Togaviridae-specific cysteine. These different poses observed for ADPr may represent snapshots of the de-ADP-ribosylation mechanism, highlighting residues to be further characterised.Alphaviruses are (re-)emerging arboviruses of public health concern. The nsP3 gene product is one of the key players during viral replication. NsP3 comprises three domains: a macro domain, a zinc-binding domain and a hypervariable region. The macro domain is essential at both early and late stages of the replication cycle through ADP-ribose (ADPr) binding and de-ADP-ribosylation of host proteins. However, both its specific role and the precise molecular mechanism of de-ADP-ribosylation across specific viral families remains to be elucidated. Here we investigate by X-ray crystallography the mechanism of ADPr reactivity in the active site of Getah virus macro domain, which displays a peculiar substitution of one of the conserved residues in the catalytic loop. ADPr adopts distinct poses including a covalent bond between the C′′1 of the ADPr and a conserved  Alphavirus, belonging to the Togaviridae family, is organised into 31 species and at least ten of them are human pathogens1. Members of the Alphavirus genus are geographically and evolutionary distinguished into “Old World” (OW) alphaviruses, represented by CHIKV, and “New World” (NW) viruses, prototyped by VEEV, as well as several species corresponding to viruses that most likely appeared from recombination events between OW and NW viruses2 or viruses of marine origin.Alphaviruses are arthropod-borne viruses among which several, such as Chikungunya virus (CHIKV) and Venezuelan equine encephalitis virus (VEEV), are emerging or re-emerging viruses. According to the 7th report of the International Committee on Taxonomy of Viruses (ICTV), the genus 3. nsP3 is organised into three domains: a macro domain (MD) at the N-terminal, a zinc-binding domain (ZBD) and a C-terminal hypervariable region (HVR). The HVR plays a key role in viral replication by interacting with several partners among which Ras GTPase-activating protein-binding protein (G3BP) and SH3 containing proteins4. The N-terminal domain is structurally associated to the class of macro domains, protein modules found in all domains of life. Despite structural conservation, macro domains participate in various cellular functions including DNA repair, cell differentiation, proliferation or apoptosis. Macro domains can recognize ADP-ribose (ADPr), poly-ADP-ribose (PAR) in their free or protein-bound form, or O-acetyl-ADP-ribose (OAADPr). In addition to binding, some macro domains can also catalyze several reactions such as de-ADP-ribosylation5. Like coronavirus or hepevirus macro domains7, alphavirus macro domains recognise ADP-ribose and have de-ADP-ribosylation activity. This latter functions are thought to be essential in both early and late replication steps8. It is postulated that de-mono-ADP-ribosylation is a viral countermeasure to cellular innate immunity mediated by the viral macro domain9.Their genome is a positive-sense single-stranded RNA molecule which is usually 11 to 12 kilobases long. The genome carries two open reading frames (ORFs). The first ORF can be translated directly from the genomic RNA in P123, and P1234 polyproteins, which are sequentially processed into four non-structural proteins (nsP), named nsP1 to nsP4. The proteolysis intermediates and the final nsPs constitute the transcription/replication complex (TRC) organised in spherules at the plasma membrane. In this TRC, nsP3 has been for a long time the least understood nsP, but recent studies revealed some of its functions in viral replication12. Structure and sequence analyses together with functional characterization allowed assignment of alphavirus macro domains to a protein family prototyped by human macroD27. Viral macro domains were found originally to have ADR-ribose-1″-phosphate phosphatase (A1″Pase) activity13. More recently, it was shown that alphavirus macro domains are able to de-ADP-ribosylate Asp or Glu side-chains of host proteins15. Some of the residues involved in ADP-ribose binding and de-ADP-ribosylation have been characterized9. However, the molecular mechanism of de-ADP-ribosylation by alphavirus macro domain remains to be clarified.The structures of the macro domains from alphavirus species VEEV, CHIKV, Sindbis virus (SINV), and Mayaro virus (MAYV) were determined using X-ray crystallography and/or NMRCulex spp. mosquitoes. GETV is geographically distributed from Asia to the north of Australia and infects mainly horses16. We produced the GETV macro domain for crystallographic studies, alone or in complex with ADP-ribose, and documented several conformations adopted by ADP-ribose in the binding site. We show here that our structures provide snapshots that could contribute to unravel the still elusive de-ADP-ribosylation mechanism at play to de-activate innate immunity responses elicited by alphavirus infection.In order to better understand this mechanism, we initiated a structure-based study of the Getah virus (GETV) macro domain, which shows a peculiar substitution for one of the most conserved residues in the catalytic loop, namely serine replacing a glycine in position 30 Fig. . GETV isTaken together, this ensemble of conformations might represent several snapshots of the de-ADP-ribosylation mechanism, highlighting residues that have not been evaluated to date.Escherichia coli and synthesized by THERMO FISCHER SCIENTIFIC. The coding sequence was cloned into a pDest14 vector using the “Gateway” cloning procedure (THERMO FISCHER SCIENTIFIC). A hexahistidine (6-His) coding sequence was added at the 3′ end to produce the GETV macro domain in fusion with a C-terminal 6-His tag. A short sequence of two codons coding for methionine and lysine were added to the 5′ end in order to allow the translation in E. coli. The bacterial growth conditions for optimal expression of GETV macro domain were obtained from an incomplete factorial expression screen17. GETV macro domain was produced in E. coli Rosetta (DE3) pLysS cells (NOVAGEN). Bacteria were grown at 37 °C with shaking (200 rpm) in Terrific Broth (TB) medium (SIGMA-ALDRICH) containing 34 µg·mL−1 chloramphenicol and 100 µg·mL−1 ampicillin. The expression of the recombinant gene was induced with 0.5 mM isopropyl β-D-1-thiogalactopyranoside (IPTG) when the bacterial cell density reached the exponential phase at OD600nm of 0.4. After induction, the incubation temperature was dropped to 25 °C for overnight expression. Subsequently, the bacterial cells were harvested by centrifugation at 4,000 g for 15 min and pellets were resuspended in 50 mL of lysis buffer made of 50 mM TRIS–HCl pH 8.0, 300 mM NaCl, 10 mM imidazole, 5% glycerol, 0.1% Triton X-100 and one tablet of complete EDTA-free protease inhibitor cocktail (ROCHE). The resuspended pellets were stored at − 80 °C until the time of use. Pellets were thawed and 0.25 mg·mL−1 of lysozyme (SIGMA-ALDRICH), 10 µg·mL−1 of DNase I (SIGMA-ALDRICH) and 1 mM phenylmethylsulfonyl fluoride (PMSF) (SIGMA-ALDRICH) were added. The samples were incubated at 4 °C for 30 min and then sonicated. Samples were then centrifuged at 13,000 g for 1 h. The supernatant was loaded onto a 5 mL His prep column (GE HEALTHCARE) for Immobilized Metal Affinity Chromatography (IMAC) using an ÄKTA Xpress system (GE HEALTHCARE). After loading the supernatant, the column was washed with a buffer containing 50 mM TRIS-HCl, 300 mM NaCl, 50 mM imidazole, pH 8.0. The recombinant protein was eluted with 50 mM TRIS-HCl, 300 mM NaCl, and 250 mM imidazole, pH 8.0. Size exclusion chromatography was next performed on a Superdex 200 HiLoad 16/600 column (GE HEALTHCARE) equilibrated in 20 mM HEPES, 300 mM NaCl, pH 7.4. The eluted protein was concentrated up to 14 mg·mL−1 using an Ultracel regenerated cellulose membrane with a 3 kDa molecular weight cut-off .The DNA coding sequence of the nsP3 macro domain (amino-acids 1 to 160) of Getah virus  was optimized for expression in 18 in a 96-well thin-wall PCR plate (BIO-RAD) using a quantitative PCR machine ICycler IQ (BIO-RAD). Briefly, the protein at a final concentration of 0.3 mg·mL−1 was mixed with a SYPRO orange solution at concentrations recommended by the manufacturer (THERMO FISHER SCIENTIFIC) in a final volume of 25 µL and tested with the following concentrations of ADP-ribose: 0.5 mM, 0.25 mM, 0.125 mM, 0.063 mM, 0.031 mM, 0.016 mM and 0 mM. Accumulative steps of temperature from 20 to 90 °C were applied to the samples. The increase of the fluorescence emitted by the probe that binds the exposed hydrophobic regions of the denatured protein was used to monitor the denaturation of the protein. A melting temperature (Tm) was calculated as the mid-log of the transition phase from the native to the denatured protein using a Boltzmann model (ORIGIN SOFTWARE).The purity of the protein was assessed on SDS-PAGE gels stained with Coomassie blue. Besides, protein stabilization by ADP-ribose was additionality checked by thermal shift assay (TSA)−1 using the commercial screens WIZARD CLASSIC 1&2 HT96, STRUCTURE 1&2 HT96, and STURA FOOTPRINT Screen 48 (MOLECULAR DIMENSIONS LIMITED) in 3-well sitting-drop SWISSCI crystallization plates (TPP LABTECH). 100 nL of crystallization solutions were added to 100, 200 or 300 nL of GETV macro domain solution using a MOSQUITO Robot (TTP LABTECH). The conditions where crystal hits were obtained were then optimized using either 96-well SWISSCI crystallization plates or 24-well hanging drop LINBRO plates. Co-crystallization experiments were set-up with GETV macro domain complemented with (1) ADP-ribose, (2) ADP-ribose and glutamic acid or (3) ADP-ribose and aspartic acid, with final concentrations of 3 mM for ADP-ribose, 50 mM for glutamic acid and 3 mM or 30 mM for aspartic acid. In general, crystals appeared after one day and were grown for approximately two weeks. Soaking experiments were performed with crystals of GETV macro domain co-crystallized with ADP-ribose by adding mother liquor supplemented with aspartic acid to the crystallization droplet followed by 2–3 h or overnight incubation at 20 °C. Afterwards, crystals were flash-cooled in liquid nitrogen using 20% of glycerol in the mother liquid as cryo-protectant.Initial crystallization trials were carried out with GETV macro domain at 14 mg·mL19 or XDS20. Data were scaled and merged using the CCP421 suite of programs POINTLESS22, AIMLESS 23 and TRUNCATE24. Random sets of approximately 5% of reflections, depending on the resolution limit, were set aside for FreeR cross-validation purposes. Where data-sets of ligand complexes were in the same space group as the native data set, the composition of cross-validation data sets was systematically taken over from the parent data set. The structure of native GETV macro domain was determined by molecular replacement with MolRep25 using the macro domain of Chikungunya virus  as a search model. The structures of GETV macro domain in complex with ligands were determined either by molecular replacement using the native GETV macro domain as a search model or by difference Fourier synthesis.Diffraction intensities were recorded on beamlines ID23-1 and ID30A-3 at the European Synchrotron Radiation Facility  and on beamline Proxima-2 at Soleil Synchrotron . Indexing and integration of the different datasets were performed using MOSFLM26, interspersed with cycles of manual model adjustments with COOT27. Ligands were fitted into unbiased Fo–Fc difference electron density maps calculated after 10 cycles of rigid-body refinement. Hydrogens were added in the riding position. Coordinates and restraints for ADP-ribose in the close conformation were retrieved from the CCP4 ligand dictionary and a model and restraints for ADP-ribose in the open conformation were generated with the CCP4 Monomer Library Sketcher. Model quality was assessed with internal modules of Coot and with the MOLPROBITY