained for E = 1, 5, 10, 15 and 20, respectively, as shown in Fig. The oscillation is further investigated in the frequency domain through a fast Fourier transform of temporal response. Different resonant frequencies of E = 1 and different β in Fig. β are listed in Table T and the amplitude A remain almost the same when β increases from 0.01 to 0.2. In contrast, the damping factor α increases significantly from 0.06 to 0.29 for the same values of β, suggesting that the oscillation damping depends remarkably on the viscosity. The dominant frequency is the same for the viscoelastic fluid with different β as shown in Fig. β, which is due to the lowest energy loss in the oscillation.Besides elasticity, the viscosity is another critical property of viscoelastic fluids which describes its resistance to gradual deformation under shear stress or tensile stress. This resistance induces friction, which slows down the flow velocity. The centerline velocities are compared for viscoelastic fluids with a fixed elasticity number E = 1 to an applied rectangular function force. Here, we define the force as:Tr is the force applied time. Figure F0 and fixed Tr = 1. The velocity increases from time t = 0 to t = Tr, and during the period, the condition is the same with one when a constant force is applied. As discussed previously, under a constant force, the velocity oscillation for the fluid with E = 1 has a period T = 13.7 and is in its ramp-up stage of the first cycle when t = Tr. However, for the rectangular force, the force is unloaded at this point. One interesting phenomenon observed is that the velocity remains constant for another 1 s after the force is unloaded until t = 2. After that, the velocity amplitude starts to drop sharply from t = 2 to t = 4 and then drop very slowly from t = 4 to t = 6. Then it becomes damped oscillation and finally ends with a velocity of 0. The length of this “platform effect”, the short-term constant velocity behaviour after the force is unloaded, is independent of the rectangular force amplitude but the magnitude of velocity increases proportionally with the amplitude. A fast Fourier transform is performed to further investigate the velocity response, as shown in Fig. f = 0.091 Hz, which is blue shifted compared to the resonance frequency f = 0.078 Hz under the constant force excitation condition as indicated in Fig. In this section, we study the transient velocity response of viscoelastic fluid flow with elasticity E = 10) and varying Tr, it continues to study the platform effect. It is found that the platform effect only appears when the force is unloaded during the velocity ramping stage of the first oscillation period, as seen in Fig. f = 0.091 Hz for different Tr, which indicates that the domain frequency does not change with Tr. In contrast, the power spectra density at the resonant frequency changes significantly when the unloading time changes. Therefore, the rectangular force does not affect the domain frequency but only determines the resonant amplitude.By using viscoelastic fluid with a larger elasticity , 3 f (0.38 Hz) and 5 f (0.63 Hz), as shown in Fig. Ts = 16 s or f ≈0.06 Hz, resonant peaks are induced at f (0.06 Hz), 3 f (0.19 Hz) and 5 f (0.31 Hz) and so on. However, when Ts is close to the natural period of viscoelastic fluid, or 4 s, other order frequencies are significantly suppressed, and only the first resonant mode at f = 0.24 Hz is strongly induced, as shown in Fig. We further study the response of viscoelastic fluid flow to a square wave force in the frequency domain. A Fourier transform is applied to each velocity response for square waves with periods of 1, 4, 8 and 16 s. The applied square wave excitation is an odd function and its corresponding Fourier expansion can be written asβ and the elasticity E of the viscoelastic fluid. It demonstrates that the period of the oscillation signal relies on the elasticity number of the fluid while the damping coefficient is dependent on viscosity.A damped oscillation velocity response to a constant force is obtained. The oscillation amplitude, period and damping coefficient can be modulated by changing the viscosity coefficient We investigate the velocity response to a rectangular force and a platform effect in a viscoelastic fluid was observed, by which the velocity is maintained at a constant value for certain time after the force is unloaded.A periodic square wave force is also applied and harmonic resonance is occurred when the applied force period matches the intrinsic period of the viscoelastic fluid. The resonance is due to the coupling between the force and the fluid and the resonant amplitude of the velocity is maximized.We investigate the transient velocity response of viscoelastic fluid flow to externally applied forces based on numerical simulations. The velocity responses to different forces are interpreted which highly depend on the intrinsic properties of viscoelastic fluid, particularly its elasticity and viscosity. Some interesting results are obtained as follows:By analyzing the response features of viscoelastic fluid excited by external forces, the transient velocity can be utilized as modulated signal when processing different force functions in microfluidic circuit. In general, the nonlinear response to the external force allows the viscoelastic fluid to be widely applied in the waveform modulation and filter applications, such as digital signal processing, signal converter, controller, signal encryption, password converter, etc.


BFV, measured by bioimpedance spectroscopy, and fluid balance were similar among the two groups. Urine vasopressin in ipragliflozin‐treated rats was negatively and positively associated with fluid balance and TcH2O, respectively. Ipragliflozin increased the renal membrane protein expression of SGLT2, aquaporin (AQP) 2 phosphorylated at Ser269 and vasopressin V2 receptor. The expression of SGLT1, GLUT2, AQP1, and AQP2 was similar between the groups. In conclusion, the SGLT2 inhibitor ipragliflozin induced a sustained glucosuria, diuresis, and natriuresis, with compensatory increases in fluid intake and vasopressin‐induced TcH2O in proportion to the reduced fluid balance to maintain BFV. These results indicate that the osmotic diuresis induced by SGLT2 inhibition stimulates compensatory fluid intake and renal water reabsorption to maintain BFV.Most of the filtered glucose is reabsorbed in the early proximal tubule by the sodium‐glucose cotransporter SGLT2. The glycosuric effect of the SGLT2 inhibitor ipragliflozin is linked to a diuretic and natriuretic effect that activates compensatory increases in fluid and food intake to stabilize body fluid volume (BFV). However, the compensatory mechanisms that are activated on the level of renal tubules remain unclear. Type 2 diabetic Goto‐Kakizaki (GK) rats were treated with vehicle or 0.01% (in diet) ipragliflozin with free access to fluid and food. After 8 weeks, GK rats were placed in metabolic cages for 24‐hr. Ipragliflozin decreased body weight, serum glucose and systolic blood pressure, and increased fluid and food intake, urinary glucose and Na We show in this study that SGLT2 inhibitor ipragliflozin induced a sustained glucosuria, diuresis, and natriuresis, with compensatory increases in fluid intake and vasopressin‐induced aquaporin‐2 phosphorylation and solute‐free water reabsorption in proportion to the reduced fluid balance to maintain body fluid volume These results indicate that the osmotic diuresis induced by SGLT2 inhibition stimulates compensatory fluid intake and renal water reabsorption to maintain body fluid volume. GK rats at 18–22 weeks of age were randomly divided to receive normal food CE2 (Veh) or CE2 containing 0.01% ipragliflozin (Ipra) (Astellas Pharma Inc.)  before treatment were similar in the two groups of GK rats . At 8 weeks of treatment, ipragliflozin treatment led to higher absolute  were not significantly different between the groups.Ipragliflozin increased both fluid intake and urine volume to a similar extent Figure a and b, s Figure , as expely Table . Blood uin Table , potentiin Table f, while in Table  and hear3.2+ and Cl− concentrations (see above) was associated with increased urine vasopressin excretion  is significantly decreased by ipragliflozin   Figure c. Ipragl) Figure d–f.r = .256, NS; Ipra: r = −.068, NS) and urine volume  were not correlated with urine vasopressin    tended to be related to urinary vasopressin     , serum glucose , serum Na+ , serum Cl− , serum K+ , serum ([Na+] + [Cl−]) , and serum ([Na+] + [K+])  did not significantly correlate with urine vasopressin excretion.To gain further functional insights, specific parameters were correlated with urine vasopressin excretion. Fluid intake . The latter is expected to induce compensatory increases in fluid intake and renal water reabsorption, thereby preventing detectable changes in body fluid volume, as documented in this study. Vasopressin was negatively correlated with fluid balance, indicating that the osmotic diuresis induced by SGLT2 inhibition enhanced vasopressin tone and stimulated compensatory mechanisms of body fluid volume homeostasis.+ excretion, and increased compensatory solute‐free water reabsorption. Without the latter compensatory mechanism, ipragliflozin might induce excessive urine flow rates that could accelerate body fluid depletion and result in renal dysfunction.The SGLT2 inhibitor ipragliflozin increased solute‐free water reabsorption with a positive correlation to urine vasopressin, which is expected to attenuate polyuria and body fluid depletion. Solute‐free water is the water without osmotic agents, and solute‐free water clearance is calculated by the formula: urine volume ‐ osmolar clearance. A negative value of solute‐free water clearance means that solute‐free water is reabsorbed in the tubule. In this study, ipragliflozin induced osmotic diuresis together with increased urinary glucose and Na+ excretion, which both contribute to the osmotic diuresis, were positively associated with urine vasopressin. The correlation was stronger for urinary glucose excretion than for urinary Na+ excretion. While the positive correlation between urinary Na+ concentration and vasopressin secretion was previously reported  rats, ipragliflozin also increased urinary fluid, glucose and Na+ excretion in addition to urine vasopressin  provided SGLT2 inhibitor ipragliflozin for this study. Over the past 36 months, V.V. has served as a consultant and received honoraria from Bayer, Boehringer Ingelheim, Astra‐Zeneca, Intarcia Therapeutics, Janssen Pharmaceutical, Eli Lilly, and Merck, and received grant support for investigator‐initiated research from Boehringer Ingelheim, Astra‐Zeneca, Bayer, Fresenius, and Janssen.T.M., S.M., and V.V. conceptualized and designed the project; T.M., K.F., M.W., and Y.W., performed animal experiments; T.M., K.F., and M.W. analyzed the data; T.M., S.M., K.F., M.W. Y.W., K.O., V.V., and D.N. interpreted the results; T.M. prepared figures for the manuscript; H.K. provided antibodies (SGLT2 and SGLT1 antibodies); T.M. and V.V. drafted the manuscript; T.M., S.M., K.F., M.W., Y.W., K.O., H.K., V.V., and D.N. edited and revised the manuscript; T.M., S.M., K.F., M.W., Y.W., K.O., H.K., V.V., and D.N. approved the final version of manuscript. Click here for additional data file. Click here for additional data file.


