Anorexia nervosa (AN) is a neuropsychological public health concern with a socially disabling routine and affects a person’s healthy relationship with food. The role of the NNAT (Neuronatin) gene in AN is well established. The impact of mutation at the protein’s post-translational modification (PTM) site has been exclusively associated with the worsening of the protein’s biochemical dynamics.Ki) of structural variants and WT 3D models.To understand the relationship between genotype and phenotype, it is essential to investigate the appropriate molecular stability of protein required for proper biological functioning. In this regard, we investigated the PTM-acetylation site of the NNAT gene in terms of 19 other specific amino acid probabilities in place of wild type (WT) through various in silico algorithms. Based on the highest pathogenic impact computed through the consensus classifier tool, we generated 3 residue-specific  structurally modified 3D models of NNAT. These models were further tested through the AutoDock Vina tool to compute the molecular drug binding affinities and inhibition constant (Ki) were relatively lower in structurally modified models as compared to WT.With trained in silico machine learning algorithms and consensus classifier; the three structural modifications , which were also the most deleterious substitution at the acetylation site of the NNAT gene, showed the highest structural destabilization and decreased molecular flexibility. The validation and quality assessment of the 3D model of these structural modifications and WT were performed. They were further docked with drugs used to manage AN, it was found that the ΔGbind  values and the inhibition constants  at the PTM-acetylation site of the NNAT gene due to possible mutational consequences, will serve as a basis to explore its relationship with the propensity of developing AN.No level of evidence—open access bioinformatics research. Other manifestations of the disease include pronounced weight loss with lower health-related quality of life (HRQoL) [Eating disorders (EDs) are characterized as a neuropsychological public health concern with socially disabling routines and cause an unhealthy relationship with food . Anorexi (HRQoL) . Studies (HRQoL) . The con (HRQoL) . Accordi (HRQoL) .By far, significant progress has not been observed in establishing the molecular basis of AN in humans, to identify any gene-level mutation or loss at post-translational modifications site (PTMs) that confers disease risk, remaining elusive , 7. PTMsPTMs in proteins not only influence secondary structural level changes, but also have a significant impact on the protein's tertiary level, which in turn influences the protein's biochemical and physiological behavior , 9. In aGermline genetic variations located in the coding region (missense rare-coding single nucleotide polymorphisms ‘SNPs’) of genes have been significantly associated with complex traits or pathogenicity, like type 2 diabetes, cancer, cardiovascular diseases, etc. . It is w. reported that any variation in gene expression status or any dysregulation in the  brain-specific NNAT leads to the development of AN [The gene(s) level association and etiology of AN remain uncertain while several kinds of research has been conducted to probe this condition genetically. Recently, the Neuronatin (NNAT) gene was reported to be associated with health and disease conditions . For insnt of AN . Extendint of AN . In 2022nt of AN .Ki) constant with the therapeutic compounds of AN. Using the molecular drug binding energies that we had initially obtained, the significant role of PTM site and their associated structural modifications were considered to predict the impact of structural modifications on drug interaction at the NNAT gene’s PTM acetylated site.In this study, we investigate the impact of structural modifications at NNAT’s PTM-acetylation site (K59) located in the cytoplasmic domain. We also predict the impact of other amino acids substituted instead of LYS at the PTM-acetylation site (59th) position on the functional stability of the protein as well as the computation of pathogenicity scores. Individually, the wild-type (WT) and the most pathogenic 3D-models obtained through residue-specific substitution (of NNAT gene) having the most pathogenic scores with prominent structural modifications at the PTM-acetylation site were investigated in terms of in silico molecular drug-binding affinities and estimation of inhibition . Information regarding cytogenic location, HGNC-approved gene symbol, GenBank accession detail, gene identifier, and other information was extracted from OMIM  database repository for comprehensive information on human genes and genetic phenotypes with their relationships. The protein-level information was accessed through the protein accession number and UniProtKB database (https://www.uniprot.org/help/uniprotkb).The publically available genomic data on the human NNAT gene were collected from the Gene database of the NCBI  website (Expasy ProtParam tool (https://web.expasy.org/protparam/). These parameters included the amino acid composition, molecular weight, atomic composition, theoretical pI, extinction coefficient, estimated half-life, instability index, aliphatic index, and grand average of hydropathicity (GRAVY). The prediction of the PTM acetylation site was investigated with the aid of deep learning MusiteDeep web server (https://www.musite.net) [The sequence-based computation of several chemical and physical parameters for the NNAT protein was done through ite.net) .th position) of the NNAT gene based on protein secondary structure, surface accessibility, percent disordered residue, torsional angles, i.e., phi (ϕ) psi (ψ) were computed from NetSurfP-2.0 web server  of Technical University of Denmark (DTU) [http://cupsat.tu-bs.de/) was applied. This tool obtained transformation in the specific atom(s) potential and torsion angle potential in terms of ΔΔG  [https://www3.cmbi.umcn.nl/hope/) web-server was used [To investigate the impact of the substitution of amino acid at the PTM-acetylation site (59rk (DTU) . To invecal/mol) . This sewas used . This towas used .https://inpsmd.biocomp.unbito.it [To predict the free energy difference causing overall structural destabilization at the PTM-acetylation site, different machine learning strategies were computed. These were originally used to investigate the impact of mutations on overall protein stability and its 3D function. The first approach was the MUpro machine learning program, used through SVM (Support Vector Machines) and NN  . The secnbito.it . Anothernbito.it . SDM . This web-server tool was used to investigate the effects of SNPs/structural substitution leading to any significant change in protein function.To further investigate and validate the expected accuracy of possibly deleterious structural modifications due to the substitution of different amino acids at the PTM-acetylation site, the PredictSNP1.0 consensus classifier predictor approach was used   level, aAfter the identification of the PTM acetylation (LYS) residue/site at the 59th position, the remaining 19 3D models having a residue-specific substitution at the 59th position were constructed through the UCSF Chimera visualization program .Ki) of WT and the structurally modified model we used a linear regression model in which we set Ki values as the dependent variable because of its ΔG dependent computation, and ΔG was the independent variable through online web-server of https://www.graphpad.com/quickcalcs/ and https://www.statskingdom.com/index.html.After a thorough literature search from the DrugBank database, the 2D structures of the drugs used to manage AN were downloaded from the PubChem database. The obtained 2D compound format was converted into a 3D PDB format through the Open Babel tool . The propI of 10.17. The highest  composition of alanine and arginine was observed while lysine was 1.2%, i.e., only one LYS at 59th position. The total number of negatively charged (D + E) residues were 4 and positively charged residues were (R + K) 10. The atomic composition of NNAT protein showed carbon (C = 424), hydrogen (H = 662), nitrogen (N = 118), oxygen (O = 108), and sulphur (S = 3) with a total number of 1315 atoms. The extinction coefficient was 17,085 M−1 cm−1, at 280 nm measured in H2O, when absorbance 0.1% (= 1 g/l) 1.850, assuming all pairs of cysteine residues form cysteine. The extinction coefficient was 16,960 M−1 cm−1, when absorbance 0.1% (= 1 g/l) 1.836, assuming all pairs of cysteine residues are reduced.The estimated molecular weight of NNAT was 9236.83 Dalton with a theoretical Escherichia coli, in vitro) with an aliphatic index of 100. The grand average of the hydropathicity index (GRAVY) is 0.217. The predicted trans-membrane helix (TMH) was 1, which started with the 13th ILE and ends at the 35th GLY, which showed the expected number of residues in TMH was 22.4976.The N-terminal of the sequence is methionine (M) and the estimated half-life is 30 h , > 20 h , > 10 h  reported stabilities in function for I-Mutant and MUpro ∆∆G  energies. However, LEU and ILE were the only two residues which were showing the stabilities of protein functions computed through Deep-DDG and INSPS tools. Through SDM approach, the energies and the other related parameters for computing the impact of protein stability upon residue-specific structural modifications showed approximately 11 residues  with a prominent reduction in structural conformation stability , 0.9598 (Chi1 = − 30.8 and Chi2 = 40.1), and 0.240 (Chi1 = 179.4 and Chi2 = 85.8), respectively.With the aid of the QUARK algorithm, five WT models were built according to rank and the best 3D model of NNAT-WT was selected based on the Ramachandran plot and quality factor analyses. After the selection and assessment of the WT model of NNAT protein, residue-specific substitution was employed through the UCSF Chimera tool for building three structural modifications at the PTM acetylation site (K59) residue. The first 3D-structural modification was the substitution of lysine (K59D) with aspartic acid followed by a proline (K59P) and tryptophan (K59W), respectively. The best 3D-models selected for K59D, K59P, and K59W structural modifications had probability scores of 0.4638  was overall 100, with > 92.9% residues in the most favored region of the Ramachandran plot. The significant outcome related to structural validation observed that there was no single residue existing in the generously and disallowed region of all four 3D models, which were constructed for further investigation. The investigation of the molecular interactions of all four homology