server28. Crystallographic models are of good quality with 99.4–100% of residues in favoured regions of the Ramachandran plot and no outliers. Data collection and refinement statistics are summarized in Table https://www.pymol.org/). Sequence alignments were made using Clustal Omega29 and graphical rendering of the alignments, considering structural information, were made with ESPript30. The atomic coordinates and structure factors have been deposited in the Protein Data Bank under accession numbers 6QZU (native GETV macro domain), 6R0F (GETV macro domain with ADP-ribose in close conformation pose 1), 6R0G, (GETV macro domain with ADP-ribose in close conformation pose 2), 6R0T (GETV macro domain with ADP-ribose in open ring conformation), 6R0P (GETV macro domain with ADP-ribose in double open ring conformation) and 6R0R .Refinement was performed using REFMAC7. A focused analysis of these residues (amino acids 30 to 33 of the nsP3 sequence) of macro domains revealed that the consensus motif is followed by a Togaviridae-specific cysteine. It can also be noticed that the GETV macro domain is an exception regarding the consensus motif, as its sequence harbours a serine instead of a glycine at position 30. We thus first verified that this macro domain is a bona fide ADP-ribose binding module. The recombinant GETV macro domain was produced in E. coli and purified under non-denaturing conditions. After purification, the integrity of the protein was assessed by thermal shift assay (TSA). TSA experiments showed that the protein could be denatured by heat in a classical folded-to-denatured transition phase (data not shown) with a melting temperature (Tm) of 46.5 ± 0.2 °C. Addition of 0.5 mM ADP-ribose to the protein solution led to a 10 °C increase of the Tm suggesting that the recombinant GETV macro domain indeed binds ADP-ribose  is encompassing aa 1,333 to 1,492 . Its sequence identity with alphavirus homologues with known structures such as CHIKV and VEEV macro domains is 69% and 57%, respectively  as a template. The crystals of the GETV macro domain belong to the space group P231 revealed closest homology with macro domains from the alphavirus family such as CHIKV (3GPG), SINV (4GUA), VEEV (3GQO) and MAYV (5IQ5) with Z-scores in the range of 32.2 to 27.8 and r.m.s.d. values of 0.7 to 1.4 Å for 158–160 pairwise aligned Cα positions.The structure of GETV macro domain consists of a central twisted six-stranded β sheet  sandwiched between one α-helix (α1) at one side and three α-helices  at the opposite site , and a putative phosphatase (1SPV) and YmdB (5CB5), a O-acetyl-ADP-ribose deacetylase, from E. coli. Interestingly, lower structural homologies than for the above structures of human and bacterial macro domains are calculated by DALI for the viral macro domain structures from the coronavirus family  strains Beaudette [3EKE] and M41 [3EWO]), with Z-scores in the range of 16.4 to 18.8 and r.m.s.d values of 1.8 to 2.3 Å for 136–143 pairwise aligned Cα positions. Thus structure-based phylogeny of macro domain does not cluster viral alphavirus and coronavirus together, raising questions on possible functional variations.A second group of close structural homologues, with Z-scores in the range of 21.4 to 19.0 and r.m.s.d values of 1.8 to 2.2 Å for 151–154 pairwise aligned Cα chains of macro domains from the three Old World alphaviruses GETV, CHIKV and SINV superimpose well, as illustrated by the low root mean square deviation (r.m.s.d.) values of approximately 0.7 Å. Only minor structural changes are observed at the level of the β3β4 loop GV33. The tight interactions established between the distal ribose and Ser30 point towards a role in substrate binding or catalysis for this residue. Not surprisingly, we found that the most important structural changes occurring in GETV macro domain upon ADP-ribose binding could be observed in the catalytic loop β2α1 and loop β5α3, which close-up over the ligand to establish tight binding interactions.Similarly to what had been observed in other macro domain/ADP-ribose complexes, the phosphate groups of ADP-ribose are lined by the catalytic loop β2α1 and loop β5α3 and tightly coordinated by hydrogen bonds with main-chain atoms of residues Val33, Ser110, Gly112, Thr113 and Phe114 and the side-chain of Thr113. Finally, the distal ribose, observed in the anomeric α-configuration, interacts with GETV macro domain through hydrogen bonds contracted between 3″-OH and the side-chain of Asn24, between 2″-OH and the side-chains of Asn24 and Ser30, and between 1″-OH and the side-chain Ser30 and the main-chain of Asp31, and establishes a stacking interaction with the side-chain of Phe114. The Ser30 of the catalytic β2α1 loop is unique to GETV macro domain and substituted by Gly in other viral macro domains harbouring the glycine-rich motif 34. In this second GETV macro domain/ADP-ribose structure the interactions between the GETV macro domain and the adenine moiety, the proximal ribose and the phosphate groups are virtually identically to the interactions described above. However, the distal ribose is tilted by approximately 60° with respect to the “classical” pose described above and observed in all other macro domain/ADP-ribose complexes described so far  to promote efficient translation initiationWe further obtained two additional GETV macro domain/ADP-ribose complexes by co-crystallizing the protein in the presence of 3 mM ADP-ribose and 30 mM aspartic acid. Diffraction data were recorded to 1.85 and 1.6 Å, respectively. Again, in these two crystal structures the interactions between GETV macro domain and the adenine moiety, the proximal ribose and the phosphate groups are comparable to those seen in the above-described models. Conversely, preliminary electron density maps, calculated before the incorporation of the ligand, clearly indicated that the distal ribose was present in the open conformation  to C2 and only one molecule is present in the asymmetric unit. We verified cautiously whether the position of ADP-ribose in this novel complex could have influenced the crystal packing and could not retrieve any plausible explanation for the change of space group. The structure was solved by molecular replacement, using the native GETV macro domain structure as a search model and the final model presents very good stereochemistry. The interactions between GETV macro domain and the adenine moiety, the proximal ribose and the phosphate groups of ADP-ribose are specular to the interactions observed in all the GETV macro domain/ADP-ribose complexes described so far. To our surprise, ADP-ribose in this structure is found in the open conformation and a covalent bond is established between 1″-C and Cys34 SG . However, when ADP-ribose and glutamic acid were added to the co-crystallization solution, in the resulting crystal structure the distal ribose (pose 2) was tilted with respect to the one observed in the previously determined ADP-ribose complex and adopted the energetically less favourable O-4′′-endo envelop configuration. Though, this strained ribose conformation is stabilized by a tighter network of hydrogen bonds contracted with the GETV macro domain when compared to the pose 1 complex structure. Furthermore, in one of the two molecules in the asymmetric unit an acetate molecule, reminiscent of glutamic acid added to the crystallization solution, coordinates the 2′′-OH and 1′′-OH hydroxyl groups, evoking the position of the leaving group after the de-ADP-ribosylation reaction. Apparently, it was the crystallization method deployed, soaking versus co-crystallization with carboxylic acids, which induced the conformational change between pose 1 and pose 2. When GETV macro domain was co-crystallized with ADP-ribose and aspartic acid, the distal ribose was found in two different open conformations, one of them closely resembling the closed-ring ribose of pose 2, the other resulting from a rotation around C4′′ and C3′′, which positioned the aldehyde function close to the α-phosphate, buried in a pocket surrounded by Cys34, Val33, Asn21 and Ala22. Open conformations of an integral ribose in the open conformation bound to macro domains have so far not been observed, but dehydrated open ADP-ribose adducts have been observed in the crystal structures of TARG138 and DraG32. Lastly, co-crystallization of GETV macro domain with low concentrations of ADP-ribose and aspartic acid (3 mM each) led to a structure where the distal ribose is covalently attached to Cys34. This covalent thio-hemiacetal adduct is reminiscent of the keto-amine transition states involving a lysine residue described for DraG32 and Targ138. It is interesting to notice that an aspartate, Asp184, proposed to be the catalytic acid/base catalyst in human MacroD140, is isosteric to Cys34, as well as Asp102 of human MacroD239 and Glu114 of T. curvata PARG41, two residues proposed to play crucial roles in catalysis. Noteworthily, DraG, Targ1, MacroD1 and MacroD2 are among the closest structural homologues of GETV macro domain. The above mentioned structural similarities advocate for Cys34 being the catalytic residue in the GETV macro domain, and maybe as well in macro domains of other alphaviruses. Cys-dependent hydrolases found in Nature are mainly represented by Cys-proteases, operating through a catalytic mechanism relying on a Cys-His-Asp catalytic triad. GETV macro domain exhibits no overall structural similarity with any known Cys-protease and the only His and Asp residues found in the vicinity of Cys34, namely His67 and Asp31, though pretty well conserved throughout alphavirus macro domains, are too far apart to form a functional catalytic triad.Intrigued by the substitution of a highly conserved glycine residue for serine and the presence of a The role of the peculiar Ser30 substituting a glycine in the catalytic loop of the GETV macro domain could ultimately not be resolved by this study. The serine residue might contribute to the trapping of ADPr in different poses that were to date not observed in the other alphavirus macro domains having a glycine in position 30. Still, the tight interactions of this residue with the distal ribose observed in the different complex structures described herein plead for a function in substrate binding or eventually a direct role in catalysis in interplay with Cys34.endo twist conformation (pose 1) as observed in most macro domain/ADP-ribose complexes documented so far. We cannot ascertain whether the covalent Cys34-ADP-ribose adduct portrays the true interaction intermediate, or whether it represents just an artefact standing for an abortive complex. In any case, the conservation in alphavirus macro domain sequences and the proximity of Cys34 to the catalytic centre argues for an important role of this residue in the catalytic mechanism. In this respect, mutational studies, which go beyond the purpose of this report, will be necessary to ascertain the true identity of the catalytic residue of the GETV macro domain.Altogether the five different conformations of ADP-ribose presented in this study could picture a conformational itinerary Fig.  represenIn this study, we describe by means of crystallographic structures different poses adopted by a molecule of ADP-ribose in the binding site of GETV macro domain. In addition to the pose of ADP-ribose found in other structures of alphavirus macro domain, this work reveals original features such as the opening of the distal ribose, and its stabilization by Ser30, representing a peculiar GETV specific substitution in the catalytic loop. In addition, we were able to identify a covalent link between ADP-ribose and a cysteine, Cys34, located in the catalytic loop, as well as several poses of ADP-ribose susceptible to provide clues about the catalytic mechanism. Since Cys34 is conserved in alphaviruses, this finding would deserve to be further explored by enzymatic assays and reverse genetics.Supplementary Information.


