For the machining process of industrial parallel robots, the gravity generated by the weight of mobile platform and links will lead to the deviation of the expected machining trajectory of the tool head. In order to evaluate this deviation and then circumvent it, it is necessary to perform the robotic stiffness model. However, the influence of gravity is seldom considered in the previous stiffness analysis. This paper presents an effective stiffness modeling method for industrial parallel robots considering the link/joint compliance, the mobile platform/link gravity, and the mass center position of each link. First, the external gravity corresponding to each component is determined by the static model under the influence of gravity and mass center position. Then, the corresponding Jacobian matrix of each component is obtained by the kinematic model. Subsequently, the compliance of each component is obtained by cantilever beam theory and FEA-based virtual experiments. In turn, the stiffness model of the whole parallel robot is determined and the Cartesian stiffness matrix of the parallel robot is calculated at several positions. Moreover, the principal stiffness distribution of the tool head in each direction over the main workspace is predicted. Finally, the validity of the stiffness model with gravity is experimentally proved by the comparison of the calculated stiffness and measured stiffness in identical conditions. In order to improve motion accuracy and machining accuracy, stiffness analysis becomes an important solution. Moreover, stiffness analysis is also very important for the design stage of a parallel robot9. This is why stiffness analysis has become a research hotspot in recent years.In many modern applications, such as manufacturing robots10: the finite element analysis method (FEA), the matrix structural analysis method (MSA) and the virtual joint modeling method (VJM). The FEA divides the target model into smaller and simpler connected element modules according to its real dimension and shape. Therefore, the modeling accuracy of FEA is very high, but its calculation cost is also very large. It needs the help of commercial FEA software to complete the modeling of the target model, and in order to ensure that the nodes of the module in the division match the nodes on the model, it needs to re-mesh the finite element model repeatedly. That's why it's expensive to calculate, and the process is time-consuming and tedious. Therefore, the FEA is not suitable for parametric stiffness model, which requires stiffness evaluation of the entire workspace.In terms of stiffness modeling, stiffness modeling methods can be mainly divided into three categories13, this method is still not suitable for the stiffness modeling of robot with the substructure of multi-node element.The MSA method takes each component of the robot as a structural unit, which is a large compliant element, and combines the main ideas of the FEA to establish stiffness model of the robot. The main idea of this method is to obtain the stiffness matrix of the robot by combining the stiffness matrix of standard elements such as links, joints and frames with matrix analysis method. However, the distortion of this method is that these substructures are regarded as regular shapes, but the stiffness matrix of their standard element cannot accurately describe the actual stiffness of these substructures. Although some scholars have made some innovations on this method14, and then elaborated by Gosselin15. Pashkevich et al.17 considered the compliance of the link on this basis, and described the translational/rotational compliance of the link and the joint as well as the coupling between them by using a 6-dof virtual spring. The method is not only simple to calculate but also reliable in calculation accuracy, so it has been widely popular24.In these approaches, the VJM is the most attractive and is adopted in this paper. This method obtains the stiffness model of the robot by establishing the force and deformation mapping relationship between joint space and operation space and applying Jacobian matrix and Hooke's law. And the overall compliance factor comes only from the joints embedded by the virtual springs. This method was first proposed by Salisbury25 combined FEA and VJM to propose a semi-analytical stiffness modeling method with high computational accuracy, which only performs FEA on some non-standard components in order to avoid excessive computational consumption. However, the method does not consider the influence of the component gravity. Chen et al.26 proposed a stiffness model for robots under the action of external gravity. On this basis, Klimchik et al.27 proposed a stiffness model for parallel robots under internal and external loads. Lian et al.28 proposed a stiffness model for a five-degree-of-freedom parallel robot by the links gravity. Wang et al.29 proposed a stiffness model of a five-axis parallel robot by considering the links gravity. However, all these stiffness models consider the gravity of the link as an external load acting on the end-effector without considering the influence of the end-effector gravity and the mass center position of the link. Also, Xu et al.30 proposed a stiffness modeling method considering the gravity combined with the deflection superposition principle applied to heavy industrial tandem robots. But this modeling method is not part of the VJM family of methods and has not been applied to parallel robots.However, with the increasing machining accuracy of current industrial processes, the requirements for stiffness models are also increasing, which requires calculations that are both accurate and efficient. Dong et al.In response to the limitations of previous studies and combining their advantages, this study proposes an effective stiffness modeling method for industrial parallel robots. It allows to evaluate the stiffness distribution of an industrial parallel robot in its task workspace considering the influence of the mobile platform/link gravity and the mass center position of each link. Firstly, the model takes into account the compliance of the links/joints by attaching 6-dof virtual springs. Secondly, the model also takes into account the gravity of the links and the mobile platform, as well as the variation of their mass center position in the workspace. Finally, only the compliance matrix of individual irregular components is identified by using the FEA-based virtual experiment to ensure the accuracy and efficiency of the model. In this paper, the Biglide industrial parallel robot in Fig. 27. Each component is either a link/slidable platform or a 1-degree-of-freedom (dof) revolute joint/prismatic joint. The moveable components are composed of the mobile platform and links. The elastic system of the Biglide parallel robot is shown in Fig. Stiffness model of the parallelogram-link (3-RR mechanism)In this section, the stiffness modeling method for the Biglide parallel robot that considers both the compliance of all components and the gravity of moveable components is presentedi is the number of limbs , j is the number of links in the 3-RR parallelogram-link structure . For accuracy of expression, i and j are taken as such throughout the whole paper.The 3-RR parallelogram-link (Pl) structure is composed of three links, which has a revolute joint at each end. By considering the effects of the gravity of the mobile platform and the revolute joints on the stiffness of each link, the Cartesian stiffness matrix (2)Stiffness model of the single limb (P(3-RR) mechanism)The three links in the parallelogram-link structure are connected in parallel, then the Cartesian stiffness matrix (3)Stiffness model of the parallel limbs (2-P(3-RR) mechanism)In the P(3-RR) mechanism, prismatic joint (actuator), slidable platform (SP) and parallelogram-link structure are connected in series, then the Cartesian stiffness matrix In the 2-P(3-RR) mechanism, the two limbs are connected in parallel and the size of the mobile platform is considered, then the Cartesian stiffness matrix (4) Stiffness model of the whole Biglide parallel robot (P[2-P(3-RR)] mechanism).KC of the Biglide parallel robot can be expressed asIn the P[2-P(3-RR)] mechanism, prismatic joint (actuator) and 2-P(3-RR) mechanism are connected in series in the Biglide parallel robot, then the Cartesian stiffness matrix Moreover, in order to solve the above equations, the static and kinematic analysis of the Biglide parallel robot is required.29. The mathematical equation of the static force/torque corresponding to each component is derived, and thus the gravity received at the component is obtained.In this section, the respective static models are developed at each component of the Biglide parallel robot, taking into account the gravity generated by the weight of the mobile platform and the moveable linksThe mechanical structure illustration of the Biglide parallel robot is offered in Fig. i}, {Ai}, {Aij}, {Bij}, {Bi}, {Mi} and {M} respectively , as shown in Fig. ij} and {Bij} are parallel to the direction of {Ai} and {Bi}, respectively, except that the origin of {Aij} and {Bij} are the points Aij and Bij, respectively. Moreover, ai represents the length of OOi ; l and L represent the length of MMi and the link (Lij), respectively; qi denotes the angle between Ai1Bi1 and O1O2 (q1 = q2 = q), d is half the length of Bi2Bi3, OiAi (length l1) and BiMi (length l2) are always parallel to the axis zo, h represents the distance from point Bi to Bi2Bi3 or the length of Bi Bi1. The orientation matrices of {O}, {Oi}, {Aij}, {Bij}, {Mi} and {M} relative to {O} can be expressed asR(.) represents a 3 × 3 rotation matrix that rotates the corresponding angle around the corresponding axis, RO is an identity matrix, and Rn is the orientation matrix of the coordinate system {On} with respect to the coordinate system {O}.To convenience the calculation, a sequence of coordinate systems is attached to each substructure of the Biglide parallel robot. These coordinate systems are