models  of NNAT with desipramine, preferred based on the lowest ΔG values  was done using 2D plots to explore the non-covalent interactions and hydrogen bond formation status  and the lowest decrease in ΔG of 22% was observed in citalopram  was performed with the 3D models of five therapeutic drugs used in the management of AN. The NNAT WT model exhibited less lower free energy (ΔG) values when compared with the other three structurally modified 3D models  (see Table Ki) for all four 3D-models  of protein–drug interactions were computed and found to be higher in the 3D-WT model of NNAT  values were estimated in all three models of  which indicate the high binding affinities of AN drugs with the protein  which means that 83.2% of the variability of Ki is explained by ΔG. Shapiro  which assumed that the data are normally distributed and correlation (R) equals − 0.912 . Shapiro–Wilk (p = 0.05572) test showed that the data are normally distributed and correlation (R) equals − 0.7858 , which means that the correlation (R) equals − 0.6699. Shapiro (p = 0.07499) test showed that the data are normally distributed and correlation (R) equals − 0.6699 , which means that the correlation (R) equals − 0.8448. Shapiro (p = 0.1742) test showed that the data are normally distributed  that lack stability in secondary or tertiary structures, ultimately impacting the normal structural basis of interactions . These PSeveral examples of PTM process actively participating in various cell activities. In signaling, for instance, kinase cascades are switched on and off by the reversible addition and removal of phosphate groups . AdditioKi). The docking output exhibited significant ΔG  values with Desipramine as well as much reduced inhibition constants (Ki) in three variant structural models, which may be interpreted as the lower the Ki, the higher the drug binding, compared to wild type. These larger variations in ΔG and Ki values serve as the most interesting attributes of structural variation at the PTM acetylation site of the NNAT gene, which in general enhances the drug-binding potential of NNAT’s variants.PTMs can also be present at interaction interfaces and can affect how proteins bind to one another . MoleculIn this work, the AN-associated human gene ‘NNAT’ was investigated to predict the impact of structural modifications at NNAT’s PTM-acetylation site (K59) through other amino acid substitutions instead of LYS. The PTM-acetylation site of this gene was already reported for its commonest molecular interactions/involvement when experiments were conducted with different drugs (as ligands) used to manage AN. Moreover, we computed the functional stability and increase or decrease in molecular flexibility of the NNAT protein with the wild type and structurally modified showing the possibilities of other amino acid substitutions through the computation of pathogenicity scores by various in silico machine learning algorithms.Ki) constants with the therapeutic compounds of AN. The main strength of this work is the computation of the lowest Ki constant in structurally modified models  as compared to the wild type, which showed that any future variation in the NNAT gene’s PTM-acetylation site in terms of the above-mentioned residues has the highest binding tendency with AN drugs. Thus, it may represent the tight binding of drug–protein interaction, thereby serving as the structural and functional basis for the propensity of AN associated with the NNAT gene. Therefore, these structural modifications at the PTM-acetylation site of the NNAT gene will be considered as a potential target to predict the impact of structural modifications on drug interaction in therapeutic intervening targets for the management of AN.Through consensus classifier-based estimation of the expected accuracy of modified structural models (at the 59th position), we found the three most pathogenic substitutions  with the highest pathogenic scores. We built wild-type and these three residue-specific substitution models and investigated them in terms of in silico molecular drug-binding affinities as well as inhibition  interactions with a mutant NNAT model (C30Y), with the most common interactions observed at the PTM-acetylation site.bind  and inhibition constants (Ki) compared to the wild type.In this study, the role of structural modifications on the PTM-acetylation site (59th position) of the NNAT gene was investigated. With the aid of other 19 residue-specific structural possibilities at the PTM-acetylation site, the effect of residue substitution on protein dynamics and the decrease in molecular flexibility with structural destabilization were reported. Interestingly, three residue modifications, i.e., K59D, K59P, and K59W, were found to be the most deleterious substitutions at the acetylation site of the NNAT gene. The 3D models of these structural modifications can markedly reduce the ΔG


The mechanical properties of ice in cold regions are significantly affected by the variation in temperature. The existing methods to determine ice properties commonly rely on one-off and destructive compression and strength experiments, which are unable to acquire the varying properties of ice due to temperature variations. To this end, an embedded ultrasonic system is proposed to inspect the mechanical properties of ice in an online and real-time mode. With this system, ultrasonic experiments are conducted to testify to the validity of the system in continuously inspecting the mechanical properties of ice and, in particular, to verify its capabilities to obtain ice properties for various temperature conditions. As an extension of the experiment, an associated refined numerical model is elaborated by mimicking the number, size, and agglomeration of bubbles using a stochastic distribution. This system can continuously record the wave propagation velocity in the ice, giving rise to ice properties through the intrinsic mechanics relationship. In addition, this model facilitates having insights into the effect of properties, e.g., porosity, on ice properties. The proposed embedded ultrasonic system largely outperforms the existing methods to obtain ice properties, holding promise for developing online and real-time monitoring techniques to assess the ice condition closely related to structures in cold regions. In recent decades, research on ice has grown remarkably. Intensive research is being performed on whether to examine global climate change ,2,3, to Currently, diverse measurement methods of ice mechanical properties have been developed in an experimental way, including uniaxial compression ,10,11, tThe ultrasonic technique is one of the most commonly used non-destructive methods in characterizations of material properties ,17, deriIn addition to experimental testing methods, numerical simulation is a valuable alternative method for estimating the ice properties by taking advantage of wave propagation simulation techniques ,31,32,33From the surveyed literature, it is observed that the current prevalent methods to determine ice properties commonly rely on one-off and destructive compression and strength tests, which are incapable of acquiring the temperature variation-induced changes in ice properties. Moreover, ultrasonic technology, as one of the most commonly used non-destructive methods for characterising material properties, is rarely applied to ice mechanical properties. In addition, due to the unique nature of ice materials, it is necessary to study how ultrasonic sensors can be embedded in ice. Furthermore, there is a lack of numerical models for wave propagation in ice with different temperatures and porosities. To address these issues, an embedded ultrasound system is proposed to test the mechanical properties of ice, and its feasibility and effectiveness have been verified through ultrasound experiments and numerical models.The rest of this paper is organised as follows: The current prevalent methods to acquire the mechanical properties of ice are typically uniaxial compression, triaxial compression, and flexural strength experiments. However, due to the brittleness of the ice material itself, fracture is inevitable in the experiment. Moreover, the time between the testing starting and the fracture ending is very short. Therefore, in a single experiment, it is not possible to obtain changes in ice properties caused by continuous temperature changes. To address the deficiencies of existing methods, an embedded ultrasonic system is built as an alternative to compression tests to obtain the mechanical properties of ice at different temperatures.Piezoelectric material can be used as both actuators and transducers, which is beneficial for its direct and inverse piezoelectric effects . Figure (1)Ice specimen3. Before freezing, all the required sensors during the ultrasonic tests are fixed in the middle of the mould with steel wires, as shown in The ice specimen is fabricated using distilled water with the purpose of avoiding excessive impurities. The dimensions of the ice specimen are 150 × 150 × 200 mmThe process for making ice samples is as follows: first, place the mould with distilled water and sensors into a refrigerator with an initial temperature of −5 °C; second, when the surface water is frozen, progressively decrease the temperature of the refrigerator by 5 °C per two hours; next, when the refrigerator temperature reaches −35 °C, the ice specimen should be fully made; and finally, the newly-made ice specimen needs to be stored in a refrigerator at −35 °C for at least 48 h to ensure a uniform temperature distribution in the ice specimen. In this way, the ice cracks caused by big temperature variations could be avoided.(2)Sensing strategyThe PZTs and temperature sensor are set in the middle of the ice specimen. The distance between the two PZTs is considered to be 70 mm. Additionally, the temperature sensor is set at the uniform level of the PZTs due to the effect of temperature stratification in ice.