Dendrites, branched structures extending from neuronal cell soma, are specialized for processing information from other neurons. The morphogenesis of dendritic structures is spatiotemporally regulated by well-orchestrated signaling cascades. Dysregulation of these processes impacts the wiring of neuronal circuit and efficacy of neurotransmission, which contribute to the pathogeneses of neurological disorders. While Cdk5 (cyclin-dependent kinase 5) plays a critical role in neuronal dendritic development, its underlying molecular control is not fully understood. In this study, we show that p39, one of the two neuronal Cdk5 activators, is a key regulator of dendritic morphogenesis. Pyramidal neurons deficient in p39 exhibit aberrant dendritic morphology characterized by shorter length and reduced arborization, which is comparable to dendrites in Cdk5-deficient neurons. RNA sequencing analysis shows that the adaptor protein, WDFY1 (WD repeat and FYVE domain-containing 1), acts downstream of Cdk5/p39 to regulate dendritic morphogenesis. While WDFY1 is elevated in p39-deficient neurons, suppressing its expression rescues the impaired dendritic arborization. Further phosphoproteomic analysis suggests that Cdk5/p39 mediates dendritic morphogenesis by modulating various downstream signaling pathways, including PI3K/Akt-, cAMP-, or small GTPase-mediated signaling transduction pathways, thereby regulating cytoskeletal organization, protein synthesis, and protein trafficking. Dendritic morphology is tightly controlled by well-orchestrated signaling events both during development and in the mature brain3. These external stimuli-mediated signaling pathways instruct the organization of dendritic trees by regulating gene transcription and protein synthesis, controlling protein and lipid trafficking along the dendrites, and coordinating microtubule- or actin-binding proteins to regulate cytoskeletal assembly and disassembly3. Accordingly, protein kinases play central roles in coordinating the activities of these cellular processes.Neurons are polarized cells with a single axon, which transmits signals, and multiple dendrites, which receive and process information from presynaptic axonal inputs. Each subtype of neurons has unique dendritic morphology, which ensures that the neuronal circuits are appropriately wired with a spatiotemporally optimal number of synaptic connections and a proper receptive field for appropriate neuronal firing5. Cdk5 possesses kinase activity that requires the binding of one of its two specific activators, p39 or p358. Cdk5 plays a pivotal role during neural development by participating in neuronal differentiation, neuronal migration, axonal guidance, and dendritic morphogenesis as well as various aspects of neuronal functions such as synaptic plasticity and neurotransmission10. Suppression of Cdk5 expression in neurons results in simplified dendritic trees11, whereas inhibition of Cdk5 by S-nitrosylation promotes dendritic complexity12. Furthermore, the neuronal activity-stimulated nuclear translocation of Cdk5 regulates the expression of genes for dendrite outgrowth13. Thus, dendritic development requires the precise control of Cdk5 activity. Accordingly, various proteins involved in the regulation of dendritic development and maintenance, including TrkB (tropomyosin receptor kinase B), microtubule-associated proteins (MAPs), and CRMP2 (collapsin response mediator protein-2), are also Cdk5 substrates17.Cdk5 (cyclin-dependent kinase 5) is a proline-directed serine/threonine kinase that is ubiquitously expressed in the central nervous system8. The expression of p35 protein is high throughout the embryonic stage, whereas that of p39 increases during postnatal differentiation4. Mice lacking both p35 and p39 exhibit inverted cortical lamination, aberrant neuronal morphology, and defective synaptic functions, which are also observed in Cdk5-knockout mice19. These observations suggest that the activity of Cdk5 is attributable to its association with these two activators, which might have overlapping functions. However, knockout of p35 but not p39 results in inverted cortical lamination20. Meanwhile, p39 knockout results in impaired axonal branching and dendritic spine morphogenesis21. Although in vitro experiments suggest that p35 and p39 share similar substrate specificity, they are spatially segregated within neurons and have different biochemical properties23. Compared to p35, p39 exhibits slower degradation, higher membrane binding and nuclear accumulation, and lower affinity for Cdk524. Therefore, Cdk5/p35 and Cdk5/p39 complexes likely have distinct functional roles by targeting specific substrates in the nervous system. However, as most previous studies have focused on Cdk5/p35, the roles of Cdk5/p39 in brain development and functioning are less understood10.The Cdk5 activators, p35 and p39, share approximately 60% sequence homology and exhibit differential developmental expression in the brainIn this study, we show that p39-associated Cdk5 activity is required for dendritic development. Depletion of p39 but not p35 phenocopies Cdk5-deficient neurons, which results in shorter and fewer dendrites compared to wild-type neurons. Moreover, RNA sequencing and mass spectrometry analyses of phosphoproteins suggest that p39 regulates dendritic complexity by modulating the expression of a signaling adaptor protein, WDFY1 (WD repeat and FYVE domain-containing protein 1). Specifically, suppression of WDFY1 rescues the defective dendritic morphology in p39-deficient neurons. Furthermore, we identify multiple phosphorylation-dependent signaling pathways that regulate cytoskeletal dynamics as well as protein synthesis and trafficking in p39-dependent dendritic morphogenesis.26. Similar to neurons expressing Cdk5-DN, neurons expressing Cdk5-Y15F mutant exhibited shorter and fewer dendrites compared to those expressing Cdk5-WT  or dominant-negative Cdk5 (Cdk5-DN) in cultured rat hippocampal neurons at 7 days in vitro (DIV) and examined dendritic phenotypes at 14 DIV. Neurons expressing Cdk5-DN exhibited defective dendritic morphology as indicated by reductions of the total number of dendrites, dendrite length, and dendritic complexity , which was comparable to that in Cdk5-deficient neurons Fig. e–h. Re-eice Fig. a–h; meanice Fig. i–l. Of np39−/− mouse brains. Three-dimensional reconstruction of the dendritic trees of Golgi-stained p39−/− cortical pyramidal neurons showed that these neurons also exhibited reduced dendritic complexity characterized by shorter and fewer dendrites  and p < 0.05. We found that the most prominent cellular processes regulated in p39-deficient neurons involved (1) the “shape change of neurites,” (2) “organization of filaments,” and (3) “quantity of lipid droplets” , Rnd1 , Chn1 , Sema4D (Semaphorin 4D), and hgf (hepatocyte growth factor), are involved in the regulation of dendritic complexity  between p39−/− and wild-type neurons  in the hippocampi between p39−/− mice and their wild-type littermates by using isobaric tags for relative and absolute quantification (iTRAQ)-based proteomics analysis  analysis based on the PANTHER classification system37 showed that the differentially regulated phosphorylated proteins in the p39−/− mouse hippocampus were predominantly protein-modifying enzymes followed by cytoskeletal proteins, metabolite interconversion enzymes, and nucleic acid-binding proteins , suggesting that they are direct substrates of Cdk5/p39  and p < 0.05. Concordant with the effects of p39 on dendritic morphology, IPA of biofunctions revealed that in p39−/− hippocampi, the most upregulated cellular processes were (1) “retraction of neurites,” (2) “depolymerization of actin filaments,” and (3) “depolymerization of microtubules.” Meanwhile, the most downregulated cellular processes were (1) “formation of cellular protrusions,” (2) “quantity of vesicles,” (3) “microtubule dynamics,” (4) “organization of cytoplasm,” (5) “organization of cytoskeleton,” and (6) “axonogenesis”  “Rac signaling,” (2) “PI3K/Akt signaling,” (3) “FAT10 cancer signaling pathway,” and (4) “regulation of actin-based motility by Rho” , and (3) “cAMP-related pathways”  are differentially regulated genes in p39−/− neurons grouped under the “shape changes of neurites” biofunction. Importantly, these genes encode downstream signaling molecules in the Sema3A (class 3A Semaphorin) signaling pathway 32, which is the binding receptor for secreted Sema3. Suppression of WDFY1 rescued the defective dendritic phenotype in p39−/− neurons, suggesting that the precise control of Cdk5/p39 activity constrains WDFY1 expression and consequently regulates dendritic morphogenesis. Thus, our study suggests that Cdk5/p39 is a critical signaling control of dendrite growth that acts by regulating Semaphorin signaling components.While Cdk5 is a critical kinase that regulates neuronal functions, most studies have focused on the regulation and roles of p35-associated Cdk5 activity48. Besides gene transcription, their actions are mediated through the regulation of protein synthesis, protein trafficking, and cytoskeletal reorganization36. Concordantly, examination of the altered phosphoproteins in p39−/− brains revealed that Cdk5/p39 regulates canonical pathways that are the downstream signaling cascades of Semaphorin/NRP/plexin, reelin/ApoER2/VLDLR, and BDNF/TrkB signaling. In particular, PI3K/Akt- and cAMP-mediated signaling are critical mediators of protein synthesis and cytoskeletal reorganization50. Moreover, Rho family small GTPases including Rac1 and RhoA play critical roles in axonal and dendritic morphogenesis; they achieve this by regulating actin assembly and organization as well as gene transcription through the activation of downstream effectors51. Nonetheless, our results suggest that dendritic morphogenesis involves crosstalk between Cdk5/p39 and multiple signaling transduction pathways.Multiple cell surface receptors and their corresponding extracellular cues, including Semaphorin/NRP/plexin, reelin/ApoER2/VLDLR, and BDNF/TrkB, play critical roles in the regulation of dendritic morphogenesisp39−/− brains revealed the alterations signaling molecules downstream of Cdk5/p39. Accordingly, we identified 3 groups of dysregulated phosphorylated proteins in p39−/− brains. The first of