Candida albicans pathogenicity is its ability to switch between yeast and hyphal forms, a process in which CaRas1 plays a key role. CaRas1 is activated by the guanine nucleotide exchange factor (GEF) CaCdc25, triggering hyphal growth-related signaling pathways through its conserved GTP-binding (G)-domain. An important function in hyphal growth has also been proposed for the long hypervariable region downstream the G-domain, whose unusual content of polyglutamine stretches and Q/N repeats make CaRas1 unique within Ras proteins. Despite its biological importance, both the structure of CaRas1 and the molecular basis of its activation by CaCdc25 remain unexplored. Here, we show that CaRas1 has an elongated shape and limited conformational flexibility and that its hypervariable region contains helical structural elements, likely forming an intramolecular coiled-coil. Functional assays disclosed that CaRas1-activation by CaCdc25 is highly efficient, with activities up to 2,000-fold higher than reported for human GEFs. The crystal structure of the CaCdc25 catalytic region revealed an active conformation for the α-helical hairpin, critical for CaRas1-activation, unveiling a specific region exclusive to CTG-clade species. Structural studies on CaRas1/CaCdc25 complexes also revealed an interaction surface clearly distinct from that of homologous human complexes. Furthermore, we identified an inhibitory synthetic peptide, prompting the proposal of a key regulatory mechanism for CaCdc25. To our knowledge, this is the first report of specific inhibition of the CaRas1-activation via targeting its GEF. This, together with their unique pathogen-structural features, disclose a set of novel strategies to specifically block this important virulence-related mechanism.An important feature associated with Candida albicans is the main causative agent of candidiasis, the commonest fungal infection in humans. The eukaryotic nature of C. albicans and the rapid emergence of antifungal resistance raise the challenge of identifying novel drug targets to battle this prevalent and life-threatening disease. CaRas1 and CaCdc25 are key players in the activation of signaling pathways triggering multiple virulence traits, including the yeast-to-hypha interconversion. The structural similarity of the conserved G-domain of CaRas1 to those of human homologs and the lack of structural information on CaCdc25 has impeded progress in targeting these proteins. The unique structural and functional features for CaRas1 and CaCdc25 presented here, together with the identification of a synthetic peptide capable of specifically inhibiting the GEF activity of CaCdc25, open new possibilities to uncover new antifungal drug targets against C. albicans virulence. Candida albicans, part of the commensal microbiota of most individuals, is an important opportunistic human fungal pathogen and can cause severe infections in immunocompromised patients  followed by a hypervariable region. The long hypervariable region of CaRas1 represents a major difference between yeast (~120 residues) and human (~20 residues) Ras proteins. Further, the presence of low complexity segments in the hypervariable region of CaRas1, including polyglutamine (PolyQ) repeats and a Q/N-rich stretch, also present in other members of the CTG-clade, makes it unique among Ras-family proteins . The hypIn yeast cells, CaRas1 is generally in an inactivated, GDP-bound form (CaRas1-GDP). CaCdc25 activates CaRas1, promoting its conversion to CaRas1-GTP and switching on the signaling pathway associated with the hyphae-specific genes , 14, 15.Despite its biological relevance, no experimental structural information is available for the full-length CaRas1 and the relative arrangement of the G-domain and the unique low complexity hypervariable region, which is predicted to be partially disordered. Also, the elucidation of the molecular basis for the activation of CaRas1 by CaCdc25 would provide crucial information for the design of new drugs to fight this fungal human pathogen.In this work, by combining biophysical techniques with artificial intelligence (AI)-based predictive modeling, we disclose structural features of this unique Ras-family protein and of its GEF CaCdc25, both isolated and complexed. We also identify a synthetic peptide capable of inhibiting the activity of CaCdc25, shedding light on its mechanism of regulation and establishing a path for the rational design of novel inhibitors of this fungal signaling pathway.CaRas1 is composed by a highly conserved G-domain, followed by an exclusive hypervariable region that contains low complexity sequence segments, including PolyQ repeats and a Q/N-rich stretch , a uniquP(r)] for the G-domain has a bell shape characteristic of globular particles with a peak at ~23 Å and a maximum dimension (Dmax) of ~45 Å  function displays a second peak at ~52 Å (ab initio models (P(r) function and the dimensionless Kratky plot for CaRas1-FL, are characteristic of a protein composed by relatively rigid two-bodies  analysis of the secondary structure of three CaRas1 truncation constructs with variable lengths of the hypervariable region  that are very similar  and the CAT domain  (Cα atoms) than those for the REM domain  . In partM and αO (residues 1222–1265)  , which p22–1265) , suggest22–1265) : (i) the22–1265) , (ii) a  hairpin , and  10−2 s−1) was considerably higher  (kobs = (1.2 ± 0.1) 10−2 s−1 for H1234E and kobs = (0.90 ± 0.05) 10−2 s−1 for H1234D), whereas replacement with an uncharged amino acid did not significantly alter the activity (kobs = (3.3 ± 0.4) 10−2 s−1 for H1234A)   than tho00-fold) -39, un H1234A) . Of note H1234A)  led to t species , while aectively . The remP(r)-derived Dmax of ∼120 Å for the G-domain/REM-CAT complex  with either CaRas1-FL or its isolated G-domain see . SAXS an complex  is in go complex ; Fig. S6 complex  and it c complex .ab initio reconstruction of the envelope reveal a more extended shape for the complex with CaRas1-FL than with the G-domain    and 1:1  = 9 µM) , with siCandida albicans without affecting other human GTPases.The CaRas1/CaCdc25 interaction mode displayed in the two AI-based models is similar to that described for human HRas and Sos1  Fig. 4AFig. 4A. 837TIINYATRVMQDNFDVQLLLVE858 to the nucleotide exchange activity assays was assessed. A dose-dependent reduction of the activity of CaCdc25 was observed , a region upstream the REM-CAT tandem occupies the G-domain binding site region. To further explore this finding, we generated several AlphaFold2 models for CaCdc25 segment 837–1306, which comprises the hypothetical inhibitory and catalytic regions . In the observed , with anobserved . This sees clade . In the es clade . These oC. albicans to fluctuations in the host microenvironment is a key aspect of its biology, critical for the commensal to pathogen transition of this opportunistic human pathogen  signal transduction pathway regulates the expression of several virulence traits involved in host recognition, tissue invasion, and evasion of host defense mechanisms. Disrupting the activation of CaRas1, which triggers the signaling pathways that drive the virulence-linked morphological transition from yeast form to a hypha state, is, therefore, a promising approach for the development of antifungal therapies. However, the highly conserved G-domain of CaRas1 , and th species , 46. Indl target . Here, wDownstream the highly conserved G-domain of CaRas1 there is a hypervariable region, unusual among Ras-family proteins, which contains low complexity sequence segments, including PolyQ repeats and a Q/N rich stretch, and annotated as unstructured in some databases for intrinsically disordered regions. Cleavage of membrane-associated CaRas1 at this hypervariable region has been proposed as a mechanism restricting CaRas1-mediated activation of the downstream adenylate cyclase (CaCyr1) and, consequently, hyphal growth . CaRas1 C. albicans cells  and the other comprising a second Q-rich region . The region connecting these two segments (residues 222–247) has a significant content of disorder-favoring glycine (∼30%) and serine/alanine (∼20%) residues. The first part of the hypervariable region of CaRas1 harbors α-helical elements, as assessed by CD and in agreement with the estimation of several secondary structure predictors. We propose that the terminal helix of the G-domain extends through the first polyQ region until near the end of the Q/N stretch, in line with the susceptibility to proteolysis of the region past N212 in ns cells . This hyns cells , where ans cells . Furtherns cells , which iS. cerevisiae and human homologs, offer novel opportunities to investigate the use for the rational design of molecules able to bind to these structured regions that eventually may have an effect in these polyQ associated processes.Interestingly, heterotypic and homotypic interactions involving α-helical and intrinsically disordered regions have been shown to mediate phase separation of septal pore-associated proteins in intracellular compartments required for septal biogenesis and cellular communication . PolyQ rCaRas1 is activated by CaCdc25, triggering the virulence-related MAPK and cAMP signaling pathways. The activated form of CaRas1, CaRas1-GTP, binds to CaCyr1 and induces a cAMP pulse that promotes the yeast-to-hypha transition . Whereas837TIINYATRVMQDNFDVQLLLVE858, only present in fungal GEFs, as an auto-inhibitory region. Conformational changes required to displace this region from the CaCdc25-CaRas1 interface are presumably dynamic processes, in accordance with the relatively high EC50 value determined for the peptide, and the underlying mechanism of auto-inhibition must be further studied.Interestingly, the observed stimulation of CaRas1 nucleotide exchange by CaCdc25 was unusually high, suggesting that this GEF is optimally poised for CaRas1 activation. In fact, the nucleotide exchange activity of CaCdc25 is 5 to 2,000-fold higher than that of characterized human GEFs -39 Ta. This hiC. albicans. In particular, the identification of a short peptide that effectively inhibits the activity of this GEF, constitutes a valuable starting point for the design and development of specific inhibitors with potential antifungal properties based on this privileged scaffold.Altogether, the fungi-related features of the sole Ras1-specific GEF identified so far  highlighMethods are summarized below and described in detail in Escherichia coli BL21 (DE3) or E. coli Rosetta (DE3) after induction with IPTG at 37°C or 20°C. Proteins were purified by immobilized-metal affinity chromatography and size-exclusion chromatography.CaRas1-FL, CaRas1-213, G-domain, and the catalytic region of CaCdc25 and its variants H1234A, H1234D, and H1234E were expressed in Diffraction data were collected at beamline BL13-XALOC of ALBA synchrotron. X-ray diffraction data collection and processing statistics are summarized in Recombinant CaCdc25 (REM-CAT tandem) was titrated with CaRas1 proteins CaRas1-FL and G-domain using a MicroCal VP-ITC system . Data were visualized and analyzed with Origin 7 software using a single binding site model. CD spectra of CaRas1 proteins were recorded using a Jasco J-815 CD spectrometer in a 0.1 cm quartz cuvette for far-UV CD spectroscopy.Guanine nucleotide exchange activity of CaRas1 proteins in absence and in presence of wild-type CaCdc25 and variants was measured by following changes in the fluorescence of the GDP derivative Mant-dGDP (Jena Bioscience GmbH) , 60 on aA peptide corresponding to the region 837–858 (TIINYATRVMQDNFDVQLLLVE) of CaCdc25 and two control peptides with scrambled sequence and similar amino acid composition as peptide 837–858 were custom synthesized . The effect of these synthetic peptides on nucleotide exchange assays was assessed.SAXS data were measured at the P12 beamline of the EMBL at the Deutsches Elektronen-Synchrotron . Data were processed and analyzed with the ATSAS 3.0 package .