expressed as {O}, {O1 and M2, it is necessary to analysis the static force/torque balance at points M1 and M2, as shown in Fig. M is the mass center of the mobile platform and coincides with the geometric center M of the mobile platform, z denotes the unit vector vertically downward; 1, 2; M expressed in the coordinate system {M}, i expressed in the coordinate system {M}, respectively.In order to evaluate the influence of the mobile platform weight at points M1 and M2 can be obtainedAccording to the decoupling of Eq. , the rea1 and M2, respectively; 1 and M2 applied at point M, respectively; 32.ij, it is necessary to analysis the static force/torque balance at point Bij, as shown in Fig. i can be displayed asIn order to evaluate the influence of the mobile platform weight on the joint Bi1, i2, i3; i to point Bi1/ Bi2/ Bi3 expressed in the coordinate system {Mi}.i1, Bi2 and Bi3 can be obtainedAccording to the decoupling of Eq. , the reai1, Bi2 and Bi3, respectively; i1, Bi2 and Bi3 applied at point M, respectively; ij, it is necessary to analysis the static force/torque balance at point Aij, as shown in Fig. ij can be displayed asmi1, mi2 and mi3 are the mass of links Li1, Li2 and Li3, respectively; Gi1, Gi2 and Gi3 are the mass center of links Li1, Li2 and Li3, respectively; i1, i2, i3; i1 to point Gi1 expressed in the coordinate system {Bi1}, i2 to point Gi2 expressed in the coordinate system {Bi2}, i3 to point Gi3 expressed in the coordinate system {Bi3}; i1 to point Ai1 expressed in the coordinate system {Bi1}, i2 to point Ai2 expressed in the coordinate system {Bi2}, i3 to point Ai3 expressed in the coordinate system {Bi3}.In order to evaluate the influence of the weight of the mobile platform and links on the joint Ai1, Ai2 and Ai3 can be obtainedAccording to the decoupling of Eq. (11), the reaction force acting on the joints Ai1, Ai2 and Ai3 applied at point M, respectively; i1, Li2 and Li3 applied at point M, respectively; i1, Ai2 and Ai3, respectively; i, it is necessary to analysis the static force/torque balance at point Ai, as shown in Fig. ij can be displayed asIn order to evaluate the influence of the weight of the mobile platform and links on the joint Ai, i to point Ai expressed in the coordinate system {Mi}.i can be obtainedAccording to the decoupling of Eq. , the reai applied at point M, i, 33. Due to the position relationship and series/parallel relationship of each substructure, the kinematic equilibrium equation is established for each substructure of the Biglide parallel robot.In this section, the kinematic analysis of the Biglide parallel robot is carried out so that the Jacobian matrix of each substructure is derivedi to Bi through each chain, as shown in Fig. In order to obtain the Jacobian matrices of each kinematic chain in the 3-RR, it is necessary to analyze the kinematic transitions from point AI3 is a 3 × 3 identity matrix.P(.) represents a 3 × 1 displacement vector that translates the corresponding distance along the corresponding axis, 34, whereby the kinematic model can be rewritten in the form of a vector function as follows1, The position and direction of the end point B1 can be extracted from the matrix According to the principle of virtual work, the virtual displacement q and Cq represent sine and cosine of the angle q1, respectively.According to the above theory, the Jacobian matrices of the first chain in the left 3-RR Pl can be obtained by deriving Eq.  as folloSimilarly, the Jacobian matrices for the second and third chains in the left 3-RR Pl, respectively, can be expressed asFor the right 3-RR Pl, the Jacobian matrices of its three chains can also be obtained in the same way.i to Mi through each limb, as shown in Fig. In order to obtain the Jacobian matrices of each kinematic limb, it is necessary to analyze the kinematic transitions from point O1 can be extracted from the matrix 1, The position and direction of the end point MAccording to the principle of virtual work, the virtual displacement According to the above theory, the Jacobian matrices of limb 1 can be obtained by deriving Eq.  as folloFor limb 2, the Jacobian matrices of its three components can also be obtained in the same way.O-axis in series with a 2-P(3-RR) parallel structure, where the 2-P(3-RR) parallel structure includes two limbs, a screw system capable of producing translation along the xO-axis, and a mobile platform, as shown in Fig. i to point M expressed in the coordinate system {M}, 36.The Biglide parallel robot is composed of a lead screw system (prismatic joint) capable of producing translation along the yx–z plane is the yellow area in Fig. 1-W4 is its main workspace, where Q1 and Q2 are the midpoints of W1W2 and W3W4, respectively.In this section, the principal stiffness of the Biglide parallel robot considering the gravity of the mobile platform and the links is investigated numerically using the developed stiffness model. The dimensional and mass parameters of the robot are shown in Table 19. Its compliance matrix Iy, Iz and Ip are the quadratic and polar moments of inertia of the cross-section, and E and G are the Young’s and shear modules, respectively.The 3-RR Pl contains three identical cylindrical links, as shown in Fig. 37. Its compliance matrix Moreover, the slidable platform stiffness can be identified on the basis of CAD models and FEA methods33. The Cartesian stiffness matrices Finally, the Cartesian stiffness matrix tx, Kty, Ktz and Krx, Kry, Krz are the diagonal elements of the Cartesian stiffness matrix In order to better evaluate the Cartesian stiffness of the Biglide parallel robot, we visualize the distribution of its principal stiffness in six directions in its workspace, as shown in Figs. tx along the x-axis with and without gravity, it can be seen that the stiffness with gravity improves compared to the stiffness without gravity, and they both decrease as the z-axis value increases; Fig. ty along the y-axis with and without gravity, it is obvious that the stiffness with gravity is the same as the stiffness without gravity, and this stiffness is a constant; Fig. tz along the z-axis with and without gravity, it has similar stiffness characteristics to Ktx; and Fig. tz is the highest order of magnitude translational stiffness, Ktx is the second and Kty is the smallest.Figure rx in Fig. rx increases with increasing z-axis values, while Kry and Krz decrease with increasing z-axis values. Furthermore, Kry is the highest order of magnitude rotational stiffness in the principal rotational stiffness, and Krx and Krz have the same order of magnitude.Figure To validate the correctness of the stiffness model with gravity, the knocking experiments were employed on the Biglide industrial parallel robot. Using a laser Doppler vibrometer as the main experimental equipment, the principal stiffness of the mobile platform center of the Biglide parallel robot was measured in all directions, as shown in Fig. 1. The values at point Q2 are listed in Table 1 and Q2 are 2.67 and 2.77%, respectively39. And the RMS values between the stiffness model without gravity and the experimental results at Q1 and Q2 are 9.043 and 9.353%, respectively. The experimental results show a good agreement with the theoretical values of the ‘with gravity’ model. Therefore, it can be concluded that the stiffness model with gravity is effective, which lays a solid foundation for the real applications.Table The influences of the gravity of the movable links, the gravity of the mobile platform and their corresponding mass centers are considered simultaneously. In order to obtain the values of gravity, the mathematical equations of the static model were established for each joint.The stiffness model of each component is established by considering its compliance matrix, the compliance of the corresponding joint, its Jacobian matrix from the corresponding mathematical equations of the kinematic model, and the corresponding stiffness matrix due to external gravity. For the accuracy of the calculation, the compliance matrix of the irregular component is identified by using the FEA-based virtual experiment.The validity of the stiffness model with gravity was verified by comparing the calculated stiffness of the Biglide industrial parallel robot with the knockout experiment. The results show that the method is able to obtain sufficient computational accuracy to predict the stiffness distribution in the task workspace. This enables the robot to obtain more accurate tool head trajectory before machining, thus improving its machining accuracy.The stiffness modeling method is also applicable to the stiffness estimation of the robot structure design stage, which provides effective help for the improvement and verification of the structure.This paper proposes a novel stiffness modeling method for an industrial parallel robot, which is important for the machining of parallel robots. The main research results are summarized as follows:


Studies demonstrate that time-restricted feeding (TRF) can regulate gut microbiota composition. However, it is unclear whether TRF could affect the gut microbial rhythmicity in growing pigs. Therefore, the present study aimed to explore the effects of TRF on the dynamic fluctuation of the gut microbiota.A total of 10 healthy growing pigs equipped with T cannula were employed. Pigs were randomly allotted to the free access (FA) and the TRF groups with 5 replicates (1 pig/replicates). Pigs in the FA group were fed free access during the whole experimental period, whereas pigs in the TRF group were fed free access three times per day within limited times . The experiment lasted for 15 days, at 06:00 a.m. of the day 16, colonic digesta were collected at a 6-h interval for consecutive 24 h marked as T06 (06:00), T12 (12:00), T18 (18:00), T24 (24:00), T30 (06:00), respectively.p = 0.870). TRF decreased the overall concentration of colonic cellulose and altered their oscillating patterns. All alpha-diversity indexes of different time points showed significant differences regardless of feeding pattern with a trough at T18 or T24. TRF shifted the trough of the alpha-diversity index Simpson and Invsimpson. TRF lost the rhythmicity of Prevotellaceae, Ruminococcaceae, Bacteroidales_S24-7_group, and Peptococcaceae and gained the rhythmicity of Pasteurellaceae, Clostridiaceae_1, Veillonellaceae, and Peptostreptococcaceae. Also, TRF altered the interaction pattern by increasing the microbes involved in the co-occurrence network and their crosstalk, especially at T24. Interestingly, the microbial variation at T24 could largely explained by colonic substrates starch , cellulose  and NH4-N .Results showed that TRF altered the distribution of feed intake without changing the total feed intake within a day (In conclusion, TRF has changed the concentrates of cellulose and the relative abundance of specific microbes and certain microbial metabolites. In addition, TRF has more powerful effects on the fluctuation modes of these nutrient substrates, microbes, and metabolites by shifting their peaks or troughs. This knowledge facilitates the development of precision regulation targeting gut microbial rhythmicity. These mTRF is generally becoming a popular therapy as it can effectively improve chronically metabolic syndromes including obesity, hypertension, diabetes, hyperlipidemia, and cardiovascular and cerebrovascular diseases induced by overnutrition, unhealthy living habits, jet lag, and time shift work in modern society . Moreove2.2.1.The experiment was authorized by the Animal Care and Use Committee of Nanjing Agricultural University . All procedures related to the experimental animal were carried out by the Experimental Animal Care and Use Guidelines of China (EACUGC2018-01).2.2.A total of 10 healthy growing pigs  with an average body weight of 56.27 ± 1.56 kg were employed in the experiment. Pigs were fitted with T-cannula at the proximal colon. Pigs were randomly allotted to the FA group and TRF group with 5 replicates (1 pig/group) according to body weight. All pigs were fed with the same commercial pellet for growing pigs. Pigs in the FA group were fed free access during the whole experimental period, whereas pigs in the TRF group were fed three times per day within limited times  to mimic the three-meal pattern in modern society . During 2.3.The starch concentration in the colonic digesta was measured by a commercial Starch Detection Kit  according to the instructions of the manufacturer. Firstly, 80% (v/v) ethanol was used to remove soluble sugars in the samples. Then the retained samples were gelatinized in a 100°C water bath. The gelatinized starch was hydrolyzed by 52% (v/v) perchloric acid. The free glucose obtained in the hydrolysate was measured through anthrone colorimetry referring to the previous reference .Cellulose concentration was measured by a commercial Cellulose Detection Kit . Shortly, cell wall materials were extracted from the digesta sample after removing the soluble impurities using 80% (v/v) ethanol and acetone. Then, the obtained cell wall materials were hydrolyzed to free glucose by sulfuric acid. The measurement of free glucose was similar to that of the starch measurement .The concentration of total protein (TP) was measured by a commercial Protein Detection Kit  using the Coomassie brilliant blue G-250 method. Both the digesta sample and standard were dissolved in saline solution. After thoroughly mixing, the absorbances were recorded at a wavelength of 595 nm. All procedures were followed to the instructions in a previous reference .NH4-N was determined by the colorimetric method referring to the previous method . In shor2.4.Microbial DNA from digesta was extracted by the cetrimonium bromide method . About 02.5.Paired-end reads were merged according to overlaps using VSEARCH (v2.20.1). Merged reads with an error threshold of more than 0.01 were removed after trimming specific primers and barcodes. Clean reads were denoised after the disposal of low-abundance noise with a miniquesize of 8 using the UNOISE3 in USEARCH (v10.0.240) to obtain amplicon sequence variants (ASVs). Chimeras were removed by aligning against the Ribosomal Database Project . Feature ASVs were produced using USEARCH (v10.0.240) and then annotated by aligning against the RDP database (v1.6) using VSEARCH (v2.20.1) with a confidence of 0.97. Read counts were normalized using an R package vegan. Alpha-diversity indices and the rarefaction curve of each group were calculated by USEARCH (v10.0.240). Principal Coordinate Analysis (PCoA) analysis based on the Bray-Curtis distance was calculated. Further, the differences among each group were identified by PERMANOVA using the adonis function in the vegan package.2.6.The concentration of lactate was determined with a commercial Lactate Assay Kit  using the colorimetric method. All procedures strictly followed the instructions in the kit. In brief, about 0.1 g digesta samples were diluted in distilled water, thoroughly mixed, and then centrifuged. A total of 0.02 mL supernatant was mixed with 1 mL of enzyme working solution and 0.2 mL chromogenic agent. The mixture was incubated at 37°C for 10 min and immediately terminated with 2 mL of stop solution. The absorbance of the reaction solution was measured at the 530 nm wavelength. The concentration of lactate was calculated following a standard curve method.The concentrations of short-chain fatty acids  were measured by gas chromatography method using Agilent 7890A gas chromatograph  as previously described . In brie2.7.The level of biogenic amines, including methylamine, putrescine, tyramine, tryptamine, cadaverine, spermine, and spermidine, was measured using liquid chromatography referring to the previous reference . Shortly2.8.via one-way analysis of variance, followed by Bonferroni-based multiple comparisons using SPSS software . The rhythmicity of alpha-diversity induces, microbes and microbial metabolites was assessed by a non-parametric JTK_circle R package . For data that conformed to a normal distribution, a two-sided Student’s t-test was used, and for data that did not conform to a normal distribution, a non-parametric test was used. Differences in different time points of each group were analyzed  package . An indepipeline . The co-3.3.1.p = 0.870, p = 0.032, p = 0.365, p = 0.151, p = 0.567, TRF has changed the distribution of feed intake without changing the total feed intake , chao1 (p = 0.004), and ACE , chao1 (p = 0.045), and ACE (p = 0.033) at T12, whereas it increased Invsimpson at T30 (p = 0.033).Up to 2,318,557 clean reads were generated from the 50 colonic digesta samples with an average of 46,371 ± 1,232 (mean ± standard error) clean reads per sample and an average clean read length of 413.74 ± 0.36 bp . RarefacFirmicutes (78.68% ± 1.91%) and Bacteroidetes (16.73% ± 1.79%) were the most dominant phylum in the colon microbial community of growing pigs (Streptococcus (10.7 ± 1.36%), Blautia (5.92% ± 0.67%), Ruminococcaceae_UCG-005 (5.43 ± 0.61%), Prevotella_9 (4.66% ± 0.84%), Alloprevotella (4.35% ± 0.57%), Subdoligranulum (4.27% ± 0.35%), Sarcina (3.71% ± 1.09%), Lactobacillus (3.21% ± 0.68%), Roseburia (2.8% ± 0.28%), and Anaerovibrio , Acidaminococcaceae , and Alcaligenaceae  exhibited significant rhythmicity regardless of the feeding mode , Ruminococcaceae , Bacteroidales_S24-7_group , and Peptococcaceae , Clostridiaceae_1 , Veillonellaceae , and Peptostreptococcaceae , Phascolarctobacterium , Anaerovibrio , Sutterella , Prevotella_9 , and Prevotella_1  showed significant rhythmicity both in the FA group and the TRF group , [Ruminococcus]_gauvreauii_group , Prevotellaceae_UCG-003 , Coprococcus_3 , Prevotellaceae_UCG-001 , Ruminococcaceae_UCG-014 , Subdoligranulum , and Peptococcus , Sarcina , Actinobacillus , Prevotella_2 , Clostridium_sensu_stricto_1 , Terrisporobacter , Romboutsia , and Roseburia  and decreased that of Peptococcus (p = 0.023).At the genus level, RF group ,B. Simil3.3.The overall microbial co-occurrence network of the FA group and TRF group had no significant difference in the populations of participant nodes and their interactions ,B. Howev3.4.p = 0.045) and the total SCFAs  and but decreased acetate at T06 (p = 0.030) and T12 (p < 0.001), isobutyrate (p = 0.029) at T24, and SCFA (p = 0.020) at T06. Although TRF has limited effects on the concentration of microbial metabolites, it has significantly changed the oscillating patterns of acetate, propionate, butyrate, isobutyrate, isovalerate, lactate, spermine, tryptamine, and putrescine , Ruminococcaceae_NK4A214_group , Terrisporobacter , [Eubacterium]_coprostanoligenes_group , Family_XIII_AD3011_group , Streptococcus , Treponema_2 , and Lachnospiraceae_XPB1014_group , whereas negatively correlated with Roseburia , Ruminococcus_2 , Incertae_Sedis , Subdoligranulum , Oribacterium  Fusicatenibacter , Coprococcus_2 , Dialister , and Erysipelotrichaceae_UCG-001 . Meanwhile, starch and cellulose had limited associations with these microbes. Starch negatively correlated with Megasphaera . Cellulose was positively correlated with Turicibacter  and Collinsella . Whereas under the TRF pattern, NH4-N positively correlated with Catenibacterium , Blautia , Oribacterium , Anaerostipes , Leeia , and Coprococcus_3  whereas negatively correlated with Prevotella_1 , Prevotella_2 , Prevotella_9 , Lachnospiraceae_UCG-004 , Lachnospiraceae_NK4A136_group , Coprococcus_2 , and [Eubacterium]_oxidoreducens_group . Cellulose and starch had tight correlations with these microbes under the TRF pattern. Cellulose positively correlated with Turicibacter , Catenibacterium , Holdemanella , Dorea , and Ruminiclostridium  whereas negatively correlated with Ruminococcaceae_UCG-013 , Ruminiclostridium_6 , Ruminococcaceae_UCG-005 , Prevotellaceae_NK3B31_group , and Prevotellaceae_UCG-001 . Starch positively correlated with Blautia , Dorea , Collinsella , Lachnospiraceae_ND3007_group , Catenibacterium , Megasphaera , Fusicatenibacter , Dialister , and Succinivibrio  whereas negatively correlated with Ruminococcaceae_UCG-008 , Ruminococcaceae_UCG-013 , Prevotellaceae_UCG-001 , and Prevotellaceae_NK3B31_group . TP has limited effects on the gut microbiota under both feeding modes. TP was positively correlated with Leeia  and Lachnospiraceae_AC2044_group , whereas negatively correlated with Solobacterium  and Holdemanella .Interestingly, further correlation analysis indicated that these gut microbes exhibited differential associations with the nutrient substrates under different feeding modes . Under t4.In the present study, we found that TRF affected the gut microbes and their metabolites by altering the nutrient substrates therein . In modeConvincing evidence indicated that TRF could entrain the periodic clock and thus affect the hormone-secretion and gene expression in the colonic mucosa . InteresOscillibacter, whereas it decreased the relative abundance of Akkermansia in mice  can be found in the article/The animal study was reviewed and approved by the Animal Care and Use Committee of Nanjing Agricultural University .WZ: conceptualization, supervision, and writing—review and editing. YS: project administration, funding acquisition, conceptualization, supervision, writing—review and editing, and methodology. HW: conceptualization, formal analysis, investigation, writing—original draft, and visualization. QL: methodology, investigation, validation, and writing—reviewing and editing. RX: methodology, validation, and writing—reviewing and editing. All authors contributed to the article and approved the submitted version.This work was supported by grants from the National Natural Science Foundation of China (32072688 and 31872362).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Long-term studies of modern zirconia implants are still insufficient. This prospective 8-year follow-up study investigated one-piece zirconia implants.Patients who had received a one-piece zirconia dental implant  were included in this study. Next to the implant survival and success rates, the radiographic and clinical implant parameters were assessed.p = 0.0120). According to the pink esthetic score, the immediate implants revealed more favorable esthetic results compared to the delayed implants after an 8-year follow-up (p = 0.0002).The overall survival rate of 67 zirconia implants in 39 patients was 100%. The overall success rate was 89.6%. Around the immediate zirconia implants, the success rate was 94.7%, and around the delayed implants, 87.5%. The immediate implants showed a significantly higher bone crest compared to the delayed implants (After 8 years, the one-piece zirconia implants presented an 89.6% success rate. Regarding the timing of implantation, in individual cases, immediate implantation can have slight advantages over delayed implantation.Immediate implants can also be considered for zirconia implants and should not be excluded on principle. Titanium implants osseointegrate into the human jaw and can thus support dentures. Provided there are no relevant interferences, this connection is permanent. As an implant material, titanium is the gold standard based on numerous long-term studies . TitaniuHowever, titanium is not necessarily without any disadvantages. If the soft-tissue situation is unfavorable, especially in the region of the anterior teeth and anterior premolars with a high smile line, the gray color of the titanium may shine through the tissue as a complication , 5.T. forsythia and P. intermedia bacterial values, the soft tissues around the zirconia implants had a lower inflammatory response to the experimental plaque formation than those around the titanium implants [At present, titanium is predominantly used in implantology, but several studies have shown that titanium and zirconia are at least equivalent functionally, such as with regard to their osseointegration –9. Due timplants . HoweverThe primary aim of the present prospective 8-year follow-up study was to evaluate the survival and success rates of immediate and delayed zirconia implants. Furthermore, clinical and radiographic images were analyzed for the hard- and soft-tissue parameters.A total of 39 patients and 67 zirconia implants  were included in the present study. Zirconia monotype implants, each with a diameter of 4.1 mm, were used. The implants were available in lengths of 8, 10, and 12 mm and in two different abutment heights of 4.0 mm and 5.5 mm. A transmucosal implant placement was performed in all cases.The patient population was related to that in a previously published investigation . Of the The primary outcome variables were the implant survival and success rates, with a comparison of those of immediate and delayed implants Fig. . If the The success rate according to Albrektsson et al. 1986) was used [86 was usAt the examination after 8 years, the peri-implant clinical parameters were assessed –22. One For the evaluation of bone changes, digital panoramic radiographs  were performed. The defined distance of the individual implant lengths was used to calibrate the radiography pictures. For such calibration purposes in radiographs, cylindrical implants with uniform and quality-regulated production dimensions are excellent. Furthermore, possible magnification during picture collection had no discernible effect. The bone levels were measured from the first bone to the implant contact to the implant shoulder, and from the bone contact of the implant over the papilla tip to the contact point of the crowns.Additionally, photographs were taken at a 90° angle around each crown. The camera setup was the same at all times . For calibration, the length of one crown was measured. All the distances were measured using the ImageJ software . The heTo assess the peri-implant soft tissue, the pink esthetic score (PES) according to Fürhauser et al.  was usedAnalyses were performed using the Prism 9 software for Mac OS X  running on Apple OS X. The Kolmogorov–Smirnov normality test was used to check whether the variables were normally distributed. A mixed-effects model was used to identify the differences between immediate and delayed implants.2 monotype implants  were investigated. All the implants were inserted using a mucoperiostal flap during surgery, and in all cases, simultaneous autologous augmentation was performed (using autologous bone particles). The definite crown placement was carried out after a 3-month healing period in all the groups; however, in the immediate cases during surgery, a temporary chair-side crown without occlusal contact points was used  were included in the present study. The mean age of the patients was 58.8 years (range: 29–84 years). The mean follow-up time for all the cases was 8 years after crown placement. ZrOThe overall survival rate was 100%, and the overall success rate was 89.6%. Around the immediate zirconia implants, the success rate was 94.7%, and around the delayed implants, 87.5%.p = 0.0120). On the other hand, no significant differences in the distance between the bone crest and the papilla tip/contact point of the crowns and papilla height (mm) were found between the groups . In addition, no detectable difference in the papilla deficit and the ratio of the papilla height to the crown length (%) was found between the immediate and delayed zirconia implants  than the delayed implants . Esposito et al. also reported better esthetic results after immediate implant placement, but they cautioned that higher implant loss rates should be expected in this case [According to Francisco et al., both the immediate and delayed implantation methods resulted in an esthetic outcome; no differences in PES were observed . Canellahis case . Neverthhis case . In the The aforementioned short- to medium-term studies reported clinically equivalent results for immediate versus delayed implant placement , 36. HowOur survey revealed that the immediate implant placement had no visual disadvantages and no significant functional limitations in the long term; it had a high survival rate and low bone resorption. However, it must be noted that in our patients, the indication for immediate implant placement was given by an experienced surgeon. These indications included the absence of inflammation, good bone volume, no mucosal disease, no untreated periodontitis, or gingivitis, no severe bruxism or clenching habits, and a compliant patient (no hard food contact to the immediate implant crown) during the 3-month healing period. It was observed that delayed implants had lower levels of success. Delayed implants were preferred in certain compromised bone situations. This may be the reason for the reduced success rate.According to the criterion of Tarnow et al.  and ChoqChu et al. found an average quotient of about 40% and defined this as the ideal esthetic value. However, they pointed out that there was still a subjective range of variation and that an esthetic ideal could be subject to social and cultural influences . The dat32 and Esposito et al.’s 33 meta-analyses. In contrast, in our long-term study exclusively related to zirconia, a 100% survival rate was observed after immediate implantation.A slightly increased risk of implant loss 1 and 5 years after immediate titanium implantation, respectively, was reported in Canellas et al.’s With the modern zirconia two-part variants, the crown can be placed via angulation. Tilted implants can be an effective and safe alternative to avoid augmentation procedures .In addition to the clinical survey, all the implants were examined radiographically. Thus, possible periapical abnormalities or radiolucencies could be excluded (no implant in the present study was conspicuous), and functionally relevant distances could be determined.In the present study, each radiographic examination was performed using panoramic radiography, a widely used method for clearly and reproducibly visualizing the entire jaw with a low radiation dose . Chopra After 8 years, one-piece zirconia implants presented an 89.6% success rate. Around the immediate zirconia implants, a higher bone crest was found, and the esthetic results were more favorable than those of the delayed implants.