such groups contains consensus Cdk5 phosphorylation S/TP sites and were downregulated in p39−/− brains. These proteins are potential substrates of Cdk5/p39, and many of them were first reported as possible Cdk5 substrates. The second group of dysregulated phosphorylated proteins consists of phosphorylated peptides that lack Cdk5 phosphorylation sites and were downregulated in p39−/− brains. For example, CRMP2, which is critical for mediating microtubule dynamics, undergoes Ser522 priming phosphorylation by Cdk5, which is essential for its sequential phosphorylation by GSK3β and hence the regulation of its activity53. The third group of dysregulated phosphorylated proteins exhibited increased phosphorylation in p39−/− brains. The altered phosphorylation of these proteins might be due to the dysregulation of other kinases in the absence of Cdk5/p39 activity. For example, kinases such as MEK1 (MAP kinase kinase 1) are negatively regulated by Cdk554. Therefore, the dysregulation of Cdk5/p39 might alter the phosphorylation of a network of proteins. Accordingly, unbiased, in-depth transcriptomic and phosphoproteomic profiling are required to characterize the roles of Cdk5/p39 in distinct cellular processes of certain brain functions such as dendritic morphogenesis.Phosphoproteomic profiling of Our results suggest that Cdk5/p39 acts as a central coordinator to regulate multiple signals from extrinsic cues to cytoskeletal signaling proteins to control the morphology of dendritic trees. Given that the precise control of dendritic arborization is critical for neural network integrity and that the dysregulation of these processes is implicated in various psychiatric and neurodegenerative disorders such as autism and Alzheimer’s disease, our results provide potential insights into the pathogeneses of such disorders.Cdk5−/− mice were kindly provided by A.B. Kulkarni  and T. Curran , and p35−/− and p39−/− mice were gifts from L.H. Tsai . All animals were bred in the Animal and Plant Care Facility of the Hong Kong University of Science and Technology (HKUST). All experiments were approved by the Animal Ethics Committee of HKUST and conducted in accordance with the Guidelines of the Animal and Plant Core Facility of HKUST.Cdk5, 5′-TGCCACGGGGAGAGACCTG-3′; rat and mouse p35, 5′-TATCAACCTCATGAGCTCC-3′; rat, mouse, and human p39, 5′-CCTGGTGTTCGTGTACCTG-3′; rat and mouse Wdfy1 #1, 5′-GCTCCTCAGTGGTTAGAAA-3′ and #2, 5′-GCGATTACTCGGGACAGAT-3′. The shRNAs were cloned into the pSUPER vector and compared to the pSUPER vector control. The knockdown specificity and efficiency of the pSUPER-Cdk5 shRNA construct have already been verified26. The knockdown specificities of the p35, p39, and Wdfy1 shRNA constructs were confirmed in p35-, p39-, or WDFY1-overexpressing HEK293T cells, respectively  to the pcDNA3 vector. The overexpression efficiency of WDFY1 in rat cortical neurons was also confirmed  and p39  were from Santa Cruz Biotechnologies; antibodies against p35  were from Cell Signaling Technology; antibodies against WDFY1 were from GeneTex ; and antibodies against α-Tubulin  and Actin  were from Sigma-Aldrich. The shRNA sequences and their targets were as follows: rat 26. To evaluate the efficiency of overexpression or knockdown, rat cortical neurons were transfected by nucleofection at 0 DIV using the Rat Neuron Nucleofector Kit  according to the manufacturer’s instructions. The overexpression or knockdown efficiency of neurons at 5 DIV was examined by western blotting.HEK293T cells were cultured in DMEM (Life Technologies) supplemented with 10% FBS (Life Technologies) and antibiotics. Lipofectamine (Life Technologies) with Plus-based transfection was performed according to the manufacturer’s protocols. Primary hippocampal or cortical neurons prepared from embryonic day 18 (E18) Sprague–Dawley rats or transgenic mice were maintained in Neurobasal medium (Life Technologies) supplemented with 2% B27 (Life Technologies). To examine dendritic morphogenesis, rat hippocampal neurons were transfected with a gene of interest together with a separate construct carrying emGFP at the indicated DIV using the calcium phosphate method as previously describedg at 4 °C for 5 min. The supernatants were saved, and the protein concentration was determined. Equal amounts of protein from each sample were run onto an SDS-PAGE gel, and the separated proteins were transferred to a nitrocellulose membrane. The membrane was blocked with blocking buffer (5% milk in TBS-T) at room temperature for 1 h, followed by incubation with primary antibodies including Cdk5 (1:1000), p35 (1:1000), p39 (1:2000), WDFY1 (1:2000), α-Tubulin , and actin  overnight at 4 °C. The membrane was subsequently incubated with horseradish peroxidase-conjugated secondary antibodies for 1 h. Signal detection was performed using SuperSignal WestPico Chemiluminescent Reagents and exposed to a Fujifilm Super RX X-ray film. The films were developed by a Kodak medical X-ray film processor.The mouse forebrains were homogenized in DPBS containing protease and phosphatase inhibitors, followed by lysis in 2× RIPA lysis buffer. The neurons were directly lysed in 1 × RIPA buffer containing protease and phosphatase inhibitors. The protein lysates were centrifuged at 10,000×Golgi staining was performed using an FD Rapid GolgiStain Kit  according to the manufacturer’s instructions. In brief, the transgenic mice were deeply anesthetized in an isoflurane-loaded chamber, and their brains were quickly dissected. The brains were then rinsed with water and gently bisected coronally. The brain pieces were incubated with equal volumes of solutions A and B for 10 days and subsequently incubated with solution C  for 3 days. The brain pieces were then slowly frozen in liquid nitrogen-chilled isopentane and sectioned at 160 μm using a CryoStar NX70 Cryostat (Thermo Fisher Scientific). The sections were dried for 2 days before staining with equal volumes of solutions D and E  for 10 min. After staining, the sections were subjected to sequential dehydration incubation in 50% ethanol, 70% ethanol, 95% ethanol, 4 times in absolute ethanol, and 3 times in xylene; each incubation step was performed for 4 min. The slides were mounted with Cytoseal 60 mountant  and dried for 2 days before imaging.56 plugin embedded in ImageJ software followed by analyses of neurite number, neurite length, and dendritic tree complexity. Sholl analysis57 was performed individually for each neuron from all groups. In brief, the center of the cell soma was set as the center of a series of concentric circles with radii at 10-μm intervals. Then, the intersections between the dendritic tree and the concentric circles were counted. Dendritic morphogenesis from transgenic mouse cortical neurons as indicated by Golgi staining was captured using a Leica DM6000 B compound microscope. The three-dimensional structure of dendritic trees was reconstructed by manual tracing using the filament tool embedded in Imaris (version 8.3.0). Dendrite number and length were also determined using the filament tool.Images of GFP-transfected hippocampal neurons were captured with a 20× dry lens using Leica SP8 confocal microscopy systems. Five to eight serial optical sections  were collected. The maximum projection of the serial images and subsequent analyses were performed using ImageJ (version 1.52a) software. Dendritic morphology was manually traced using the Simple Neurite TracerHprt.RNA was extracted using the NucleoSpin RNA column (MACHEREY–NAGEL) according to the manufacturer’s instructions. Single-strand cDNA was first synthesized using a PrimeScript RT Reagent Kit . Quantitative real-time PCR was performed with a Premix Ex Taq Kit  using a 7500 Fast Real-Time PCR System (Applied Biosystems). The mRNA expression was normalized to that of p39−/− mouse embryos and their wild-type littermates were cultured until 10 DIV. RNA was extracted using the NucleoSpin RNA column (MACHEREY–NAGEL), and RNA integrity was evaluated by a 2100 Bioanalyzer (Agilent). RNA samples with an RNA integrity number greater than 9 were selected for mRNA enrichment using oligo (dT) beads and fragmentation followed by cDNA library construction by Novogene (Beijing). The transcriptome profile of each sample was generated by Novogene on the Illumina HiSeq X platform. In brief, quality control was performed for the RNA sequencing dataset using FastQC58 and RSeQC59. Read mapping, counting, and differential gene expression analysis were performed using HISAT2, StringTie60, and DESeq261, respectively. The RNA sequencing dataset was submitted to Ingenuity Pathway Analysis 62 to identify the most regulated pathways. The pathways that met the following criteria are shown: activation z-score > 1.2 or <  −1.2 and p < 0.05.Cortical neurons from E18 p39−/− mice and their wild-type littermates were processed for iTRAQ labeling by Shanghai Applied Protein Technology. In brief, hippocampal tissues were separately lysed in SDT buffer  and sonicated. Six samples were labeled using the iTRAQ method and mixed. Phosphorylated peptides were subjected to TiO2-based enrichment followed by LC–MS/MS analysis in Thermo Scientific Q Exactive (Shanghai Applied Protein Technology). Unique peptides and protein mapping were performed using Proteome Discovery 1.3 (Thermo Electron) with reference to the UniProt database63 (mouse).The hippocampi of 3 pairs of 1-month-old p < 0.05 were selected for GO analysis based on the PANTHER classification system37. Pathway analysis was also performed using IPA in the categories of “biofunction” and “canonical pathways” similar to RNA sequencing analysis. The criteria for the output pathway were as follows: activation z-score > 1.5 or <  − 1.5 and p < 0.05.Dysregulated phosphoproteins meeting the criterion of U-test or Student’s unpaired t-test was performed where appropriate to evaluate the significance of differences between 2 experimental conditions. Kruskal–Wallis one-way ANOVA followed by Dunn’s test was performed where appropriate to evaluate the significance of differences of 3 or more experimental conditions. All experiments were performed independently at least 3 times or on 3 animals per group.All data are presented as mean ± SEM. The Mann–Whitney Supplementary Information 1.Supplementary Information 2.Supplementary Information 3.


