Staphylococcus aureus pathogenicity islands (SaPIs) are a type of mobile genetic element that play a significant role in the pathogenesis and virulence of this microorganism. SaPIs are integrated in the chromosome under the control of the master repressor Stl, but they can be horizontally transferred at a high frequency due to certain bacteriophages. Thus, a phage protein can bind to the SaPI Stl and induce the SaPI cycle, spreading the SaPI virulence factors to other bacterial populations. We report the dissemination mechanism of SaPIs mediated by endogenous prophages in S. aureus clinical strains. We reveal the induction of SaPIs by a co-resident prophage in seven clinically relevant strains, and we further study this mechanism in MW2, a community-acquired methicillin-resistant S. aureus strain that contains two bacteriophages (ɸSa2mw and ɸSa3mw) and one SaPI (SaPImw2) encoding for three enterotoxins . ɸSa2mw was identified as responsible for SaPImw2 induction, and the specific phage derepressor protein DUF3113 was determined. The Stl-DUF3113 protein interaction was demonstrated, along with the existence of variants of this protein in S. aureus phages with different abilities to induce SaPI. Both Stl and DUF3113 are present in other Staphylococcus species, which indicates that this is a generalised mechanism. Staphylococcus aureus is a widespread pathogen that colonises the skin and mucosa of healthy adults. S. aureus is found in both hospital and community environments, causing a variety of infectious diseases from minor skin infections to serious conditions such as osteomyelitis or endocarditis2. The high pathogenicity of this microorganism is due to the broad spectrum of virulence factors present in its genome. Remarkably, many of these virulence factors such as toxins, adhesins or invasins are part of its mobile genetic elements (MGE)4.Staphylococcus aureus pathogenicity islands (SaPIs) and the bacteriophages are two closely related MGEs that have been identified in S. aureus and whose mobilisation mechanisms have been studied5. SaPIs contain virulence genes that can be disseminated amongst bacteria populations by means of certain phages7. SaPIs act as molecular parasites, using different mechanisms to interfere with the normal biology of phages, to encapsidate in phage particles and to promote their own spread12.The acquisition of most MGEs is produced by horizontal transfer, pac and cos13. They can be packaged in full-sized procapsids by pac phages or packaged in DNA units delimited by cos sites in cos phages. Additionally, pac SaPIs can interfere with pac phages via several proteins such as TerS or CpmAB to reduce the capsid size and exclusively pack the island genome16. Recently, SaPIs that do not encode TerS or CpmAB homologues have been identified, they are cos SaPIs and they can use the packaging mechanisms of pac and cos phages17. These cos SaPIs encode for Ccm, which is responsible for small capsid formation and interferes with the packaging mechanism of cos phages18.SaPIs, as bacteriophages, can be packaged using two different mechanisms: 19. Stl acts as a repressor, binding to a region between two divergent promoters and inhibiting the transcription of SaPI genes21. The SaPI life cycle starts by the infection of a helper phage or by activation of an endogenous helper prophage by the SOS response. This response can be caused by oxidative stress, exposure to UV-irradiation or antibiotic treatment24. Once the prophage is activated or the cell is infected by the phage, a bacteriophage protein binds to Stl, triggering the release of the Stl repressor from the SaPI DNA. Disruption of the Stl-SaPI DNA complex allows the expression of SaPI proteins and the initiation of the excision-replication-packaging (ERP) cycle of the SaPI25  family, involved in homologous recombination, induces SaPI229. These four phage derepressors are able to induce only a few SaPIs. Furthermore, it has been shown that Stl repressors may have different domains to interact with unrelated phage proteins but perform the same conserved function30. Therefore, there are still many uncertainties about SaPI induction, and the identification of new derepressor proteins is key to understanding this induction mechanism and the subsequent dissemination to other bacteria.The interaction between Stl and the phage derepressor protein is the first step of the SaPI cycle. In the different SaPIs, Stl sequences are not conserved. On the other hand, derepressor proteins are specific for each interaction. Therefore, bacteriophages have different capacities to induce SaPIs according to whether they present derepressor proteins which are able to bind to specific Stls. All phage derepressor proteins studied so far are known as moonlighting proteins because they have more than one function, apart from their role in SaPI induction, a second function is supposed to be beneficial for the phage. The functions of four bacteriophage proteins have already been described. Dimeric and trimeric dUTPases of various phages are derepressor