An electrospinnable zein core solution was prepared and processed with a sheath comprising ethanolic solutions of LiCl. The width of the zein nanoribbons formed (W) was found to be more closely correlated with the spreading angle and straight fluid jet length than with the experimental parameters (the electrolyte concentrations and conductivity of the shell fluids). Linear equations W = 546.44L − 666.04 and W = 2255.3θ − 22.7 could be developed with correlation coefficients of Rwl2 = 0.9845 and Rwθ2 = 0.9924, respectively. These highly linear relationships reveal that the process characteristics can be very useful tools for both predicting the quality of the electrospun products, and manipulating their sizes for functional applications. This arises because any changes in the experimental parameters would have an influence on both the process characteristics and the solid products’ properties.The accurate prediction and manipulation of nanoscale product sizes is a major challenge in material processing. In this investigation, two process characteristics were explored during the modified coaxial electrospinning of zein, with the aim of understanding how this impacts the products formed. The characteristics studied were the spreading angle at the unstable region ( For polymer processing engineering, a key requirement is to be able to accurately interrelate the experimental conditions and the properties of the final products ,2,3. ThiD) is a function of the working fluid properties (w), the operational conditions (o), and the environmental parameters (e): i.e., D = f .C), viscosity (η), surface tension (δ), and conductivity (σ); the operational conditions include the applied voltage (V), the fluid flow rate (F), and the fiber collection distance (L); and the environmental parameters comprise of temperature (T), humidity (H) and the possible vacuum (U)  . Thus, although a lot of effort has been expended to predict and manipulate the diameters of electrospun nanofibers, the results are typically far from satisfactory ,49. DuriHere, for the first time, we design a method to elucidate the interrelated relationships between the working fluids, the electrospinning process characteristics, and the nanoribbons formed during the modified coaxial electrospinning of zein. Zein is one of the best understood plant proteins. Extracted from maize, it has been widely used as a coating for candy, nuts, fruit, and pharmaceuticals. Zein can be processed into resins and other bioplastic polymers, which can be extruded or rolled into a variety of plastic products . Zein haZein (98% purity) was purchased from Shanghai Hewu Biotechnology Co., Ltd. . Anhydrous ethanol and lithium chloride were obtained from the Husheng Reagent Co., Ltd. . Water was double distilled just before use.v/v) ethanol/water mixture, which showed a yellow color. Four LiCl solutions in ethanol  were utilized as the sheath fluids, and the resultant nanoribbons were labeled as Z1, Z2, Z3, and Z4, respectively. The conductivities of the sheath fluids were assessed using a DDS-11 digital conductivity meter .The core fluid consisted of 28 g zein in 100 mL of a 75%/25% , a power supply , a homemade concentric spinneret, and an aluminum-coated flat piece of cardboard as the collector. The ambient temperature and humidity were 21 ± 4 °C and 53 ± 6%, respectively. All the working processes were recorded using a digital camera . Following optimization, the collection distance and voltage were fixed at 20 cm and 17 kV, respectively.The surface morphologies of the electrospun products were observed by scanning electron microscopy  at 20 kV acceleration voltage. Before observation, the samples were sputter-coated with gold under vacuum. The images were analyzed using the ImageJ software , with measurements taken at over 100 different places to determine the average ribbon diameter.Traditionally, coaxial electrospinning is carried out using an electrospinnable sheath fluid to encapsulate either a core liquid which may be spinnable or unspinnable ,24. SomeThe homemade concentric spinneret and the electrospinning apparatus used in this work are shown in The electrospinning process consists of three successive stages: The formation of a Taylor cone, the straight fluid jet emitted from the Taylor cone, and the unstable region, which is composed of numerous bending and whipping loops. The formation of the Taylor cone is a balance between the electrical force exerted on the droplets exiting the spinneret, and the surface tension of the working fluids. When the conductivity of the working fluid increases, the electrical forces should increase correspondingly. Thus, an increase in the LiCl concentration in the sheath fluid is expected to result in a stronger electrical force being applied to the working fluids. Under the same applied voltage and spinneret-to-collector distance, this force will greatly change the behaviors of the working fluids. Digital photographs of these are given in SEM images of the resultant nanoribbons and their diameter distributions are shown in Although a single-step and straightforward process for creating nanoribbons, the electrospinning process is in fact very complicated. This complexity is reflected in two ways. First, the process involves the overlap of multiple disciplines such as hydrodynamic science, polymer science and rheology, and electric dynamics. Second, a small change in the working fluid properties can greatly influence the process and its products. L = 3.38 − 5.25 × 104σ, with a correlation coefficient of RLσ2 = 0.9761. Similarly, the spreading angle of the unstable region gradually increased with conductivity . These linear equations suggested that the LiCl concentration and conductivity of sheath working fluid directly influenced the width of the zein nanoribbons fabricated. These equations can hence be exploited to predict the size of the products from this electrospinning process, and provide useful information for optimizing the working processes. A wide variety of experimental parameters have been investigated in terms of their effect on the properties of electrospun fibers, and the solution conductivity of working fluid is recognized as being of major importance . In thisIt is a common strategy to optimize the experimental conditions through simultaneous investigations on several levels of an experimental parameter, just as here with the LiCl concentration. However, only a small part of the related publications has taken a further step to disclose the inherent relationship between the vital properties of the working fluid with the final product’s quality. Here, the conductivity of sheath LiCl solution showed a better linear relationship with the width of zein ribbons than the LiCl concentration. Thus, among many other solution properties such as surface tension, viscosity, and rheological properties, conductivity is the most important property of LiCl solution that exerted influences on both the working processes, and also the resultant ribbons’ quality. W = 546.44L − 666.04; Rwl2 = 0.9845). Similarly, a linear equation W = 2255.3θ − 22.7 connects the width of the ribbons with the spreading angle (Rwθ2 = 0.9924). These relationships show that these parameters can be very useful tools for predicting the properties of the ribbons fabricated. The detailed observations of the electrospinning process discussed in Right from the rebirth of electrospinning, a wide variety of experimental parameters have been studied to disclose their potential roles during the electrospinning processes. These parameters can all be manipulated by the researchers directly and changed within a certain range, which are concluded in F1) and gravity . Within the bending and looping fluid jets, repulsive forces will include those between different loops (F2) and those within the different parts of a single loop (F3). It is the F3 forces that draw and narrow the working fluids. The spreading angle will be a parameter that reflects the combined actions of F1, F2, and F3. An increase in sheath solution conductivity will increase all three forces. An increase in F1 would act to decrease the spreading angle. However, an increase in F2 would make the fluid travel time increase during the drawing process, and thus provide a trend of enlarging the spreading angle. In addition, an increase in F3 would make the loops larger, and correspondingly increase the spreading angle. Thus, the combined effects of F2 and F3 appear to have a more marked influence on the electrospinning process than F1, and as a result, the greater the conductivity of the sheath fluid, the larger the spreading angle observed. Similarly, another process characteristic, i.e., the length of straight fluid jet, has received the influences of LiCl concentration directly and comprehensively.A schematic diagram of the modified coaxial electrospinning process is presented in In the biomedical applications of electrospun nanofibers, whether for tissue engineering or advanced drug delivery systems, the accurate manipulation of nanofiber diameter is very important for the fibers’ functional performances ,58,59. TW) was found to be directly correlated with the concentration of LiCl (C) and the conductivity of the sheath fluid (σ), with linear relationships of the form W = 1033.2C − 26.9 (R12 = 0.9297), and W = 11177.86 − 0.29σ (R22 = 0.9639) determined. Further, the width of the zein nanoribbons (W) were found to have still closer linear relationships with the spreading angle in the unstable region (θ), and the length of the straight fluid jet (L) .Using an electrospinnable zein solution as the core fluid and LiCl solutions as the sheath working liquids, a series of modified coaxial electrospinning processes were performed, and a number of zein nanoribbons successfully prepared. The nanoribbon width (Today, electrospun nanofibers are rapidly approaching commercial applications in several fields such as drug delivery, food packaging, water treatment, and air filtration ,61, and