In this study, the bag breakup behavior of the polymer droplet is investigated numerically. The simple coupled level set and volume of fluid (S-CLSVOF) method and the adaptive mesh refinement (AMR) technique are employed in the droplet breakup cases at different Weber numbers and Ohnesorge numbers. The nature of the polymer solution is handled using Herschel–Bulkley constitutive equations to describe the shear-thinning behavior. Breakup processes, external flow fields, deformation characteristics, energy evolutions, and drag coefficients are analyzed in detail. For the bag breakup of polymer droplets, the liquid bag will form an obvious reticular structure, which is very different from the breakup of a Newtonian fluid. It is found that when the aerodynamic force is dominant, the increase of the droplet viscous force will prolong the breakup time, but has little effect on the final kinetic energy of the droplet. Moreover, considering the large deformation of the droplet in the gas flow, a new formula with the cross-diameter ( The fluids used in many spray processes mostly contain various kinds of additives, such as polymers and nanoparticles, which can make rather dramatic changes to the rheological behavior of the fluids. These fluids usually exhibit non-Newtonian behaviors, such as viscoelastic, shear-thickening, and shear-thinning . The fluWe) and Ohnesorge number (Oh). For a low Ohnesorge number (Oh < 0.1), with increasing the We number, the five breakup typical breakup modes occur: vibrational, bag, multimode, sheet-thinning, and catastrophic [To understand the droplet breakup process, experimental studies have been extensively conducted. It has been found that the droplet breakup of a Newtonian fluid is mainly governed by the Weber number  , volume g et al. ,27 used o et al.  used diro et al.  used couThe paper is structured as follows. In U is the velocity vector of the flow field, p is the pressure, Fσ is the volume force, and ρ is the fluid density. The phase fraction α is used to represent a space mesh cell whether is occupied by the dispersed phase or the continuous phase. When the cells are full of the dispersed phase, the value of α is unity; the continuous phase corresponds to zero. When the mesh cells contain both the dispersed phase and the continuous phase, the value of α is between 0 and 1, which denotes an interface between the two phases.The problem considered in this work is the polymer solution droplet breakup in airflow. The simple coupled level set and volume of fluid (S-CLSVOF) method is used in our paper, which can accurately capture the complex process of the interface evolution and has good mass conservation. The S-CLSVOF multiphase model has been proven to be capable in revealing the deformation mechanisms of liquid droplets by Yang et al. . In theiUcα(1 − α)) is introduced to sharpen the interface [Uc is the compression velocity to suppress diffusion of the interface, which can be calculated as follows:αc is compression coefficient, generally a constant greater or equal to 1. The term ∇α/|∇α| is introduced convection of volume fraction function normal to the interface. Then the term α(1-α) can be used to ensure itself invalid in the outside of the interfacial area and the divergence operating guarantees conservation in terms of the entire compression term. The phase-fraction transport equation for the VOF function α is solved in the whole computational domain as a guarantee of the mass conservative nature.In the original VOF function (3), the additional compression term ∇ ⋅ Γ as prime ψ guess value, where Γ is a non-dimensional number. Then re-distanced by a reinitialized equation. The formula is as follows:τ is the artificial time step. S(ψ0) is a sign function defined with S(ψ0) = ψ00|/|ψ. The solution of ψ converges to |∇ψ| = 1, which is a signed distance function around the interface, and the interface position is defined at the contour-line ψ = 0. The number of iterations (corrψ) meet the following condition:ε is the interface thickness. Then the interface normal vector n obtained from the LS field function is also used to calculate the interface curvature κ and volume surface tension σF to ensure the accuracy of the interface calculation.σ is the surface tension coefficient and δ is the Dirac function used to ensure that the surface tension acts on the gas-liquid interface. The physical properties and the fluxes across the cell faces can be defined using a smoothed Heaviside function:μ1 and ρ1 are the viscosity and density of the liquid droplet, gρ and gμ are the density and viscosity of the gas.At the same time, introducing the level set function We), Ohnesorge number (Oh), Reynolds number (Re), and non-dimensional time (T). At higher flow velocity, inertial forces deform the drop and lead to its breakup, which is characterized by the aerodynamic Weber number. The Ohnesorge number relates the viscous forces to inertial and surface tension forces. The Reynolds number is used to describe the ratio of the inertial force to the viscous force. As the breakup process is not instantaneous, experimentally observed times are typically made non-dimensional using the characteristic time. The detailed definition is as follows:rU is the initial relative velocity between the droplet and ambient, σ is the surface tension, t is the dimensional time, θ is the drop-to-ambient density ratio, D is the initial diameter of polymer droplet.The study of droplet breakup is inseparable from some dimensionless parameters. Commonly used dimensionless numbers include Weber number  or shear-thickening (n > 1) behavior. In this paper, the non-Newtonian water/carbomer solutions are taken into account. Its shear-thinning property is approximated by the Herschel–Bulkley rheological model . Hersche0μ is the zero shear viscosity.The model can be rewritten as a generalized Newtonian fluid model to define the apparent viscosity of polymer solution as ,33,(15)Oh number changes as follows [For non-Newtonian fluids, considering the effects of viscous dissipation and elastic recovery, the  follows :(16)OhefD = 5 mm is placed in the cube computational domain. The droplet is placed on the normal axis of the gas inlet boundary surface, and the distance from the boundary surface is controlled as 2D.The computational domain is shown in The setup of the computational domain needs to consider both the size and the grid resolution. A suitable computational domain size can ensure that the boundary conditions do not affect the simulation. There are four computational domain sizes for simulation verification. The computational domain size settings and the initial stage of the droplet are shown in The deformation and breakup of the droplet are simulated under different computational domain size. The results are as shown in iniT and the bag breakup time bagT no longer change obviously. The initial breakup time is defined as the interval required for a droplet to deform beyond the oblate spheroid shape, and the bag breakup time is defined as the time when the bag first breaks. Finally, the computational domain size 8D · 8D · 24D (Domain 3) is selected for simulation.As shown in The grid size of the interface, determining the accuracy and numerical stability of droplet deformation simulation, is important for capturing the liquid-gas interface. The result of using adaptive mesh refinement near the interface shows in D/Δx = 80, 160 and 320 are given in x is the minimum grid size. The results demonstrate that the droplet deformation and breakup are nearly independent of the mesh size when the D/Δx is larger than 160. Therefore, the interface grid resolution of D/Δx = 160 is adopted to research the deformation and the fragmentation of the droplet in all of the following simulations.The contours of the droplet related to three numerical resolutions with We = 22.09 and Oh = 0.0021. The comparison between the numerical and experimental results are shown in To validate the accuracy of the numerical model, the simulations are compared with the experimental data. In the experiment, the carbomer solution with a mass fraction of 0.015 wt% was chosen for the experimental study of droplet breakup. The single carbomer solution droplet injected into continuous air flows were investigated by using a high-speed camera under the condition of We number and Oh number on the droplet breakup process is analyzed. The Oh number can be calculated by Equation (15). For the polymer solution (Carbomer), the liquid density 1ρ is 1000 kg/m3, and the surface tension σ is 0.0751 kg/s2. The computational parameter settings of the numerical simulation cases are shown in In the present study, the influence of the We of 8.25, 21.1, and 33.3 are respectively implemented to study the effect of We on the droplet breakup morphology. A sequential picture of droplet deformation and breakup is shown in We = 8.25, the thickness of the oblate droplet is larger than in other cases. Additionally, the breakup of the droplet is not a bag breakup in this case, but close to that. As the We number increases to 33.3, the thickness of the droplet becomes thinner during the deformation. The droplets can form an obvious bag shape under the action of airflow. The droplet deformation degrees have expanded significantly. However, compared with the experiment results from Kulkarni et al. [The process of bag breakup can be divided into four stages: deformation, bag growth, bag breakup, and ring breakup . For comi et al. , the fraThe deformation of a droplet is closely related to the velocity field around it. For all cases in We number on the bag breakup is more clearly reflected. With the increase of the We number, the thickness of the droplet during the deformation stage gradually decreases, and the droplet becomes more easily break. But during the breakup, the liquid bag stretches into a filament, and only a small number of sub-droplets are separated from the mother droplet.The results obtained for the droplet shapes in the 2D domain are presented in wiseD is the deformed drop diameter in the stream-wise direction and croD is the deformed drop diameter in the cross-stream direction. These two diameters are converted into a dimensionless number by wiseD/D and croD/D to describe the degree of the droplet deformation.The initial stage of droplet breakup is from spherical shape deform into a shape that can be approximated as an oblate ellipsoid. This is illustrated in We numbers  and three Oh numbers . In Oh = 0.002, the stream-wise deformation (wiseD/D) initially decreases due to droplet flattening, followed by an increase owed to the formation of the liquid bag, while the cross-stream deformation (croD/D) increases during the whole duration of the process. For the cross-stream deformation, although the trend shows an upward tendency, there are differences in each stage. In the initial stage, the cross-stream deformation (croD/D) of the droplet will increase to a relatively fixed value. In the intermediate stage, the deformation will still increase, but the rate of rising will decrease. This indicates that there is a deformation block point between the initial and intermediate stages. As seen in We = 21.1 and 33.3. This is mainly because the bag structure formed by the external aerodynamic force is in a relatively stable stage under these two conditions. At this stage, the deformation degree of the droplet is relatively stable.As shown in Oh number increases, the tendency of droplet deformation decreases, which shows the opposite trend compared with Oh number presents the increase of viscous force which results in a lower deformation rate. When the Oh number is low (Oh = 0.02 and 0.002), the trend of droplet deformation has no significant difference. This is related to the viscous force of the droplet in these two cases. In these conditions, the dominant effect of droplet deformation is still the aerodynamic force, while the effect of the viscous force is small. Therefore, when the Oh value is low, the deformation degree of the droplet in the breakup process changes little. However, when Oh = 0.2 (Oh > 0.1), the droplet deformation is evidently inhibited.In E) of the droplet can be calculated as follows:cellsN is the number of the computational cell. cellα is the volume fraction of the liquid phase. cellv is the volume of a computational cell. 1ρ is the liquid density, ijku, ijkv and ijkw are the