proteins of SaPIbov1 and SaPIbov5. Sri protein, which binds to DnaI and inhibits host cell replication, is the derepressor protein of SaPI1. SaPIbov2 was shown to be induced by ORF15 of the 80α phage, but its function still remains unknownS. aureus clinical strains and focused on SaPImw2 induction in the MW2 strain. MW2 is a community-acquired methicillin-resistant S. aureus (MRSA) strain that presents 19 unique toxins32, some of them encoded in the SaPImw2 pathogenicity island. We demonstrated that the ɸSa2mw phage is able to induce SaPImw2, and we identified the phage derepression protein responsible for the induction and horizontal transference of the SaPImw2 genome. Finally, derepressor homologous proteins were identified in various phages. All of the proteins showed different abilities to interact with Stl and, consequently, different capacity to induce SaPImw2.SaPI induction by helper phages has been studied in phi11, phi12 and 80α lysogens, but there has been no demonstration of SaPI induction by endogenous phages in clinical strains. In this work, we demonstrate the ability of certain quiescent bacteriophages to induce resident SaPIs. We studied the SaPI induction process in 14 S. aureus clinical strains were treated with mitomycin C to activate the SOS response and induce endogenous phages to check whether these phages are able to activate the resident SaPIs , and lacks the small terminase. The differences in migration and the assignment in two types (CCC or L) of the lower band among the analysed strains are consistent with the presence of cos and pac SaPIs and phages. MW2, C and USA300 encode cos SaPI and cos phages with similar cos sites, so the SaPIs can be induced and mobilised by their endogenous phages. A, E, N315 and COL contain pac SaPIs and cos phages, so there might be induction but not packaging in these strains.To explain the absence of an L SaPI band in A, E, N315 and COL strains, corresponding with SaPIs that have been packaged, the SaPI and prophage sequences of the clinical strains were analysed to identify whether they are After induction, SaPI is excised from the chromosome and circularised. To clearly confirm that SaPI induction has occurred, SaPI excision from the chromosome was confirmed by PCR using specific primers recognising the flanking region of each SaPI integrase type  gene was inserted, replacing enterotoxin type C (sec4), an accessory gene of the pathogenicity island. SaPImw2 belongs to a SaPI subfamily in which the classical SaPI operon I is not present and contains a conserved phage cos site sequence (cggcgggggc)35. As SaPImw2 is a cos SaPI, in the replacement, the SaPI genome size must not be affected, because the SaPI size genome is a prerequisite for high-frequency SaPI transfer by cos phages18.To follow SaPImw2 replication and mobilisation, a chloramphenicol (Cm) marker was introduced in the SaPI genome, which resulted in strain GTM750  with regard to RN4220 ɸSa2mw (GTM752), which confirmed the interference. The relationship between SaPI and the bacteriophage is a parasitism relationship, in which SaPI benefits but the phage is impaired  . As shown in Fig. cad), generating 9 new plasmids (from pGTM11 to pGTM19), and were transformed into GTM755 (RN4220 pGTM2). In this case, pGTM11 showed β-lactamase activity and corresponded to ORF MW1424. This ORF encodes for a hypothetical protein, DUF3113 (UniProtKB code A0A0H3JWD1_STAAW), which belongs to the DUF3113 superfamily.To identify which protein of ɸSa2mw could be responsible for the interaction with Stl and, therefore, for SaPImw2 induction, a total of 7 regions of ɸSa2mw were cloned into the plasmid pGTM3 (pCU1_Pad) Fig. . Due to 37. Furthermore, it has also been noted that phages with mutations in the derepressor gene are able to form plaques in strains that contain an inducible SaPI37. We demonstrate in this study that SaPImw2 blocks plaque formation by ɸSa2mw. However, after several attempts to infect a SaPImw2-positive strain (GTM751) with ɸSa2mw lysate, two plaques were obtained. The sequence of the DUF3113 derepressor gene from the phage genomes obtained from the plaques showed mutations in the ribosome-binding site and one mutation in the start codon , which suggests that this gene is responsible for SaPImw2 induction  and in GTM753 (RN4220 ɸSa2mw SaPImw2 entC::cat), which generated GTM756 and GTM757, respectively. To confirm our previous results, SaPImw2 mobilisation was tested by Southern blot. No SaPI specific band was detected when DUF3113 was not present  in the mutant strain (GTM759), the SaPI titer was fully restored.Finally, to confirm that DUF3113 is responsible for SaPImw2 mobilisation, SaPI and phage titres were studied by induction with mitomycin C of the ɸSa2mw lysogen wt and DUF3113 mutant strain and in the absence and presence of SaPImw2 38. To test the in vitro interaction between DUF3113ɸSa2mw and StlSaPImw2, a size-exclusion chromatography assay was performed, and all the relevant peak fractions were analysed by SDS-PAGE. His6-tagged StlSaPImw2 and His6-tagged DUF3113ɸSa2mw