Dear Editor,6-methyladenine (6mA) modifi-cation, which was found in bacteria, archaea, viruses, and eukaryotes ranging from unicellular protists, fungi, and ciliates to multicellular plants and animals, has been proposed to be potentially associated with some important biological processes such as gene expression regulation and oncogenic pathways /α-ketoglutarate (α-KG)-dependent dioxygenases, which catalyze demethylation of various substrates including DNAs, RNAs, and proteins  and single-site methylated single-stranded DNA (ssDNA) . We founC. elegans. Mass spectrometric analysis of endogenous actin extracted from C. elegans cells identified a mono-methylation modification on Lys85  as a type of post-translational modification in C. elegans (ok3133), suggesting that NMAD-1 is associated with the demethylation of actin K85me1 in C. elegans  of 10.7 ± 1.7 μM and 1.07 ± 0.11 μM, respectively  in the presence of Mg2+ and NOG at 2.20 Å resolution  at the N-terminus to further facilitate the crystallization. In the crystal structure, MBP contributes to crystal packing but does not interfere with the cofactor binding or constrain the overall structure of NMAD-1  , and the minor β-sheet by three antiparallel β-strands (β13–β10–β11). The helices η3 and η5 and helices η4 and α4 locate on two sides of the jelly-roll fold, respectively. The large α-helix α3, together with the small 310 helix η2, stacks and buttresses the major β-sheet from the back. The DSBH domain is surrounded by the NTE domain, the NRL domain, and the CTD, with the NRL domain and the CTD packing on one side and the NTE domain on the opposite side  domain, a potential nucleotide-recognition lid (NRL) domain, a double-stranded β helix (DSBH) domain, and a C-terminal domain (CTD); the NRL domain contains the Flip1 and Flip2 motifs . Similar (η2–η5) . The sevite side .2+ and NOG bind to the active site with well-defined electron density  as well as two oxygen atoms of NOG and a water molecule  in vitro and its deficiency dramatically increases actin methylation level in vivo. Our structural and biochemical data revealed that NMAD-1 assumes a typical DSBH domain and contains a highly conserved catalytic site for the metal ion and cofactor binding and actin demethylation. The unique NRL domain and the CTD play critical roles in the substrate selectivity. Our research highlights NMAD-1 as an actin K85me1 demethylase in nematode and provides molecular insights into the catalytic mechanism, which paves the way for further investigation of the functional roles and mechanisms of NMAD-1 in actin K85me1 maintenance and DNA replication and repair. Whether the binding of NMAD-1 to DNA repair and replication machinery relies on actin K85me1 requires further investigation.In summary, we found that NMAD-1 is able to directly bind to and demethylate [mjad008_Supplemental_FileClick here for additional data file.


In underground mining, the dip angle is one of the widely recognized factors that cause the asymmetric deformation of the goaf/stope roof, but characterizing the degree of asymmetric roof deformation is still a challenge. The goal of this research is to try to solve this problem with a theoretical model and numerical method. In an inclined ore seam, the mining load produces both normal and tangential effects on the inclined roof. A theoretical model was developed employing thin plate theory for enabling describe the asymmetric deformation of the roof caused by inclination. The proposed model describes not only the bending deformation state of the roof but also the deformation characteristics. Subsequently, the law of asymmetric deformation of roofs with varying inclinations was presented by numerical method. Under the same conditions, the numerical results of the asymmetric deformation of the roof are consistent with the theoretical results. Finally, the degree of asymmetrical deformation was characterized and quantified by the distance between the maximum subsidence point and the center of the roof. There exist three modes of asymmetric deformation, which are controlled by both dip angle and in-situ stress ratio. The results show that the shear load caused by dip angle is the root cause of asymmetric deformation of the roof. This study provides a theoretical basis for the asymmetric deformation control of the inclined roof. Room and pillar mining is one of the essential methods for underground mining, which features a series of temporary or permanent pillars to support the overlying rock pressure and maintain the stability of the roof. In this mining method, workers conduct mining activities in a space (stope) supported by natural or artificial pillars. In the process, the space (stope) must be stable to ensure the safe mining of the ore body. After the ore body mining is completed, this space (goaf) also needs to be durable to control the surface collapse caused by the movement of the rock strata. Once the pillars in the goaf are destabilized, or the exposed area of the roof is too large, it may induce the deformation and instability of the roof and bring severe challenges to the safety of underground production. Therefore, studying the deformation characteristics of the stope/goaf roof is one of the significant ways to reveal its stability.1 investigated the destabilization mechanism and stability control in stope mining roadway below the remaining coal pillars based on theoretical analysis, numerical simulation, and industrial testing. They found the law of stress transfer and proposed the corresponding support technology. The paraffin was melted to simulate the mining process in an actual three-dimensional physical experiment; the results show that the floor and roof deformation is symmetric, and the maximum flexure point is in the center of the excavation area2. The field monitoring and numerical method were used to explore deformation and failure patterns of gob-side entry driving heading adjacent and concluded theoretical criteria. Based on these results, a series of preventive techniques were developed to control the roof3. Abousleiman et al.4 investigated deformation mechanics and parametric sensitivities through the discrete element method. The results of parametric sensitivities confirmed that the self-supporting capacity is greatly influenced by entry depth and fine-scale bedding and then is determined by the stiffness and strength of intact materials. Zhu et al.5 carried out two physical similarity experiments to find the failure propagation of pillars and roofs. They divided it into two stages: the first stage is steady movement, and the second stage is the instability propagation stage. Roof collapse due to inefficient support of rock bolts is studied by field observations, numerical simulation, and lab tests. According to the situation, the improved support systems were designed to prevent such accidents7. In room and pillar mining, the remaining pillars will aggravate the damage to the roof. Thus, it is worthwhile to explore how the pillars affect the roof 9. Wang et al.11 drew stress circles of the entry roof in each stage of the whole life cycle based on the Mohr-Coulomb theory to judge whether the roof is damaged according to the strength envelope curve. The large deformation of the surrounding rock is not only affected by the stress but also by the movement of the upper roof. Sinha et al.13 proposed that three separate reinforcement factors are used to evaluate roof support plans. Mondal et al.14 established a predicted model that described the correlation between the cut-out distance of the continuous miner and the roof convergence through numerical simulations. This model was verified by observed data to determine the optimal cut-out distance. Chai15 and Pan et al.16 reveal the mechanism of ground pressure behavior induced by roof strata deformation using field testing technology and theoretical method.In flat seam mining, physical experiments, numerical simulations, and field monitoring are performed to reveal the deformation and failure modes. Fu et al.17 evaluated the stability of roadways with a hard roof by beam theory and numerical method and compared it with field monitoring. Besides, the roof is modeled as an Euler-Bernoulli beam clamped by pillars and rocks to deduce the roof fracture process18. Zhang et al.19 explored failure and deformation characteristics in working face end by numerical simulation and thin plate theory. As the advance of the working face, the failure of the roof at the end of the goaf is periodic. According to the breaking characteristics, a thin plate model with three fixed sides and one free side is established. As the excavation of the ore body, the roof, regarded as a thin plate, is subjected to different boundary conditions. The stress distribution and fracture modes will change under different supports21. Ma et al.22 considered that pressure arch theory is used to derive the load borne by the goaf roof. Based on this load, the roof is modeled as a thin rectangular plate with four fixed support points to determine the optimum thickness. The thin plate theory is no longer applicable to this situation if the thickness is thick enough. These studies are aimed at the flat seam.In terms of theoretical research on roof deformation, Sun et al.23 and mining projects24. Affected by the inclination of the orebody, the surrounding rock behavior of inclined orebody mining is different from that of horizontal orebody26, such as stress state, deformation law, and failure mode. Das et al.27 studied the influence of dip angle on the mechanical behavior of pillar and roof, the results show shearing effect and stress concentration is comparatively more severe at the dip side working. Li et al.28 used physical simulation and theoretical analysis to research roof structure stability formed by a three-hinged arch. With the dip angle increasing, the possibility of the roof structure becoming unstable due to large deformation decreases significantly, while the probability of the roof structure’s sliding instability above the tailgate increases. And a detailed field survey was proposed to evaluate the stability of inclined bedded surrounding rock mass and identify the high risking regions29. The influence of inclination on the deformation and failure of the roof is negligible32. Though existing research have revealed that the roof forms symmetrically in the strike direction and asymmetrical bending in the dip direction, the degree of dip influence on the asymmetric deformation of roofs needs to be further studied.In general, the dip angle of geological strata will influence rock engineering characterizations, which is a recognized phenomenon in tunnelThe goal of this research is to solve the issue mentioned above by combining theoretical and numerical methods. The theoretical model of asymmetric deformation of an inclined roof is developed by thin plate theory. Then the characteristics of roof deformation with variable dip angle are studied by numerical method. The numerical results and theoretical model results are compared and analyzed to look forward to the inclination effect of the roof asymmetric deformation mechanism. In order to further explore the law of asymmetric deformation, the coupling effects of in-situ stress ratio and dip angle on the magnitude and degree of roof deformation are studied. Finally, three deformation modes are proposed.In underground mining, the roof of the goaf/stope could be regarded as a thin plate, and then the thin plate theory is employed to investigate the deformation law. Existing research has proved that the stope/goaf roof mainly undergoes the expected load and bends symmetrically in flat seam mining. When the room and pillar method is used to extract the inclined ore seam, the goaf/stope roof is subjected to the load of the overburden rock mass, the horizontal lateral pressure, and the support of pillars, as shown in Fig. To simplify the model and calculations, some assumptions need to be made.