Introduction: Cerebral pulsation is a vital aspect of cerebral hemodynamics. Changes in arterial pressure in response to cardiac pulsation cause cerebral pulsation, which is related to cerebrovascular compliance and cerebral blood perfusion. Cerebrovascular compliance and blood perfusion influence the mechanical properties of the brain, causing pulsation-induced changes in cerebral stiffness. However, there is currently no imaging technique available that can directly quantify the pulsation of brain stiffness in real time.Methods: Therefore, we developed non-invasive ultrasound time-harmonic elastography (THE) technique for the real-time detection of brain stiffness pulsation. We used state-of-the-art plane-wave imaging for interleaved acquisitions of shear waves at a frequency of 60 Hz to measure stiffness and color flow imaging to measure cerebral blood flow within the middle cerebral artery. In the second experiment, we used cost-effective lineby-line B-mode imaging to measure the same mechanical parameters without flow imaging to facilitate future translation to the clinic.Results: In 10 healthy volunteers, stiffness increased during the passage of the arterial pulse wave from 4.8% ± 1.8% in the temporal parenchyma to 11% ± 5% in the basal cisterns and 13% ± 9% in the brain stem. Brain stiffness peaked in synchrony with cerebral blood flow at approximately 180 ± 30 ms after the cardiac R-wave. Line-by-line THE provided the same stiffness values with similar time resolution as high-end plane-wave THE, demonstrating the robustness of brain stiffness pulsation as an imaging marker.Discussion: Overall, this study sets the background and provides reference values for time-resolved THE in the human brain as a cost-efficient and easy-touse mechanical biomarker associated with cerebrovascular compliance. The brain is a pulsatile organ that expands by approximately half a milliliter due to the arterial pulse wave . This imDirect measurement of vessel compliance is challenging because it requires knowledge about the mechanical stress associated with a measured change in the blood flow . Transcrin vivo human brain.Here, we propose an alternative approach to study brain pulsatility and vascular compliance based on elastography. Elastography uses conventional imaging modalities to measure macroscopic tissue stiffness, for example, by sensing externally induced shear waves in soft tissues non-invasively . In vascElastography of the brain has been mainly based on MRI , while aFor the aforementioned reason, cerebral time-harmonic elastography (THE) has been developed based on sonography through the temples and acquisition of externally induced harmonic shear waves from 27 to 56 Hz, similar to the frequency range of MRE . THE wasTherefore, here, we developed time-resolved cerebral THE with a frame rate of 100 Hz to continuously capture the effects of CAP on brain stiffness over several heartbeats. In healthy volunteers, we performed two experiments. In one experiment, we used a high-end, plane-wave ultrasound scanner, which allowed us to acquire color flow images and stiffness maps in an interleaved fashion. This experiment was designed to ensure that established flow measurements and novel elastography captured the same physiological event on a shared time axis. In a second experiment, we used conventional line-by-line imaging to acquire only time-resolved stiffness changes without flow measurements, which facilitates clinical translation. Altogether, we aim to 1) report, for the first time, pulsation-induced changes in brain stiffness in the temporal lobe, basal cistern, and brain stem directly compared with cerebral blood flow and 2) demonstrate the implementation of this method on a clinical and cost-efficient ultrasound system based on conventional line-by-line imaging.The study was approved by the institutional review board of Charité—Universitätsmedizin Berlin (EA1/004/19). Written informed consent was obtained from all volunteers before participating in this study. Two groups of 10 healthy volunteers each  were prospectively included. Descriptive data of all volunteers  are summarized in In the first experiment, high-end, plane-wave imaging  for interleaved acquisitions of cerebral blood flow (CBF) using color flow imaging and shear wave speed (SWS) by THE was applied to group 1 (CBF-THE). In the second experiment, cost-efficient, line-by-line imaging  was applied to the second group of volunteers for stiffness mapping (c-THE). In both CBF-THE and c-THE experiments, ECG data were continuously recorded for assigning CBF and SWS to cardiac phases. Each measurement took 8 s and was repeated five times to increase the statistical power.Volunteers were investigated in a supine position on a custom-designed vibration bed  with the head placed above the vibration unit for efficient transfer of harmonic vibration energy into the brain  Kreft e. To avoiTHE processing relied on the phase-difference extraction of the local axial displacement between adjacent in-phase and quadrature (IQ) frames. The temporal Fourier transform was then applied to the computed displacement data, and time-resolved complex wavefields  were obtk-MDEV inversion . For this, Gaussian-based spatiotemporal filters with a low-pass threshold of 555 rad/m for noise suppression and first-order derivative for suppression of compression waves were applied. The wave numbers were deduced from the phase gradient of The final maps of SWS were obtained by averaging over directions:R) and relative to the CBF peak (τΔ) was quantified and tabulated.Processing took approximately 15 min for the CBF-THE data and 30 s for the c-THE data. Regions of interest (ROIs) for the temporal lobe, basal cistern, and brain stem were manually drawn based on the anatomical B-mode image. SWS variations over time were analyzed after averaging within these regions for each time step. For color flow imaging processing, a region covering the middle cerebral artery was automatically selected through thresholding. A threshold of 5 cm/s was empirically set based on the amplitude of the background noise. A temporal moving boxcar filter of 3-pixel width was applied for noise suppression. The envelope of the flow spectrum was computed to obtain the time variation in CBF within the middle cerebral artery. R–R intervals were extracted from the acquired ECG signals with wavelet-based peak detection  using thR and τΔ were tested against zero using the Wilcoxon signed rank test. Pearson’s correlation coefficient was used to analyze possible correlations between the relative change in SWS and delay times τR and τΔ in the global ROI, with demographic parameters, such as age, BMI, heart rate, and mean arterial pressure, and the relative change in CBF. The relative change in SWS, mean SWS, and delay time τR obtained from CBF-THE was compared to c-THE using the Wilcoxon signed rank test. Nonparametric tests were chosen due to the small number of volunteers. All p values <0.05 were considered significant. The group size was estimated based on a power analysis assuming an effect size of 10%–20% at a 5% significance level and a power of 0.8 for the variability of stiffness parameters encountered in healthy adult subjects.Relative changes in SWS and CBF over the R–R-interval were tested for each subregion using the paired Wilcoxon signed rank test. Delay times τIn all volunteers, time-resolved SWS and, in the CBF-THE group, time-resolved CBF were obtained. Group SWS and CBF values on a time axis normalized to one R–R-interval are presented for all four regions in R) were 180 ± 30 ms in the global ROI, 210 ± 50 ms in the temporal parenchyma, 180 ± 60 ms in the basal cisterns, and 160 ± 40 ms in the brain stem. In all regions except the temporal lobe, there was no significant time delay between the peak systolic SWS and peak systolic CBF (τΔ). In the temporal lobe, τΔ of 50 ± 50 ms was observed, suggesting a slight delay in the SWS wave after the CBF wave . Data acquired by c-THE are summarized in Group SWS within the global ROI measured by c-THE was similar to CBF-THE, with a mean SWS of 1.78 ± 0.08 m/s, relative SWS changes of 9.9% ± 2.9%, and a delay in the SWS peak to the R peak of 211 ± 36 ms. There was no significant difference in the values obtained by CBF THE (mean SWS: To the best of our knowledge, this is the first study in which changes in brain stiffness due to cerebral arterial pulsation have been directly observed without cardiac gating and time averaging, that is, quasi-real time. We observed a change in SWS in synchrony to CBF pulsation, from which we concluded that CAP significantly affected brain stiffness. This effect was present in all regions, which underscores the relevance of the relative SWS change as a potential biomarker of cerebrovascular compliance. It should be noted that THE was less constrained by accurately locating anatomic landmarks than color flow imaging, which is limited to the middle cerebral artery. As a result, the overall time required, including probe positioning, was shorter for THE than for color flow imaging. Because there was no significant temporal shift between the SWS peak and the CBF peak of arterial pulsation, we can conclude that SWS measurement provides a robust and cost-effective imaging marker, that is, complementary to Doppler imaging.Given the extensive literature on elastography in highly perfused organs, we speculate that the observed variation in brain stiffness is related to cerebrovascular compliance . SpecifiAn exception here is our own previous work in which cardiac-gated MRE was used to measure CAP-induced stiffness changes . In thisFurther studies investigating the effects of different states of perfusion and pressure on the temporal modulation of cerebral stiffness are required to better understand the observed stiffness variation. In this context, the effects of dehydration and water uptake on brain stiffness have been studied based on cerebral THE . HoweverR with the heart rate may be due to the fact that we only investigated healthy volunteers with a relatively narrow range of heart rates. In future studies including patients with tachy- or bradycardia, we expect τR to be sensitive to the heart rate. However, this study focused on method development and first-time demonstration of CAP-induced stiffness alterations to provide a reference for larger cohort studies in a clinical setting.The main limitation to our study is the lack of clinical data. It would be interesting to see how stiffness pulsation changes upon the relief of intracranial hypertension in patients undergoing lumbar puncture. A possible change in stiffness pulsation over a wider age range and in conditions such as mild cognitive impairment and dementia is also warranted for future studies. In addition, the relatively small number of subjects precludes a conclusive analysis of physiological effects on changes in brain stiffness, as well as the assessment of possible timing differences between CBF and SWS waves. The insignificant correlation of τIn summary, our study demonstrated the feasibility of time-resolved cerebral THE for the assessment of cerebrovascular compliance based on pulsations of tissue stiffness. Plane-wave imaging-based THE showed that brain stiffness in healthy volunteers changes from minimum values during cerebral diastole to maximum values during cerebral systole in the order of 10% with variation across anatomical regions. This direct relationship between the stiffness wave and arterial blood pulse wave could make THE a sensitive imaging marker for brain compliance changes due to cerebrovascular pulsation, which could be used for diagnostics and treatment monitoring. Furthermore, relative stiffness changes measured by line-by-line-based THE was shown to be a cost-effective alternative to plane-wave-based THE that is ready to use in the clinic for the noninvasive measurement of brain stiffness associated with intracranial pressure and cerebrovascular compliance.