(3)ConsiderationsPreliminary tests with a distance between the two PZTs are conducted to determine the appropriate properties. Comparing the results at 25 mm, 50 mm, and 70 mm, it is found that when the distance between the two PZTs is small, the wave packets of the longitudinal wave and the shear wave cannot be distinguished. The reason is that the propagation speed of the wave is very fast. When the shear wave propagates, the longitudinal wave has not been fully received, which causes the longitudinal wave and shear wave to be superimposed on each other, so it is difficult to distinguish a separate shear wave packet.Wave velocity, one of the key properties of wave propagation research, is defined as the velocity at which a disturbance propagates in specified materials. It mainly depends on the material properties, structural geometries, and external excitations. The longitudinal and shear wave velocities are the most widely used variables in ultrasonic-structural analysis. Their relationships with structural properties are formulated as follows:E, G, and μ) can be achieved with the measured longitudinal and shear wave velocities (lV and sV) (shown in Equations (3)–(6)). These relationships, which are the fundamentals of the characterizations of the ice properties, can be written as follows:ρ is the density, E is Young’s modulus, μ is Poisson’s ratio, and lV and sV represent the velocity of the longitudinal wave and the shear wave, respectively.According to Equations (1) and (2), the material properties (such as (1)Test processThe experimental apparatus for the ultrasonic test is presented in A is the amplitude, n denotes the number of signal cycles, and cf represents the central frequency.The excitation part includes the wave generator and desktop. Firstly, the waveform of excitation is generated on the desktop. Then, a tone burst signal, consisting of sinusoids modulated by the Hanning window , is utilThe designated excitation is then transferred into the Agilent 33250A arbitrary wave generator, which converts the excitation from a digital signal to an analogue one. The output terminal of the waveform generator is connected to the PZT through a Bayonet Nut Connector cable. Because of the positive piezoelectric effect, the PZT deforms in the longitudinal direction of the ice, leading to the generation of longitudinal waves. The output voltage of the waveform generator, which regulates the excitation amplitude, is set to be 10 V in order to ensure a fully deformed piezoelectric ceramic sheet.In the receiving part, the PZT transducer generates current due to the inverse piezoelectric effect. Based on the characteristics of PZT, this generated current has a linear relationship with its deformation. Thus, the captured current from the receiver can be regarded as the propagated longitudinal wave in the ice. This received current is then amplified by a fixed-gain universal preamplifier, PXPA3, to increase its amplitude. The transfer gain of the charge amplifier is 10 mv/pc. Then the current is introduced into the Agilent DSO7034B oscilloscope to be converted into a digital signal. The sampling frequency of the oscilloscope is set to 50 MHz. In particular, the application of the waterproof glue on the surface of PZT not only makes the sensor insulated but also prevents the generated current from leaking into the ice. In addition, there is no extra circuit other than the experimental equipment. Therefore, the measured current from the receiver thoroughly originates from the inverse piezoelectric effect caused by the longitudinal wave.During the ultrasonic test, the ice specimen is covered with a foam box, which is a common thermal insulation material in daily life and is used to slow down the impact of external temperature on water, thus slowing down the speed of water icing. If the freezing speed is too fast, it can cause the ice surface to expand and crack. Cracking ice will badly affect the experimental results. The internal temperature is monitored in real-time through the temperature sensor. By continuously recording these internal temperatures and the corresponding received signals, the non-destructive monitoring of wave propagation in ice under the condition of temperature variation is realised.(2)Determination of signal propertiesn and fc) on the right-hand side of Equation (7) need to be determined in advance. Preliminary tests with different n and fc are conducted to determine the appropriate properties. The measured ultrasonic signals with different n and fc are shown in Two properties  than in cases of having a larger number of cycles .In the preliminary test, the response signal results of 2 periods, 3 periods, 4 periods, and 5 periods are compared and analysed. The experimental results in cf = 250 kHz, 300 kHz, 350 kHz, 400 kHz, 450 kHz, and 500 kHz) than in cases of having smaller central frequencies (cf = 150 kHz and 200 kHz). On the other hand, the results in Accordingly, a normalised 2-cycle 250 kHz tone burst signal shown in  is emploThe mode reflection/conversion is inevitable at the external and internal boundaries of the ice specimen, contributing to a complex multi-mode wave signal. Moreover, the measured signals could be adversely affected by environmental noise. Therefore, it is necessary to rectify the measured signals to extract the inherent characteristics of the interested signal rather than those induced by mode reflection/conversion and noise. In this study, a wavelet transform-based threshold denoising process is adopted, with the results presented in Considering the faster propagation of the longitudinal wave compared with the shear wave, the first and second peaks of the ultrasonic waveform can be regarded as the longitudinal wave and the shear wave, respectively. 3, which is the average value determined by the drainage method [In the experiments, the density of the utilised ice specimen was 890 kg/me method ,46,47. CIn nature, ice contains pores, which are related to the growth process of ice. The formation of ice from water is a process from the outside to the inside. After the surface freezes, the air in the water cannot pass through the ice, forming pores inside the ice. These pores vary in size and are randomly located, so randomly distributed circular pores are used in the manuscript to simulate the pores inside the ice. The dimension, distribution, and amount of the entrapped air bubbles highly affect the dynamic mechanical properties of ice. Hou et al.  indictedIn order to better compare the numerical and experimental results, four sets of experimental results were selected as the model material’s mechanical properties. The specific values are shown in 2, and the pores (air bubbles) are concentrated within a central region of 180 × 180 mm2. Additionally, the round pores in the 2D model are utilised. Before establishing the model, we observed and measured a large number of pores in natural and artificial ice. These pores, except for those larger than 5 mm on the surface of the ice, are very small in size inside the ice, some of which cannot be measured using conventional measurement methods. In order to restore the uniformly distributed pores accumulated in the ice, the porosity during simulation was fixed, the distribution was selected from the range of most pore sizes, and the appropriate pore distribution was calculated using MATLAB R2018a. They are classified into small pores having diameters of 0.5–1 mm and large pores having diameters of 1–1.5 mm, with the volume ratios being 6:4. This volume ratio was obtained through extensive testing, which not only meets the requirements of achieving porosity within the model but also achieves a uniform distribution of pores within the model. Moreover, the pores in the ice model are reciprocally independent, with distances between the pores greater than 1.5 mm. In the modelling process, random pores are first generated using MATLAB R2018a, and then the generated pore model is imported into the ice model built in ABAQUS 6.14. The final model is obtained by cutting out random pores from the original ice model. In the model, the excitation of the PZT actuator is simplified by applying a concentrated force at the same position as the PZT sensor [In the numerical model, ice is treated as a linear solid without considering its nonlinear behaviour or tensile or compressive damage. The dimensions of the tested specimens are 210 × 210 mmT sensor . The conThe porosity is obtained using the calculation method of Cox and Weeks . The spe3) is described as a function of temperature as [The density of pure ice ature as :(11)ρiTiIn the established numerical model, the density of the ice sample obtained from the experiment is employed to calculate the porosity at different temperatures following Equations (10)–(12).−8 s. These small computational properties can ensure the accurate capture of the propagative behaviour of the ultrasonic wave.Three 2D ice models shown in  with difThe waveforms received by the response point at four temperatures are extracted, and the drawn waveform is shown in With the application of ice properties from experiment tests, the numerical results of longitudinal and shear wave velocities at different temperatures can be obtained, as shown in To reveal the existence of pores on the wave propagation in ice, this section compares the numerical results attained by a non-porous ice model and a model with 3% porosity. The result of −17.2 °C is randomly selected to demonstrate the process of wave propagation in ice in numerical simulations. Of course, other temperature results can also be selected for display. The selection of different temperatures has no effect on the propagation process of waves in ice. The comparison results of wave propagations are depicted in 3, and the pores are concentrated within a central cuboid range of 140 × 140 × 45 mm3. Similar to the 2D model, the random pores in the 3D model are spheres, which are classified into the small size with diameters of 0.5–1 mm and the large size with diameters of 1–1.5 mm. The ratio of small and large pores is 6:4. Each pair of pores has a distance larger than 3 mm. Additionally, the porosity of the 3D model can be designated in accordance with the porosity of the 2D model (shown in Equations (10)–(12)). Three 3D ice models with porosities of 0.5%, 1%, and 3% are counted below.In this section, the 3D random pore ice model is built by expanding the 2D model. The dimensions of the investigated 3D model are 150 × 150 × 50 mmThe coordinates of the centre and the diameter of the pores are randomly generated. When the diameter rotates 360 degrees around the centre, a spherical pore is developed. All pores of the entire model are shown in −8 s. The grid map is shown in The excitation signal in the 3D model adopts the waveform signal of The mechanical properties of ice at various temperatures obtained from the experiment are input into the 3D numerical model as the material properties, and the shear wave together with the longitudinal wave velocities at different temperatures can be obtained. Finally, all wave velocities are plotted as a scatter diagram, as shown in Four groups of data are selected from all these numerical outcomes. The waveforms of wave propagation in ice at these four temperatures are shown in This part investigates the influence of porosity on wave propagation in ice using a 3D model. The normalised