(1) The pillars will not yield under combined compression-shear loading and be regarded as an elastic foundation. (2) There is no large crack around the roof; the boundary condition is regarded as fixed support. (3) The tangential load only deforms the roof along the inclined direction and ignores the shear deformation.33, the stress distribution on the four sides of the roof need not precisely satisfy the stress boundary conditions as long as the resultant force meets. Then,σx represents the normal stress in the x direction, h is the thickness of the roof, and FTx represents the resultant force of normal stress on the surface in the x direction. Similarly, FTy is the resultant force of normal stress on the surface in the y direction, and FTxy are resultant force of shear stress around the boundary, as shown in Fig. qn is the support loads of the pillars, and its expression isn is the number of pillars; Ap is the top surface area of a pillar; Ar is the area of the roof; L is the height of the pillar; Ep is the elastic modulus of pillar material, and w represents the deflection of the roof.When the roof is subjected to normal load only, there is lateral ground pressure along the direction of roof thickness and the lower surface is subjected to the support force of the mine pillars. According to St. Venant’s theoryentclass1pt{minimaD is bending stiffness, and it is obtained asEr is the elastic modulus of the roof rock mass; μ is the Poisson’s ratio of the roof.According to the thin plate theory, the equilibrium equation of the roof is given in the differential form,From the assumption (2), the boundary condition is considered as fixed support, and the boundary condition is expressed in terms of deflection asC is constant, and wm is an arbitrary function to ensure that the deflection satisfies the displacement boundary condition.Let the roof deflection equation be expressed as follows,Vε is the deformation energy of the roof. Under the boundary condition of fixed support, the deformation energy could be given as,In addition, the Ritz method establishes the variational equation of the roof.a and b are half the length and width of the roof, respectively.Ulteriorly, the functional expression of the deflection isC is obtained by substituting Eqs. (The expression of parameter ing Eqs.  and 9)  C is obting Eqs. ,10\documThen, substituting Eqs.  and 11)11) into According to assumption (3), on the boundary opposite to the direction of tangential stress , the ground stress will prevent the roof from moving, on the other boundary, as the new displacement space caused by the roof deformation, the rear rock layer does not affect the longitude deformation under the ground stress. For the transverse flexural deformation of the roof, considering the clamping effect of the upper and lower strata, the roof rock has no deformational space, thus, is fixed around. The longitudinal deformation is the deformation of the roof strata itself, which needs further solving. Since the longitudinal deformation is minimal, the influence of the rock mass at the boundary of the strike is ignored. Therefore, the equilibrium equation of the roof is as follows,Fx obtained from the boundary condition isThe From physical and geometric equations in elasticity, the expressions are given as,By combining Eqs.  and 16)16), the x + x0) in the inclined direction. At this time, the deflection equation of the roof under combined compression-shear load is written asC is determined by Eq. .Equation  indicated by Eq. , and thed by Eq. . From Eqθ is the dip angle of the seam.Further, the expression of vertical displacement is obtained from Eq. ,19\documA gently inclined phosphate deposit is regarded as the research object to study the dip effect on the deformation behavior of the roof by numerical method. The phosphate ore layer is located at the Doushantuo Formation of the Upper Aurignacian. The orebody is stratified and produced in line with the occurrence of the strata, without horse-stone. The occurrence elevation of the ore layer is from 480 to 1130 m; the buried depth is about 250–600 m, and the dip of the seam varies from 0° to 25°. And the thickness of the seam is equal to from 0.55 to 9.13 m. The roof is dolomite containing phosphorus bands and phosphorus nodules, and the rock layer is medium-thick and stable in distribution. Some areas of the floor are mudstone and shale containing banded phosphorite or phosphorus masses, and the rest are phosphate-bearing powdery dolomite. According to the occurrence characteristics of the ore layer, the room and pillar method was selected. A rip pillar of 5 m in width is left between the ore blocks, the top and bottom pillars are arranged along the direction, the top pillar is equal to 5 m, and the bottom pillar is 5 m. The sectional transportation roadway is arranged in the top and bottom pillars. The room is arranged horizontally along the strike in the block, and regular point pillars are left in the goaf. The length and width of the point pillar are 5 m × 5 m, the interval along the strike is equal to 10 m, and the interval along the dip is 8 m, as shown in Fig. 35 is used to estimate the strength parameters of rock mass and is given as,The Hoek-Brown criterionσmc and tensile strength σmt of rock mass are obtained by making σ3 = 0 and σ1 = 0, respectively.In the above formula, the uniaxial compressive strength m, s, and RMR is given as,mi is a constant for intact rock, the strength of rock mass can be evaluated by Eqs. (And the relationship between the constant  by Eqs.  ~ (22).36.Em represents the elastic modulus of rock mass, Ei represents the elastic modulus of intact rock; and D is the blasting influence coefficient (0 ~ 1).In addition, the elastic modulus of rock mass is calculated by the empirical equation proposed by Hoek and DiederichsAccording to the mine geological report and laboratory test results, Eqs.  ~ (23) a3D software 37 is used to establish numerical deposit models with dip angles of 0°, 10°, 20°, 30°, and 40°, respectively. To the dip of the seam is the negative x-axis. The strike length of the stope is 85 m, and the width along the inclined direction is 47 m. There are 15 pillars left in the goaf, whose length and width are 5 m × 5 m, and the height of the pillar is 6 m. The deposit model is divided into 8 layers from bottom to top, and the model dimensions are 425 m × 282 m × 208 m, as shown in Fig. To explore the dip effect on the displacement of the goaf roof, the FLACThe average overlying strata thickness of the seam is 300 m. The overlying rock load is about 6.7 MPa, and the ratio of in-situ stress is equal to 1.2, then the horizontal ground stress applied is 8.2 MPa. The fixed support at the bottom and around the model prevents the model from moving. The model is assigned to the Mohr-Coulomb model.x-axis. The curves on the right side of the contour are vertical displacements on the two lines (V1 and V2) along the strike direction. The curves below the contour are vertical displacements on the four lines  along the inclination direction. When the dip angle is equal to 0°, the vertical displacement of the roof is more than 18 cm. The negative sign indicates the displacement direction. The vertical displacement in the center of the roof is the largest and reaches 21 cm. Taking the central axis of the roof as the center, the displacement in the strike direction and inclination direction are equal, respectively, and the distribution law is consistent, as shown in Fig. Figure θ is equal to 0°, the displacement mainly occurs in the vertical direction, and the total displacement is similar to the vertical displacement. As the increase of dip angle, the total displacement increases appreciably, while the vertical displacement changes little relatively. The deformation law is in accordance with that in the vertical direction, and the total displacement continues to reflect symmetry along the strike direction and asymmetry along the inclination direction.Figure x = 136 m, the displacement of the left side increases with the increase of the dip angle, while the displacement of the right decreases with the increase of the dip angle, as shown in Fig. Figures Figures According to the decomposition of force, the normal load acting on the roof is obtained,σv represents the vertical in-situ stress before mining; σh represents the horizontal in-situ stress before mining.In the same way, the tangential load acting on the roof is obtained:a = 23.5 m, b = 42.5 m, Eq. a = 23.5 rom Eqs.  and 25)a = 23.5 x-axis, namely the inclination upward direction, as shown in Fig. The contour map of the roof can be drawn from Eq. , as showxoff is the offset distance; Δxmax is the maximum longitudinal compression of the roof boundary, i.e., the boundary end with free deformation space; Δx0 is the distance between the geometrical center before and after deformation, i.e., the offset distance of the geometrical center. If the offset distance is larger, the asymmetrical deformation is more serious; on the contrary, the asymmetrical deformation is smaller.To analyze the asymmetry of the roof deformation, the distance