A 21-year-old woman presented with an upper left lobe mass, discovered in a context of asthenia, dyspnoea, wheezing, flushes and evening fever. Initial CT imaging revealed a heterogeneous mass predominantly endobronchial into the bronchus of the lingula with latero-aortic and perihilar adenopathies. Positron emission tomography-CT scan found a hypermetabolism of the tumour  as well as in mediastinal lymph nodes (SUV=2.2). Initial fibroscopy performed found a stenosing endoluminal tumour. Left superior lobectomy and mediastinal lymph node dissection were performed.http://virtualacp.com/JCPCases/jclinpath-2018-205259/ and consider your diagnosis.Review the high quality, interactive digital Aperio slide at Hematoxylin eosin safron (HES) slide 1:Carcinoïd tumourPulmonary myxoid sarcomaInflammatory myofibroblastic tumourMyxoid liposarcomaPulmonary haematomaEWSR1 fluorescence in situ hybridisation (FISH)ALK immunohistochemistrySynaptophysin immunohistochemistryEGFR, ALK, ROS1)Molecular analysis for lung carcinoma  and correspond to the fusion transcript EWSR1/ATF1. The genetic characteristic of PMS is often the   translocation with the EWSR1-CREB1 fusion gene. EWSR1 is found in most chromosomal translocations of sarcomas, with nearly 16 types of partners indexed.EWRS1/ATF1 can be found rarely in this type of tumour. ATF1 encodes for a cyclic AMP protein responsive element which is constitutively product after the translocation with EWRS1.ATF1, however, is not specific for myxoid sarcoma, since it is also found in clear cell sarcoma and angiomatoid fibrous histiocytoma.Pulmonary myxoid sarcoma (PMS) is a very rare low-grade tumour, with only about 15 cases described in the literature. q3; q12 trThe immediate operative follow-up was simple, and the patient received no further treatment. At 6 months of surgery, the patient had no evidence of clinicoradiological recurrence. The risk of relapse is low; however, there is a metastatic potential with few described cases of secondary cerebral, renal and pulmonary localisations.EWSR1 fluorescence in situ hybridisation (FISH).Q1 Pulmonary myxoid sarcoma; Q2 Mesenchymal tumours of the lung are very rare; the most frequent is pulmonary hamartoma, a benign tumour.Pulmonary myxoid sarcoma (PMS) is a low-grade tumour, often localised partially endobronchial and exceptionally metastatic.EWSR1 translocation.The diagnosis of PMS is morphological and confirmed by the presence of


In recent years, with the increase in cancer mortality caused by metastasis, and with the development of individualized and precise medical treatment, early diagnosis with precision becomes the key to decrease the death rate. Since detecting tumour biomarkers in body fluids is the most non‐invasive way to identify the status of tumour development, it has been widely investigated for the usage in clinic. These biomarkers include different expression or mutation in microRNAs (miRNAs), circulating tumour DNAs (ctDNAs), proteins, exosomes and circulating tumour cells (CTCs). In the present article, we summarized and discussed some updated research on these biomarkers. We overviewed their biological functions and evaluated their multiple roles in human and small animal clinical treatment, including diagnosis of cancers, classification of cancers, prognostic and predictive values for therapy response, monitors for therapy efficacy, and anti‐cancer therapeutics. Biomarkers including different expression or mutation in miRNAs, ctDNAs, proteins, exosomes and CTCs provide more choice for early diagnosis of tumour detection at early stage before metastasis. Combination detection of these tumour biomarkers may provide higher accuracy at the lowest molecule combination number for tumour early detection. Moreover, tumour biomarkers can provide valuable suggestions for clinical anti‐cancer treatment and execute monitoring of treatment efficiency. These genetic alterations not only promote tumour development but provide researchers with a chance to chase the disease status at the same time. Although the term “tumour biomarker” now covers any molecular, biochemical, physiological, or anatomical property that reflects tumour's presence and status which can be quantified or measured, an ideal tumour biomarker is preferred to be collected non‐invasively from body fluids, such as the blood. These biomarkers include microRNAs, ctDNAs, proteins, exosomes and CTCs released by the tumour and circulating in the body fluids.https://www.fda.gov/newsevents/newsroom/pressannouncements/ucm560167.htm]. In this review, we will overview some current tumour biomarkers, discuss their biological functions, evaluate their roles in clinical treatment and compare the strength and limitations between different detected markers (Table ), which may provide a prospect for the clinic applications of these markers during different stages of tumour development and anti‐cancer treatment .Generally, tumour biomarkers are not expected to simply show the status of tumour, but to exhibit important functions for tumour's survival, growth and metastasis. Based on this fact, tumour biomarkers are recently regarded as treatment targets. Moreover, tumour biomarkers get an emerging role to direct the treatment of anti‐tumour drugs. In 2017, Food and Drug Administration (FDA) accelerated the approval of Keytruda (pembrolizumab), an antibody drug targeting PD‐1(programmed death 1), for the treatment of adult and paediatric patients with unresectable or metastatic solid tumours that have been identified as having a specific genetic feature (or tumour biomarker) referred to as microsatellite instability‐high (MSI‐H) or mismatch repair deficient (dMMR). Doctor Richard Pazdur, the acting director of the Office of Hematology and Oncology Products in the FDA's Center for Drug Evaluation and Research and director of the FDA's Oncology Center of Excellence, recommended this work as “this is an important first for the cancer community,” he said, “Until now, the FDA has approved cancer treatments based on where in the body the cancer started‐for example, lung or breast cancers. We have now approved a drug based on a tumor's biomarker without regard to the tumor's original location.” [22.1miRNAs are small non‐coding RNAs (ncRNAs) that target corresponding messenger RNAs (mRNAs) to post‐transcriptionally downregulate certain gene expression. miRNAs were first identified in Caenorhabditis elegans in 1993,2.2The first study linking miRNA with cancer was published in 2002.2.2.1The Let‐7 family include 13 different members and have been reported to be related with many types of cancer, and it was recognized as a tumour suppressor generally. Let‐7 regulates cancer cell cycle and proliferation by targetingRAS genes,2.2.2miR‐15/16 is also an important tumour‐suppressing miRNA during various types of tumour progression. It can regulate apoptosis through targeting FEAT/METTL13,2.2.3The function of miR‐21 is mainly tumour promoting, since it targets many genes that are important tumour suppressors. These targeted genes mainly related to cell apoptosis, growth, invasion and tumour migration, such as BCL2,2.2.4Members of miR‐29 family usually act as tumour suppressors, and their downregulation always related to many types of cancer. They directly target cell cycle gene CDK6,2.2.5ThemiR‐34 family are well known to regulate cell cycle, senescence, apoptosis and invasiveness in cancer. They target at genes that encode factors required for G1/S transition such as MYC, E2F, CDK4 and CDK6. They also target anti‐apoptotic genes such as BCL2, SIRT1 and genes involved in tumour cell invasion such as MET.2.2.6The genes targeted by miR‐155 are involved in multiple pathways related to multiple cancer‐related processes. For example, SMAD5 regulates the epithelial‐mesenchymal transition (EMT) process, while SOCS1, INPP5D and CSF1R regulate cell proliferation, and CASP3, FADD, APAF1 and FOXO3A regulate cell apoptosis.so some reviews also summarized the miRNA clinical usage by cancer types.Currently, there are about thousands of studies about miRNAs as tumour biomarkers, including numerous reviews that have summarized the detail information about the history, classification and functions of tumour‐related miRNAs. Since tumour is of highly heterogeneity, different cancer types have different regulating molecule mechanisms, 2.3In cancer patients, cancer‐related miRNAs will get some changes in expression or mutations and resulted in abnormal functions that facilitate cancer progression. The high‐throughput sequencing was applied to analyse the expression and mutation of miRNA genes and identified a series of aberrant expression profiles in many human cancers types, such as lymphoma,2.3.1In plasma, the combination of miR‐21, miR‐145 and miR‐155 could help distinguish lung cancer patients with 69.4% sensitivity and 78.3% specificity.2.3.2The reason why miRNAs can be used for the classification of cancers is that different tissues have different miRNAs expression pattern, and miRNAs can reflect the origin of a specific type of tumour or even cellular subsets. In a blind study including 22 different tumour types, classifying tumours according to tissue of origin, the miRNA expression signatures can reach accuracy higher than 90%.2.3.3Since miRNAs have important regulatory functions during cancer development, their levels can reflect tumour status to some extent and thus could predict the outcome of therapy response. For example, low level of let‐7, a tumour suppressor miRNA, is correlated with poor prognosis including tumour size, overall survival and early recurrence. Moreover, the expression of miR‐21, a tumour‐promoting miRNA, is negatively correlated with relapse‐free survival of diffuse large B‐cell lymphoma (DLBCL) patients.2.3.4In chronic myeloid leukaemia (CML), the level of cells with the BCR‐ABL rearrangement is widely used to characterize the disease progression, and decreases after imatinib treatment. It was reported that miR‐451 levels negatively correlate with BCR‐ABL levels and can monitor the therapy effect of imatinib at both the time of diagnosis and after treatment.2.3.5The first microRNA‐based anti‐cancer therapy is MRX34, a synthetic miR‐34a mimic that is loaded into liposomal nanoparticles,33.1Cell‐free DNA (cfDNA) is small pieces of DNAs released into blood by various mechanisms mainly including cell apoptosis and necrosis. It was first identified in 1948 by Mandel and Metais in the blood of healthy people.3.2ctDNAs were initially used to identify the presence of tumour in 1994, when Vasioukhin et al detected tumour‐specific RAS mutations in the plasma of cancer patients.3.2.1Abundant mutations have been detected in the ctDNAs of patients with various types of cancer. For example, PIK3CA mutations,3.2.2DNA methylation plays important regulatory roles in gene expression and genome stability. For example, high levels of 5‐methylcytosine at the promoter region always result in gene transcriptionally silence. And methylation at the promoter region or non‐coding sequences is often dysregulated in many types of tumour and is associated with tumour initiation, progression, dissemination and metastasis.3.3It is believed that cancers are results of gene mutation accumulation. These oncogenic genetic alterations can not only facilitate tumour progression and metastasis, but also be closely correlated with acquired treatment resistance.3.3.1Present studies for ctDNAs used in diagnosis are lack of large scale study, and the specificity is not ideal enough for early diagnosis of certain types of cancers. This is partially because the detection methods at present are limited to detect the very low amount of ctDNAs in early stage of cancer patients, and some mutations such as KRAS are not specific for certain types of tumour but exist in many tumour types.Recently, Dennis Lo group use plasma Epstein‐Barr virus DNA to screen for nasopharyngeal