waveforms at different porosities are shown in This section compares the numerical and experimental results to explicitly verify the reliability of the established 2D and 3D numerical ice models. Taking the case of temperature −17.2 °C as an example, the corresponding numerical and experimental results are presented in (1)With the artificial ice specimen made of distilled water, the experiment results indicate the velocities of wave propagation in the ice decrease gradually with the elevated temperatures. Moreover, the velocity of the longitudinal wave is within the range of 3954.8–3787.88 m/s, while the velocity of the shear wave is within the range of 1831.54–1797.64 m/s;(2)The experimentally obtained wave velocities have been brought into known formulas to calculate the material properties of ice at different temperatures, including Young’s module, Poisson’s ratio, shear modulus, and bulk modulus. The results have shown that the values of the four properties have a downward trend with the increase in temperature;(3)With the help of the numerical models, the wave propagation in ice has been investigated, and the influence of varying temperatures on the wave propagation has been discussed in detail. The relative errors are within the range of 0.15–5.7% according to the comparison of numerical and experimental results, which proves the validity of the experimental results and reasonability of the calculated ice mechanics properties;(4)By comparing the waveform diagrams of the non-porous model and different porosity models, it can be found that the porosity affects the wave propagation velocity. By which, the greater the porosity, the slower the wave propagation velocity;(5)This research proves that the random pore model can simulate ice well. Additionally, by modifying the properties of the input model, more different ice models at different temperatures can be obtained, which provides a reliable modelling method for later research on ice. In this study, a sophisticated embedded ultrasonic system is proposed to inspect the mechanical properties of ice in real time and online. This embedded ultrasonic system provides a platform to continuously obtain the response of the ice. With this system, the ice properties under specific temperature conditions are identified based on the intrinsic relationships between the wave propagation velocities and the mechanical properties of ice. Furthermore, the feasibility and effectiveness of the proposed embedded ultrasonic system-based method are validated via ultrasonic experiments and numerical simulations. Both numerical and experimental results demonstrate the effectiveness of the proposed embedded ultrasonic system-based method to inspect the mechanical properties of ice. The conclusions can be summarised as follows:


E pluribus unum , to enable high subzero ice nucleation temperatures by assembly of ice-nucleating proteins into large functional aggregates.Organisms have evolved efficient molecular strategies to control the nucleation and growth of ice. Although these strategies have developed independently across biological kingdoms, they all seem to use proteins to construct extended functional domains. While for bacteria, the use of large proteinaceous units to build superior ice-making complexes is established, the identity of fungal INs remains unknown. Here, we demonstrate that small extracellular proteins, of which over a hundred are capable of assembling in cell-free environments, make up the fungal INs that enable ice formation at warm temperatures. Our findings highlight that nature uses a common strategy,  Fusarium acuminatum. We find ice-binding and ice-shaping activity of Fusarium IN, suggesting a potential connection between ice growth promotion and inhibition. We demonstrate that fungal INs are composed of small 5.3 kDa protein subunits that assemble into ice-nucleating complexes that can contain more than 100 subunits. Fusarium INs retain high ice-nucleation activity even when only the ~12 kDa fraction of size-excluded proteins are initially present, suggesting robust pathways for their functional aggregation in cell-free aqueous environments. We conclude that the use of small proteins to build large assemblies is a common strategy among organisms to create potent biological INs.Biological ice nucleation plays a key role in the survival of cold-adapted organisms. Several species of bacteria, fungi, and insects produce ice nucleators (INs) that enable ice formation at temperatures above −10 °C. Bacteria and fungi produce particularly potent INs that can promote water crystallization above −5 °C. Bacterial INs consist of extended protein units that aggregate to achieve superior functionality. Despite decades of research, the nature and identity of fungal INs remain elusive. Here, we combine ice nucleation measurements, physicochemical characterization, numerical modeling, and nucleation theory to shed light on the size and nature of the INs from the fungus  The crystallization of water is the most prevalent liquid-to-solid phase transition on Earth. Ice formation is thermodynamically favored at temperatures below 0 °C, but the crystallization process is kinetically hindered by the cost of the ice nucleus interface. Consequently, pure water microdroplets can be supercooled to temperatures as low as −46 °C, below which homogenous ice nucleation seems to be unavoidable . In natuPseudomonas, Pantoea, and Xanthomonas, which enable ice formation at temperatures close to 0 °C   –13. The e fungus , 10. Alte fungus , 14. Bote fungus –18.Fusarium INs are cell-free secreted soluble macromolecules that are stable at pH values from 2 to 12 (Fusarium INs to be <100 kDa based on molecular weight cutoff (MWCO) filtration experiments . The results are combined using Vali’s equation into a single freezing curve of F. acuminatum, shown in mN represents the total number of active INs above a certain temperature (Nm(T), indicate the presence of highly efficient INs, consistent with previous studies . The freezing curve of the ice-affinity purified INs looks similar to that of the aqueous Fusarium extract, with a slight decrease in the total number of INs . It is worth mentioning that high β-sheet contents were also found in INPro derived from bacteria  obtained from dilution series of three independent experiments with aqueous extracts from individual fungal cultures. To obtain the distribution of heterogeneous ice nucleation temperatures of the fungal INs, we extracted the differential freezing spectrum nm(T) from each experimental cumulative freezing spectrum Nm(T) using the heterogeneous underlying-based (HUB) backward code (Nm(T) data, as shown in Fusarium sample is a linear combination of Gaussian subpopulations. The mean square error (MSE) between the experimental and predicted Nm(T) decreases from ~15 to 1% as the number of subpopulations increases from one to three . The differential spectra nm(T) (Nm (T) of SI Appendix, Table S1). The comparable contribution and overlap of these subpopulations imply an almost continuum distribution of IN sizes. This suggests that the subpopulation of more potent IN dominates the freezing of water by the organism in its natural environment.ard code . The codra nm(T) B that beSI Appendix, Fig. S8 shows that consecutive freeze–thaw cycles of the same sample have only minor impacts on the ice nucleation ability of IN from F. acuminatum and the corresponding freezing spectrum. In contrast to fungal INs, repetitive freeze–thaw cycles alter the freezing spectra of bacterial INs, and the activity of their most active INs is significantly reduced , 187 nm2 (Thet = −6.8 °C), and 53 nm2 (Thet = −11 °C) . We emphasize that these areas are the minimal ones required to nucleate ice at the corresponding temperatures, and match those of squares with sides 17, 13.7, and 7.3 nm, respectively. For reference, the narrower rectangular surface that nucleates ice at −6.8 Å has a width of 8.4 nm and a length of ~45 nm, resulting in about twice the area of the 13.7 × 13.7 nm2 surface that promotes ice nucleation at that temperature. Below we use the estimated square IN areas to provide lower bounds of the number of protein monomers involved in the ice-nucleating particles produced by F. acuminatum.To interpret the position of the peaks in the differential spectrum surfaces . The calsurfaces . We firsperature . The preF. acuminatum is consistent with the results of filtration experiments that showed Nm to be unchanged by filters with nominal cutoff down to 100 nm, minimally impacted by filters with nominal cutoff at ~9 nm (300 kDa) and strongly impacted by filters with smaller pores   . HoweverFusarium INs. Fusarium INs in 50 mM sodium phosphate in 0.3 M NaCl buffer (pH 7.0). The elution profile of the Fusarium samples showed prominent peaks at ~5.20, ~7.40, ~10.98, and ~12.40 min, and a smaller peak at ~13.5 min , gel electrophoresis, and matrix-assisted laser desorption/ionization-time-of-flight (MALDI-TOF) mass spectrometry of the ice-affinity purified 13.5 min C. Based Fusarium fractions retain their ice nucleation activity at low supercooling . The IN peaks for the 660 kDa fraction  overlap with the two warmer IN peaks obtained from the whole sample (−6.8 and −5.3 °C), while clearly lacking the population of less active nucleants (around −11 °C) obtained from the whole Fusarium extract. On the other hand, the three IN peaks obtained from the 12 kDa sample  encompass those found in the two less efficient peaks of the whole sample, while lacking the most potent IN population around −5 °C. These results strongly suggest that even when small subunits are initially present, there exists a robust mechanism for them to reassemble into larger INs. Without a reassembly mechanism, the experimentally observed activity of the ~12 kDA SEC fraction at higher temperatures would not be possible (We find that both large (~660 kDa) and small (~12 kDa) SEC possible C.F. acuminatum and SDS-PAGE gel electrophoresis (Fusarium IN. The amino acid content showed high contents of aspartic (15%) and glutamic acids (19%) (acid or amide form) as well as of threonine (10%) and serine (8%) . A globular protein of ~10 kDa would have a molecular diameter of ~2.8 nm . The much warmer nucleation temperatures obtained with the 12 kDa SEC fraction  evince that Fusarium INs consist of small protein units that assemble into larger complexes in solution.The presence of small subunits with an estimated weight below 10 kDa is supported by MALDI spectra of ice-affinity purified solutions of phoresis B. The MA ~2.8 nm  and nuclF. acuminatum through a combination of experiments, nucleation theory, and modeling results. If we assume that