between the maximum subsidence point of the roof and the center of the roof is used to characterize the degree of asymmetrical deformation. This distance is called “the offset distance,” as shown in Fig. θ = 45° as the turning point, when θ is smaller than 45°, the offset distance increases as the dip angle increases. Conversely, when θ is greater than 45°, the offset distance moves backward as the dip angle increases. It can be concluded from Eq.  is obtained,To conclude the variation law of vertical displacement with inclination angle, the ratio of in-situ stress is regarded as a constant, then the differential of (σv is constant and has no influence on the variation law of the derivative. LetThe in-situ stress θ ∈ , the slope at the two ends,Due to the inclination angle θ = 0°, the vertical displacement slope equals 0. And when θ = 90°, the slope is associated with the ratio of in-situ stress. This law is consistent with the variation as shown in Fig. Obviously, when Let the derivative in Eq.  be equalλ is equal to 1.5 at the left branch curve, and the maximum is equal to 0 at the right branch curve. The results show that Eq. (λ, the maximum vertical displacement increases or decreases with the addition of inclination angle. When the ratio of in-situ stress is between 0 and 1.5, the maximum vertical displacement of the roof decreases with the increase of inclination angle.The function curve of Eq.  was presthat Eq.  has two that Eq. . The casλ is equal to 1.0. when λ is greater than 1.0, the maximum vertical displacement shifts downward and vice versa. As far as the variation of the maximum vertical displacement is concerned (As shown in Fig. λ is equal to 1.5 is the demarcation point of the maximum vertical displacement. When λ is greater than 1.5, the maximum vertical displacement increases and decreases with the change in the inclination angle. When λ is less than 1.5, the maximum vertical displacement decreases with the increase of the inclination angle. Thus, to directly present the pattern of asymmetric deformation of the roof in the above law, when the ratio of in-situ stress λ is equal to 0.6, 1.4, and 2.0, respectively, the function graph was drawn, i.e., the vertical displacement along the centerline of the roof, as shown in Fig. x-axis, namely the roof tilt upward. When the ratio of in-situ stress is greater than 1.0, the maximum vertical displacement point moves in the negative direction of the x-axis, namely the tilt down, as shown in Fig. As the aforementioned show that the roof asymmetrical deformation mode will be determined by the ratio of in-situ stress and inclination angle, and the mode of asymmetric deformation of the roof will be presented. In terms of the maximum vertical displacement deviating from the central position of the roof (As shown in Fig. A theoretical model was developed to describe the asymmetric deformation of the roof caused by inclination. The proposed model incorporates the deformation effect of the roof under the combined action of normal compression load and tangential shear load. Normal compression load bends the roof, while the tangential shear load causes the roof deformation along the inclined direction and changes the symmetry of the roof deformation. These two kinds of deformation effects are superimposed together, resulting in asymmetric roof deformation.The numerical method was used to investigate the asymmetric deformation characteristics of the roof with varying dip angles. The vertical displacement changes less, and total displacement increases faster as the increase of dip angle. The influence of horizontal displacement is small in the goaf with a small inclination, but the closure of the goaf with a large inclination arises from it. In terms of displacement distributions, inclination leads to the displacement of the roof being symmetrical along the strike and asymmetrical along the inclined direction. The numerical results were compared with the theoretical model, which shows that the roof deformation laws obtained by the two methods are consistent.The distance between the maximum subsidence point and the center of the roof was defined to characterize the degree of asymmetric deformation, the larger the distance is, the greater the degree of asymmetric deformation is; on the contrary, the smaller the asymmetric deformation. When λ > 1.0, the maximum deformation position shifts downward along the roof inclination, and the greater the degree of asymmetric deformation is with the increase of the ratio of in-situ stress. Similarly, when λ < 1.0, the maximum deformation position shifts upward to the tilt, and the smaller the initial stress ratio, the greater the degree of asymmetric deformation. When λ is constant, the degree of asymmetric deformation increases at first and then decreases with the increase of inclination angle. The degree of asymmetric deformation is the most when the dip angle is equal to 45°.There exist three modes of asymmetric deformation, which are determined by both dip angle and in-situ stress ratio λ. When λ < 1.0, the maximum subsidence position shifts upward along the dip, and the maximum vertical displacement decreases with the increase of the dip angle. When 1.0 < λ < 1.5, the maximum subsidence position migrates downward along the dip, and the maximum vertical displacement decreases with the inclination increase. When λ > 1.5, the maximum subsidence position is shifted downward along the dip. With the rise of the dip angle, the maximum vertical displacement gradually increases and then decreases.In this research, the dip effect mechanism of asymmetric deformation of the goaf roof was investigated by theoretical and numerical methods. A theoretical model was proposed for describing the asymmetric deformation of the roof. Then the degree of asymmetric deformation was characterized, and several modes of asymmetric deformation were revealed. The main conclusions have been summarized as followings.


In this work, the changes in the deformation rate of engineered wood flooring were in focus with cold-pressing, response surface methodology, and adaptive network-based fuzzy inference system were used to explore the relationship between deformation rate and processing parameters, including adhesive spreading rate, pressing time, and pressing pressure. According to the results, the deformation rate was positively related to pressing time, while it increased first and then decreased with both the increase of adhesive spreading rate and pressing pressure. Meanwhile, a mathematical model was developed, and the significant influence of each term on the deformation rate was analyzed. This model had high feasibility and can be used to describe the relationship between the deformation rate and processing parameters. Furthermore, an adaptive network-based fuzzy inference system model was established. It has higher accuracy than that of the response surface methodology model, and it can be used for predicting deformation rate and optimizing processing parameters. Finally, an optimal processing conditions with the lowest deformation rate was determined as follows: 147 g/m Engineered wood flooring is a new wooden product originating in Northern Europe. With the rapid development of preparation technology, engineered wood flooring is popular globally because of its stable quality, beautiful texture, and easy installation and maintenance , 2. EngiIn the industrial manufacturing of engineered wood flooring, the warping deformation is an important indicator for judging its quality of dimensional stability , 6, 7. WResponse surface methodology (RSM) is a collection of mathematical and statistical techniques, and it is widely adopted for modeling and analyzing . RSM wasAdaptive Network-based Fuzzy Inference System (ANFIS) was first proposed by Jang  based onControlling the deformation of the engineered wood flooring is the key to improving product quality. The related reports show that RSM  and ANIFTo this end, this work aims to improve the quality of engineered wood flooring. RSM and ANFIS were used to explore the changes in deformation rate at different processing conditions, and the optimal processing parameters were determined. This work is hoped to provide scientific support for the industrial processing of engineered wood flooring.Betula spp.) was used as the surface board, and the substrate material was made of Poplar (Populus sp.) with different thicknesses. Meanwhile, polymer isocyanate adhesive (API) was prepared by , it was used for the preparation of engineered wood flooring.As shown in RSM and ANFIS were used to explore the changes in deformation rate at different conditions . Table 2In this work, Sugeno-ANFIS was adoptO1,i is the deformation rate, and μAi(x1), μBi-2(x2), and μCi-4(x3) are Gaussian membership functions.In the fuzzification layer, the input variable is converted into the membership of each fuzzy set, and each node is represented by a node function of The product layer shows the rule applicability, where the output of each node is the product of the input signals  20]. Me. Me20]. In the layer of defuzzification, the crisp values can be obtained from the fuzzy values with the adaptive nodes by In the layer of the output layer, the deformation rate was used as the output variable and was acquired by fw is the deformation rate, Hmax stands for the maximum chord height in mm, and W donates the width in mm of engineered wood flooring. Each processing combination was repeated five times, and the average values were used to describe the deformation rate of engineered wood flooring.Measurement standards for the deformation rate of engineered wood flooring were performed according to the GB/T 18103–2013 . The deformation rate can be obtained based on fw is the deformation rate in %, R stands for the adhesive spreading rate in g/m2, and T donates the pressing time in s, and P is the pressing pressure in MPa.Changes in the deformation rate of engineered wood flooring were analyzed by using RSM, and a quadratic model was developed, as shown in R2 and Adjusted-R2 were used to make fit statistics as given in R2 and Adjusted-R2 were all close to 1. They all showed a good correlation between predicted and measured deformation rate values.In order to verify the feasibility of the developed model, standard deviation, coefficient of variation, Furthermore, the correlation graph for the predicted and actual deformation rate is displayed in i.e., If the p-value of a term is lower than 0.05, this term can be considered as significant, otherwise insignificant [The primary assumption for conducting analysis of variance (ANOVA)  is that nificant . Thus, tR, T and P, two-level interaction effects of R×P and T×P, and products of R2, T2 and P2, they were all less than 0.05, it can be obtained that those terms had a significant impact on the deformation rate. However, only the two-level interaction effects of R×T is higher than 0.05, and it has the insignificant contribution to the deformation rate.Furthermore, the values of variables of Meanwhile, it can be obtained that the deformation rate was positively related to the pressing time. With the extension of cold pressing time, the adhesive had enough time to penetrate, forming a continuous and durable adhesive layer. The substrate and surface board were well bonded, and the dimensional stability increased. Finally, the changes in deformation rate also increased first and then decreased with the increase of pressing pressure. The increased pressing pressure made the adhesive layer fully in contact with the boards’ surfaces, resulting in a lower deformation rate. However, as the pressing pressure continued to increase, the higher pressing pressure may destroy the wood fiber with a counterproductive effect. Thus, the deformation rate increased first and then decreased as the pressing pressure increased.