cancer. In the study, a total of 20,174 participants underwent nasopharyngeal cancer screening, and the sensitivity and specificity were 97.1% and 98.6%, respectively.3.3.2Some patients cured by surgery still receive adjuvant chemotherapy in case of tumour relapse. Studies showed that detecting ctDNAs before and after surgical resection can identify individuals with residual disease,3.3.3The level of ctDNA is closely correlated with tumour burden and therapeutic responses. It has been reported that its levels increased rapidly with disease progression and declined correspondingly after successful treatment in melanoma,3.3.4Recently, there are many new methods for the detection of ctDNA to monitor emerging resistant mutations during anti‐cancer treatment, which allow us to choose appropriate treatment based on specific mutations detected in the drug‐resistant tumour for each individual. For example, in colorectal cancer patients undergoing anti‐EGFR treatment, detecting KRAS mutations in ctDNAs of patients with anti‐EGFR therapies can identify relapse10 months before radiographic documentation of disease progression.There are many more reports which introduce ctDNAs as cancer biomarkers at different aspects; a selection of reviews4Compared with other types of tumour biomarkers, cancer‐related proteins are earlier and more widely used in the clinic. Until now, numerous proteins have been identified to be upregulated with tumour burden, which can either be detectable in tumour tissues or in patients’ blood.4.14.1.1At present, American National Cancer Institute lists the protein tumour markers that are now used in clinic, for example, alpha‐fetoprotein (AFP) for liver cancer and germ cell tumours, CA15‐3 for breast cancer, CA19‐9 for pancreatic cancer and gastric cancer, CA‐125 for ovarian cancer, carcinoembryonic antigen (CEA) for colorectal cancer and some other cancers, and so on. Other protein biomarkers also include calcitonin for medullary thyroid cancer, CD20 for non‐Hodgkin lymphoma, chromogranin A (CgA) for neuroendocrine tumours, beta‐2‐microglobulin (B2M) for multiple myeloma, and so on.4.1.2In breast cancer, there is a clear molecular subtype based on some important protein such as ER, PR and HER2, whose function is correlated with breast cancer progression. And the combination of several genes was also commercially used to predict the clinical outcome of breast cancer patients.4.24.2.1At present, the accuracy of a single protein biomarker can only discriminate cancer patients and healthy individuals, which is certainly not enough for early diagnosis and further clinical use. Currently, only few body fluid‐based protein markers were approved by FDA, and none of them have high accuracy for early clinical diagnosis. One promising way to increase the accuracy for disease diagnosis is to combine several protein markers. For example, the OVA1 test for ovarian cancer identified five protein markers in serum including CA125, transthyretin, apolipoprotein A‐I (APOA1), β2‐microglobulin and transferrin4.2.2In breast cancer patients, 21 proteins were identified from an antibody microarray containing 135 antibody fragments, whose functions related to the development of metastasis. The combination of these 21 proteins could distinguish patients at high or low risk for developing metastasis, with an ROC AUC of 0.85.4.2.3Another function that is widely used in clinic is to monitor the therapy efficacy. Besides some traditional tumour biomarkers such as CA125, many studies work to identify other new tumour biomarkers in different cancer types to improve the present situation. For example, the level of a newly identified tumour biomarker Hsp90α in patients’ plasma showed significant correlation with therapy efficacy in lung cancer.55.1Exosomes are 30‐100 nm small vesicles secreted by cells to the extracellular matrix or body fluids. It was first discovered in 1980s by Johnstone group who declared that transferrin receptor could be selectively released in circulating vesicles, which was later named exosomes.5.2Exosomes play an important role in cell‐cell communication, since exosomes can package certain RNAs, DNAs, proteins and other metabolism from the donor cells. There are emerging evidences that tumour cells secret exosomes to facilitate cancer growth, angiogenesis, invasion, metastasis, immunity and even drug resistance acquirement.5.2.1e stranded.The nucleic acids in exosomes include RNAs such as miRNAs, mRNAs, tRNAs, lncRNAs5.2.2Tumour‐derived exosomes can transport many proteins to establish a complex metastatic microenvironment. For example, HSP70, HSP90 and survivin can inhibit apoptosis and promote cellular proliferation.5.35.3.1One advantage for exosomal markers in clinical detection is its stability to avoid from enzyme‐based degradation compared with circulating markers, which may increase the accuracy of the detection. For example, miRNA‐1246 shows a sensitivity of 71.3% and a specificity of 73.9% for the diagnosis of oesophageal squamous cell cancer (ESCC), and its level is also correlated with the tumour metastasis and poor survival.5.3.2Similar to the diagnosis property, exosomal biomarker also shows values in prognosis and prediction. For example, in tongue squamous cell carcinoma (TSCC), the higher level of caveolin‐1 (CAV1) in exosomes is negatively correlated with recurrence and survival.5.3.3It was reported that the amount of cisplatin in exosomes released from cisplatin‐resistant cells is 2.6 times higher than that from cisplatin‐sensitive cells after treatment with cisplatin.5.3.4Since exosomes play an important role in cancer growth, metastasis and drug resistance, some drugs target to inhibit the secretion of exosomes or just remove exosomes from blood circulation.Although many challenges exist, it is still a promising field of biomarker, and interested readers are referred to some excellent reviews.66.1CTCs are tumour cells from a primary tumour that circulate in the blood around the body, and act as seeds for subsequent secondary metastatic tumour at distant organs. The amount of CTCs in blood is very low at about 1‐10 CTCs per mL of whole blood in metastatic patients.6.2Since studies have recognized that CTCs are heterogeneous, which means a CTC cluster may not only contain different sizes or components of CTCs, but also include tumour‐associated stromal cells. These certain different characteristics have distinct biological functions and higher metastatic potential,6.36.3.1The origin and function of CTCs determine that it can be detected in patients already undergoing metastasis. But for early‐stage non‐metastasis patients, it can rarely be detected in the circulation, which may limit its sensitivity and specificity for cancer diagnosis. However, in some cases, it can be used to distinguish lung cancer from benign lesions in patients at CTC count over 25.6.3.2The numbers and characteristics of CTCs are getting widely studied for the use of survival prognosis or therapy response prediction. For example, in metastasis breast cancer, 46.9% of the patients had higher CTC level (≥ 5 CTCs/7.5 mL), which meant lower progression‐free survival and overall survival compared to patients with lower CTC number (<5 CTCs/7.5 mL).6.3.3Patients with lower CTC level after certain treatment exhibit better survival compared to those patients remain high CTC level. For example, in metastatic breast cancer, after one cycle of chemotherapy, patients with decreasing CTC levels have a better prognosis than patients with persistently high CTC levels.6.3.4The response of tumour cells to therapy can be dynamic; thus, measuring CTCs during the course of therapy may reveal tumour changes timely and provide us guides for further treatment. However, until now, only limited studies showed CTC‐based treatment direction applicable. For example, breast cancer patients with HER2‐negative setting but HER2‐positive CTCs were treated with trastuzumab or observation. The results showed that 27 of 36 patients treated with trastuzumab became CK19 mRNA‐negative compared to 7 of 39 observation patients, and trastuzumab treatment also decreased the risk of disease recurrence and prolonged disease‐free survival.Some reviews that summarized the advantages and challenges in this field also listed here for readers who are interested.7Large portions of cancer death are caused by metastasis, so early diagnosis becomes the key to decrease the death rate. Since detecting tumour biomarkers in body fluids is the most non‐invasive way to identify the status of tumour development, it has been widely investigated for the use in clinic. These biomarkers include different expression or mutation in miRNAs, ctDNAs, proteins, exosomes and CTCs. For the use of early diagnosis, which requires the detection of tumour markers at early stage before metastasis, high sensitivity and specificity are very important. Due to the characteristic of CTCs, which are often detected when metastasis already happened, the sensitivity and specificity for early diagnosis are not high enough to be ideal prospective marker for diagnosis. Other molecular markers such as miRNAs, ctDNAs and proteins can be secreted by tumour cells at very early stage to facilitate tumour development and metastasis, thus could be detected at an early stage Figure . HoweverAfter the diagnosis of cancer, patients usually need certain anti‐cancer treatment. Another important function for tumour biomarkers is to direct the determination of therapeutic regimen. Many oncogenic miRNAs, ctDNAs and proteins have functions to facilitate cancer progression and metastasis, so they usually correlate with poor prognosis Figure . CTCs, wAnother important clinic use for tumour biomarker is to monitor the treatment efficiency. Since the tumour markers could reflect the status of tumour development, these levels could evaluate whether the treatment is effective to inhibit tumour development. Meanwhile, it can monitor whether there is a relapse after a period of remission Figure . HoweverDuring the anti‐cancer treatment, tumour cells may evolve new properties to gain drug resistance. These properties can be reflected in the genomic change of metastasis tumour cells, and the genetic information in CTCs provides an ideal way to identify these changes Figure . At presAt present, traditional tumour biomarkers widely used in clinic are still at protein level. However, due to their limited sensitivity and specificity, novel serum biomarkers such as CTCs and nucleic acids will have a great advantage in the future. Although, novel biomarkers have their own technical limitation, and protein markers may not soon be replaced, it is a trend that using different biomarkers in combination to increase the sensitivity and specificity. In the era of individualized medical treatment and precise medical treatment, the diagnosis and treatment decision relied much on the information provided by tumour biomarkers. One important event for this era is that in this year, FDA first approved a drug based on a tumour's biomarker without regard to the tumour's original location. And we believe that researchers will pay more attention on the molecular functions and the underlying mechanisms of these tumour biomarkers, to have a more precise use in the clinics in the future.Not applicable.Not applicable.The authors declare that they have no competing interests.JHL and LM wrote the manuscript and created the figures. DZ and JFG collected the related paper. YPJ, ZHH and DGL provided guidance and revised this manuscript. All authors approved the final manuscript.