the 5.3 kDa monomer is the smallest unit and it has a globular fold, then its radius would be ~1.1 nm . A functional assembly of at least 150 5.3 kDa units would be required to tile the minimal IN surface that nucleates ice at −4 °C, ~100 to nucleate at −5 °C, ~50 at −6.8 °C, and ~16 at −11 °C . This range of aggregate sizes is consistent with those observed in the size exclusion chromatography of the ice-affinity purified solutions , suggesting the existence of robust mechanisms for their efficient reassembly in cell-free aqueous environments.We combine physicochemical characterizations of ice-affinity purified P. syringae display functional INPro aggregates in their outer membrane that can nucleate ice at high onset temperatures . Growth occurred at room temperature for one week and then at 6 °C for about four weeks. Pure water was obtained from Millipore Milli-Q® Integral 3 water purification system , autoclaved at 121 °C for 15 min, and filtered through a 0.1 µm bottle top filtration unit . For the droplet freezing experiments, aqueous extracts of fungal mycelium were prepared as described previously with the following modifications , and the success of the purification was checked by determining the ice nucleation activity of the ice-affinity purified Fusarium samples using TINA measurements and by gel electrophoresis . The ice-affinity purified solution was used for SEC experiments and to obtain MALDI, SDS-PAGE, and CD spectra.Rotary ice-shell and ice-slide purification was used to purify the ice-nucleating macromolecules of the crude fungal extract. Details of the purification method have been described elsewhere , 46. In The ice-affinity purified extract was lyophilized and dissolved in water. The protein in the clear solution (~4 mg/mL) was analyzed by HPLC using a G2000SWXL TSK gel column (7.6 mm × 30 cm). The elution buffer was 0.05 M sodium phosphate in 0.3 M NaCl, pH 7.0. The flow rate was 1 mL/min, with absorbance recorded at 220 or 280 nm.Aliquots of the ice-affinity purified extracts were mixed with a fifth volume of 6x Laemmli buffer containing 5% of β-Mercaptoethanol and were heated at 95 °C for 5 min. Samples were loaded onto a MiniPROTEAN® TGX™ Stain-free Precast Protein Gel  next to a molecular weight marker . The electrophoresis setting was a constant voltage of 175 V for 40 min. Image acquisition of the gel was performed using a ChemiDoc MP Imaging system and the Image Lab software .fice) and the counting error were used to calculate the cumulative number of IN (Nm) with the associated error using Vali’s formula and Gaussian error propagation (Ice nucleation experiments were performed using the high-throughput Twin-plate Ice Nucleation Assay (TINA), which has been described in detail elsewhere . In a typagation . All exppagation .CD spectra of the ice-affinity purified extracts were recorded at a 1 nm interval from 260 to 180 nm using a Jasco J-1500 spectrometer. CD measurements were performed in a rectangular cell with the optical path of 0.1 cm. CD measurements were taken at 90 °C or room temperature, and the equilibration time for every sample before each set of measurements was 15 min. All spectra were background subtracted and processed using the Spectra Manager Analysis program from JASCO.MALDI measurements were carried out on a rapifleXTM MALDI-TOF/TOF mass spectrometer from Bruker Daltonik GmbH. The instrument is equipped with a scanning smartbeam 3D 10 kHz Nd:YAG laser at a wavelength of 355 nm and a 10-bit 5 GHz digitizer. The acceleration voltage was set to 20 kV and the mass spectra were recorded in positive ion mode. Calibration was done with the Bruker peptide mix and the Bruker protein calibration standard I and II in a mass range of up to 70 kDa. Sample preparation was done by mixing a saturated solution of sinapinic acid dissolved in water/acetonitrile  with an aqueous solution of the analyte in equal amounts. Aliquots of the ice-affinity purified extracts were measured with random walk ionization across the sample spot. Typically, 8,000 shots were averaged per spectrum.Fusarium extract concentration of ~10 mg/mL in water using a Clifton Nanoliter Osmometer (Ice shaping was determined at a smometer . Ice shaNm(T). The output of the HUB-backward is the differential spectrum nm(T) in terms of the distribution of subpopulations of INs that reproduce the cumulative freezing spectrum Nm(T) of Fusarium.We used the HUB-backward stochastic optimization code to extract the distribution of heterogeneous ice nucleation temperatures from the experimental cumulative nucleation spectra . The HUBD, the difference in chemical potential between liquid and ice ∆μ, and the ice–liquid surface tension γice-liquid Click here for additional data file.


P = 0.042 and 54.7% vs. 35.9%, P = 0.033, respectively). Misplacement screws  occurred more often in the FH group than in the SPC guide group . The incidence of proximal facet joint violation (FJV) was higher in the FH group than in the SPC group . The radiation dose and time in the SPC guide group were comparable to those in the FH group (P = 0.063 and P = 0.078). The average operative time was significantly longer in the SPC guide group than in the FH group . Other clinical parameters, such as the average bone mineral density (BMD), intraoperative blood loss, and postoperative hospital stay, were not significantly different. Oswestry disability index (ODI) and back pain visual analogue scale (VAS) scores were significantly improved in both groups compared with preoperatively. SPC guided screw placement was more accurate than the fluoroscopy-assisted FH technique for single-level MIDLF at L4/5. Patients undergoing SPC-guided screw placement can achieve similar clinical outcomes as the fluoroscopy-assisted FH technique.This study aimed to assess the accuracy of cortical bone trajectory (CBT) screws placement guided by a spinous process clamp (SPC) guide. A total of 32 patients who received single-level midline lumbar fusion (MIDLF) surgery between June 2019 and January 2020 were retrospectively analyzed and divided into free-hand (FH) and SPC-guided groups according to the surgical approach. In the FH group, CBT screws was implanted with the assistance of fluoroscopy, while in the SPC group, CBT screws was implanted using the SPC navigator hardwire. A total of 128 screws were assessed in this study, with higher rates of clinically acceptable screw placement (grades A and B) and grade A screws in the SPC group than in the FH guide group (92.2% vs. 79.7%,  However, pedicle screw implantation can be problematic in patients with osteoporosis and obesity2. In addition, the starting point for pedicle screws (PS) is lateral to the midline, near the lateral wall of the facet joint, resulting in the risk of a facet joint violation (FJV) during dissection of the paravertebral muscles or screw placement4. In 2009, Santoni et al.5 first reported the cortical bone trajectory (CBT) screw fixation technique, which compensated for the biomechanical deficiency of pedicle screw fixation in patients with osteoporosis. Compared with PS, the CBT method maximizes the purchase of the pedicle and vertebral cortical bone through the screw thread contact with the cortical bone and enhances the fixation strength. Lumbar fixation with CBT technology has been described as a midline lumbar fusion (MIDLF) surgery6. The new pathway follows a caudo-cephalad sagittal path and a medial–lateral path in the axial plane, which reduces the skin incision length, muscle dissection, and superior facet joint exposure.Posterior lumbar interbody fusion (PLIF) is an effective therapy for lumbar degenerative diseases and has been widely used in spinal surgery9. Three-dimensional (3D) printed template guides, 3D navigation, and robotic-assisted surgery systems have been developed to improve accuracy of screw placement13. However, an extended paraspinal soft tissue dissection and increased radiation exposure limit their widespread application14. Based on the experience of CBT surgery and the advantages and disadvantages of existing navigators, our center has developed and designed 3D spinal navigation technology with independent intellectual property rights. This 3D spine navigation technique relies on bone-anchored spine tracking guided by spinous process clips (SPC). In this study, we will compare the accuracy of screw placement using SPC technique with fluoroscopy-assisted free-hand (FH) technique and introduce the SPC technique by means of a retrospective study.Previous studies have reported screw misalignment rates between 0 and 12.5%A review of patients who were diagnosed with lumbar degenerative diseases and underwent single-level MIDLF surgery at L4/5 with CBT screw internal fixation from June 2019 to January 2020, identified a total of 32 patients who were eligible. Patients were divided into two groups according to surgical approach: FH (16 cases) and SPC guide (16 cases) groups. All surgeries were performed by the same surgeon. This study was approved by the institutional review board.The inclusion criteria were as follows: (1) a diagnosis of L4/5 single-segment lumbar degenerative diseases, (2) ineffective conservative treatment for > 6 months, (3) follow-up time ≥ 1 years, and (4) complete preoperative and postoperative imaging data. Exclusion criteria included the following: (1) a history of lumbar surgery; (2) severe neurological symptoms ; (3) spinal deformity with Cobb angle more than 20°; (4) spinal tumor; (5) severe osteoporosis  method ≤ − 2.5, associated with osteoporotic fracture); (6) Lumbar fracture and (7) comorbidities with contraindications to surgery  with similar diseases and systemic conditions that cannot tolerate surgery.The 3D CT scans of the lumbar spine were generated using Picture Archiving and Communication Software (PACS) . The 3D reconstructions were used to plan the caudocephalad and medial–lateral paths of CBT screws Fig. . In the Preoperative measurements should be made in sagittal and coronal CT images of the lumbar spine Fig. . The SPC15. The cranial exposure stopped at the inferior aspect of the facet joint, and the lateral exposure stopped at the lateral border of the pars region. The exact entry point was the intersection of the lateral margin of the pars interarticularis and the inferior level of the transverse process16. A 1.7-mm drill bit was used to drill the complete path from the entry point along the cortical bone trajectory, approximately 10° laterally and 30° cranially, and stopped at a depth of 20–25 mm. A burr was used to probe the tactile feedback through the pedicle wall before the CBT screw was inserted along the trajectory. With the assistance of lateral and anteroposterior