velocity component. As shown in We number , the kinetic energy of the droplet is low when breakup. With the increase of the We number, the total kinetic energy of the droplet also raises. When the breakup occurs at the cases of the same We number, the increase in the viscous force has a hindering effect on the energy growth rate during the droplet movement, but this effect is clearly reflected when Oh = 0.2 (Oh > 0.1). Although the high viscous force will hinder the growth rate of the kinetic energy of droplets, the total kinetic energy of the droplet during the breakup process is approximate. Especially, for the cases of We = 33.3, the total kinetic energy of the droplet almost identical, and the kinetic energy value is 0.00022 J. However, the breakup time will be extended with the increasing of Oh number. The change of kinetic energy of droplet is closely related to the deformation of droplets. As shown in We number, the deformation degree of the droplet shows no obvious difference at the breakup time, which is consistent with the trend of the droplet kinetic energy. Aerodynamic forces affect the deformation of droplets. In the process of droplet shape changing from spherical to flat, the contact area between droplet and airflow is determined by the cross-stream deformation of droplet. The faster the cross-stream deformation of the droplet changes, the larger the contact area between the airflow and the droplet surface. Eventually, the kinetic energy of droplet increases faster. According to the result of the analysis of droplet deformation, when the effect of aerodynamic force is higher, the viscosity of the droplet has less influence on the final evolution of kinetic energy. This leads to a situation that the kinetic energy of the droplet increases faster, but the final total kinetic energy is similar.In the process of droplet breakup, the energy is provided by aerodynamic force. As shown in The drag coefficient of the droplet is important for evaluating the process of droplet breakup. When a droplet is in ambient airflow, it will be affected by the airflow. The unequal distribution of the static pressure is formed over the droplet surface, which can cause the deformation of the droplet. As a result, the droplet will be compressed in the stream-wise direction of the airflow. In this process, the drag coefficient of the droplet will change greatly. According to Temkin and Kim , the stacroD) is used in calculating the frontal area. Equation (18) can be transformed into:In the definition of drag coefficient used here, considering that the droplet will deform in the airflow, the cross-stream diameter  and Oh  numbers. As shown in We number increases, the drag coefficient raises, which is related to the kinetic energy of the droplet. The growth of kinetic energy can accelerate the deformation of the droplet. The deformation in the cross-stream direction causes an enlargement for the contact surface between the droplet and the airflow. Then the resistance force on the leeward side of the droplet amplifies, resulting in a raise for the drag coefficient. According to the trend of kinetic energy in We number, the droplet drag coefficient not only continues to rise, but also rises faster. It is worth noting that the drag coefficient reaches its maximum value before the droplet breakup. After the bag breakup time, the drag coefficient decreases rapidly.Oh numbers is the same as that in Oh = 0.002, 0.02, and 0.2). For the cases of Oh = 0.002 and 0.02, the evolution of the drag coefficient is basically in coincidence. According to the evolution of the kinetic energy, the increase of viscous force will have a slight effect on the droplet’s energy. As a result, the deformation of the droplet is similar when it is broken, causing the drag coefficient is so close. Additionally, with the Oh number increases, the growth trend of the droplet drag coefficient will slow down.As shown in dC largely was a function of the degree of deformation of the droplet from the research of Hsiang and Faeth [y represents the non-dimensional displacement of the drop equator, which can be written as y = 1 − (D/croD)2. d,sphereC is the coefficient of drag for a sphere at the same Reynolds number Re > 2000. Its value is 0.47 here. For the deformation of the bag breakup initial stage, it was found that nd Faeth . Then Lind Faeth  proposedWe = 8.25, 21.1, and 33.3) is compared with the result of Liu’s empirical expression. When We = 8.25, the drag coefficient obtained by simulation is lower than the result of the empirical expression. When the We number is higher , the drag coefficient which changes with the non-dimensional displacement is higher than the result of the expression. As the We number increases, the result shows that the drag coefficient in the deformation state will increase. It can be found that the empirical formula of Liu et al. is not suitable for describing the drag coefficient in this research.As shown in Based on the simple coupled level set and volume of fluid method (S-CLSVOF) and adaptive mesh refinement (AMR) technique, the bag breakup of the polymer solution droplet was studied by numerical simulation. The S-CLSVOF method combines the advantages of VOF and LS methods and the AMR technique significantly reduces the computational cost. From numerical simulations, the effects of the velocity field on the breakup results of the polymer droplet were investigated. Furthermore, the droplet deformation, the energy evolution, and the drag coefficient were discussed in detail. The conclusions are as follows:(1) The shear-thinning droplet bag breakup mode is similar to the Newtonian, but the difference is that the shear-thinning droplet has a mostly intact rim, and the liquid bag forms ligaments. Moreover, during the process of droplet breakup, the velocity distribution and the droplet deformation influence each other. The vortices located on the leeward side of the droplet changes from symmetrical to asymmetrical, which continuously affects the morphological change of the droplet.We = 33.3), the increase of viscous force has little effect on the total kinetic energy of the droplet when it breaks. However, it will extend the breakup time significantly.(2) For polymer solution droplet bag breakup, when the Weber number is higher (croD) is introduced to calculate the frontal area, the new formula of the drag coefficient is proposed. This formula can be used to estimate the transient drag during the bag breakup process. For the cases of moderate Weber number (We = 18.5) in the bag mode, the value of the drag coefficient is approximate when the droplet breaks up, which is not affected by the effect viscous force to some extent. (3) Considering the deformation of the polymer droplet, the cross-stream diameter (


Mutated residues were located either in or adjacent to several acidic amino acid stretches – formerly indicated to be involved in CPR:CYP interactions – or close to two tyrosine residues suggested to be involved in FMN binding. Several of the identified positions co-localize with mutations found in naturally occurring CPR variants that were previously shown to cause CYP-isoform-dependent effects. The mutations do not seem to significantly alter the geometry of the FMN-domain but are likely to cause very subtle alterations leading to improved interaction with a specific CYP. Overall, these data suggest that CYPs interact with CPR using an isoform specific combination of several binding motifs of the FMN-domain.NADPH cytochrome P450 oxidoreductase (CPR) is the obligatory electron supplier that sustains the activity of microsomal cytochrome P450 (CYP) enzymes. The variant nature of the isoform-specific proximal interface of microsomal CYPs indicates that CPR is capable of multiple degenerated interactions with CYPs for electron transfer, through different binding mechanisms, and which are still not well-understood. Recently, we showed that CPR dynamics allows formation of open conformations that can be sampled by its structurally diverse redox partners in a CYP-isoform dependent manner. To further investigate the role of the CPR FMN-domain in effective binding of CPR to its diverse acceptors and to clarify the underlying molecular mechanisms, five different CPR-FMN-domain random mutant libraries were created. These libraries were screened for mutants with increased activity when combined with specific CYP-isoforms. Seven CPR-FMN-domain mutants were identified, supporting a gain in activity for CYP1A2 , 2A6 , or 3A4 (N151D). Effects were evaluated using extended enzyme kinetic analysis, cytochrome  NADPH cytochrome P450 oxidoreductase (CPR) is the crucial electron donor of all microsomal cytochrome P450s (CYPs), involved in drug and xenobiotic metabolism, but also in other key biochemical processes such as cholesterol and fatty acid homeostasis and steroid hormone biosynthesis . Moreovein vivo existence of CPR:CYP stoichiometry’s in favor of CYP, implying competition between individual CYP isoforms in binding to CPR in the ER  competition were performed, to confirm improved interaction. Structural analyses were carried out to rationalize the role of the mutated FMN-domain residues in the CPR:CYP degenerate interaction. Collectively, our data seems to indicate that each CYP interacts with CPR in a isoform specific manner, involving specific combinations of binding motifs of the FMN-domain which were formerly identified to be involved in the CPR:CYP interactions.The present study describes the search for structural features of CPR’s FMN-domain, responsible for its degenerated interaction with CYPs, for effective sampling of open conformations. This was accomplished through the isolation and study of FMN-domain mutants selected for increased CYP activity when combined with specific isoforms. These mutations, expected to lead to improved interaction of CPR with these CYPs, should be informative on the localization and nature of features required for this “one-serve-all“-type of interaction. Random mutation libraries of the FMN-domain in full length human CPR were created, with increasing mutation frequencies. Each of these libraries was combined with three representative human drug metabolizing CYP isoforms , phylogety assay . Using mL-Arginine, thiamine, chloramphenicol, ampicillin, kanamycin sulfate, isopropyl β-D-thiogalactoside (IPTG) (dioxane-free), δ-aminolevulinic acid, glucose 6-phosphate, glucose 6-phosphate dehydrogenase, nicotinamide adenine dinucleotide phosphate (NADP+ and NADPH) were obtained from Sigma-Aldrich . LB Broth, bacto tryptone and bacto peptone were purchased from BD Biosciences . Bacto yeast extract was obtained from Formedium . Ethoxyresorufin, methoxyresorufine and coumarin were obtained from BD Biosciences  and dibenzylfluorescein from Santa Cruz Biotechnology . Resorufin, 7-hydroxy coumarin, fluorescein and dichlorophenolindophenol (DCPIP) were obtained from Sigma-Aldrich . A polyclonal antibody from rabbit serum raised against recombinant human CPR obtained from Genetex  was used for immune-detection of the membrane-bound CPR. All other chemicals and solvents were of the highest grade commercially available.POR cDNA . Error-prone PCR (epPCR)  using BLAST (version 2.3) (NCBI) and MultAlin . Five different libraries were generated with increasing mutation frequencies  of human  (epPCR)  was used (epPCR) , which ycies see .wt . Alternatively, mutated fragments were used as mega-primers and cloned back into plasmid pLCM_POR using mega-primer PCR of the whole plasmid (mwPCR) (DpnI treatment (Thermo Fisher Scientific). The five FMN-domain mutant-libraries, harbored in the pLCM_POR plasmid were used to transform E. coli PD301 (mut/CYP versus when containing wild type CPR: CPRwt/CYP).The five pools of the mutated FMN-domain segments present in pUC_POR were cloned into the human full-length wild type CPR expression vector pLCM_PORwt , through (mwPCR) , followeli PD301 , 2007, ali PD301  for humamut/CYP clones were picked from overnight grown LB agar-plates supplemented with chloramphenicol 10 μg/L, ampicillin 50 μg/L and kanamycin 15 μg/L, and transferred to single wells of flat-bottom 96-well microplates , previously filled with 200 μl LB broth supplemented with antibiotics (see above). This procedure was partially executed with the use of a Biomek 2000 Laboratory Automation Workstation  and the Kbiosystems K2 automated