Elastic constants derived from seismic-scale measurements are often used to infer subsurface petrophysical properties based on rock-physics relationships established from either theoretic model or core-scale measurements. However, the spatial heterogeneity of rock physical properties at the local scale has a significant impact on this relation. To understand this problem, we built a scaled physical model comprised of artificial porous layers with different pore fluids. After conducting a two-dimensional marine seismic survey over the physical model, the physical modeling data ware then used to retrieve the elastic constants of the layered package. The seismic-scale results reveal that the identification of reservoir fluid properties is improved using elastic constants that is more sensitive to pore fluid properties. The results of numerical simulations show that Lamé moduli provide more insight into rock properties and pore-fluid contents than P-wave impedances, and that the relationship between the upscaled elastic constants and the effective fluid bulk moduli at the seismic scale is usually not perfectly preserved at the reservoir scale. To interpret seismic-scale elastic constants for petrophysical properties, the rock physics relationship need to be carefully calibrated. The findings will help us understand the upscaling of rock-physics transform, which will improve the accuracy of geological property predictions from seismic-scale elastic constants. Seismic signatures are important sources of information on the physical properties of subsurface and commonly used to infer reservoir fluid properties, based on the relationship between undrained elastic constants and pore-fluid bulk modulus established at local scale. However, one issue with this is that the relationship between undrained elastic constants and pore-fluid bulk modulus established in the laboratory or well can be different and may not be directly used in interpreting seismic data whose spatial scale is much coarser. The commonly used theory describing wave propagation in fluid-saturated media is Biot’s equation of poroelasticity1, which forms the basis for relating poroelastic constants with the fluid bulk modulus for homogeneous media. The prediction of Biot and Gassmann’s equations2 have been confirmed by both laboratory and field experiments5; however, this theory has been limited by the explicit assumptions of homogeneous fluids and solid phases, and it is often used to establish the relationship between undrained poroelastic constants and the pore-fluid bulk modulus for centimeter-scale rocks or porous layers (such as reservoirs). Laboratory measurements have shown that the Biot-Gassmann equation may have different behavior for heterogeneous systems6. Determining the valid relationship between poroelastic constants and the effective fluid bulk modulus of heterogeneous systems at seismic scale remains challenging.Seismic methods are among the principle tools used in oil and gas exploration, CO14. Multiple methods exist for the upscaling of elastic properties from finer-scale measurements. Gelinsky & Shapiro9 derived the analytical expressions for effective stiffness tensors of a layered porous package at no-flow and quasi-static conditions. Berryman12 deduced the compliance form expression for stratified porous media under the same assumptions used in Gassmann’s equations. Wollner & Dvorkin15 discussed a method for estimating the effective solid bulk modulus and fluid bulk modulus of a layered poroelastic package from fine-scale measurements. Recently, authors have been investigating the rock physics transform at different scales16. For example, Moysey & Knight17 show that the field-scale rock physics relationships may not be consistent with those established on core-scale measurements. Berryman12 shows that Biot’s equation is not the correct equation at the macro-scale, when there is significant heterogeneity in the medium’s fluid permeability. Dvorkin & Wollner18 show how to deal with the issue of upscaling rock-physics laws by using synthetic examples and conclude that the rock-physics transform between the elastic constants and the petrophysical properties established on the borehole-scale data approximately holds at the seismic scale under certain conditions. Wollner & Dvorkin19 explore the seismic-scale dependence of the effective fluid bulk modulus upon water saturation and find that this relation trends toward an arithmetic average of the individual bulk moduli of the pore-fluid phases. However, the fluid-dependence of poroelastic constants at the seismic scale is poorly understood. This is due to the fact that the direct measurement of seismic-scale relationship between undrained elastic constants and effective fluid bulk moduli is a hard task if possible, and it is very difficult to verify this relationship at the seismic scale with elastic constants deduced from field-scale data. In addition, there are few literatures about laboratory experiments to study seismic-scale relationship between undrained elastic constants and effective fluid bulk moduli for heterogeneous media.Stratified poroelastic materials are typical heterogeneous composites. Much effect has been devoted to estimating the effective properties of heterogeneous composites in the geophysical literatures21. In this study, physical modeling and numerical simulations are used to explore the effect of upscaling on the fluid dependence of undrained elastic constants at the seismic scale. The present work is restricted to heterogeneous layered systems arising from the layering of homogeneous porous materials. We define the seismic scale  and the reservoir scale  as two distinct scales of interest. It is well known that mesoscopic heterogeneities can cause dispersion and attenuation of seismic waves due to sub-wavelength scale wave-induced fluid flow26. To emphasize the poroelastic behavior of layered porous media, our focus here is on the seismic-scale dependence of poroelastic constants upon the effective fluid bulk moduli of heterogeneous systems at no-flow limits. Our approach to the derivation of rock-physic relationships at the seismic scale involves two-dimensional physical modeling and numerically forward simulation using one-dimensional earth models. First, physical modeling, which is believed the best way to mimic real wave propagation in fluid-saturated porous media, is used to produce real reflection data, which are then inverted to the seismic-scale elastic constants. Next, the physical properties of each layer in the physical model, such as porosity, bulk moduli of pore-fluid, drained and undrained rocks, are upscaled using different upscaling methods. Finally, the seismically inverted elastic constants are compared with those obtained from numerical simulations. The results of this study can potentially improve the quality of interpretation of seismic-scale elastic constants for rock physics properties.Physical modeling has been a useful tool to better understand the relationship between seismic responses and scaled porous layers in laboratory analogs of field reservoirs. The reflection amplitude variation with increasing offset acquired by physical modeling experiments can be used to retrieve elastic constants, which useful for discriminating lithology types and identifying pore fluids7 and T8), as is typical for such physical models. Hence, these layers can be treated individually as an isotropic homogeneous medium. The T7 and T8 layers are made up of synthetic, consolidated porous materials composed of the mixtures of quartz grains and resin  shooting arrangement was employed for data acquisition. The minimum offset (defined as the distance between a source and receiver) was 16 mm, the maximum offset was 328 mm. Source and receivers were moved apart at increments of 16 mm in opposite directions. A total of 241 CMP gathers were recorded along the seismic line located in the middle of the physical model Fig. .P-wave reflection from the top of the physical model. Event 9 is the reflection from the base of the physical model. The most notable event is event 4, which resulted from the larger impedance contrast between the low-velocity layer T5 and its surrounding mudstone layers. These strong reflections prevent the transmission of the propagating wave energy, resulting in reduced reflection amplitudes from the lower formation. Event 8 is a P-wave reflection from the top of the low-velocity layer T9. Events 5 and 9 can be considered as markers used to calibrate the relationship between other events and the corresponding formations. The events corresponding to the reflection from the top of the T7 and T8 porous layers occur at approximately 1100 ms and 1145 ms, respectively. The reflections from the bases of these layers are not visible because the layer thickness is much smaller than the scaled seismic wavelength. The P-wave multiples and converted wave events are visible on the section, especially on the part above event 4. The data also contain other coherent events near the T7 and T8 layers. While the primary reflections from the target are consistent among the different CMP gathers, the coherent noises signals are not. These multiple coverage data can be used to reduce the influence of non-primary reflections on the seismic amplitudes.A sample CMP gather from the physical model is shown in Fig. 27. The directional behavior of transducers makes the amplitude with different offsets undesirable variations, and should be compensated prior to any seismic amplitude analysis. Following the work of Duren28 and Mahmoudian et al.29, directivity can be corrected by dividing measured amplitudes by the cosine of the angle between the wave propagation direction and the vertical direction. The propagation direction at the location of a transducer is called the emergence angle21. In the reflection amplitude correction, a ray-tracing algorithm was used to determine the primary’s raypath , bulk modulus (K), and the first Lamé modulus  of saturated rocks, are highly correlated with pore-fluid properties. For our synthetic porous layers, the air-filled layers have lower λ value than those of the water-filled layers. The second Lamé modulus  of the saturated layers is not affected by pore-fluid properties. The ratio of the Lamé modulus to the shear