fluoroscopy and identification of anatomical landmarks, bilateral CBT instruments of the cortical screw fixation system  were implanted at the appropriate position16.Fluoroscopy-assisted Free-hand CBT screw placement followed the standard MIDLF surgical approach. The standard MIDLF surgical incision was 1–2 cm smaller than the pedicle screw incision because CBT instruments were placed more caudally than PS instruments17. The screw accuracy was graded based on the modified Gertzbein–Robbins method 18. Perforations worse than grade C were deemed unacceptable11. The assessment of the proximal FJV included adjacent cranial and all fixed segments19. The cranial and lateral angles of the CBT screws were assessed in the sagittal and axial planes, respectively. Radiation exposure parameters were obtained from the C-arm equipment. Clinical data, such as Oswestry disability index (ODI), and back pain visual analog scale (VAS) scores, were evaluated preoperatively and at final follow-up.Postoperative CT reconstruction was used to assess the accuracy of the screw placement between the SPC guide and FH groups. The location of the screw inside the vertebral bodies or pedicle was measured in millimeters in the medial, lateral, cranial, caudal, and cephalad endplate and vertebral cortex directionsP < 0.05.Statistical analyses were performed using SPSS, version 25.0 . Continuous variables are presented as mean ± standard deviation (SD), whereas non-continuous data are presented as numbers or ratios. For comparison between groups, the χ2 test was used for categorical variables ; non-continuous data were compared using Pearson's chi-square test. Statistical significance was considered as The study complied with the Declaration of Helsinki and was approved by the Ethics Committee of the Beijing Chao-yang Hospital, Capital Medical University. Informed consent was waived because of the retrospective study design, which was approved by Ethics Committee of Beijing Chao-Yang Hospital, Capital Medical University.2 (15.00 ~ 32.00 kg/m2). The operative time in the SPC guide group was significantly longer than that in the FH group . The BMD, intraoperative blood loss, and length of postoperative hospital stay were not significantly different between the groups  males and 20 (62.5%) females, with a mean age of 61.9 ± 5.8 years (range: 54–72 years), follow-up time of 15.0 ± 2.1 months (range: 12–21 months), and body mass index (BMI) of 23.9 ± 3.8 kg/mP = 0.042). The proportion of remaining screws  was greater in the FH than in the SPC group .Table The direction of screw misplacement is presented in Table P = 0.030). The cranial angle of the cortical screw in the SPC guide group was much larger than that in the FH group , as was the lateral angle of the cortical screw  . There were no significant differences in ODI and back pain VAS scores in the preoperative and final follow-up periods (≥ 12 months postoperatively) between both groups . A possible explanation is that the SPC device-guided screw was much more caudal, so a large cranial angle was needed to purchase the cortical bone from the lower starting point. The lateral angle of the cortical screw trajectory was higher in the SPC guide group than in the FH group . This may be because the hardware-restricted screw trajectory was closer to the midline.The trajectory of the cortical screw was directed approximately 25° cranially and 10° laterally13, using robotic-assisted screw placement resulted in a reduction in radiation exposure to the medical team, but intraoperative CT scans increased the radiation dose to the patient.No studies have compared the radiation exposure between SPC guides and fluoroscopy-assisted FH techniques. In our study, the radiation dose and duration for both the staff and patients were the same in both groups. This may be because the SPC guide surgical procedure was like FH, and there was no need for additional positioning fluoroscopy compared with FH screw placement. In previous studiesThe operative time was slightly longer in the SPC guide group than in the FH group. The SPC guide requires a few minutes to insert each screw due to the precise adjustment of the cranial and lateral angles of the guide. The intraoperative blood loss was the same in both groups—no additional or extended incisions were required for the spinal surgery with an SPC guide; this protects the cephalic facet joints from excessive dissection.25, our center found that the use of SPC improved screw placement accuracy. Accurate screw placement greatly increases the likelihood of patient symptom improvement and surgical success after surgery.Patients in both groups were similar in terms of clinical recovery. There were significant differences in ODI and back pain VAS scores between preoperative and last postoperative follow-up. Patients who underwent both procedures showed significant improvements in pain intensity and functional status postoperatively compared to preoperatively. At the same time, there was no statistically significant difference in ODI and back pain VAS scores at the last follow-up between the two groups. SPC assisted CBT screw placement was similar to Free-Hand CBT screw placement in improving patient symptoms and clinical outcomes. This is similar to the conclusions of previous cadaveric studies of this device. In cadaver studiesThis study had some limitations. First, this study was performed on patients who underwent L4/5 single-level spinal surgery, implying that the conclusions may not apply to subjects undergoing other segment and multi-level fusion surgeries. Second, the small sample size limits the evaluation of screw accuracy and surgical radiation exposure, and the conclusions drawn in this study lack confidence and representativeness. Third, a 1-year follow-up period was not sufficient to truly assess the clinical and radiographic results of the screw placement accuracy. One-year follow-up is insufficient to reflect the impact of low FJV in reducing the incidence of adjacent segment degeneration, and facet joint degeneration requires longer follow-up to observe. Finally, all spinal surgeries were performed by the same surgeon; therefore, the study could not account for changes in technology and experience.For lumbar cortical bone trajectory devices, SPC-guided screw placement improves accuracy compared to fluoroscopy-assisted FH technique. Patients receiving SPC-guided assisted screw placement achieved equivalent outcomes in patients receiving fluoroscopy-assisted FH techniques. However, long-term efficacy requires longer follow-up and larger sample size studies.


Schistosoma haematobium is the most prevalent of the human-infecting schistosome species, causing significant morbidity in endemically exposed populations. Despite this, it has been relatively understudied compared to its fellow species, S. mansoni. Here we provide the first comprehensive characterization of the S. haematobium Tegument Allergen-Like protein family, a key protein family directly linked to protective immunity in S. mansoni infection. Comparable with observations for S. mansoni, parasite phylogenetic analysis and relative gene expression combined with host serological analysis support a cross-reactive relationship between S. haematobium TAL proteins, exposed to the host immune system as adult worms die, and closely related proteins, exposed during penetration by the infecting cercarial and early schistosomulae stages. Specifically, our results strengthen the evidence for host immunity driven by cross-reactivity between family members TAL3 and TAL5, establishing it for the first time for S. haematobium infection. Furthermore, we build upon this relationship to include the involvement of an additional member of the TAL protein family, TAL11 for both schistosome species. Finally, we show a close association between experience of infection and intensity of transmission and the development of protective IgE responses to these antigens, thus improving our knowledge of the mechanisms by which protective host immune responses develop. This knowledge will be critical in understanding how control efforts such as mass drug administration campaigns influence the development of host immunity and subsequent patterns of infection and disease within endemic populations. S. haematobium is the most prevalent of the human infecting schistosomes. Along with S. mansoni, it is responsible for the majority of schistosomiasis cases that are borne by the populations of sub-Saharan Africa, where the global burden of this infection is centered. Here, we provide insight into the IgE antibody response that protects against these infections. Through utilization of in silico analysis in combination with immuno-epidemiological studies, we explore the relationship between host immune protection and a parasite protein family named the Tegument Allergen-Like (TAL) proteins. Our results show that several members of the TAL protein family are important in host protection to both these major schistosome species. For the first time we demonstrate that a progressive cross-reactive TAL-IgE response occurs against S. haematobium, similar to that previous observed in S. mansoni infection. We additionally expand upon previous knowledge for S. mansoni, identifying further complexity in the cross-reactive relationship between TAL family members, providing evidence of a key role for family member TAL11 in induction of the protective host immune response. Schistosoma haematobium and S. mansoni are the prevalent infections. The acquisition of protective immunity against infection with Schistosoma worms is a gradual process thought to naturally occur over several years, however, the mechanism is not fully understood. Evidence from immuno-epidemiological studies principally supports the hypothesis that a humoral response is acquired following cumulative exposure to antigens that are released as adult worms die [Schistosoma transmission dynamics and subsequent planning of infection control measures.Schistosomiasis is a disease of considerable public health importance resulting in severe morbidity and reduced quality of life in over 290 million people affected by the disease worldwide . The majorms die ,4 and inorms die . Whilst orms die , improviS. mansoni infection, members of a parasite protein family, the Tegument Allergen-Like (TAL) proteins, induce IgE responses that are strongly associated with human immunity [Schistosoma species [Fasciola hepatica, F. gigantica, Clonorchis sinensis and Opisthorchis viverrini [S. mansoni were SmTAL1 [In immunity ,8. The Timmunity  and prot species ,11,12,13iverrini –17. The iverrini . EF-handiverrini ,19,20 ane SmTAL1 , SmTAL2 e SmTAL1 , and