were expressed (plasmids pGTM22 and pGTM23) and purified. Figure SaPImw2, His6-DUF3113ɸSa2mw and the complex His6-StlSaPImw2-His6-DUF3113ɸSa2mw. The His6-StlSaPImw2 chromatogram (blue) showed two peaks (PK116 and PK165), and the His6-DUF3113ɸSa2mw chromatogram (green) showed one peak (PK187). However, the complex His6-StlSaPImw2 - His6-DUF3113ɸSa2mw (orange) eluted in 3 peaks: PK116, PK135, PK187. PK116 and PK187 corresponded to specific elution volumes from free His6-StlSaPImw2 and His6-DUF3113ɸSa2mw, respectively. However, the new peak, PK135, was associated with the protein complex, as was confirmed by SDS-PAGE.SaPI induction occurs through direct protein interaction between the phage derepressor protein and the SaPI repressor StlSaPImw2 and untagged DUF3113ɸSa2mw were expressed (plasmids pGTM22 and pGTM24), and His6-tagged StlSaPImw2 was bound to a metal affinity resin and incubated with untagged DUF3113ɸSa2mw. The co-elution of both proteins was confirmed by SDS-PAGE . Furthermore, to check the specificity of StlSaPImw2-DUF3113ɸSa2mw, the Stl of SaPIbov1, which is not induced by DUF3113ɸSa2mw, was used as a control (His6-StlSaPIbov1). This protein construct was also expressed and incubated with untagged DUF3113ɸSa2mw; however, in this case, no interaction was detected , was evaluated and, as expected, they did not co-elute  showed that 80α and ɸ12 mobilised this SaPI successfully. As expected, ɸ11 was unable to transfer SaPImw2  strain. SaPImw2 induction was tested by Southern blot after treatment with CdCl2  tagged with 3xflag and then transformed into GTM755 (RN4220 pGTM2). The β-lactamase activity varied between the tested strains, which supported the Southern blot results  and a phage with a DUF3113 protein similar to DUF3113ɸSa2mw (61% identity). In the same way, we located a SaPI that encodes for a Stl and a phage with a DUF3113 in the S. aureus strain TCH70 showing 100% identity to present in MW2. These results demonstrate that the mechanism described is general in Staphylococcus spp.To determine whether DUF3113 is also present in another iae Fig. . In addi34. For this reason, it is very important to know how these SaPIs are mobilised and, consequently, how they spread their virulence factors among bacteria of the same species and even among bacteria of different genera. In this paper, we characterised the mobilisation mechanism of SaPImw2 carrying genes for enterotoxin sec, sel and ear. The last of the listed genes is linked to ampicillin resistance.SaPIs encode for virulence factors such as superantigens, epidermolytic toxins, biofilm formation genes, and iron transport or antibiotic-resistance genes . Therefore, these MGE have a high clinical relevance25. There are many SaPIs with unknown inducers. It has recently been demonstrated that the Stl sequences of certain SaPIs have acquired multiple domains to bind to different phage inductor proteins29. On the other hand, SaPIs and bacteriophages are in continuous co-evolution. Subsequently, much remains to be understood about the SaPI induction mechanism.The Stl sequences of the SaPIs are not conserved among different families, and, therefore, each SaPI family is induced by different phage proteinsS. aureus genome. Most strains contain more than one prophage and at least one SaPI39. Based on the fact that SaPI interference mechanisms are counterselective for the phages and that the phages capable of relieving Stl repression are not able to form plaques on a SaPI-containing strain25, endogenous phages able to induce co-resident SaPIs are considered unlikely to be found. However, this study showed that SaPI induction by endogenous phages naturally occurs in human clinical S. aureus isolates, as we demonstrated for the MW2, USA300, COL, N315, A, C and E strains.Prophages and SaPIs are abundant in the pac SaPIs encode for the genes cpmA, cpmB, ppi, ptiA, ptiB and ptiM, which are responsible for interference with pac phage packaging. On the other hand, cos SaPIs, which encode the ccm gene, cause severe interference in cos phage packaging18. However, there are no described interference mechanisms between pac SaPIs and cos phages. Therefore, in strains COL, N315, A and E, in which the SaPIs are pac and their co-resident phages are cos, bacteriophages may have been acquired by horizontal transfer regardless of the SaPI presence, since they were not affected by interference mechanisms.There are some possible explanations for this finding. SaPIs have different interference mechanisms that negatively affect the phage packaging machinery. On the one hand, cos SaPI SaPImw2, which is induced and packaged by the cos phage ɸSa2mw. In this case, we think that SaPImw2 may have been acquired after the phage.In contrast, MW2, as described, contains the cos prophages and one cos SaPI. We describe that the cos SaPIc is induced by cos ɸ6c, but probably, this phage is not responsible for packaging because the cos site and its flanking region, which is important for mobilisation and packaging, are completely different between SaPIc and ɸ6c. However, ɸ2c