modulus, λ/μ, has advantages in discriminating pore-fluid properties. These elastic constants of the physical model can be retrieved using seismic inversion techniques, which are routinely used in seismic exploration. A deterministic model-based pre-stacked inversion scheme33 was used in this study because the physical modeling data are of high quality and almost free of noise. It is an ideal dataset with known stratum structures and known elastic parameters of each layer. The inversion uses a generalized linear inversion algorithm34 and assumes that a seismic trace is the result of the convolution of angle-dependent wavelets with reflectivity. This inversion was done iteratively by conjugate gradient methods, where the initial low-frequency models were modified until the resulting synthetic seismographs matches the seismic trace within some acceptable bounds. The result is a broadband model of λ, μ, and ρ; the resulting λ/μ is shown in Fig. P-wave impedance was also carried out; the inversion result is shown in Fig. The offset-dependent reflection amplitude is the seismic response of elastic contrast across an interface. It provides information on the elastic constants and even pore-fluid properties of layers. Elastic constants, such as the 35.From the comparison, we can see that the inverted elastic constants significantly improve the identification of the stratigraphy within the physical model. While the stacked seismic data outline the major stratigraphic boundaries along the seismic profile, it is difficult to distinguish the reflections of the air-filled layers from those of the water-filled layers in the section  at times of 1148–1240 ms; the event corresponding to the air-filled sandstone-body of the T7 layer is displayed in warmer-colors at the east end of the section (at CMPs greater than 127) at times of 1068–1140 ms. There are four fluid-filled sandstone-bodies within the T8 layer. The first event corresponding to air-filled body1 is sharp, and exhibits lateral continuity at the west end of the profile (at CMPs less than 46) at times of 1250–1280 ms; the second event corresponding to water-filled body1 is identifiable in the middle of the section (CMPs 47–93) at times of 1216–1248 ms. The third event corresponding to air-filled body 2 is clearly visible in the middle of the section (CMPs 95–128) at times of 1180–1210 ms; the fourth event, corresponding to water-filled body 2, is identifiable at the east end of the section (at CMPs greater than 120) at time of 1050–1178 ms. All air-filled layers are clearly visible and can be distinguished from the water-filled layers. However, these features are not as clearly resolved in the impedance results shown in Fig. 8 layer from air-filled bodies 1 and 2 (first and third events) at the west end of the inverted Ip section. This may have been due to the fact that quartz is characterized by a low λ value (∼8.1 GPa) and a moderate μ value (44.4 GPa)36. For quartz-rich sandstones, the presence of water in the pore spaces may cause a significant increase in λ; gas-bearing rocks have lower λ. Goodway37 proposed that λ contains more useful information about the resistance to pressure-induced changes in volume. Hence, λ is more helpful than seismic impedance when it comes to determining pore-fluid properties. On the other hand, the relationship between the displacement and the stress of media in seismic wave propagation is determined by wave equations, which directly involve the ratio of density and modulus, not the seismic impedances. Consequently, λ and μ provide more insight into the rock properties and fluid content. The inversion results demonstrate that improved identification of reservoir boundaries is possible using elastic constant that is more sensitive to pore fluid properties. Therefore, it is important to understand the fluid dependence of elastic constants at the seismic scale.The inversion results indicate that the inversion removes the wavelets and efficiently improves the vertical resolution in our target zone (at times of 1060–1280 ms). However, the inverted impedance values are less useful when it comes to identify the lateral boundaries of different fluid-filled rocks in a layer. By comparing the known stratigraphy of the physical model Fig. , it is cp Fig.  is less p Fig. . In the 9 was used to estimate the seismic-scale poroelastic response of these porous layers. Poroelastic Backus averaging produces an anisotropic effective medium, where the vertical components of the upscaled poroelastic stiffnesses C33 and C44 can be converted to upscaled impedances or Lamé moduli, which can be directly compared to the seismically inverted variables. In addition, we compute the upscaled porosity and density using the volumetrically weighted average; we also compute the arithmetically volume-averaged bulk modulus of the pore fluid, which is used for reference. A representative model was designed based on the physical model ; in the other, the porous layer is fully filled with water (the blue solid curve shown in the third and fourth tracks). To calculate the elastic properties of the earth models at a coarser scale, the physical properties of each layer in the earth model were upscaled using two running windows, where the first window size was equal to the length of the scaled seismic wavelength used in our physical modeling , and the second was equal to the thickness of the porous layer , where the latter is approximately a quarter of the length of the former. The poroelastic Backus averaging results with the seismic-scale window are displayed in Fig. As expected, the results produced by different upscaling methods vary. For instance, with the seismic-scale window, the arithmetically upscaled porosity , Gassmann’s isotropic fluid substitution operation is approximately accurate38. Thus, an effective pore-fluid bulk modulus exists that will yield the undrained poroelastic response of the effective medium. To understand the seismic-scale dependence of poroelastic constants on the fluid bulk modulus, we first compared the forward-upscaled pore-fluid bulk moduli with the inverted pore-fluid modulus in an effort to analyze the magnitude of the pore-fluid bulk modulus predicted by the upscaling process. The seismically inverted elastic constants and numerical experiment results then were used to quantitatively study the fluid dependence of elastic constants at the seismic scale.Gassmann’s equation is valid for a medium with homogeneous fluids and monomineralic solid phases. However, poroelastic Backus averaging replaces a layered medium with an effective, homogeneous anisotropic body at a coarse scale. When the Thomsen anisotropic parameter Kf using the arithmetic average (AR), the harmonic average (HR), and the mean (i.e. Hill’s averages) (ARHR). The inverted fluid bulk moduli from the numerical experiments were plotted against the forward-upscaled fluid bulk moduli in Fig. 18. Hence, the inverted To evaluate the magnitude of the upscaled fluid bulk modulus, the inverted fluid bulk modulus 2, the difference between the undrained and drained bulk moduli u, Ip, and λ/μ) and the drained elastic constants were calculated using Gassmann’s equation at the reservoir scale. Similarly, the differences between the upscaled undrained and the drained elastic constants were also estimated using poroelastic Backus average at a coarse scale. We used a relative difference, defined by the ratio of the difference between the upscaled quantities .The difference between the undrained and drained elastic constants quantitatively represents the extent of variation in the elastic constants induced by pore-fluid changes. Therefore, the differences between upscaled undrained elastic constants and drained ones were calculated from our numerical experiments at a coarse scale. These differences then were divided by the corresponding drained constants (to determine the relative variation) and plotted those variations against the ratio of the wavelength to the thickness of a layer Fig. . Similarp and λ/μ values. The relative variation of inverted Ip is greater than that of the upscaled Ip, and the relative variation of inverted λ/μ is smaller than the variation of the upscaled values. These inverted quantities derived from physical modeling data are highly reliable because these relative variations or differences are relative values deduced simultaneously from the seismic dataset with the same quality. There are some discrepancies between the seismically inverted quantities and the numerically upscaled ones, suggesting that the poroelastic Backus average weakens the effect of pore-fluid on Ip and enhances the pore-fluid effects on λ/μ. We note that both the seismically inverted and numerically upscaled λ/μ values are more sensitive to the pore-fluid properties than Ip is at the seismic scale. As a result, we conclude that it is the fluid-sensitivity that enables us to distinguish the air-filled zones from the water-filled zones in the seismically inverted λ/μ profile. At the same time, the lateral boundaries of these air-filled and water-filled zones are less well resolved in the inverted Ip section.This comparison shows that the poroelastic Backus upscaled curves are very close to the inverted Ip when it comes to identify fluid distribution, even for sub-resolution fluid-saturated reservoirs. This observation suggests that different elastic parameters have different sensitivities to reservoir pore fluid properties at the seismic scale, and that knowledge of the upscaling for elastic constants is essential to fully understand the fluid dependence of elastic constants at a coarse scale. Results of numerical simulation by poroelastic Backus averaging demonstrated that the fluid dependence of the elastic parameters of layers at the reservoir scale is well defined by Gassmann’s equation. However, the dependence of the undrained elastic constants, such as the bulk moduli, the Lamé moduli, and the impedances, on pore-fluid properties is different at the seismic scale, due to the difference in the methods used to calculate the effective fluid bulk modulus and the effective elastic moduli. For a saturated stratified medium, the effective fluid bulk modulus depends linearly on the local fluid properties whereas the relationship between the local and effective elastic constants is most likely nonlinear. Hence, upscaling affects the sensitivity of the elastic constants to the pore-fluid properties. λ/μ is more fluid-sensitive than Ip at various scales. It is this reason that the seismically inverted λ/μ data can actually determine the sub-resolution lateral variation of pore fluid properties within a reservoir. Generally, the relationship between the upscaled elastic constants and the effective fluid bulk modulus at the seismic scale is not the same as the relationship as that of the reservoir scale. However, the seismic-scale dependence of the undrained elastic constants on the pore-fluid properties of heterogeneous composites can be quantified using a Gassmann-type relation with the specific fluid bulk modulus that accounts for the pore fluid properties, the spatial arrangement of saturated patches, and the amount of upscaling.In this study, we collected seismic data from a scaled physical model with porous layers saturated different pore-fluids, to retrieve elastic constants variations with fluid saturated layers at the seismic scale. The results of seismically inverted elastic constants revealed that λ/μ is more sensitive to reservoir pore-fluid properties and is more helpful than the inverted IThe seismic-scale dependence of poroelastic constants upon the effective fluid bulk modulus is revealed by both physical modeling and numerical simulation experiments. A deeper understanding of this relationship will allow us to improve the estimates of petrophysical properties using the seismic-scale elastic constants.The physical modeling system used in this study mainly consists of the transducers (the transmitting and receiving instruments), the main control computer , the position controlling unit, and a large water tank (Supplementary Fig. Supplementary information