SmTe SmTAL1 , previoumansoni [S. haematobium [Several studies have provided evidence for strong cross-reactivity amongst IgE responses to EF-hand containing proteins, resulting in cross-sensitization between environmental and food allergens –25 and imansoni  and S. hmatobium . Of intematobium . Whole-mmatobium , which smatobium . HoweverS. haematobium TAL protein family has been identified, a TAL1 orthologue which has a closely related sequence to the corresponding S. mansoni protein [S. haematobium, although there is evidence for similar TAL1-specific IgE responses to those observed for S. mansoni [S. haematobium genome and the subsequent updated version [S. haematobium TAL proteins, specifically those proteins orthologous to the S. mansoni proteins associated with protective IgE responses: ShTAL1, ShTAL3, and ShTAL5. We also take the opportunity to further characterize the S. mansoni protective response by testing the hypothesis that SmTAL11 induces an IgE response following worm death that contributes to the development of delayed concomitant immunity, and to examine the corresponding response in S. haematobium infection.To date, only one member of the  protein . Further mansoni ,28. Ther version , we takeEthical clearance was granted by the Uganda National Council of Science and Technology (Reference number: UNCST: HS59) and the Malian Ethical Review Committee of the National Institute for Research in Public Health (decision 0002/INRSP/DAP/SP- 2005), respectively. In Uganda, consent forms were translated into the local language and informed written consent was obtained from all adults and from the parents/legal guardians of all children under 15. Whilst, in Mali, oral informed consent was given by adult participants and by parents or guardians of participating children. At the time of the study oral consent was deemed acceptable by the Malian Ministry of Health, due to cultural reasons and low literacy rates in the Malian villages.S. mansoni; and the other from three villages in the Segou Region, Mali, located along the River Niger and one of its tributaries, that are endemic for S. haematobium. Briefly, the Ugandan cohort comprised n = 175 male individuals between 7 and 60 years of age. Median S. mansoni infection intensity within this cohort was 587 eggs per gram of feces. The Malian cohort comprised a total of n = 261 individuals between 5 and 40 years of age. These individuals resided in villages with either moderately high transmission intensity  or very high transmission intensity . Full descriptions of the study cohorts can be found elsewhere [S. mansoni endemic Ugandan cohort this comprised Kato Katz egg counts performed in duplicate on three stool samples collected on different days. Similarly, for the S. haematobium endemic Malian cohort, egg counts were performed on three 10 ml filtered urine samples, collected on different days. Blood samples were collected into EDTA from both cohorts at baseline and 9-weeks post-treatment and the plasma harvested by centrifugation. Plasma samples were treated with 0.3% tributyl phosphate/1% Tween 80 to inactivate encapsulated viruses prior to measurement of specific antibody responses. CAA measurement was performed on a 40 μl sample of plasma from each participant in the Malian cohort at Leiden University Medical Center (LUMC) as previously described [IgE responses to the TAL protein family were examined across two separate study populations: one a fishing community situated on Lake Victoria, endemic for lsewhere . Quantitescribed . All samS. mansoni parasite material was a gift from Prof David Dunne (University of Cambridge). Total RNA was isolated as previously described [S. haematobium material was kindly provided by Prof Ron Hokke  and processed as described for S. mansoni.escribed . S. haemS. mansoni TAL proteins [S. haematobium genome assembly ; 2) the presence of at least one predicted N-terminal EF-hand domain (InterPro domain: IPR011992), and 3) a C-terminal dynein light chain (DLC) domain , with an exception for TAL10, for which the S. mansoni orthologue was previously found to contain a DLC region that is not predicted by domain prediction tools [S. mansoni TAL were used in BLASTp searches against the predicted protein database of the S. mansoni genome assembly .Amino acid sequences from well-characterized proteins ,9,12 werNA78265; ). In linS. haematobium genome [S. mansoni [mRNA transcription data for the TAL sequences was extracted supplementary materials published alongside the most recent annotation of the m genome  and a me mansoni .Sequences were aligned using the Multiple Sequence Comparison by Log-Expectation tool (version 3.8 ) and conS. haematobium worms, Egyptian Strain, ligated into the expression vector pGEX-1λT  and expressed as a fusion protein with glutathione-S-transferase (GST), as described previously [E. coli and purified as described previously [The full coding transcript sequences were cloned from cDNA from adult eviously . Recombieviously . 4 μg ofeviously .Recombinant proteins were analyzed by liquid chromatography tandem mass spectrometry (LC-MS/MS). LC-MS/MS experiments were performed using a Dionex Ultimate 3000 RSLC nanoUPLC (Thermo Fisher Scientific) system and a Q Exactive Orbitrap mass spectrometer (Thermo Fisher Scientific), according to protocol in S. haematobium_20230323 database (28959 sequences), the S._mansoni_20201214 (14182 sequences) database and the E. coli database 20221010 (4460 sequences). Variable modifications of oxidation (M), deamidation (NQ), and a fixed modification of carbamidomethyl (C) were applied. The peptide and fragment mass tolerances were set to 20 ppm and 0.1 Da, respectively.The MS/MS data were submitted to the Mascot search algorithm  and searched against a common contaminants database 20190401 , the Human IgE and IgG4 ELISAs were performed to measure the TAL antigen specific IgE and IgG4 antibody concentration in individual plasma samples from each study site. The saturating coating concentration for each recombinant antigen was identified using a coating inhibition assay, as described elsewhere . RecombiFor reciprocal inhibition assays, ‘competitor’ recombinant TAL proteins were added at a concentration of 150 μg/ml to a pool of plasma, diluted 1:20 with PBS/10% (v/v) fetal calf serum (Thermo Fisher Scientific), derived from 10 individuals with a known response to each of the respective TAL proteins under investigation. The plasma was then incubated at room temperature for 1 hour before adding to the ‘target’ recombinant TAL protein coated plate and continuing the IgE ELISA described above.S. mansoni infection two years after treatment, with adjustment for age and treatment efficacy (9-week epg). Epidemiological evidence supports the manifestation of processes affecting worm fecundity in S. haematobium that do not appear to occur in S. mansoni [Schistosoma parasite load is typically assessed through the measurement of the number excreted eggs; yet, due to the non-linear relationship between CAA and egg excretion in S. haematobium, egg counts are an unreliable measure of worm burden, instead the use of CAA is preferable in assessing S. haematobium infection intensity [S. mansoni were observed in the Malian cohort, the provision of stool samples to confirm the absence of co-infection was also low, due to cultural reasons. Missing information on S. mansoni infection status was therefore estimated using multiple imputation chain equations (MICE) in R, with predictive mean matching over 25 imputations. The predictive variables in the imputation were age, transmission intensity, sex, ln(caa + 1), ln(Sh eggs + 1), ln(SWA-IgG1), ln(SWA-IgG4), ln(SWA-IgE) and ln(SWA-IgA), ln(Sh28GST-IgG1), ln(Sh28GST-IgG3), ln(Sh28GST-IgA), and detectable ShTAL1-IgE responses. Complete data sets were available for all predictive variables.All statistical analysis was conducted in R (version 3.4 ). Detect mansoni . Schistontensity . In the S. haematobium reinfection status at two years post-treatment as a binary outcome, with the justification that detectable egg excretion is an indicator of infection, regardless of worm burden. Post-treatment models were again adjusted for potential confounding predictors. All models were reduced by stepwise removal of non-significant variables. Since the data were log-transformed prior to analysis, regression coefficients were exponentiated and the results expressed as the geometric mean (GM) odds ratio.It has been suggested that IgG4 antibodies may compete for the same epitopes and therefore acts to block IgE pathways . TAL-speS. haematobium proteins  which did not show orthology to existing SmTALs. After BLASTp searches of the S. mansoni genome predicted protein dataset, it was shown this ShTAL was an ortholog (87.5% identity) of the previously uncharacterized S. mansoni protein assigned here as SmTAL14 . The BLASTp searches resulted in the identification of 13 predicted proteins . Eleven S. mansoni v9 TAL5 and TAL6 sequences shows sequence similarity of TAL5 to the 5’ end and TAL6 to the 3’ end of the Shaem_V3.0 annotation of ShTAL5 (Further examination of the Shaem_V3.0 predicted ShTAL5 sequence (XP_035588243) identified a probable error in the annotation of the ShTAL5 and ShTAL6 sequences, merging the two genes. Subsequent alignment of the ShTAL5 Shaem_V3.0 sequences against the Shaem_V1.0 and f ShTAL5 . Furtherf ShTAL5 .S. mansoni and S. haematobium TAL orthologues, TAL3, TAL4, TAL5 and TAL11 share greatest sequence identity, with ShTAL 3 and 5 sharing 45.35% sequence identity: ShTAL5 and 11 sharing 46.51% sequence identity, and SmTAL5 sharing 44.77% identity with both SmTAL3 and SmTAL11. Full percentage sequence identity data for this group of TAL proteins can be found in the Table B in Amongst the S. mansoni, a Maximum Likelihood tree was constructed for the conserved regions detected by Gblocks analysis , one clade including S. mansoni and S. haematobium TAL1, 2, 8, 12 and 14 proteins, whilst the other includes the remaining S. mansoni and S. haematobium TAL3, 4, 5, 7, 9, 10, 11, 13 and TAL6 proteins . Individuals who were found to have a detectable TAL specific IgE response were identified as an IgE ‘responder’ for a specific TAL (greater than the mean + 3 x standard deviations of the non-endemic control response). 