−3, less than 0.001. Meanwhile, based on the predicted results with input-output pairs by the ANFIS model, it can be found that the predicted deformation rate values were close to the actual values, and its average error was equal to 1.50×10−7, which is lower than that of the RSM model. Thus, it can be obtained that the ANFIS model has higher accuracy than the RSM model, and it can be used to describe the relationship between the deformation rate and processing variables.According to the experimental results in 2, pressing time in s, and pressing pressure in MPa, and the last column is the output result of the deformation rate. Following this reasoning process, inferences can be made based on input parameters regarding the ANFIS’s predictive function. The height of the yellow area within the triangle stands for the membership values of fuzzy sets. Based on the ANFIS result, when the input processing variables of adhesive spreading rate, pressing time, and pressing pressure were equal to 155 g/m2, 12s, and 1.2 MPa, respectively, the third proportion of reasoning rule is lowest with the deformation rate of 0.09.The Sugeno inference system  was used2 adhesive spreading rate, 12s pressing time and 1.2 MPa pressing pressure, and at those variables, the actual average deformation was equal to 0.0843%. It can be calculated that its error rate was 6.88%. According to the ANFIS model, when at the processing variables of 155 g/m2 adhesive spreading rate, 12s pressing time, and 1.2 MPa pressing pressure, the predicted and actual lowest deformation rate can be obtained as 0.0864% and 0.0829%, respectively. The ANIFS model had a lower error rate (4.22%) than the RSM model (6.88%). This result is consistent with the previous result in the section 3.2.In the industrial processing of engineered wood flooring, the deformation rate is crucial for the evaluation index. It directly influences the final product quality , 32. Thu2, pressing time of 12s, and pressing pressure of 1.2 MPa. Meanwhile, the combination of parameters was proposed to be applied in the industrial processing of engineered wood flooring with lower deformation rate and production costs.According to the measurement standard of engineered wood flooring , the deformation rate in the width direction must be less than or equal to 0.02%, and both the deformation rates results optimized by RSM and ANFIS models meet the standards of engineered wood flooring. Considering production costs, the optimal processing conditions were determined: adhesive spreading rate of 147 g/mIn this work, a cold-pressing experiment was carried out to explore the deformation rate of engineered wood flooring, and RSM and ANFIS were used to investigate the effect of adhesive spreading rate, pressing time, and pressure on the deformation rate. The main conclusions are listed as follows:The deformation rate increased first and then decreased with both the increase of adhesive spreading rate and pressing pressure, and it showed an increasing trend with the increase of pressing time.R, T, and P, the two-level interaction effects of R×P and T×P, and the products of R2, T2, and P significantly impacted the deformation rate.A mathematical model was developed using RSM, and it has high feasibility and can be used to describe the relationship between the deformation rate and processing parameters. In this model, the terms of An ANFIS model was obtained, which has higher accuracy than the RSM model. ANFIS model can also be adopted for the prediction of deformation rate and the optimization of processing parameters.2, pressing time was 12s, and pressing pressure was 1.2 MPa. This combination of processing parameters was proposed to be used in manufacturing engineered wood flooring for higher product quality and lower production costs.Comprehensive comparison of the RSM and ANIFS model results, the optimal processing conditions were determined with the lowest deformation rate, where the adhesive spreading rate was 147 g/m


This essay reexamines molecular evidence supporting the existence of the ‘preisthmus’, a caudal midbrain domain present in vertebrates (studied here in the mouse). It is thought to derive from the embryonic m2 mesomere and appears intercalated between the isthmus  and the inferior colliculus . Among a substantial list of gene expression mappings examined from the Allen Developing and Adult Brain Atlases, a number of quite consistent selective positive markers, plus some neatly negative markers, were followed across embryonic stages E11.5, E13.5, E15.5, E18.5, and several postnatal stages up to the adult brain. Both alar and basal subdomains of this transverse territory were explored and illustrated. It is argued that the peculiar molecular and structural profile of the preisthmus is due to its position as rostrally adjacent to the isthmic organizer, where high levels of both FGF8 and WNT1 morphogens must exist at early embryonic stages. Isthmic patterning of the midbrain is discussed in this context. Studies of the effects of the isthmic morphogens usually do not attend to the largely unknown preisthmic complex. The adult alar derivatives of the preisthmus were confirmed to comprise a specific preisthmic sector of the periaqueductal gray, an intermediate stratum represented by the classic cuneiform nucleus, and a superficial stratum containing the subbrachial nucleus. The basal derivatives, occupying a narrow retrorubral domain intercalated between the oculomotor and trochlear motor nuclei, include dopaminergic and serotonergic neurons, as well as a variety of peptidergic neuron types. The isthmic organizer is in a way complex, because it presents two different but adjacent morphogen sources—releasing FGF8 and WNT1, respectively—on its isthmic and midbrain sides , forms Fgf8; . The who protein . However protein , the org protein ,7. The i protein ,8. It wa protein ,10,11,12Ulterior studies have elaborated on the hypothesis that the observed isthmic induction effects were due to release of the FGF8 morphogen. Collagen microbeads impregnated with a solution of FGF8 protein were found to also induce cerebellar primordia at the competent sites cited above , is preisthmus )After some 40 years of progress in these aspects, it seems odd that there still exists a neuromeric unit—the m2 mesomere that occupies us here—that is largely unknown by embryologists and anatomists, even though it was first postulated 100 years ago  and glimOtx2 as defining the caudal boundary of the midbrain, we decided to map the position of the problematic ‘falsely isthmic’ midbrain nucleus relative to the Otx2 boundary, adding other local markers such as Fgf8, Gbx2, and Pax2. These data revealed that indeed the nucleus was molecularly mesencephalic, that is, Otx2-positive. It lay rostral to the Otx2-negative isthmic derivatives, but, surprisingly, caudal to the structurally and molecularly distinct auditory structures . We noticed that some other structures seemed to be in the same situation and could be jointly labeled selectively with Pax2 (not so with the auditory midbrain and the rest of m1).Eventually, Hidalgo-Sánchez et al.  applied novel conclusion that our Otx2/Pax2-positive domain caudal to the torus had to be the missing brain domain derived from the m2 mesomere Dach1, EbOn the whole, the anatomic assessment of the preisthmus first reported by Hidalgo-Sánchez et al.  in the cOtx2, En1, and Pax5 and resembled the preisthmic profile . The region first loses the intraventricular protrusions a–f,j andOtx2 at E13.5, when the IC domain has already reduced its earlier Otx2 signal to its ventricular zone . However, at E15.5 the Tcf7l2-positive IC mantle starts to extend towards the toral area, finally occupying it fully over E16.5 and E17.5, thus creating the pattern shown at E18.5 (Allen data). We thus think that the most reasonable interpretation is that the toral area belongs to the IC within m1, being its caudalmost, dorsalmost, and latest differentiated part. Possibly due to its closeness to the isthmic organizer, it may be subjected at early stages to anti-neurogenic signaling, perhaps vehiculated by the En1 and Pax5 genes, if not by Wnt1, and perhaps also making it susceptible to subsequent postnatal degeneration.It may be discussed whether the toral region should be ascribed to the dorsal end of the preisthmus within m2 or whether it represents merely a molecularly peculiar extension of the inferior colliculus within the caudalmost dorsal m1. The early pattern of lar zone a–g, suggimordium a,b, whilral area aa,bb. AtOur studies enrich available genoarchitectural knowledge on the developing preisthmic midbrain domain in the mouse and establish on a strong basis its early developmental boundaries with regard to both the isthmic hindbrain and the rest of the midbrain, starting with the rostrally adjacent auditory midbrain and the rubral m1 tegmentum. The possibility that the preisthmus contains the progeny of the m2 mesomere postulated by von Kupffer, Palmgren, and Vaage ,18,32 is