colony picker system . Culture microplates were incubated at 37°C, for 16 h with agitation (250 rpm), and subsequently supplemented with 10% glycerol and stored at −80°C.CPRStored (−80°C) cultures were transferred by replicate plating to new flat-bottom 96-well microplates, previously filled with 200 μl LB broth supplemented with antibiotics (see above) and incubated at 37°C, for 16 h, at 250 rpm. Subsequently, 50 μl of the grown cultures was used to inoculate a 96-deep well plate , previously filled with 1400 μl TB medium, pH 7.5 (except for the CYP3A4 containing strains cultured at pH 6.8), supplemented with designated antibiotics (see above), 2 g/L peptone, 1 mg/L thiamine, 0.04% (v/v) trace elements solution, IPTG 0.2 mM, δ-aminolevulinic acid 0.05 mM (CYP1A2 expressing clones) or 0.1 mM (CYP2A6 and CYP3A4 clones). Cultures were grown at 27°C, at 310 rpm agitation for 22 h, using gas-permeable membranes .CYP content of individual well-cultures was determined using the method described by kobs) [pmol of fluorescent product formed/(pmol of CYP per minute)] were measured. Cultures of CPRwt/CYP and CPRnull/CYP were used as controls in all experiments. Control strains were obtained for each CYP : one expressing CPRwt, through expression plasmid pLCM_PORwt, or with the mock plasmid pLCM (lacking POR cDNA), each combined with the respective human CYP expression plasmid (pCW_CYP)  . Clones mut/CYP clones using GeneJET Plasmid Miniprep Kit (Thermo Fisher Scientific). The cDNA encoding full length human CPR of isolated clones was extensively sequenced, using four sequencing primers (see Plasmid DNA was isolated from overnight cultures of selected CPRmers see  for idenmut/CYP clones were prepared and characterized for CYP- (CO-difference spectrophotometry), CPR- (immune-detection by western blotting) and protein-contents (Bradford assay), using previously described methods  to determine steady-state kinetic parameters, using GraphPad Prism 5.01 Software   .E. coli BL21-DE3 and purified as reported by kobs) were measured at least in triplicate [pmol of fluorescent product formed/(pmol of CYP per minute)].Full length human CYB5 was expressed in 2, aligned and analyzed (position-numbering was based on NCBI consensus sequences NM_000941.3) using the AliView software version 1.25 . The alignment was performed with the MUSCLE algorithm from the AliView embedded routine.Sequences of CPR proteins were downloaded from Universal Protein Resource (UniProt)wt as the starting material. Mutations were constructed with the YASARA software3 and two independent molecular dynamics simulations were run at 298 K for 24 ns, using the AMBER14 force field, with 0.9% NaCl and pH 7.4. Snapshots of the simulation were taken every 100 ps. The YASARA software was used to calculate the coordinates of the average molecule for the WT and mutants and the root mean square fluctuation (RMSF) deviations calculated for each atom introduced as B factors.The structural analysis of three mutants  was performed using the crystal structure PDB 5FA6 of the FMN-domain of human CPRt-test was performed for calculation of the two-tailed P-value. The analysis was performed with 95% confidence interval using the GraphPad Prism 5.01 Software. The significance level considered in all the statistical tests was 0.05.Variance in data was analyzed through one-way ANOVA with Bonferroni’s multiple comparison test. The unpaired Student’s POR gene carrying random mutations were generated with increasing frequencies, namely 0.9, 1.0, 1.2, 1.3, and 1.4 mutations per FMN-domain segment . From the 2376 CPRmut/CYP clones screened, seven were selected due to enhanced CYP activities (kobs increase ranging from 1.2 to 7.25 × fold)  . The cDN × fold) .mut/CYP clones for confirmation of increased CYP activity and for further detailed analysis. Characterization of contents of heterologous expressed proteins from the selected seven CPRmut/CYP clones is shown in wt for each CYP, demonstrating no significant differences (P > 0.05). The only exception was found for the A229T CPR variant, for which the CPR:CYP1A2 ratio was approximately three times smaller when compared to CPRwt. Thus, the data of this mutant was interpreted subsequently with caution.Membrane fractions were isolated from the selected seven CPRkcat) of the seven selected CPRmut/CYP candidates, when compared to those measured with CPRwt/CYP  content and redox potential for all CPR mutants. In summary, the observed differences in CYP activities for the different CPRmut originate only from their improved interactions with their CYP partner, with the possible exception of the A229T mutant (vide supra).Detailed analysis using membrane preparations confirmed enhanced turnover rates  were determined for the seven CPR-FMN-domain mutants with various CYB5/CPR ratios for CYP1A2, 2A6, or 3A4-mediated reactions , at low and high CYB5/CPR ratios. This was particularly true for CYP2A6 and CYP3A4  for which they presented increased activities  are probably not altered by the mutations and thus that the effects of the mutations are probably more related to modified interactions between CYPs and CPRmut. As such, subtle changes in ionic interactions between the FMN-domain mutants and these CYPs may well be obscured by the major ionic strength effect on CPR’s open/closed dynamics.In order to verify if the FMN-domain mutants have altered isoform specific sensitivities toward ionic strength , activities of CYPs with their specific CPR mutants were tested with various NaCl concentrations . The CPRmut/CYP2A6 activity profiles were analogous to CPRwt/CYP2A6 and thus the optimal concentration of NaCl (between 50 and 150 mM) to obtain maximal velocity of CYP2A6 is undistinguishable between CPRwt and CPRmut. However, at ionic strength above 300 mM, all CPRmut displayed increased sensitivities to ionic strength which translated into lower CYP2A6 activities. The nature of the CPR mutations, for which there is no evident pattern of electrostatic change , together with the fact that the increased sensitivities to ionic strength are specific to CPRmut that have augmented activities with CYP2A6, may again indicate specific effects of the mutations on the recognition with CYP2A6 although effects on the open/closed dynamics of CPR cannot be totally excluded based on our former observations.On the contrary, this was not the case for the CPR mutants obtained with CYP2A6 . With NaLittle is known about the mechanism by which CPR selects one of its many ET partners . It seemwt and CPRmut combined with CYP1A2, which may hinder the detection of possible binding differences between wild type and mutant CPRs. Indeed the ability of CYB5 to bind CYP and to compete with CPR has recently been demonstrated by NMR studies to be dependent on multiple factors including the effect of the substrate bound and membrane anchoring  depends partly on the level of ionic interactions in the CPR:CYP complex, which our former  , which hwt and CPRmut  to phenotypical normal individuals with, e.g., infertility (POR mutations.Natural occurring variations of these CPR motifs may alter CYP-activity profiles, with the potential of causing specific genetic susceptibilities and pathologies. Drugs are metabolized for their excretion, frequently with involvement of multiple CYP isoforms. Natural occurring FMN-domain variants of these motifs may change the relative involvement of CYP isoforms, leading to altered metabolic profiles. In turn, this may potentially be related to lack of efficacy in drug treatment and/or adverse drug reactions. Likewise, genetic variations of residues forming the FMN-domain motifs may influence specific CYPs involved in steroidogenesis. Naturally occurring variants of the ertility . Former ertility . Our datThe authors dedicate this research to the memory of Dr. Henry W. Strobel.All datasets generated for this study are included in the article/FE, GT, and MK: planning experiments. FE, DC, BG, and SB: performed experiments. All authors: data analysis and interpretation, writing, reviewing, editing of the manuscript, and approval to the final version of the manuscript. GT and MK: coordination and funding acquisition. All authors reviewed and gave approval to the final version of the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Chondrostereum purpureum (Pers. Ex Fr.) Pouzar, has been investigated in Europe, Northern America and New Zealand for its ability to decay hardwood stumps and thus prevent sprouting. The aim of these investigations has been to find an alternative to mechanical (cutting only) and chemical sprout control . Mechanical sprout control is not an efficient option due to hardwood tree species’ ability to re-sprout efficiently after cutting, and therefore management costs are high. Chemicals would be efficient but due to their harmful effects on the environment, alternatives are needed. The fungal treatment, i.e., cutting accompanied with C. purpureum inoculum is an environmentally friendly and efficient option for sprout control. This mini-review comprises the role and function of C. purpureum in biocontrol of trees: the ecology of C. purpureum, its sprout control efficacy, factors affecting sprout control efficacy, devices in biological sprout control, potential risks, and the future perspectives of biological sprout control.A decay fungus, • A fungus Chondrostereum purpureum is efficient in preventing sprouting of hardwoods• C. purpureum is not sensitive to environmental conditions• Devices should be developed for cost-efficient biological sprout control Microorganisms such as fungi and bacteria, or the compounds that they produce, have potential as biological control agents in preventing the growth of harmful pests and diseases as described in many mini-reviews  Pouzar, that can be utilized as a biological control agent due to its efficient ability at preventing sprouting, potentially even as efficiently as chemicals , alder (Alnus incana (L.) Moench, A. rubra Bong.), box elder , and cherry species  with stump mortalities of 80–100% after the treatment  (Hamberg and Hantula Sorbus aucuparia L.), goat willow , and black locust (Robinia pseudoacacia L.) with stump mortalities less than 60% , has been observed in birch (Betula pendula and B. pubescens) , rowan (Sorbus aucuparia), and European aspen (Populus tremula) but also in other hardwoods (Hamberg Although  Hamberg . Height Sorbus aucuparia), aspen , and gray alder (Alnus incana), also produce root suckers that increase the number of competing saplings around cultivated trees , and the physiological state of a tree , the sprout control efficacy of C. purpureum is good when the treatment is performed in spring or summer but it seems to decrease towards the end of the growing season , sprout control efficacy is highest in summer while in spring and autumn, it is clearly lower (Hamberg Populus tremula), the fungal treatment has been successful early in spring  saplings 0.5–6.0 cm in stump diameter were cut and treated with C. purpureum inoculum, larger stumps died faster than smaller stumps (Hamberg and Hantula Alnus incana), all stumps irrespective of stump diameter were prone to the treatment , but this effect disappeared during the second growing season following stump treatment (Hamberg and Hantula C. purpureum to kill inoculated stumps. Both increasing volume of standing trees (> 5 cm in diameter at breast height) and the number of other saplings around a treated stump increase stump mortality , conspecific mature trees around an investigated stump—possibly belonging to the same clone—can provide support for stumps treated with C. purpureum  in the field  but two growing seasons after the fungal treatment, this effect on stump mortality is no longer observed , rain showers may initially delay the sprout control efficacy of C. purpureum but three growing seasons after the fungal treatment, stump mortality is as high for stumps treated in a rainstorm as in sunny weather  and its hybridization with the European H. annosum (Fr.) Bref. (1888) in Italy  reproduction. Therefore, the genes of the biocontrol strain will mix freely with those of the natural population of C. purpureum as soon as basidiospores are produced. In this process, the combination of alleles in the obviously efficient isolate to be used will break down by genetic recombination, and the original genotype will not spread outside the