To describe the multicolour (MC) imaging characteristics associated with choroidal osteomas (CO) and their secondary complications.Retrospective descriptive case series of eleven eyes of ten patients with CO. Findings of multicolour imaging were correlated with visual acuity, clinical features, lesion characteristics and findings from other imaging modalities.Infrared reflectance (IR) images showed calcified CO lesions as hyporeflectance (dark) areas while decalcified lesions were seen as iso reflectance  areas. Overlying RPE atrophy on IR were seen as white areas. MC images showed color variations depending upon the reflectivity of the tumour material tumour and retinal pigment epithelial (RPE) atrophy. Green color was noted in calcified CO tumour while decalcified CO tumour showed no color change. RPE atrophy were seen as bright orange areas. Green and blue reflectance images were not able to pick the choroidal osteoma lesion. Other changes secondary to CO like presence of choroidal neovascular membrane, hemorrhage and/or fluid in the retinal layers were identified on green and blue reflectance images.MC imaging is a useful tool in our arsenal of existing imaging modalities in the assessment of CO and its secondary changes. Change in reflectance of the IR and MC images can be used as an indicator to assess the extent of tumour decalcification and its secondary changes and therefore, can aid in prognostication in the same. It has the potential to replace color fundus photography in documentation and follow up of patients with CO. Choroidal osteoma (CO) was first described by Gass et al.  in 1978 The aim of the study is to describe the MC imaging features in CO in conjunction with color fundus photography (CFP), fundus autofluoroscence (FAF) and OCT.In this retrospective study, CO cases who had undergone multimodal fundus imaging were collected from 2 tertiary retina referral centres . The diagnosis was based on the presence of a yellow-white to orange-red mass deep to the retinal pigment epithelium (RPE) and bone density on ultrasonography. All patients had undergone CFP, FAF, OCT and MC imaging in the study. Institutional review board approval was obtained for this retrospective study.The clinical details of each patient were collected retrospectively by review of records, including age, gender, laterality and ocular symptoms. Each patient underwent complete ocular examination including best-corrected visual acuity, slit-lamp examination, and indirect ophthalmoscopy. Lesion characteristics recorded for each eye included lesion location within the fundus, extent of calcification or decalcification, and the presence or absence of sub retinal fluid (SRF) or intraretinal fluid (IRF) with/without choroidal neovascular membrane (CNV).Color fundus photography was done using either Optos Daytona ultra-wide field color fundus camera  or Zeiss 450 Fundus camera. Data included foveal involvement by the tumour , tumour color  and presence of calcification or decalcification. Calcification was defined as an orange lesion in the fundus located deep underneath the intact RPE and no visible choroidal vessels. Decalcification  was defined as pale areas within the osteoma, with overlying RPE thinning and visibility of underlying choroidal vessels.All patients had OCT, FAF and MC imaging performed by confocal scanning laser ophthalmoscope using a Heidelberg Spectralis HRA-OCT . OCT data included tumour surface configuration (flat or depressed), effects of tumour on overlying retina , presence of SRF/IRF with/without CNV. Tumour depth was measured using the calliper function through the epicentre of the tumour. The findings of FAF were described as iso, hypo or hyper AF. The patterns described on MC imaging with infrared reflectance (IR), green reflectance (GR) and blue reflectance (BR) were described as dark areas (hypo) or white areas (hyper) or no changes. On MC images, the color of the lesion varied from greenish to yellowish orange to orange depending upon the state of tumour calcification and RPE atrophy. The scanning field was 30° in most cases. 55° field images were obtained in eyes with large sized lesions. In addition, FA, ICGA and OCT-A were performed in select patients only when a suspicion of CNV was present.We analysed the MC imaging features in CO and corelated it with that of CFP, FAF and OCT using the HRA-OCT unit.There were 11 eyes of 10 Asian patients included in the study. The clinical and demographic features are mentioned in Table The OCT data was recorded by evaluating the scans passing through the macula and over the CO lesion. The mean central retinal thickness was 259.91 µm (range 146–328 µm). The mean tumour thickness was 625.3 µm (range 407–956 µm). The retinal pigment epithelium (RPE) overlying the tumour was intact in 6 eyes while it was disrupted/irregular in remaining 5 eyes. In addition, CNV formation was noted in 5 eyes, focal choroidal excavation was seen in 4 eyes while SRF without CNV was seen in 2 eyes.Fundus autofluorescence findings varied depending on the ophthalmoscopic appearance of each lesion. Heterogeneous lesions exhibited multiple FAF patterns that depended on the characteristics of those corresponding portions of the lesions. Of the 11 eyes with lesions, 5 eyes had areas of iso AF while the remaining 6 eyes had a combination of hyper and hypo AF areas. The findings on FAF depended on the tumour characteristics like the extent of calcification and also on associated retinal findings like presence of CNV, hemorrhage, SRF/IRF and RPE atrophy.MC imaging was performed in all eyes using the cSLO Heidelberg Spectralis HRA-OCT  with a scanning field of 30° and sometimes 55°. IR images were the most efficient in identifying CO. The IR images identified ossified portions of the tumour as dark (hypo reflectance) areas while deossified portions showed iso-reflectance (no change) areas. White (hyper reflectance) areas were seen in RPE atrophy. The GR and BR images showed either no change or white areas depending upon the presence of hemorrhage and/or fluid in the retinal layers. On MC images, the color of the lesion varied from being green to no change to bright orange depending upon the tumour content and RPE atrophy. Green color was noted in calcified tumour while decalcified tumour showed no change on multicolour images. Orange areas were noted in eyes with areas of decalcified tumour with overlying RPE atrophy Figs. , 2, 3, 4Seven eyes with SRF/IRF and clinical suspicion of choroidal CNV were imaged further with FA and ICGA and OCT- angiography in some cases. CNV was identified in 5 eyes and treatment were administered with anti-VEGF therapy in 4 eyes. One eye had scarred CNV; hence, it was observed.Multi color scanning laser imaging is a recently introduced non-invasive innovative technology developed for Spectralis SD-OCT . In scanning laser ophthalmoscopy, a single point of laser light of a specified wavelength is scanned across the retina in a series of parallel lines and enabling an alternative method of capturing fundus images , 9. It uCO is a rare benign ossifying tumour of the choroid characterised by the presence of mature, spongy cancellous bone. On histopathology, dense bony trabeculae with marrow spaces traversed by pathognomonic dilated thin-walled blood vessels, termed spider or feeder vessels are seen. These vessels connect the choriocapillaris to the underlying larger choroidal vessels . ChoroidFundus autofluoroscence images does not show the osteoma lesion when the overlying RPE is intact. However, in areas of atrophic RPE, hypo AF (dark) areas are seen.The MC image in CO shows color variations due to the variable reflectance produced by the tumour. The green colour on MC images are seen in eyes with calcified tumour while decalcified choroidal osteoma shows no colour change. Areas of RPE atrophy are seen as bright-orange areas. Pigment clumping over the tumour surface is usually difficult to identify ophthalmoscopically against the orange intrinsic tumour color. On MC images, pigment clumps are identified as yellow or orange spots while on IR images, they are seen as bright white spots.Poor visual acuity in eyes with CO is usually seen when the decalcification with overlying atrophy of RPE and photoreceptors is located underneath the fovea. Thus, presence of bright orange areas on MC image and white areas on IR image at the sub foveal region can predict poor visual acuity. Hence, MC imaging can be considered as a useful tool in disease prognostication.MC imaging has some advantages over CFP . It is: Our study has the advantage of having sufficient number of eyes with MC images in a rare disease like CO. We also had the multicolour image findings of the disease in its different stages; thus, helping us to understand better the role of MC imaging in CO. Our study had several limitations as well. Absent follow-up images meant inability to describe MC imaging changes over time. All ancillary imaging studies were not used in each patient, and raster scans on SD-OCT may have missed pertinent portions of the lesions. Larger series with longer follow-ups and comparison with other imaging modalities will elucidate greater utility of MC imaging for choroidal osteomas. Present study illustrates multicolour imaging features of CO lesion, which is hitherto not described in English language published literature.MC imaging is a useful tool in our arsenal of existing imaging modalities in the assessment of CO and its secondary changes. Changes in IR reflectance and MC images can be used as an indicator to assess the extent of tumour decalcification and its secondary changes and therefore, can aid in prognostication in the same. It has the potential to replace CFP in documentation and follow up of patients with CO.