Using hypothesis-learning-driven automated scanning probe microscopy (SPM), we explore the bias-induced transformations that underpin the functionality of broad classes of devices and materials from batteries and memristors to ferroelectrics and antiferroelectrics. Optimization and design of these materials require probing the mechanisms of these transformations on the nanometer scale as a function of a broad range of control parameters, leading to experimentally intractable scenarios. Meanwhile, often these behaviors are understood within potentially competing theoretical hypotheses. Here, we develop a hypothesis list covering possible limiting scenarios for domain growth in ferroelectric materials, including thermodynamic, domain-wall pinning, and screening limited. The hypothesis-driven SPM autonomously identifies the mechanisms of bias-induced domain switching, and the results indicate that domain growth is ruled by kinetic control. We note that the hypothesis learning can be broadly used in other automated experiment settings.  •Hypothesis learning combines machine learning with physical hypotheses•Hypothesis learning enables physical discovery in the experiment•Hypothesis learning is implemented in operating scanning probe microscopy•Hypothesis learning identifies the ferroelectric domain growth mechanism autonomously The need for automated experimentation has been recently recognized across multiple areas of instrument-based sciences, including X-ray scattering, electron, and scanning probe microscopy, necessitating the development of algorithms for navigating multidimensional compositional or processing spaces. Autonomous discovery of physical laws via experiment has emerged as a rapidly emerging topic for machine learning in physical sciences. Here, we report the development of a hypothesis-learning-based automated experiment, which autonomously identifies the mechanism behind materials’ response during operating experiments. This approach can be applied to a broad range of physical and chemical experiments with relatively low-dimensional control parameter space and for which the possible competing models of the system behavior that ideally cover the full range of physical eventualities are known. Hypothesis-learning-driven automated scanning probe microscopy allows physical discovery during experiments, where the hypothesis learning algorithm implemented on an operating microscope identifies the physical mechanism behind the material’s response. In the correlative models, complications arise due to the out-of-distribution shift effects, which are explored both in model examples and in applications in medical imaging and automated driving. Secondly, compared with classical ML problems, physical sciences offer a challenge of active learning with very limited experimental budget. However, it is also well understood that in physical sciences, the nature of scientific domain offers a rich set of prior knowledge in forms ranging from known physical laws and constraints and expected parameter values to difficult-to-define physical intuition.,,,,Particularly of interest are the applications of active learning where the ML agent interacts with a physical object via a suitable measurement tool, i.e., an automated experiment. The need for automated experimentation has been recently recognized across multiple areas of instrument-based sciences, including X-ray scattering, electron, and scanning probe microscopy.The important limitation of the classical BO strategies with the Gaussian process is the use of the non-parametric kernel-based models. In this case, the internal correlations across the data space are used to select the locations for a new experiment. However, these models do not contain any specific physical assumptions or relationships. Hence, in many cases, the efficiency of BO-based methods is only within an order of magnitude from classical grid search-based strategies. At the same time, often, the behaviors of these systems are understood within potentially competing theoretical models or hypotheses.Recently, we have introduced the approach for physics-informed BO in automated experiments, referred to as hypothesis learning.Here, we illustrate the hypothesis-learning-based automated experiment for the explorations of the domain-switching mechanisms in classical ferroelectric materials. While shown for a model system, this approach is more general and can be broadly used for exploration of other scanning probe microscopy (SPM)-based electrochemical reactions and for automated experimentation in scattering, microscopy, and materials synthesis.The bedrock element of physical sciences is the validated set of quantitative symbolic relationships between the physical parameters, numerical constants, and observables. Examples range from the fundamental laws of the Newtonian mechanics to expressions defining current-voltage relationships in semiconductors. In certain cases, these relationships are derived from fundamental laws and symmetries. In others, they represent a useful empirical generalization, valid under specific conditions. Using these relationships underpins all areas of physics research, and deriving these relationships is often equated with the understanding of the relevant physical mechanisms.The research process often involves iterative cycles between the acquisition of the experimental data and their interpretation in terms of specific models. In some cases, the underlying symbolic relationships are discovered via exploratory data analysis, with the subsequent interpretation based on the functional form of derived relationships. In other cases, a number of competing models can be derived based on prior knowledge and fundamental physical laws, and the model best matching the experiment is selected to represent the relevant physics. In all cases, models include not only the symbolic form, per se, but also the expected values of the internal parameters that are known with different degree of certainty, naturally cast in the Bayesian inference (BI) framework.Hypothesis learning is developed as an approach to implement this iterative cycle as a part of the automated experiment .27 Here,During the hypothesis learning, the agent performs the experiment, returning the scalarized value of the functionality of interest in a selected point of the parameter space. The measured values are used to perform the BI on the list of probabilistic models (hypotheses) wrapped into the structured Gaussian processes,,,,,,,,,,,,,,,,,,The phenomenological mechanisms for ferroelectric domain growth in piezoresponse force microscopy (PFM) have been extensively explored for over two decades.Hence, despite its apparent simplicity, domain switching in ferroelectrics is a complex process that is affected by the intrinsic thermodynamics of the domain formation, domain wall pinning in the spatially non-uniform probe field, and screening charge generation and dynamics. Any of these can serve as a process limiting stage, forming an ideal setting for hypothesis-learning applications. Importantly, at the mesoscopic level, these mechanisms provide the full range of possible physical eventualities, and thus the hypothesis list is assumed to be complete.,,,,,Here, we enumerate the hypotheses for the domain growth based on (1) thermodynamic control in the presence or absence of surface screening charges, (2) kinetic control of domain wall motion via pinning, or (3) kinetic control via screening charge dynamics. This list of possible limiting factors is exhaustive for the domain formation in PFM, and hence the selected hypotheses are expected to cover the full list of experimental eventualities. The analysis of the laws of domain growth in these cases was carried out by a number of groups over the last two decades,rcr.Here, model I corresponds to the partial internal screening of the depolarization field by space charge carriers and domain wall thickening. For this case, the equilibrium domain radius depends on the tip voltage as,Model II corresponds to a Landauer-Molotskii (LM) approach of infinitely thin domain walls, very prolate domains, and their breakdown see .60,61 Fo,,,,d is the effective tip size, Model III: alternative to the thermodynamic control of the domain size is the kinetic control, in which case the domain size is determined by the kinetics of the domain wall motion. From general theory of the disordered media, the domain wall velocity in the uniform field follows the classical dependence including pinning, creep, and then depinning and linear motion.rived as  or wall pinning (model III). If the screening charges are slow and sparse, then the domain growth is limited by the charge injection. The experimental evidence toward this behavior was obtained by Yudin et al.The simple consideration of the mass and charge balance suggest that in the PFM experiment, the screening charges can be generated only at the tip-surface junction. In this case, assuming general power law voltage dependence of the generation rate and diffusional or drift transport of charge species, the kinetics of the domain wall growth can be described as3 (BTO) thin film  single-sided epitaxial-polished SrTiO3 substrates at 100 millitorr with a pulse rate of 5 Hz from a stoichiometric SrRuO3 ceramic target. Subsequently, 80 nm BTO was grown at 10 millitorr with a laser pulse rate of 10 Hz from a stoichiometric BTO target. The fluence for both thin-film layers was maintained at approximately 1.2 J/cm2. Substrates were prepared by sonication in a warm (∼70°C) deionized water bath for 1 min followed by an anneal at 1,000°C for 12 h to produce TiO2 termination with step and terrace surface morphology.BTO thin films were grown via pulsed laser deposition (PLD) in 99.9999% pure OThe hypothesis-learning-driven automated BEPFM measurement is based on an Asylum Research Cypher microscope equipped with a National Instruments DAQ card with LabView and a Field Programmable Gate Arrays with Python Jupyter Notebook. For domain writing, FPGA moves the tip to a desired location and applies a DC bias, followed by a BEPFM image measurement performed with NI, FPGA, and Cypher. The FPGA performs scan (move tip) and send to trigger to the NI DAQ card to perform BE measurements simultaneously. These processes are embedded in a Jupyter Notebook. When a measurement finishes, the Jupyter Notebook analyzes the BEPFM phase image to obtain the domain size and saves the domain size in Google Drive. Then, the hypothesis training is performed in Google Colaboratory with this domain size (and previous domain size), followed by saving the next writing parameters for the next experiment.https://github.com/ziatdinovmax/gpax. The probabilistic models were wrapped into the structured Gaussian processes,D was the available (measured) data. The reward function was defined asi. The python script used to run the hypoAL during the experiment can be found in the The hypothesis learning (hypoAL)