does present a cos site and its flanking region with 89% identity with SaPIc, which suggests that this phage is probably able to mobilise this SaPI. Therefore, the assumption is that ɸ6c is the responsible for the induction, while ɸ2c is mainly involved in packaging. Phage major capsid protein (CP) is the target for Ccm SaPI protein interference. These two proteins present in the C-terminal have high structural similarity18. In our case, Ccm SaPIc presents a high structural similarity with CPɸ2c and no similarity with CPɸ6c. Therefore, it is probable that SaPIc may only interfere with ɸ2c  and did not decrease the phage titre, which indicates that in laboratory conditions, DUF3113 is not an essential protein.DUF3113, identified as the SaPImw2 derepressor, is a small, non-essential protein and is sufficient for SaPImw2 derepression. All derepressor phage proteins have a dual role: a primary function related to the phage biology and a secondary function related to SaPI mobilisation. The best studied example is the dUTPase protein, which prevents the incorporation of uracil into DNA and is able to mobilise SaPIbov1ɸ11 and DUF3113ɸ2c variants did not derepress SaPImw2. Instead, DUF311380α and DUF3113ɸ6c variants were more effective at inducing SaPImw2 than DUF3113ɸSa2mw. The higher capacity to induce SaPImw2 corresponds with greater affinity for the Stl repressor. Overexpression of DUF311380α and DUF3113ɸ6c variants in a SaPImw2-positive strain affected bacterial growth because SaPIs overexpression has a high cost for the bacteria. On the other hand, overexpression of DUF3113ɸSa2mw produced normal bacterial growth of the SaPI-positive strains, even though there was SaPImw2 induction. Possibly, the lower capacity to induce the SaPI cycle caused SaPI and the bacteriophage to be in equilibrium within MW2.In other phages, DUF3113-homologous proteins were chosen to try to understand the interaction mechanism with the Stl repressor and subsequent SaPI induction. DUF3113cos phages, but the cos site sequence of ɸSa2mw is identical to that of SaPImw2, so this phage could both induce and encapsidate SaPImw2. However, lysis of the MW2 culture after mitomycin C treatment was higher than that in the ɸSa2mw lysogen. This suggests that ɸSa3mw is only involved in lysis, which improves the mobilisation rate.As previously mentioned, strain C presents two prophages that seem to be hijacked by SaPIc, which is mobilised in a coordinated way. ɸ6c induces the SaPI, and ɸ2c is involved in packaging. Phage collaboration can also be suspected in the MW2 strain. The SaPI titre from MW2 (ɸSa2mw and ɸSa3mw) was three orders of magnitude higher than that of ɸSa2mw lysogen, which indicates that although ɸSa2mw is responsible for SaPImw2 induction, ɸSa3mw increases SaPImw2 mobilisation. In this case, both phages are S. aureus strains. Additionally, the study shows signs of a new SaPIs strategy using the machinery of more than one phage in a coordinated way to increase SaPI transduction. A new derepressor protein has been characterised, but more extensive studies are necessary to identify other derepressor proteins and to better understand the mechanism of SaPI mobilisation and the consequent transfer of virulence factors.In conclusion, our study demonstrates the existence of SaPI mobilisation in clinical . S. aureus strains were cultured in tryptic soy broth (TSB) or agar (TSA) plates supplemented with erythromycin  or chloramphenicol  as needed. Escherichia coli were grown in Luria-Bertani broth (LB) supplemented with ampicillin  or kanamycin  as appropriate. Both were grown at 37 °C.The bacterial strains used in this study are listed in Supplementary Table S1S. aureus strains were grown up to OD540: 0.2–0.3 and were then treated with mitomycin C (2 μg /ml) to activate the SOS response and induce the resident prophages. Bacterial cultures were incubated at 32 °C and 80 rpm for 4 h or until lysis occurred. The cultures were filtered (0.22 µm filters), and the obtained phage lysates were diluted and spotted on the susceptible prophage-free RN4220 strain42. Phage from the centre of an individual plaque were extracted. PCR of the phage integrases was performed to check the lysogeny. GTM752 was obtained using this method.540 = 1.4 at 37 °C for 15 min and plated in TSA containing the corresponding antibiotic. After 24 h at 37 °C, the colonies were counted.To test the phage-induced SaPI mobilisation (SaPI o transducing titre), different dilutions of the filtered lysates (100 µl) were used to infect 1 mL of the acceptor strain RN4220 up to ODDNA manipulations were performed using standard procedures. The primers used in this study are listed in Supplementary Table 43. For sample preparation, S. aureus strains were grown to OD540: 0.2–0.3 and were then induced with mitomycin C (2 μg/ml). The cultures were incubated at 32 °C and 80 rpm. Samples were taken 90 minutes after phage induction. Then, 1 ml of the sample was centrifuged, and the pellet was resuspended in 50 µL lysis buffer ). After 30 min at 37 °C, 47.5 µl of 2% SDS