Modification of corn starch using ultrasonic waves to improve its freeze-thaw resistance in frozen model doughs and buns. Analysis was performed by rheometry, low-field-intensity nuclear magnetic resonance imaging, Fourier infrared spectroscopy, and scanning electron microscopy. The results showed that the addition of ultrasonically modified corn starch reduced the migration of water molecules inside the model dough, weakened the decrease of elastic modulus, and enhanced the creep recovery effect; the decrease in α-helical and β-fold content in the model dough was reduced, the destruction of internal network structure was decreased, the exposed starch granules were reduced, and the internal interaction of the dough was enhanced; the texture of the buns became softer and the moisture content increased. In conclusion, ultrasound as a physical modification means can significantly improve the freeze-thaw properties of corn starch, providing new ideas for the development and quality improvement of corn-starch-based instant frozen pasta products. With the accelerated pace of people’s life, frozen products are increasingly favored by consumers. During the transportation and sales process, the quality of frozen dough often deteriorates due to temperature changes, so improving the quality characteristics of frozen dough has become a hot research topic. The internal components of dough in frozen products are complex, and starch and protein, as the main components, play a vital role in the quality of dough . Some stAs the first major grain crop in China, corn has been widely used in the food industry because of its rich nutritional value. Corn starch is the main component of corn, with a content of about 70%. Due to the defects of starch such as poor freeze-thaw stability and easy aging, it seriously limits its application. To improve freeze-thaw stability, enhance food quality, and expand application areas, raw materials are often treated using physical, chemical, or biotechnological means. Chemical treatment tends to introduce new groups and is not desirable from a food safety point of view ,5. The aUltrasonic is a kind of sound wave with a frequency higher than 20 KHz, which is used to modify starch granules through the force of cavitation effect and mechanical effect, and is widely used in food and pharmaceutical fields . The stuThis study was conducted to investigate the improvement mechanism of ultrasonically modified maize starch on the freeze-thaw properties of frozen model doughs. The ultrasonically modified corn starch-gluten protein reconstituted model dough was used to investigate the improvement effect of ultrasonically modified corn starch on the anti-freeze-thaw properties of the model dough and its application in steamed buns. By analyzing the rheological properties, moisture distribution, and microstructure of the ultrasonically modified corn starch model dough during the freeze-thaw process, the reasons for the changes in the quality characteristics of its steamed buns were elucidated, and the mechanism of the changes in the anti-freeze-thaw characteristics of the ultrasonically modified corn starch model dough was revealed. It aims to provide a theoretical basis for the development and quality control of convenient quick-frozen grain-starch-based products.Corn starch was provided by Shanghai Ruiyong Biotechnology Co., Ltd. of China . Gluten protein was provided by Henan Relent Biotechnology Co., Ltd. of China (protein content > 90%). Dried yeast was obtained from Angel Yeast Co Ltd., Hubei, China. All reagents are analytical grade.w/w) was prepared and mixed well by magnetic stirring. Ultrasonic power of 120 W and ultrasonic time of 20 min  were used to treat and obtain ultrasonically modified corn starch.A solution of corn starch with a mass fraction of 6% (w/w), and the ultrasonically modified corn starch was reconstituted with gluten protein in this ratio. The ratio of flour to water was 2:1. The fully kneaded model dough was kept stable at room temperature for 20 min and evenly divided into several small doughs. The dough was frozen at −20 °C for 22 h and thawed at 30 °C for 2 h as a freeze-thaw Cycle (FT). The freeze-thaw cycle lasted 5 times. The ultrasonically modified corn starch model doughs were denoted as UCS-G, FTU1-G, FTU2-G, FTU3-G, FTU4-G, and FTU5-G. The natural corn starch model doughs were denoted as CS-G, FTC1-G, FTC2-G, FTC3-G, FTC4-G, and FTC5-G.The ratio of starch to protein in commercially available flour was measured to be 85:15  . The dou2 of the sample was determined using a multi-pulse echo sequence (CPMG) and the pulse parameters were as follows: TR = 2000 ms, TE = 0.250 ms, NECH = 10,000, SW = 100 KHz, PRG = 2, and NS = 16.The moisture distribution state of frozen model dough was analyzed using low-field-strength MRI  . The traAnalysis of the qualitative properties of frozen model dough was performed using a physical property analyzer . A physical property analyzer with a P/0.5 cylindrical probe was used to analyze the textural properties of the model dough. The velocity was 3 mm/s before, 1 mm/s during, and 5 mm/s after the test.Determination of dynamic rheological properties of frozen model dough was carried out using a rheometer  . About 2Creep recovery characteristics of frozen model doughs were analyzed using a rheometer  . The creThe method was adopted from Zhao et al.  and Fan w/w), and scanned 64 times from 4000 to 400 cm−1 at a resolution of 4 cm−1. Deconvolution of the amide I bands was performed to analyze the secondary structure of the model dough during the freeze-thaw cycle.The secondary structure of the frozen model dough was analyzed using Fourier infrared spectroscopy . The model dough was freeze-dried under vacuum, mixed with KBr at a ratio of 1:100 . The samples were fixed for gold spraying, and the apparent morphology was observed at a voltage of 3.0 KV with a magnification of ×500.The method was adopted from Bai et al.  and Fan Steamed buns were photographed and measured using a Sightline Benchtop tabletop vision system.Analysis of the textural properties of steamed buns using a physical property analyzer . The bun samples were analyzed using a physical property analyzer with a P36R probe. The speed was 3 mm/s before the test, 1 mm/s during the test, and 3 mm/s after the test.m is the mass of drying to constant weight.The steamed buns were allowed to stand at room temperature for 30 min, and a sample of about 2 g was taken from the central part, dried to constant weight at 105 °C, and weighed. The calculation formula is as follows:p < 0.05) and were plotted using SPSS 25 for ANOVA and Origin 2020 for plotting.Data are the means of 3 replicate trials and are expressed as x ± s. Different letters represent significant differences (p < 0.05). The cavitation effect of ultrasonic treatment exposes more free radicals in corn starch and increases the interaction with water molecules and protein molecules during the freeze-thaw process. This interaction binds the moisture inside the dough, inhibits the conversion of non-freezable water, and reduces the freezable water content [The water molecules in the dough exist in many ways, and the main component of freezable water is free water. The formation of ice crystals is one of the main factors causing deterioration in the quality of frozen dough, and the amount of ice crystals depends on the amount of freezable water . Therefo content .The quality of frozen pasta products mainly depends on how the internal moisture is distributed during freezing and thawing, and low field strength NMR technology can visually analyze the state of moisture presence. 2 curve of the ultrasonically modified corn starch model dough shifted to the left during the freeze-thaw process and the water mobility became weaker. As can be seen from p < 0.05), which is consistent with the results of freezable water content. The reason may be that the ice crystals produced by freezing and thawing weaken the binding force of proteins, starches, and other substances in the dough to water, thus affecting the distribution of water inside the dough. Several studies have also shown that the freeze-thaw process increases the release and redistribution of water molecules [From olecules ,22. At tolecules  showed tp < 0.05) and the springiness value of FTU3 increased by 14.93% (p < 0.05) compared with FTC4-G. The water in the dough is mainly composed of strong and weak bound water, and this phenomenon may be caused by the addition of ultrasonically modified corn starch, which enhances the hydration of each component in the model dough through hydrogen bonding. Zhang et al. [The hardness, springiness, cohesiveness, and reversibility of the model dough were changed during the freeze-thaw cycle and characterized by a physical property meter. As shown in g et al.  also shoThe dough rheological property is a major factor affecting the product quality; the elastic quality of dough is expressed by the elastic modulus G′, the viscous quality of dough is expressed by the viscous modulus G″, and the loss angle tangent value tanδ is the ratio of viscous modulus to elastic modulus, which represents the proportion of polymer and reflects the interaction between the components in the dough . That isAs can be seen from The viscoelasticity of the ultrasonically modified corn starch frozen model dough was further analyzed by obtaining fitting parameters through power law equations. The k′ and k″ values are positively correlated with the strength of the model dough, and the n′ and n″ values represent the molecular interaction forces in the model dough . As show0 represents the fluidity of the model dough when the shear stress is withdrawn. The Jmax values of the ultrasonically modified corn starch model doughs were higher than those of natural corn starch, and the Jmax values of FTU4-G increased by 12.61% (p < 0.05) compared to FTC4-G, indicating a reduced degree of dough hardening. It was noted that under the same freezing conditions, the Jmax value decreased as the freezing time increased [Creep recovery characteristics reflect the trend of rheological changes in model dough under constant pressure and the recovery trend of model dough deformation when constant pressure is removed. As shown in ncreased . The ratncreased . During p < 0.5) and the disulfide bond