Plasmodium falciparum is a unicellular, intracellular protozoan parasite, and the causative agent of malaria in humans, a deadly vector borne infectious disease. A key phase of malaria pathology, is the invasion of human erythrocytes, resulting in drastic remodeling by exported parasite proteins, including molecular chaperones and co-chaperones. The survival of the parasite within the human host is mediated by P. falciparum heat shock protein 70s (PfHsp70s) and J domain proteins (PfJDPs), functioning as chaperones-co-chaperones partnerships. Two complexes have been shown to be important for survival and pathology of the malaria parasite: PfHsp70-x-PFE0055c (exported); and PfHsp70-2-PfSec63 (endoplasmic reticulum). Virtual screening was conducted on the drug repurposing library, the Pandemic Response Box, to identify small-molecules that could specifically disrupt these chaperone complexes. Five top ranked compounds possessing preferential binding affinity for the malarial chaperone system compared to the human system, were identified; three top PfHsp70-PfJDP binders, MBX 1641, zoliflodacin and itraconazole; and two top J domain binders, ezetimibe and a benzo-diazepinone. These compounds were validated by repeat molecular dockings and molecular dynamics simulation, resulting in all the compounds, except for MBX 1461, being confirmed to bind preferentially to the malarial chaperone system. A detailed contact analysis of the PfHsp70-PfJDP binders identified two different types of modulators, those that potentially inhibit complex formation (MBX 1461), and those that potentially stabilize the complex (zoliflodacin and itraconazole). These data suggested that zoliflodacin and itraconazole are potential novel modulators specific to the malarial system. A detailed contact analysis of the J domain binders (ezetimibe and the benzo-diazepinone), revealed that they bound with not only greater affinity but also a better pose to the malarial J domain compared to that of the human system. These data suggested that ezetimibe and the benzo-diazepinone are potential specific inhibitors of the malarial chaperone system. Both itraconazole and ezetimibe are FDA-approved drugs, possess anti-malarial activity and have recently been repurposed for the treatment of cancer. This is the first time that such drug-like compounds have been identified as potential modulators of PfHsp70-PfJDP complexes, and they represent novel candidates for validation and development into anti-malarial drugs. Plasmodium falciparum, which causes a severe form of malaria in humans, encodes 49 J domain proteins (PfJDPs), of which 18 are predicted to be exported into host cells during the intracellular erythrocytic stage of the life cycle  thereby augmenting malaria pathogenicity . PfHsp70-2 is essential to parasite survival , corresponding to the homologous human partnership of Homo sapiens GRP78 (HsGRP78)-Homo sapiens Sec63 (HsSec63) involved in protein translocation into the ER -resident chaperone, survival , and is o the ER . Intereso the ER . We propThe advent of publicly available drug repurposing libraries has provided an opportunity to apply virtual screening approaches to identify novel inhibitors with validated drug-like properties. A prime example of such a library is the Pandemic Response Box (PRB), which is a collection of approximately 400 small molecule compounds with demonstrated potent anti-viral, anti-bacterial, anti-fungal or anti-neoplastic activity . TherefoP. falciparum proteins of interest were retrieved from PlasmoDB (https://plasmodb.org). The amino acid sequences of the human and Escherichia coli proteins of interest were retrieved from Uniprot (https://www.uniprot.org). To carry out various protein-protein and protein-ligand interaction studies, protein crystal structures of the Hsp70 Nucleotide Binding Domains (NBDs) and DNAJA1 J domain were obtained from the Protein Data Bank  crystal structure (PDB ID: 5NRO) (E. coli DnaJ (EcDnaJ) (PDB ID: 5NRO) (Mus musculus (mouse) DnaJ (PDB ID: 2CUG) as a template for HsSec63. All the above modeling procedures were carried out using Modeller Version 10.1 (https://colab.research.google.com/). The models predicted with SWISS-MODEL as well as AlphaFold2 were almost identical to those predicted with Modeller except for some variations in the helix-IV region of the J domains predicted by AlphaFold2 (Sequences of D: 5NRO) . The comD: 5NRO)  as a temion 10.1 . The 3D ion 10.1  and Alphion 10.1  implemenphaFold2 , promptihttps://www.ebi.ac.uk/Tools/msa/clustalo/)   , and rengn.html) .https://www.mmv.org/mmv-open). Compound file conversion to PDBQT format was carried out using Open Babel (http://openbabel.org)  for virtual screening . The PRBbel.org) .https://www.rcsb.org/) in the ADP-bound form, while the NBD of HsGRP78 was retrieved in the AMP-PCP -bound form, and using the respective PDB IDs as mentioned in https://wenmr.science.uu.nl/haddock2.4/) (https://vina.scripps.edu) .The NBD domains of PfHsp70-x, HsHsp70, and PfHSP70-2 were retrieved from PDB database (ock2.4/)  using deock2.4/) . The valock2.4/)  to generock2.4/) . The comock2.4/) . Efficiepps.edu)  using anhttps://www.ebi.ac.uk/thornton-srv/software/LigPlus/) (https://server.poissonboltzmann.org). Pharmacokinetic and drug likeness prediction of top binder compounds was conducted using the SwissADME online server  . The LigigPlus/)  was usede server  to evaluhttps://cgenff.umaryland.edu/; https://valdes-tresanco-ms.github.io/gmx_MMPBSA/dev/examples/Protein_ligand_CHARMMff/) and Protein-ligand with LPH (lone pair: hydrogen) particles after removing the lone pairs not supported in gmx_MMPBSA algorithm . The first 100 frames were discarded and binding free energy for the remaining 900 frames with the interval of 2 frames was considered for calculations.Molecular Dynamics (MD) simulation of the top five screened compounds was performed to analyze the conformational behavior and stability of the binding pose using GROMACS version 2022.2 software package  followedThis study explored the interactions of two PfJDPs with their corresponding PfHsp70s; PfHsp70-x-PFE0055c and PfHsp70-2-PfSec63. The analyses of these malarial chaperone-co-chaperone complexes in comparison to the homologous human complexes are presented, followed by the outcomes of a virtual molecular-docking-based screen of the PRB database.E. coli (EcDnaK-EcDnaJ), has revealed the contact residues of three important binding sites: (i) the J domain helix II interface with the NBD; (ii) the HPD motif and J domain helix III interface with the SBD; and (iii) the J domain HPD catalytic interface with the NDB, linker region and SBD . A detailed structural analysis of the canonical Hsp70-JDP complex of  and SBD . The J d and SBD . This prUsing EcDnaK as a reference, a multiple sequence alignment was created of the region of the NBDs of PfHsp70x, Human Hsp70 , PfHsp70-2 and Human GRP78  that forms an interface with helix II of the J domain; and using EcDnaJ as a reference, a multiple sequence alignment was created of the J domains of the PFE0055c, DNAJA1, PfSec63 and HsSec63 . A high viz., 206 (E), 211 (D), 217 (E) in the reference NBD of EcDnaK , 26 (K), 27 (R) of the EcDnaJ J domain making the helix II interface, are conserved in the PFE0055c and human DNAJAI J domains. However, the third residue, corresponding to 27 (R) of the EcDnaJ J domain is mutated to L in both Sec63 proteins  and negatively charged (NBD) residues making up the interface ; Table 1Virtual screening to identify JDP inhibitors was carried out using two strategies. The first strategy made use of the complex between the Hsp70 NBDs and corresponding JDP J domains to look for potential ligands from the PRB library which exhibited the potential to disrupt the interaction between the components of the complex. The second strategy, on the other hand, mines for ligands which show preferential binding to the JDP J domains, thereby limiting the binding of J domain to the NBD.viz., PfHsp70-x-PFE0055c, PfHsp70-x-DNAJA1, HsHsp70-DNAJA1 and HsHsp70-PFE0055c, to search for compounds which bind to PfHsp70-x complexes preferentially as compared to the HsHsp70 complexes. The docking was carried out using the NBD of the Hsp70 proteins and the J domain of the JDP proteins. In addition, C86 was used as a reference compound as it has been implicated in disrupting the complex formation between PfHsp70-x and PFE0055c  unit, and all possess H-bond acceptor sites making this group chemically consistent.PFE0055c and DNAJA1 are cytosolic/exported JDPs, so the virtual screening setup was targeted at four complexes PFE0055c . The binPFE0055c . The topPFE0055c , and relPFE0055c . With thAn overview of the different docked poses for each of the compounds has been depicted in 833990, 9819085 and 10046204 are known anti-viral agents whereas the compounds 60196939 and 2862146/MBX 1641 are both anti-bacterial compounds. It is notable that all these compounds possess binding affinities higher than the HsHsp70-DNAJA1 complex. The compounds 833990, 60196939 and 2862146/MBX 1641 seem to be specific for PFE0055c while the compounds 9819085 and 10046204 preferentially bind both PfHsp70-x complexes as well as the HsHsp70-PFE0055c complex, suggesting they are potential pan-inhibitors like C86.A graphical comparison of docking poses for PFHsp70-x-PFE0055c and HsHsp70-DNAJA1, selected on the basis of their binding affinity to the interface region have been presented in 2862146/MBX 1641 docked completely within the interface. In PfHsp70-x-PFE0055c, 2862146/MBX 1641 overlaps with the positive control C86, forming a stronger H-bond with the same residue (K98) in the J domain of PFE0055c that makes contact with C86, in addition to having similar hydrophobic/other non-covalent interactions with amino acid residues K97, Y100, R101, A104 (J domain) and I220 (NBD). Interestingly, in the HsHsp70-DNAJA1 complex, 2862146/MBX 1641 is oriented in a manner that it forms H-bonds with both proteins in the complex; forming H-bonds with K220 in HsHsp70, and with K28 in DNAJA1 . It seems that 2862146/MBX 1641 is acting as molecular glue binding together HsHsp70 and DNAJA1. In addition, 2862146/MBX 1641 is predicted to form hydrophobic/other non-covalent contacts with residues G12, E21, A25, K24, K28 of the J domain and E192, T211, D213, I216, E218 and K220 of the NBD. C86, seems to bind the HsHsp70 NBD only via