and 2.5 µl of proteinase K (20 mg/ml) were added, and the mixture was incubated at 55 °C for 30 min. Next, 11 µL of loading buffer dye 10X was added, and the mixture was shaken for 20 min. The samples were cold (N2)/heat (65 °C) treated three times.Southern blot was performed by standard proceduresTM AP substrate pack (BIO-RAD).The standard SDS minilysates were resolved on a 0.7% agarose gel at 20 V overnight, transferred to a nylon membrane (Roche) via capillary action and blotted with specific Digoxigenin-labelled probes and anti-DIG antibodies. Specific primers (Supplementary Table 2 (2 μM) and harvested (1 ml) after 2 h. The pellets were resuspended in 200 μl lysis buffer  and incubated 1 h at 37 °C. SB buffer with β-mercaptoethanol was added, and the samples were heated 10 min at 95 °C. Samples were electrophoresed on a 15% SDS-PAGE gel, transferred to a PVDF membrane and incubated with 5% non-fat milk in TBST  for 60 min. The membrane was washed with TBST, incubated with anti-FLAG antibodies (Sigma-Aldrich) and revealed according to the protocol supplied by the manufacturer.For Western blot, the strains were treated with CdCl44, as previously described25. pGTM1 was constructed by 3-piece and pGTM21 by 2-piece overlap assembly PCR. The primer pairs used are listed in Supplementary Table S. aureus RN4220 and transduced to MW2 and different lysogens. Allelic replacement was carried out by a two-step procedure. First, the pMAD plasmid was integrated into the chromosome by homologous recombination under non-permissive conditions (44 °C), and in the second step, the plasmid was avoided under a permissive temperature (30 °C). Mutation was confirmed by DNA sequencing.To delete the DUF3113 gene and introduce the Cm marker in SaPImw2, we used the plasmid pMADS. aureus under inducing conditions from the cadmium-inducible promoter (Pcad) in the expression vector pCN51, as previously described25.The plasmids expressing allelic variants of DUF3113 proteins were prepared by cloning PCR products obtained with the oligonucleotide primers listed in Supplementary Table 540: 0.2 and induced with CaCl2 (1 µM). Lysogens of different phages were also transformed with pGTM2 and induced with mitomycin C. Samples were taken after 2 h for a β-lactamase activity assay using nitrocefin as a substrate. Changes of the OD at 490 nm were registered during 20 min (every 30 s) in the Synergy H1 microplate reader. β-lactamase activity units were calculated using the formula (ΔVmax(OD490)*1000/min)/OD650.The plasmid pCN41 was used to clone the intergenic regulatory region of SaPImw2 fused to the β-lactamase reporter gene contained in this plasmid, which generated pGTM2. A cadmium-inducible promoter was introduced into the pCU1 plasmid and used to overexpress allelic variants of the DUF3113 protein. Plasmids were electroporated into RN4220 pGTM2, and the transformed strains were grown up to ODE. coli BL21(DE3). E. coli cells containing the recombinant plasmids were propagated in 500 ml of LB broth (50 µg/ml kanamycin). Cultures were grown until the OD650 reached 0.6–0.8, then isopropyl-β-D-thiogalactopyranoside  was added to reach a concentration of 1 mM. After induction, the cultures were grown overnight at 16 °C and 200 rpm. Cells were harvested by centrifugation (5000 g for 10 min at 4 °C) and resuspended in phosphate buffer . The cells were lysed by sonication (Amplitude 70% 3 min: 3 s ON and 10 s OFF) and centrifuged (11000 g for 10 min). Supernatants were applied to a metal affinity resin  and incubated for one hour at RT. The hexahistidine-tagged proteins were eluted with 100–500 mM imidazole gradient buffers. Elution fractions were analysed by SDS/PAGE and by size-exclusion chromatography.Stl and DUF3113 genes were amplified by PCR and cloned into the pET28a vector. The primers were designed to generate an N-terminal 6xHis-tag fusion Stl protein and a 6xHis-tag fusion DUF3113 protein. The plasmids were transformed into For pull-down assays, the primers were designed to generate N-terminal 6xHis-tag fusion Stl proteins and untagged DUF3113 proteins. The 6xHis-tag Stls were incubated for 1 h with metal affinity resin and for 1 h with untagged DUF3113 proteins. Pull-down elution was performed with 250 mM imidazole buffer. Elution fractions were analysed by SDS/PAGE and by size-exclusion chromatography.TM 75 26/60 column running on a ÄKTATM pure25 system  was used to study the interaction of the selected proteins. The column was equilibrated in 20 mM phosphate buffer containing 300 mM NaCl at pH 7.4, and the elution was performed at 2.6 ml/min at 25 °C. The protein concentration was 17 μM for 6xHis-tag StlSaPImw2 and 40 μM for 6xHis-tag DUF3113ɸSa2mw. The injection volume was 7.5 mL. Calibration of the column was performed with aldolase (158 KDa), covalbumina (75 KDa), BSA (66 KDa), ovalbumina (44 KDa), dimer ribonuclease (27.4 KDa), dimer ubiquitin (17 KDa), ribonuclease (13.5 KDa) and ubiquitin (8.5 KDa) (Supplementary Fig A SuperdexSupplementary Information