content of FTU3-G increased by 21.59% (p < 0.05) compared to FTC3-G. Thus, the ultrasonically modified corn starch resulted in the inhibition of the conversion between sulfhydryl groups and disulfide bonds in the model dough, attenuating the extent of internal structural damage.The quality of dough depends on the tight network structure formed between starch and gluten protein, and the disulfide bond and free sulfhydryl group can be converted to each other, which is conducive to maintaining the stability of protein molecular structure and directly reflects the stability of dough . Figure −1. A stretching vibration peak can be clearly seen at 3350 cm−1, which is related to the formation of hydrogen bonds [en bonds . The posen bonds . Therefop < 0.05) compared to FTC2-G and the β-folding content increased by 4.48% (p < 0.05) compared to FTC5-G. It showed that the hydrogen bonding interaction force in the ultrasonically modified corn starch model dough was enhanced and the viscoelasticity of the dough was increased, which was consistent with the rheological results in this paper and with the results of Zhou et al. [u et al. .The microstructures of the model doughs under different numbers of freeze-thaw cycles are shown in p ˂ 0.05), and the ultrasonically modified corn starch buns had a better appearance.p ˂ 0.05), indicating that the ultrasonically modified corn starch dough could attenuate the damage produced by the freeze-thawing process, and the dough had strong air-holding property and the quality of buns was improved [Specific volume is the ratio of volume to mass, which represents the fluffiness, tissue state, and quality of the buns. As shown in improved .p ˂ 0.05) and the elasticity increased by 9.47% (p ˂ 0.05) compared with FTC3. When the frozen dough was steamed, the water gradually evaporated, causing the hardening of the bun crust.The texture characteristics directly characterize the quality of the buns, the harder the hardness the worse the taste, and the lower the elasticity the harder the texture . As showp ˂ 0.05) compared to FTC4, with less moisture loss in the buns, resulting in increased internal moisture content.As can be seen from p < 0.05); the mobility of water molecules was reduced; the polymer ratio increased and the creep recovery process had a higher Jmax value; the hardness value of FTU4-G was 7.25% lower than that of FTC4-G (p < 0.05); less dough hardening; less conversion between free sulfhydryl groups and disulfide bonds; less precipitated starch particles; more regular network structure; enhanced internal interactions; and more stable structure. Compared with natural corn starch buns, the specific volume of ultrasonically modified corn starch buns increased, the hardness of FTU3 decreased by 28.48% compared with FTC3 (p < 0.05), the texture became softer and the internal water-holding capacity increased. In conclusion, the addition of ultrasonically modified corn starch improved the rheological properties of frozen model doughs, inhibited the migration of water molecules, reduced the degree of microstructural damage, significantly improved the freeze-thaw resistance of frozen doughs, expanded the application areas of corn starch, and provided a theoretical basis for the development of starch-based instant frozen pasta products.In this study, the dough was reconstituted by ultrasonically modified corn starch and gluten protein to investigate the improvement effect of ultrasonically modified corn starch on the anti-freeze-thaw properties of frozen model dough and to study the improvement effect of its quality characteristics of steamed buns. Compared with the natural corn starch model dough, the transverse relaxation time curve of the ultrasonically modified corn starch model dough shifted to the left; the freezable water content of FTU4-G was 2.49% lower than that of FTC4-G (


One of the most significant environmental problems in the world is the massive release of dye wastewater from the dyeing industry. Therefore, the treatment of dyes effluents has received significant attention from researchers in recent years. Calcium peroxide (CP) from the group of alkaline earth metal peroxides acts as an oxidizing agent for the degradation of organic dyes in water. It is known that the commercially available CP has a relatively large particle size, which makes the reaction rate for pollution degradation relatively slow. Therefore, in this study, starch, a non-toxic, biodegradable and biocompatible biopolymer, was used as a stabilizer for synthesizing calcium peroxide nanoparticles (Starch@CPnps). The Starch@CPnps were characterized by Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), Brunauer–Emmet–Teller (BET), dynamic light scattering (DLS), thermogravimetric analysis (TGA), energy dispersive X-ray analysis (EDX) and scanning electron microscopy (SEM). The degradation of organic dyes, methylene blue (MB), using Starch@CPnps as a novel oxidant was studied using three different parameters: initial pH of the MB solution, calcium peroxide initial dosage and contact time. The degradation of the MB dye was carried out via a Fenton reaction, and the degradation efficiency of Starch@CPnps was successfully achieved up to 99%. This study shows that the potential application of starch as a stabilizer can reduce the size of the nanoparticles as it prevents the agglomeration of the nanoparticles during synthesis. Dye residues found in wastewater can have detrimental effects on the environment and living organisms. Industries, such as cosmetics, printing, food processing, textiles and paper, are significant contributors to this issue. One particularly harmful dye is methylene blue (MB), a cationic dye commonly used in the dyeing industry . Due to 2O2 oxidation  is the initial concentration of KMnO4, and 72.08 is the molar mass of CP. Experiments were run in triplicate. Equation (5) represents the permanganate reaction between hydrogen peroxide and permanganate ions under acidic conditions. From the equation, it can be seen that the reduction of the permanganate ion to Mn2+ by oxidation with hydrogen peroxide leads to the emission of oxygen gas and the formation of water. The reaction is assisted by manganese sulphate (MnSO4), which provides an excess of Mn2+ to prevent the oxidation of the chloride ions.Calcium peroxide content in the synthesized Starch@CPnps was calculated using Equation (4):2 = 0.99), the absorbance was converted to concentration, and the percentage degradation of the MB dye was calculated using Equation (6):0 and [MB]t represent the initial concentration (20 ppm) and concentration of MB dye (ppm) at various time intervals (min), respectively.Different parameters, including the initial pH of MB dye solution , initial dosage of the sample , and contact time (0–60 min), were investigated in the degradation studies of MB dye. The experiments were carried out in a batch procedure using a series of Erlenmeyer flasks at room temperature (25 ± 2 ˚C). The MB dye was diluted from the stock solution to a concentration of 20 ± 0.1 ppm, and the pH of the solution was adjusted by adding either HCl (0.1M) or NaOH (0.1M) ,33. A sp–1. The phase analysis of the sample was evaluated using X-ray diffractometry (XRD)  in the range of 2θ = 20° to 80°, using CuKα radiation and a step size of 4°/min. X’Pert HighScore Plus software version 2.2.4  was used to analyze data from XRD, and the full width at half maximum (FWHM) of the peaks was calculated. The thermal stability of the sample was examined using Mettler Toledo TGA/SDTA 851  in a nitrogen atmosphere, with a heating rate of 10 °C min−1 and at the temperature range of 50 °C to 600 °C. The size and polydispersity index (PDI) of the Starch@CPnps dispersed in ethanol were determined using a particle sizer  by measuring at a scattering angle of 90°. The surface morphology and elemental analysis were characterized using scanning electron microscopy (SEM)  magnification: 500–300,000). Additionally, Brunauer–Emmet–Teller (BET) analysis was conducted using Micromeritics  degassed at 80 °C for 24 h in a nitrogen environment (77 K).The FTIR analysis of the synthesized Starch@CPnps was performed using FTIR instruments (Nicolet) in the range of 4000 to 500 cm−1 was attributed to the hydroxyl group’s vibrational mode of the O—H bond, which may originate from water absorbed from the humid environment. An intense peak can be seen in the spectra located between 1479 cm−1. This peak denoted the presence of the carbonate group of calcites [−1 and 874 cm−1 can be seen, respectively, appeared due to O—O stretching vibrations of peroxide. As for starch spectra, a broad peak appeared at 3284 cm−1 which was attributed to the stretching vibrations of O—H groups potentially including hydroxyl groups from water, alcohol, phenol and carboxylic acid.calcites . Moreove−1 represents the hydroxyl group of chemisorbed and/or physisorbed H2O. Peaks at 1413 cm−1 are attributed to the C—H bending and angular deformation of the C—H bond in the starch molecules [−1 can be assigned to the skeleton vibrational mode of glycosidic linkage C—O and C—H stretching vibrations of starch molecules [−1, 1600 cm−1, 1410 cm−1 and 1014 cm−1. Furthermore, a prominent peak can be observed at 1410 cm−1, attributed to the carbonate group (CO32−) in calcites. The peak at 1600 cm−1 appeared due to the presence of hydroxyl group from moisture in the sample. In addition, two absorption peaks at 709 cm−1 and 870 cm−1 appeared to correspond to the O—O stretching vibration of peroxide [Moreover, a small peak at 1635 cmolecules . Furtherperoxide .