Advanced dispensing technology is urgently needed to improve the jetting performance of fluid to meet the requirements of electronic product integration and miniaturization. In this work, an on–off valve piezostack-driven dispenser was used as a study object to investigate the effect of needle structure on jetting performance. Based on fluid dynamics, we investigated nozzle cavity pressure and jet velocity during the dispensing process using theoretical simulation for needles with and without a side cap. The results showed that the needle with a side cap had larger jet velocity and was capable of generating 8.27 MPa of pressure in the nozzle cavity, which was 2.39 times larger than the needle without a side cap. Further research on the influence of the nozzle and needle structural parameters showed that a nozzle conic angle of 85°–105°, needle conic angle of 10°–35°, and side clearance of 0.1–0.3 mm produced a dispenser with a large jet velocity and stable performance, capable of dispensing microscale droplets. Finally, a smaller droplet diameter of 0.42 mm was achieved in experiments using a glycerol/ethanol mixture, with a variation range of ± 4.61%. Fluid dispensing technology controls the quantitative distribution of liquid to specific areas in a device ,2,3. NowJetting dispensers effectively overcome the shortcomings of contact dispensers. These dispensers instantaneously create high pressure in the nozzle cavity to squeeze liquid out. Movement of the vertical substrate direction is avoided, greatly improving the working efficiency and protecting the needle ,11,12,13This study mainly focused on the influence of needle structure on an on–off valve piezostack-driven dispenser’s jetting process. A displacement amplifier with two piezoelectric actuators was used, and its working principle is introduced herein. The effect of needles with and without a side cap on nozzle cavity pressure was then investigated and fluid velocities from the nozzle outlet during dispensing were analyzed by simulation. Moreover, parameters of the needle and nozzle were determined and processed for experiments. Finally, a control method for the dispenser with an enhanced squeezing needle was explored.r, ton, tf and toff, respectively. Therefore, dispensing cycle T = tr + ton + tf + toff.In order to study the influence of needle structure on the dispensing process, an on–off valve piezostack-driven dispenser was used, the configuration of which is shown in By analyzing the jetting process of the dispenser, smooth dispensing of fluid should meet the following conditions. (1) Reasonable feed pressure. Although sufficiently high pressure can ensure smooth jetting of the fluid, it has a great influence on the shape of the droplet. For a fluid with small surface tension, high feed pressure will form a larger droplet, which is a contamination of the packaged devices. (2) Suitable nozzle and needle matching form. The matching between a needle and nozzle usually involves linear contact, and so suitable matching form can ensure the fluid has sufficient kinetic energy during dispensing. In order to completely cut off a fluid, it is necessary to study the influence of needle–nozzle matching form on pressure and velocity. (3) Strong squeezing capacity of the needle. Effective needle structure can provide greater squeezing pressure in the small gap, thereby accumulating kinetic energy for jetting of the fluid. However, an improvement of squeezing capacity also means that there will be appreciable suction as the needle rises, so a slight increase of supply pressure is needed to make up for it.r, and a length of dL, while the shear force is τ and the pressure force on the end surface is p. According to the no-slip boundary condition, the velocity of a power-law fluid in the nozzle is as follows [nozzle is the radius of the nozzle, ∆P is the pressure difference between the inside and outside of the nozzle, L is the length of the nozzle tube, η is the dynamic viscosity, and n is the flow exponent. The flow exponent n, also known as the non-Newtonian exponent, represents the degree of deviation between the fluid and a Newtonian fluid. Specifically, n = 1 corresponds to a Newtonian fluid, n < 1 corresponds to a dilatant fluid, and n > 1 corresponds to a pseudoplastic fluid. The velocity of the fluid along the central axis of the nozzle, vc, is the maximum; that is, when r = 0,Study of the dispensing process required knowledge of the fluid’s flow characteristics in the nozzle pipe, which were affected by the characteristics of the liquid, structure of the dispensing mechanism and characteristics of fluid flow. Flow characteristics include fluid properties such as viscosity, density, surface tension, and compressibility, and structural parameters such as nozzle diameter, nozzle length, and boundary deformation, as well as the effects of differential pressure of the nozzle inlet and outlet, gravity, friction, acceleration, boundary slip and continuity of fluid flow. However, some factors have little influence and can be ignored or approximated, which is beneficial for simplifying a model. In our simplified model, the following assumptions were made. (1) The fluid is incompressible and the flow of the fluid during jet formation satisfies the continuity principle. That is, the mass of the fluid flowing into any section should be equal to the mass of the fluid flowing out of any other section at the same time. (2) The effect of gravity is negligible. (3) The effect of shear force on fluid viscosity is ignored. (4) The fluid wall has no deformation and no slip boundary. (5) The axial flow velocity is much higher than the radial flow velocity, so that the radial flow can be ignored.  follows ,24:(1)v During the dispensing process, the needle with a side cap generated 8.27 MPa of pressure in the nozzle cavity, and produced droplets with an average volume of 1.166 μL. Respectively, the pressure and volume were 2.39 times and 0.94 times that produced by the model without a side cap. These results suggest that the needle with a side cap had an enhanced squeezing effect on the fluid compared to the needle without a side cap. This clearly increased the pressure of the nozzle cavity and the velocity of jet, and was also beneficial for obtaining small droplets. (2) For the needle with a side cap, the parameters—set at a pressure of 3 bar, a nozzle conic angle θ of 85°–105°, a needle conic angle α of 10°–35° and a side clearance β of 0.1–0.3 mm—made a dispenser with a large jet velocity and stable performance, which was able to produce microscale droplets. (3) A control method for the dispenser with an enhanced squeeze needle was proposed. The minimum droplet diameter obtained for this dispenser was 0.42 mm, measured at a duty cycle of 2%; the droplets variation range was ± 4.61%. The experimental results showed that the enhanced squeezing needle was able to obtain larger nozzle cavity pressure during the dispensing process, which is beneficial to the high frequency operation of the dispenser. By selecting appropriate structure parameters for the needle, the dispenser can obtain small droplets and have good droplet consistency. In future work, we will further study the dispensing process based on the fluid dynamics theory, and consider structural parameters—such as the nozzle and needle—in order to better guide the design and control of the dispenser. In addition, we will carry out dispensing experiments of fluids with different viscosities and verify the performance of the dispenser through more reasonable evaluation methods.