treated areas. Therefore, the risk of widespread dispersal of a highly virulent C. purpureum clone does not exist.Population analyses  in nature will slow down such a change, if it even occurs. Regardless, the development of genetic diversity of this fungus should be followed over time where its use in the biocontrol of hardwood sprouting becomes a common practice.The unwinding of allele combination is true also, as in the case of the Finnish biocontrol strain R5, which was created by a short breeding program  are not willing to register the product in the EU, and as there is no registration, the possible developers of such machinery are not interested in investing in such developments. The need for an efficient sprout control is, however, increasing as the workforce for manual treatments is declining, and therefore the self-defeating circle will probably be broken sooner or later. If so, the final solution could be a lightweight mini-harvester due to the need for carrying large amounts of liquids.The economic limit—i.e., the challenge to be overcome—of using biological control in forest regeneration sites can be set to the price of the second round of a man-made treatment with a clearing saw, as today two-phase PCT-work is typically conducted in northern Europe. The main issue to be solved will be how to target the biocontrol agent exactly on the stumps of cut hardwoods which are small in diameter, instead of spreading most of it off the target. In order to solve this, both purely mechanical solutions where collecting aligns the stump surfaces with the face of the treatment nozzle and more advanced technology using, e.g., artificial vision and intelligence to recognize and individually treat each stump surface can be imagined. In both cases, the additional time consumption of the treatment should be minimized (Laine et al. C. purpureum on different continents are obvious despite their biological conspecificity (Hamberg et al. As genetic differences between Chondrostereum purpureum, is efficient in decaying wood and as a fungal inoculum is a potential option in controlling excessive regrowth of hardwoods from stumps. Sprout control efficacy of C. purpureum varies in different tree species, and the growth of fungal hyphae within a stump is also affected by the physiological state of a host tree. Biological sprout control is not sensitive to environmental conditions, and therefore it can be used also during hot and rainy periods and in different soil moisture conditions. However, fungal inoculum should be spread on fresh stump surfaces immediately after cutting. From this point of view, fully mechanized devices capable of carrying the weight of fungal inoculum are optimal options in biological sprout control in the future.A decay fungus,


Distribution mismatch caused by various resolutions, backgrounds, etc. can be easily found in multi-sensor systems. Domain adaptation attempts to reduce such domain discrepancy by means of different measurements, e.g., maximum mean discrepancy (MMD). Despite their success, such methods often fail to guarantee the separability of learned representation. To tackle this issue, we put forward a novel approach to jointly learn both domain-shared and discriminative representations. Specifically, we model the feature discrimination explicitly for two domains. Alternating discriminant optimization is proposed to obtain discriminative features with an l2 constraint in labeled source domain and sparse filtering is introduced to capture the intrinsic structures exists in the unlabeled target domain. Finally, they are integrated in a unified framework along with MMD to align domains. Extensive experiments compared with state-of-the-art methods verify the effectiveness of our method on cross-domain tasks. A basic assumption of many machine learning algorithms is that the training and testing data share the same distribution. Now, data sources are more diverse due to the lower costs of data acquisition. For visual images, it may cause inconsistent distribution with some small changes such as lighting conditions, acquisitions, or backgrounds. It is expensive to label each source’s data. Domain adaptation aims to train a robust classifier based on a labeled source domain to predict on an unlabeled target domain , which aAn intuitive idea for domain adaptation is to re-weight the training samples and reduce the distance between the source and target domains at the instance level . AnotherMany studies focus on dimensionality reduction to facilitate calculation and visualization . SimilarMost existing methods attempt to shorten the distance between two domains in different feature spaces while maintaining certain statistical characteristics . DespitWe propose a novel unsupervised domain adaptation solution to reduce domain discrepancy and extract discriminative features simultaneously. Compared to existing works, the proposed method models feature distinctiveness with explicitly constraint. Comparisons with state-of-the-art methods show that our method works well in accuracy and efficiency.Alternating discriminant optimization is proposed to obtain discriminative features in the labeled source domain, which utilizes an l2 objective to measure feature distinctiveness. We use a toy example to demonstrate how it works.We combine sparse filtering and maximum mean discrepancy into an integrated framework, and propose an unified optimization method with full-batch and mini-batch gradient descent.The rest of the paper is organized as follows. In this section, we give a definition of transfer leaning and explain its relationship with domain adaptation. According to whether the labeled samples in the target domain are available, the problem can be divided into semi-supervised and unsupervised domain adaptation. In this paper, we focus on unsupervised domain adaptation, which means that the target domain does not have any labeled samples. Following that, we introduce sparse filtering and maximum mean discrepancy.X and a marginal probability distribution Y is the label space and There are two important concepts in transfer learning, domain and task. A domain, ) and target data , where data in two domains have different distributions, domain adaptation (DA) aims to find the label of target data . When the test set is completely unlabeled, it is called unsupervised domain adaptation, which is also the focus of this paper. The mathematical form is defined as follows  adopts pseudo labels to align the conditional distributions of two domains.Correlation alignment (CORAL): . CORAL [AAAI2016] obtains transferable representations by aligning the second-order statistics of distributions.Confidence-aware pseudo-label selection (CAPLS): .CAPLS [IJCNN2019] uses a selective pseudo labeling procedure to obtain more reliable labels.Modified A-distance sparse filtering (MASF): .MASF [Pattern Recognit.2020] employs an L2 constraint combining sparse filtering to learn both domain-shared and discriminative representations.Selective pseudo-labeling (SPL): .SPL [AAAI2020] is also a selective pseudo labeling strategy based on structured prediction.Generalized softmax (GSMAX): . GSMAX [Inf. Sci.2020] aims to learn smooth representation with both labeled source domain and unlabeled target domain.The selected state-of-the-art methods are:Follow the experimental setting of JDA and MASF, we set the subspace dimension y is the true label, so Following the setting of ,36, we r(1) Initialization. We find that setting the initial value near 0 can significantly improve the convergence. In this paper, we set it to (2) Gradient descent. We set the maximum number of iterations to 200 and the step size to 0.1.https://github.com/wobuhuiyingyu/DA_DSF.(3) Our code will be available at DSF vs. NN. According to the results, DSF is significantly better than NN. NN cannot handle the domain discrepancy, thus results in unsatisfying performance. On the other hand, it indicates that our method is able to learn transferable representations.DSF vs. CORAL, JDA. DSF is superior to CORAL and JDA. These two methods are classical distribution matching methods, but they have limited considerations on the discrimination of learned representations.DSF vs. MASF. MASF is another framework based on sparse filtering, which adopts a modified DSF vs. CAPLS, SPL. Objectively speaking, our method DSF has comparable performance when compared state-of-the-art works, only 0.5% decreasing on average accuracy. It reveals that the proposed discriminative features are applicable for domain adaptation problems.In this section, we report the accuracy of the proposed method (abbreviated as DSF for discriminative sparse filtering) and other state-of-the-art works; the results are shown on The difference of sample numbers, also referred as class weight bias, is a fundamental problem for measuring distribution differences. Existing measurements, e.g., MMD and CORAL, employ the first/second/higher order moments to quantify distribution differences, which assume that the source and target data share the same class weights; however, such an assumption does not always hold . However, our method also yields good classification results. The reason is twofold: (1) the class weight biases are not so severe that they will lead to catastrophic accumulation of errors. (2) There are other regularizations, i.e., the proposed ADO and sparse filtering. The ideal features should be both domain-shared and discriminative, so the negative effects can be further suppressed. Another interesting phenomenon is the different results after changing the order of two domains; this can be explained by the information asymmetry. Imagine that two sets A and B, where A∈B, so if we choose B as training set and A for testing, the model would achieve satisfactory performance. If the order is changed, the model would fail since A cannot provide enough discrimination power.✓and ✗to denote the status of two components, e.g., MMD (✓) + ADO (✗) indicates that current model is MMD regularized sparse filtering. As For better understanding of the proposed method, we conduct an ablation study to analyze how different components contribute to the final performance. Since there are too few samples for some domains of the Office-Caltech10, e.g., 157 images in total for DSLR, we use ImageCLEF for ablation study only. Compared to original sparse filtering, we proposed two strategies, i.e., MMD for distribution matching and ADO for source discrimination. Through the arrangement and combination of two elements, we can construct In this paper, we introduce two parameters, (1) In this situation, we do not care about the discriminability of both domains. All we need is to reduce domain discrepancy by reducing the MMD loss, which is similar to TCA .(2) Extended from TCA, we hope to obtain discriminative representations while reducing domain discrepancy in some sense. However, if they are too large, we cannot learn transferable knowledge across domains. As T as the number of iterations; the overall computation complexity of algorithm is Using given notations, the computational cost is detailed as follows: In this section, we record the running time (feature extraction + classification with NN) of previous experiments. All algorithms are implemented via MATLAB 2017a and executed on a Windows PC with Intel Core i7 CPU at 3.6GHz and 8GB RAM. In this section, we discuss the influence of different gradient-based optimization methods on the proposed framework.In the previous section, we show how to apply gradient descent for optimizing the proposed method, which means that we need all data  Since the target domain has no labels, sparse filtering is introduced to capture its discriminative structure in nature. (b) For the labeled source domain, we propose alternating discriminant optimization to directly model the relation of learned representation and labels; a toy experiment of XOR problem shows its validity. (c) We integrate MMD into the framework to reduce domain discrepancy and a unified optimization based on gradient descent is raised. Adequate experiments show that the proposed method is comparable or superior to existing methods. Furthermore, we give a mini-batch based optimization framework such the proposed method can be applied in large-scale problems. In the future, we plan to study how different metrics work to measure domain discrepancy.