The origin of homochirality in life is a fundamental mystery. Symmetry breaking and subsequent amplification of chiral bias are regarded as one of the underlying mechanisms. However, the selection and control of initial chiral bias in a spontaneous mirror symmetry breaking process remains a great challenge. Here we show experimental evidences that laminar chiral microvortices generated within asymmetric microchambers can lead to a hydrodynamic selection of initial chiral bias of supramolecular systems composed of exclusively achiral molecules within milliseconds. The self-assembled nuclei with the chirality sign affected by the shear force of enantiomorphic microvortices are subsequently amplified into almost absolutely chirality-controlled supramolecular gels or nanotubes. In contrast, turbulent vortices in stirring cuvettes fail to select the chirality of supramolecular gels. This study reveals that a laminar chiral microflow can induce enantioselection far from equilibrium, and provides an insight on the origin of natural homochirality. Symmetry breaking and chiral amplification are fundamental principles in chemistry and biology but the control of initial chiral bias remains a great challenge. Here the authors show that chiral microvortices can lead to a selection of initial chiral bias of supramolecular systems composed of achiral molecules. At the supramolecular level, chirality plays important roles in biological activities such as DNA duplication, protein folding, and enzyme catalysis3. Intriguingly, some achiral molecules can evolve in size, complexity, and function through self-assembly into chiral supramolecular systems by spontaneous mirror symmetry breaking9. These self-assembly processes of achiral molecules might be responsible for the origin and early evolution of life, making them subjects of immense interest over the past several decades12.Chirality, which can be observed from the subatomic levels to galactic scales, is a fundamental characteristic in nature20, circularly polarized light irradiation25, or the combination of hydrodynamic, magnetic, thermal, or light factors30. For example, clockwise (CW) or counterclockwise (CCW) stirring of a solution containing exclusively protonated achiral porphyrin molecules in cuvettes leads to the formation of J-aggregates (dye aggregates with an absorption band shifted to a longer wavelength of increasing sharpness than that of the monomer31) of opposite handedness after removing the vortex motion. The phenomenon has been interpreted as the effect of the chiral polarization in a mirror symmetry breaking scenario19, but also that macroscopic hydrodynamic forces could shift the equilibrium of a racemic mixture of J-aggregates, driving a redistribution of chiral aggregates favored by the stirring32. Moreover, the enantiospecific reversible effect on J-aggregates in dynamic stirring conditions is reversible, due to the temporary chiral ordering of nanoparticles in the flows34. In contrast to the flow-driven chirality in solutions, stirring during gelation fails to affect the supramolecular chirality in gels, which has been determined stochastically by initial spontaneous symmetry breaking6. On the basis of these contradictory observations, it remains an enigma how an efficient hydrodynamic force could be created and how it controls over the supramolecular chirality during the self-assembly process.Symmetry breaking of achiral molecules in the self-assembly process could be biased by purely physical fields, such as hydrodynamic flow by stirring35. The velocity of flow near the vents could reach several meters per second, and there is a large change to create high-speed microvortices  up to 104 rpm for flows over rock micropores36. These microvortices may provoke the aggregation of concentrated molecules under non-equilibrium conditions, leading to the emergence of supramolecular chirality, or even the appearance of living organisms39.On the prebiotic Earth, rock micropores in the size range from tens to hundreds of micrometers are ubiquitous in the vicinity of hydrothermal vents in the oceanEnlightened by natural rock micropores, we design a microfluidic device to induce counter-rotating laminar chiral microvortices (CW and CCW) inside opposing microchambers, to control over the supramolecular chirality of assemblies either in gels or solutions, exclusively from achiral molecules. The high magnitude of the shear gradient in laminar microvortices allows the alignment and twist of the supramolecular nuclei against the Brownian regime within milliseconds when mirror symmetry breaking occurs. These nuclei with a certain chiral bias correlated with the rotation sense of microvortices are subsequently amplified into supramolecular aggregates with nearly absolute chirality.6, and tetra-(4-sulfonatophenyl) porphyrin), TPPS413, which have been reported to exhibit symmetry breaking during gel formation or aggregation, are selected. We first investigate the flow-induced self-assembly of BTAC  and two individual DMF/H2O mixtures  are injected into the microfluidic device through the middle and