−1 from Starch@CPnps spectra.The results of FTIR analysis of Starch@CPnps suggest that the interaction between the hydroxyl groups of starch and the surface of the CPnps is likely due to hydrogen bonding, as illustrated in 2 by the Joint Committee on Powder Diffraction Standards (JCPDS-03-0865) and are consistent with the results of previous studies [The XRD patterns of the synthesized Starch@CPnps and CP commercial are shown in  studies ,39. As t studies . The preβ is the FWHM of the XRD peak at the diffraction angle. The average size of Starch@CPnps was determined to be 4.76 nm, calculated using the intense peak at 2θ = 35.8° with a d-spacing of 2.52 Å. The small value of the average sizes for the Starch@CPnps sample could be due to the addition of starch, which prevents the agglomeration of the nanoparticles in the solution.The average particles sizes of Starch@CPnps were calculated using the Debye–Scherer equation, as shown in Equation (7):2 at 390 °C [TGA and its first derivatives (DTG) were utilized to determine the thermal stability of CP commercial, starch and Starch@CPnps, as shown in t 390 °C . The thet 390 °C . The the2 in the synthesized Starch@CPnps was determined by using the stoichiometry of the decomposition reaction given in Equation (8) and the formula outlined in Equation (9) [o is the initial mass of the sample (g). The ratio of 72.08:32 is the molar mass of CP to the eliminated oxygen, and the number of moles of released oxygen for each mole of the sample was assumed to be 0.5. The CP content for the Starch@CPnps sample calculated by the above method was 67.6%, coinciding with the purity determination by permanganate titration (Table 3).Additionally, the amount of CaOtion (9) .2CaO2 →The particle size and distribution of Starch@CPnps and CP commercial were analyzed using dynamic light scattering (DLS). As shown in 2 content from permanganate titration, BET and DLS analysis. The BET analysis was used to compare the specific surface area, pore size and pore volume of Starch@CPnps with CP commercial. For Starch@CPnps, it shows that the average content of calcium peroxide in the product obtained was 72.3%. The CaO2 content of the synthesized Starch@CPnps is consistent with CP commercial, as the CaO2 content of these products, such as 466271 Sigma Aldrich and 21157 Alfa Aesar, are approximately 65–75%. Furthermore, the results show that Starch@CPnps have a larger specific surface area compared to CP commercial. Specific surface area is a measure of the total surface area of nanoparticles per unit mass. A larger specific surface area corresponds to a larger pore size and pore volume for Starch@CPnps compared to CP commercial. The small particle size of Starch @CPnps contributes to the larger surface area, while the varying size of CP particles results in a smaller surface area and a bigger average size. The surface area of a material is a measure of the total area of the surfaces of its particles. As Starch@CPnps has a larger surface area compared to CP commercial, this can be attributed to the application of starch as a stabilizer, which prevents agglomeration of the nanoparticles during the synthesis step. The larger surface area of Starch@CPnps is beneficial to improve the degradation of MB dye performance in a later section.(i)Effect of Initial pH3). (Fe(OH)3) reduces the catalytic activity of the Fe(II) and slows down the oxidation of the MB dye. By maintaining a value of around pH 3, the Fe(II) remains in the solution, and the reaction proceeds at a faster rate. As described in the literature, the oxidation reaction strongly depends on the particle size. The smaller the nanoparticles, the larger the specific surface area, which allows for a faster oxidation reaction [reaction ,44. Figu(ii)Effect of Calcium Peroxide Initial Dosage2 used as a source of •OH. Therefore, the influence of different CaO2 dosage  on the degradation of 20 ppm MB at pH 3 with 0.1 g Fe(II) at room temperature (25 ± 2 °C) was studied. The pH of the MB dye solution was kept at pH 3, as the optimal pH for Fenton oxidation has been determined in the previous section. As illustrated in 2 increased from 0.05 g to 0.2 g. The highest degradation efficiency for both samples  was observed at a sample dosage of 0.6 g. As a result, the optimal initial dosage of CaO2 was determined to be 0.6 g. Research conducted by Tavares et al. [2O2), also plays a role in the formation of •OH. The increase in the dosage of CP is associated with the increase in the concentration of H2O2, which acts as the oxidizing agent in the Fenton reaction. As the concentration of H2O2 increases, the number of •OH radicals generated also increases, resulting in an acceleration rate of reaction for the degradation of the MB dye.The efficiency of the Fenton process, which produces hydroxyl radicals (•OH), is directly affected by the amount of CaOs et al.  has also(iii)Effect of Contact TimeThe results presented in It is essential to study the effect of contact time, as the duration of contact between the oxidant and contaminant is a critical design parameter for the degradation process. By understanding the optimal contact time, capital and operating costs in the industry could be decreased significantly. Additionally, this information can be used to design and optimize treatment processes for the removal of other contaminants in aqueous solutions. Furthermore, the results of this study can be used to develop a more efficient and economical method for the treatment of industrial wastewater.t is the residual concentration of MB dye, Co is the initial concentration of MB dye (20 ppm), and k1 is the rate constant, which can be calculated from the slope of the plot from Equation (10).The data from 2 is the rate constant, which can be calculated from the slope of the plot from Equation (11).The pseudo-second-order equation is represented by the following Equation (11):1 and k2 and their corresponding correlation coefficients R2 are given in 2 for the pseudo-second-order model. The rate constant (k2) increased as the Starch@CPnps dosage increased, with the highest value of 0.0869 M−1min−1. The results indicate that the pseudo-second-order model better describes the degradation of methylene blue (MB) by Starch@CPnps via the Fenton process [The data obtained from the experiments were analysed using two different models, the pseudo-first-order and the pseudo-second-order equation. The results of the analysis are shown in  process .2 and water results in the formation of H2O2. Next, Equation (12) shows the reaction of Fe2+ with H2O2, where Fe2+ acts as a catalyst to break down the weak bond of H2O2 [−OH) and hydroxyl radicals (•OH), which are strong oxidizing agents [As shown in Equation (2), the reaction of CaO of H2O2 . This reEquation 2 shows tg agents . The hydg agents .Fe2+ + 2, H2O and some inorganic ions [The possible degradation pathway of methylene blue (MB) dye by hydroxyl radicals (•OH) is depicted in nic ions .2/g), larger pore size (92.50 nm) and pore volume (1.65 cm3/g). Furthermore, the presence of starch as a stabilizer helped to maintain good aggregation stability, as evidenced by the monodisperse peak and lower PDI value (0.325) of Starch@CPnps. The degradation rate of MB dye by Starch@CPnps in an aqueous solution was also better described by the pseudo-second-order model. This study highlights the potential of using starch as a stabilizer to control the size of nanoparticles and Starch@CPnps as a promising oxidant for wastewater remediation. Further research is required to extend these findings to other contaminants, such as pharmaceuticals and organic pollutants, present in aqueous systems.In this study, the use of starch as a stabilizer to prevent the agglomeration of synthesized Starch@CPnps is explored. This study also presents the first attempt to produce calcium peroxide nanoparticles using calcium oxide as a precursor. The synthesized Starch@CPnps were characterized using various characterization techniques, such as FTIR, XRD, SEM, TGA, BET and DLS. The results showed that compared to CP commercial, the synthesized Starch@CPnps had a smaller average hydrodynamic size (47 ± 2 nm), larger surface area (35.60 m


World Psychiatry, the official journal of the World Psychiatric Association, was founded in the year 2002. From the very beginning, its aims have been: a) to reach as many psychiatrists as possible worldwide, disseminating information on recent significant clinical, service and research developments, using a language that can be assimilated by most of them; b) to give voice to psychiatrists of all regions of the world, encouraging submission of research papers, commentaries and reports on innovative service modalities. The two main criteria by which an article submitted to the journal is evaluated have been from the beginning: a) its relevance to everyday clinical practice of the average psychiatrist; and b) its usefulness to foster the average psychiatrist’s professional growth. From its first issue, the journal has been freely available online. In the year 2008, World Psychiatry received its first impact factor, that was 3.896. On that same year, the publication of the Spanish edition of the journal was started. The impact factor of World Psychiatry has then increased year after year, up to the value of 79.683 reached in July 2022. For the eighth consecutive year, World Psychiatry has been no. 1 in the Clarivate’s category of Psychiatry, and for the fifth consecutive year no. 1 in the entire Clarivate’s Social Science Citation Index. All the issues of the journal are now freely available both on the PubMed system and on the WPA website. The journal reaches now, in its online or printed edition, more than 60,000 mental health professionals worldwide. One of the main factors explaining the success of the journal is the continuing attempt to identify in advance topics which are going to become very visible in the international literature and relevant to ordinary clinical practice. The journal has been recently praised by the World Health Organization for the representation of members from low/middle income countries in its Advisory Board, which was at that time 32.3%, while among the other top ten psychiatric journals it was 1.9%. Furthermore, every issue of the journal includes contributions from all continents.None Declared


The journal is broad-based and publishes articles in diverse disciplines related to molecular biology, as evident from its scope  and various sections . To keep the scope of the journal broad is a conscious decision, as we intend to publish articles from different disciplines and articles that are multi-disciplinary in nature. Recently, we have added ‘Molecular Pathology’ as one of the areas within the scope of the journal to reflect the goal of the journal, which is to publish high-quality papers in diverse disciplines related to molecular biology. The most important factor, from our perspective, is the quality of the work being published. In this regard, the journal continues to evolve and keeps getting better.Current Issues in Molecular Biology (CIMB) (