134 individuals  had a positive response to one or more of SmTAL1, 3, 5 or 11, with 79% (11/14) of IgE responders to SmTAL11 also found to be responders to SmTAL1, SmTAL3 and SmTAL5. Likewise, individual IgE responses in the Malian cohort show an overlap in S. haematobium TAL protein responses. Sixty-five percent (28/43) of ShTAL11 responders were quadruple responders, with IgE also measurable for ShTAL1, ShTAL3 and ShTAL5. Indicating that individuals seropositive for TAL11-IgE may be a subset of those with a detectable TAL5, TAL3 and TAL1-specific IgE response in S. mansoni and S. haematobium infection.Despite similarities to the peptide sequence of TAL3 and comparable transcription across the different lifecycle stages, TAL11 has not previously been explored in relation to protective immunity. To elucidate this relationship, the specific post-treatment IgE responses to SmTAL1, 3, 5 and 11 were analyzed in relation to their epidemiological profiles (Uganda). IgE responses to the equivalent S. haematobium antigens demonstrate a similar cross-reactivity profile to that previously shown between SmTAL3 and SmTAL5, reciprocal inhibition ELISAs were conducted  or SmTAL11 , comparable to pre-incubation with SmTAL5 , was obs control ; whereas control , indicat control . Suppres control ; nor was control . Finally mansoni  or S. hamatobium . BindingPopulation based linear regression models demonstrate that increasing host age and having a positive IgE response to SmTAL11 was significantly associated with reduced intensity of reinfection at two years post-treatment . Seropositivity for combined SmTAL1, SmTAL3, SmTAL5 and SmTAL11 specific IgE was also significantly associated with reduced reinfection intensity at two years post-treatment, even after accounting for age in the model . PairwisBeing seropositive for ShTAL3-IgE  was negatively associated with baseline infection intensity in cross-sectional models of anti-ShTAL responses and infection intensity (as measured by CAA), that accounted for age, village of residence and the relevant TAL-specific IgG4 response. ShTAL5-IgE  also demonstrated a negative association with baseline infection intensity, though not significantly. Specific IgG4 responses were significantly associated with higher baseline CAA . Adjusting for ShTAL3-specific IgG4 was required to maintain the effect of the negative association between seropositivity for ShTAL3-IgE and baseline infection. The results of models without adjustment for TAL-IgG4 are provided in Table C in Although two-year follow-up CAA data were not available for analysis of the association between post-treatment ShTAL-IgE seropositivity and intensity of reinfection, logistic regression models were built to test whether post-treatment ShTAL protein IgE seropositivity was associated with reinfection status as determined by detection of eggs in the urine at two years. Being IgE seropositive to ShTAL1, 3 and 5  was significantly associated with protection against reinfection and remained so when age and village were accounted for in the model .S. mansoni [S. mansoni, a family of secreted proteins identified as a potential intervention target [The IgE antibody response has long been associated with both allergy and immunity in parasitic infections, with sequence identity and structural similarity between environmental allergens and parasite proteins having been utilized in the prediction of allergen-like protein families in  mansoni . These s mansoni . Immunog mansoni . Cross-r mansoni . The imp mansoni . In human target ,26.These studies establish processes of cross-reactivity as vital in our understanding of host-pathogen interactions; interactions that can lead to exacerbation of pathology, or aid or hinder the development of protective responses, key knowledge for assessing therapeutic targets. Here, for the first time, we conducted comparative analysis of the Tegument Allergen Like (TAL) protein family across two of the major human infecting schistosomes, with a particular focus on their role at the host-parasite interface, humoral cross-reactivity, and the resultant host protection.S. haematobium V3.0 genome, including an orthologue of a previously uncharacterized S. mansoni protein, assigned TAL14. Analogous with the phylogeny of S. mansoni TAL proteins, the S. haematobium TAL phylogeny revealed that the TAL proteins cluster within two subclades (98% support): the Group 1 TAL proteins comprising TAL1, 2, 8, 12 and 14 and the Group 2 proteins comprising the remaining TAL proteins: TAL3, 4, 5, 6, 7, 9, 10, 11, and 13. Amongst the Group 2 proteins TAL3, 4, 5 and 11 share the greatest sequence identity with S. mansoni and S. haematobium TAL3, 5 and 11 sharing moderate sequence identity, between 30–60%. Whilst Aalberse [et al. [We identified 14 TAL proteins in the Aalberse  noted thAalberse . FitzsimS. mansoni, Smtal5 is expressed throughout the cercaria [S. haematobium transcription data for those TALs proposed to be associated with protective human IgE responses [S. haematobium TALs does differ slightly from that of S. mansoni, the lifecycle stage transcription profiles of Shtal1, 3 and 11 remain consistent with the hypothesis that antigen specific IgE induced by worm death drives protective immunity in S. haematobium. Whilst the transcription data are not available for Shtal5 due to mis-annotation of the version 3 genome, similarity across the other TAL family members suggests that it is highly likely that Shtal5 shares the transcription profile of Smtal5. In addition, post-treatment increases observed in specific IgE antibody titers to ShTAL1, ShTAL3 and ShTAL11 are in accordance with the patterns seen in S. mansoni [Identifying the developmental gene expression profiles for the ShTAL sequences can enable our understanding the human immune response to this family of proteins. Each lifecycle stage evokes a distinct immune response as a result of the anatomical environment in which they reside, and the frequency of antigen exposure to the immune system ,8. Severcercaria , evidencesponses , we founSecreted and surface expressed proteins have garnered significant interest in the search for vaccine targets. The schistosome tegument plays an important role at the host-parasite interface and, whilst it associated with immune evasion strategies, it is also considered to be the parasite structure most susceptible to immune-mediated attack by the host . SeveralFasciola gigantica [A recent study of cross-reactivity between allergen-like proteins suggests that glycans may also play an important role in the development of cross-reactive immune responses . Glycosyigantica . PotentiS. mansoni has previously been proposed to result from SmTAL3-specific IgE cross-reactive to SmTAL5 that is exposed to the human host on the invading cercaria and early schistosomula [S. mansoni TAL11-specific IgE response to be strongly associated with reduced reinfection intensity at two years. This association was also seen for those with a positive response to multiple SmTAL proteins , which was expected due to the degree of overlap between SmTAL-IgE responders.IgE mediated protective immunity to Antibody affinity studies would improve our understanding of this relationship still further; however, there are several challenges regarding experimental design and the nature of specific antibody responses in serum from schistosomiasis endemic areas, most notably the polyclonal nature of the antibodies and the presence of non-IgE antibodies that are specific to the same antigens.S. haematobium demonstrates similar cross-reactivity profiles between ShTAL3, ShTAL5 and ShTAL11 to those seen for S. mansoni proteins, although a few key differences between the responses are observed. The extent to which ShTAL3 binding is inhibited by ShTAL5 and ShTAL11 is not as high in S. haematobium compared to the equivalent S. mansoni TAL protein inhibition. Furthermore, pre-incubation with ShTAL3 does not appear to completely inhibit ShTAL5 binding. Unlike the equivalent S. mansoni protein, the transcription data presented here suggest that ShTAL3 has a high level of expression in the egg, in addition to expression in the adult worm. ShTAL3-specific IgG4 responses may consequently block or regulate the cross reactive IgE response, to reduce the pathology that would result from high IgE responses to tissue trapped eggs [ped eggs .S. mansoni. Regression models did not, however, lend support to the contribution of S. haematobium TAL11 to partially protective immunity. The power to detect an association between ShTAL11 seropositivity and reduced reinfection, however, was limited in this study by the number of individuals seropositive for ShTAL11 specific IgE. Furthermore, CAA titers at reinfection may be more sensitive at detecting this relationship due to a closer reflection of true reinfection rates [In the study population-based analysis, a protective effect of IgE to ShTAL proteins was observed, with having a detectable IgE response to a combination of ShTAL1, ShTAL3 and ShTAL5 significantly associated with a lack of reinfection at two years, providing evidence for the progressive development of a protective IgE response, similar to that demonstrated in on rates  that areon rates ,45. Protin silico and parasite transcriptional analyses to explore the relationship between the TAL protein family expression and human immunity to reinfection. It provides important development in our understanding of protective immune responses to S. mansoni and for the first time, comparative analysis of this important protein family for S. haematobium, the most prevalent of human infecting schistosomes. We provide evidence for a cross-reactive delayed concomitant immunity driven protective response in S. haematobium, in line with previous observations for S. mansoni. In addition, overlapping IgE seroprevalence to multiple TAL proteins, combined with observable cross-reactivity between TAL protein family members, suggests that adult worm expressed SmTAL11 and ShTAL11 may also drive development of the protective IgE immune response, thus providing further support to the hypothesis of delayed concomitant immunity to these parasites of great public health importance.This study utilized immuno-epidemiological inquiry, in combination with S1 TextFig A. Lifecycle transcription profiles of S. haematobium TAL proteins. Fig B. Lifecycle transcription profiles of S. mansoni TAL proteins. Fig C. Gel electrophoresis of purified SmTAL and ShTAL proteins. Fig D. Pre- and post-treatment (Rx) seroprevalence of IgE responses to S. haematobium TAL proteins by age and village, as a proxy for force of transmission. Table A. Percent identity matrix between ShTAL1, 3, 5 and 11 and SmTAL1, 3, 5 and 11. Table B. Recombinant antigen coating concentration. Table C. Association between pre-treatment ShTAL-specific IgE responses (seropositivity) and baseline CAA, as a measure of worm burden. Table D. Association between pre-treatment ShTAL-specific IgE responses (seropositivity) and baseline CAA, as a measure of worm burden.(DOCX)Click here for additional data file.