two side inlets  and left (L-) outlet. The optimization experiments are carried out to identify the critical conditions (BTAC concentration of 61 mg mL−1 and temperature of 40 °C) in which the chirality of supramolecular systems is dependent on the rotation direction of microvortices  is 80% (n = 253) in BTAC gels from the L-outlet, and that of right-handed helical twists  is 86% (n = 271) in gels from the R-outlet . The effect of microvortices on chiral selection in BTAC gels is confirmed by repeating the experiments 28 times using 28 microfluidic devices. The CD spectra of BTAC gels reveal 27 positive and 28 negative CD signals for the R- and L- outlets , are used as the building blocks and ionic stabilizer, respectively , as determined by cryo-electron microscopy (cryo-EM), suggesting a helical arrangement of individual protonated TPPS4 monomers , reveals a rapid assembly of TPPS4 monomers into a large number of primary nuclei (~260 nm long) within 5 min  laminar vortices in the left (right) microchamber  or M (P) microvortex  chirality . The highest rotation speed of 4 × 104 rpm is also confirmed by high-speed microscopic observation of microvortices  simulations. The mismatch of flow velocities ber Fig. . Simulatity Fig. . The chi4) building blocks are rotated and diffused into the DMF/H2O (HCl/C2mim+) solutions driven by microvortices. The assembly time is estimated as 0.7 ms for BTAC and 0.5 ms for TPPS4, implying a rapid formation of primary nuclei inside the microchamber (Supplementary Methods)41. These instantly formed nuclei are aligned in the laminar flows, and be able to detect the velocity gradients due to the increase in size. A shear force (Fs) originated from the shear rate gradient is applied to the nuclei, with the maximum of 1.6 pN for BTAC nuclei and 0.1 pN for TPPS4 nuclei on the basis of the maximal shear rate gradient of 8 × 1010 m−1 s−1 43, thus exerting a net torque that is strong enough to twist the nuclei and to give rise to a chiral bias within tens of ms  can exert a viscous shear force on instantly formed nuclei to compete with intermolecular forces, allowing for rapid selection of the initial chiral bias that is correlated with the rotation sense of microvortices within tens of millisecond. An almost absolute control (96%) over the chirality of BTAC gels or TPPS4 nanotube solutions is realized after amplification. This study presents a distinct means for rapid and primary enantioselection far from equilibrium. We anticipate that our investigation may provide a hint as to the origins of natural homochirality, i.e., the critical role of oceanic vortices in protein folding and self-assembly in early Earth.In this work, a versatile microfluidic platform has been presented to investigate the initial symmetry breaking and chiral selection in self-assembled systems of achiral molecules. The generated laminar chiral microvortices  was purchased from Beijing Chemicals (China). 5,10,15,20-Tetraphenyl-21H, 23H-porphinetetrasulfonic acid, disulfuric acid, and tetrahydrate (TPPS4∙2H2SO4∙4H2O) were purchased from Dojindo Laboratories (Japan). 1-Ethyl-3-methylimidazolium tetrafluoroborate (C2mimBF4) was purchased from J&K (China). Hydrochloride acid  was purchased from Beijing Chemicals (China). Polydimethylsiloxane (PDMS) was purchased from Dow Corning (USA). T3050 photoresists were provided by Baisiyou (China). Milli-Q water (18.2 MΩ cm at 25 °C) was used in all cases.1,3,5-Benzenetricarbonyl trichloride, ethyl 4-aminocinnamate, trimethylamine, and tetrahydrofuran (THF) were purchased from Alfa Aesar (USA). BTAC monomers were synthesized by adding 1,3,5-benzenetricarbonyl trichloride (0.2 M) in 10 mL THF solution to ethyl 4-aminocinnamate (0.4 M) and triethylamine (0.8 M) in 20 mL THF solution, followed by a 12-h stirring at room temperature. The filtrated product was concentrated by rotary evaporation and precipitated by adding 50 mL methanol. The solid precipitate was collected by filtration and washed consecutively with 20 mL water and 20 mL methanol. The product on the filter paper was dried to form powders. 52. Using computational fluid dynamic (CFD) simulations and bright-field microscopy observations, the distributions of middle infusion were investigated under four different flow conditions: 10–1–10 mL h−1, 20–1–20 mL h−1, 30–1–30 mL h−1, and 40–1–40 mL h−1 for the side–middle–side inlets  was infused from the two side inlets at 30 mL h−1 for each side. The flow rates were accurately controlled by syringe pumps . Temperature was maintained at 40 °C by immersing the microfluidic devices in a water bath. Samples were collected 1 min after all the injections reached equilibrium. The samples separately collected from the two outlets were aged for 40 min at room temperature of 27 °C before spectra measurements.Using the inclined microchannels, 61 mg mL4∙2H2SO4∙4H2O aqueous solution (20 µM) was injected into the microchannel through the two side inlets at a flow rate of 30 mL h−1 for each side. The mixture solution (0.4 M C2mimBF4 + 1.5 M HCl) was injected through the