hydrophobic interactions/other non-covalent interactions. This analysis indicates that 2862146/MBX 1641 has a binding preference to the J domain residues in the PfHsp70-x-PFE0055c complex while it maintains contacts with both the partners in the HsHsp70-DNAJA1 complex having a competitive inhibitory potential in the malarial system and stabilizing effect in the human system.An in-depth analysis of the H-bonding and hydrophobic interactions between ligand and target protein was performed for the best docked energy complexes alongside C86 that served as positive control for the malarial complex and a negative control for the human complex . Results10955174 and 135398740 were not considered for further analysis as all the binding poses were located outside of the interface region. In addition, the binding affinity values for individual docked poses for all compounds screened was also compiled  are anti-bacterial, four  are anti-viral and three  are anti-fungal  followed by 55283/itraconazole . However, compound 60196939  had the largest difference in binding affinity followed by the compound 6098 .The majority of the dockings were specific to the interface region in contrast to the trend observed for the docking screen of PfHsp70-x-PFE0055c compare . This mai-fungal . All the76685216/zoliflodacin and 55283/itraconazole were found to be the best-docked solutions as depicted in 76685216/zoliflodacin forming four H-bonds across both proteins in each complex. The modulator 76685216/zoliflodacin forms four H-bonds with residues Y149, R150 , S153 of the J domain and Y348 of the NBD in PfHsp70-2-PfSec63 complex while maintaining hydrophobic/other non-covalent interactions with residues K145, L153, H157, D159, Y178 of the J domain and residues E214, K352 of the NBD. The interaction of the HsGRP78-HsSec63 complex with 76685216/zoliflodacin also involved four H-bonds with residues R125 , L129 of the J domain and D355, D357 of the NBD apart from making hydrophobic/other non-covalent interactions with residues L126, K129 (J domain) and S354 (NBD).On the basis of the visual inspection of docked poses in the interface region, compounds 55283/itraconazole forms four H-bonds with both proteins in the HsGRP78-HsSec63 complex, but only forms three H-bonds with PfHsp70-2 in the PfHsp70-2-PfSec63 complex. However, the H-bonds with the PfHsp70-2-PfSec63 complex involve residues E213, E214 and N236 of the NBD, with the former two being reported to be critical for NBD-J domain complex formation in the malarial system  and residues from NBD regions other than the reported interface. Overall, the data suggested that these modulators potentially inhibit the malarial system, while stabilizing or minimally inhibiting the human system.The compound l system . On the viz., 22 (R), 26 (K), 27 (R)  . The 3D The docking solutions were sorted based on the difference in binding affinities between PFE0055c and DNAJA1 . The sor150311/ezetimibe, 2867190/benzo-diazepinone), 10077130/vorapaxar, 1317590, 9911469/FK-788) specific for PfJDPs are anti-viral in nature. Out of the PFE0055c J domain specific binders, the majority of them are anti-viral (1684/pleconaril), 2768133, 3783668, 51354502, 55245/mifepristone, 16739062, 56668933) followed by anti-bacterial  and anti-fungal  in reported bioactivity. The comparative graphics of all the PfJDPs specific inhibitors depicts their overall interaction maps with different J domains , 26 (K), 27 (R) of the EcDnaJ J domain), i.e. 27 (R) to L in PfSec63 and HsSec63 J domain  with the highest binding energy difference between malarial and human J domains, to highlight specific contact residues and H-bond formation  in addition to making some contacts with helix I residues  and helix-III residues  while the compound 2867190/benzo-diazepinone formed hydrophobic contacts with helix-II residues  in addition to making some contacts with helix I residues . However, the presence of helix II residues at the interface  of both Hsp70-JDP and J domains complexes. The conformational stability of the protein-ligand complexes was initially monitored in terms of the variation in the RMSDs over the simulation period ; Table 3For PfHsp70-x-PFE0055c-MBX 1641, MBX 1641 remains bound to the complex after the initial stabilizing period of about 4.5 ns with few incidents of dissociation of the J domain-MBX 1641 complex from PfHsp70-x, resulting in the MMPBSA Binding energy of -12.3 kcal/mol, while for HsHsp70-DNAJA1-MBX 1641, MBX 1641 maintained its bound conformation to the complex throughout the 10 ns simulation, resulting in the MMPBSA Binding energy of -17.17 kcal/mol ; Table 3The PfHsp70-2-PfSec63-itraconazole and PfHsp70-2-PfSec63-zoliflodacin complexes maintained their overall conformation and binding pose stability giving the MMPBSA Binding energy values of -21.17 and -16.48 kcal/mol, respectively, as compared to their human counterpart complexes, HsGRP78-HsSec63-itraconazole and HsGRP78-HsSec63-zoliflodacin, with MMPBSA Binding energy values of -16.9 and -5.08 kcal/mol, respectively ; Table 3For the MD simulation of drug candidates bound to the J domains, the PFE0055c J domain-ezetimibe complex maintained the binding pose conformation after the initial 2ns of simulation with MMPBSA Binding energy value of -12.68 kcal/mol, performing slightly better than the DNAJA1 J domain-ezetimibe  and PFE0055c J domain-C86 control . Both PFE0055c J domain-benzo-diazepinone and DNAJA1 J domain-benzo-diazepinone complexes resulted in higher MMPBSA Binding energy values of -15.03 and -14.85 kcal/mol, respectively, as compared to the control PFE0055c J domain-C86 complex  ; Table 3There have been extensive studies on small molecule compounds that disrupt Hsp70-JDP interaction in bacterial, yeast and human systems . HoweverThe use of molecular docking for virtual screening of drug repurposing libraries have been found to be very useful in discovering new anti-malarial drugs. Such strategies are more practical and less expensive than traditional approaches, while the use of drug repurposing libraries of compounds already approved for human use, rules out the need to perform expensive human toxicology studies . The ava60196939). These compounds possess a diverse chemical space and were originally discovered as potent anti-bacterial, anti-viral and anti-fungal agents  bound primarily to the J domain ; or 2) equally well to the J domain and NBD . Hence two different types of small molecule modulators have been identified, those that could disrupt the complex by inhibiting formation, and those that could disrupt the function of the complex by making it too stable or less dynamic. Indeed, given that both zoliflodacin and itraconazole were validated as having differential binding affinity to the malarial chaperone complex over the human chaperone complex, suggests that they are potential novel modulators specific to the malarial system. A detailed contact analysis of the top two J domain binders (ezetimibe and the benzo-diazepinone), revealed that they not only bound with greater apparent affinity to the J domain of PFE0055c compared to that of DNAJA1, but also adopted the preferred pose, primarily making contact with helix II on the J domain of PFE0055c while binding to other regions of the J domain of DNAJA1. These data suggest that these compounds are potential specific inhibitors of the malarial chaperone system over the human system.2862146/MBX 1641 and 76685216/zoliflodacin are anti-bacterial while 150311/ezetimibe and 2867190/benzo-diazepinone are anti-viral in nature, and 55283/itraconazole is an anti-fungal agent. These compounds have been reported to inhibit a variety of biological processes , a target to develop anti-malarial drugs (in vitro growth assays. However, itraconazole was also found to be partially active against P. berghei malaria in mice (P. falciparum growth (Itraconazole is a FDA-approved drug of the triazole class known for more than 30 years for its clinically proven anti-fungal activity , and recal drugs . In addi in mice . Ezetimi in mice , therebym growth . Ezetimim growth .in vitro and in vivo assay. In addition, while the protein-protein docking conducted in this study was based on experimental Hsp70-JDP complexes, solving the crystal structure of the PfHsp70-PfJDP complexes would greatly accelerate further drug-discovery studies of this system.This is the first time that the PfHsp70 NBD-PfJDP-J domain interface has been explored as a drug target in virtual screening against a library of small molecule compounds. The virtual screening strategies outlined in this study have identified a number of potential modulators specific for PfHsp70-PfJDPs complexes involved in survival and pathogenicity of the malarial parasite. Since these compounds were deposited in the PRB because of their drug-like properties, they could potentially be readily developed into novel anti-malarial drugs. Furthermore, this study provides a PfHsp70-PfJDP drug-target platform for further studies on other drug-repurposing small molecule libraries. However, given the predictive nature of this virtual screening study, the potential small molecule modulators need to be tested for their biochemical activity in Hsp70-JDP binding studies and chaperone assays, and their effect on the growth of malaria parasites using Using virtual screening strategies, a diversity of drug-like compounds were identified which showed affinity and specificity for binding to PfHsp70-PfJDP complexes known to be important for the survival and pathogenicity of the malarial parasite. We were able to identify compounds with differential binding affinity for PfHsp70-x-PFE0055c, PfHsp70-2-PfSec63 and J domains of both PFE0055c and PfSec63 as compared to their human counterparts. Overall, these virtual screening strategies have identified a number of potential small molecule disruptors of these PfHsp70-PfJDP complexes. The five top scoring compounds, with the highest differential binding affinity and relevant docking poses, have been in advanced clinical studies, including the two FDA approved drugs, itraconazole and ezetimibe, which have previously been reported to have anti-malarial activity. This is the first time that such drug-like compounds have been identified as potential modulators of PfHsp70-PfJDP complexes, and they represent novel candidates for validation and development into anti-malarial drugs. Experimental validation of these compounds with respect to their inhibition of PfHsp70-PfJDP interaction, anti-malarial activity and cytotoxicity are a high priority for future studies.