middle inlet at a flow rate of 1 mL h−1. The experimental observation and sample collection were performed 1 min after all the injections reached equilibrium. The samples separately collected from the two outlets were aged for 2 h before spectra measurements. All the TPPS4 experiments were performed at room temperature of 27 °C.TPPSu was the flow velocity vector, ρ was the fluid density and set as 103 kg m−3, p was the pressure, ν was the kinetic viscosity and set as 10−6 m2 s−1, ci was the species concentration, and Di was the mass diffusion coefficient of the species and set as 10−10 m2 s−153. All the governing equations were solved by commercial CFD software Fluent 6.4 . The Navier–Stokes equations for the flow field were solved using the SIMPLE algorithm for pressure–velocity coupling. Both Navier–Stokes equations and species governing equation used second-order upwind scheme for spatial discretization. Hexahedral grids were generated using Gambit  for inclined microchannels. Nonslip boundary conditions were implemented on the microchannel walls. Velocity inlet boundary conditions were applied for the three inlets to match the experimental flow rates and outflow boundary conditions were applied to the two outlets.CFD simulations were performed to investigate the flow motion and species transportation at the experimental flow rates, which were obtained by solving the Navier–Stokes equations and species governing equation based on Fick’s law:The data that support the findings of this study are available from the corresponding authors on reasonable request.Supplementary InformationPeer Review File


Hyperthermia therapy is a treatment modality in which tumor temperatures are elevated to higher temperatures to cause damage to cancerous tissues. Numerical simulations are integral in the development of hyperthermia treatment systems and in clinical treatment planning. In this study, simulations in radiofrequency hyperthermia therapy are reviewed in terms of their technical development and clinical aspects for effective clinical use. This review offers an overview of mathematical models and the importance of tissue properties; locoregional mild hyperthermia therapy, including phantom and realistic human anatomy models; phase array systems; tissue damage; thermal dose analysis; and thermoradiotherapy planning. This review details the improvements in numerical approaches in treatment planning and their application for effective clinical use. Furthermore, the modeling of thermoradiotherapy planning, which can be integrated with radiotherapy to provide combined hyperthermia and radiotherapy treatment planning strategies, are also discussed. This review may contribute to the effective development of thermoradiotherapy planning in clinics. Hyperthermia therapy is used as an adjunctive cancer treatment modality in which the temperature of cancerous tissues is increased to enhance the clinical efficacy of chemotherapy and radiotherapy –4. RadioHyperthermia treatment planning (HTP) includes the selection of an optimal treatment technique that is in current use and for which several tools and techniques have been developed. Previous review articles have shown that HTP is an essential approach and has a pivotal role in the control, improvement, and assessment of hyperthermia treatment quality –8. HTP, To improve treatment quality, simulation techniques have been extensively used in clinics, and HTP techniques have been developed for clinical use –13. An Hhttp://www.comsol.com), CST Studio Suite (http://www.cst.com), and Ansys (http://www.ansys.com), can also be used for calculating EM and temperature distributions. Commercial software packages are available for HTP. The most widely used simulation software for locoregional hyperthermia treatment is Sigma HyperPlan , which was developed by the Konrad Zuse Institute; however, this software is limited to modeling locoregional hyperthermia systems. More flexible treatment planning systems have been developed, including the AMC DIVA HTP system , SEMCAD X , and Sim4Life , which include additional and advanced treatment planning tools such as animal and human phantom models, tissue models, magnetic resonance imaging (MRI) modules, and dispersive fitting modules. Besides these specialized HTP tools, general commercial software, including COMSOL Multiphysics , J is the current density (A·m−2), H is the magnetic field strength (A·m−1), B is the magnetic flux density (T), and σ is the electrical conductivity (S·m−1).A summary of the major mathematical models used for HTP is detailed below. The EM field distribution during RF heating can be calculated using Maxwell's equation. The finite-difference time-domain (FDTD) method can be used for a wide range of frequencies (250 Hz–3 GHz) , 16–25:.For capacitive heating, quasistatic approximation is used to obtain the potential distribution –29:(3)∇−ρ is the mass density (kg·m−3), SAR is the specific absorption rate (W·kg−1), and Qr is the EM power absorbed (W·m−3).The E-field calculation from the FDTD and quasistatic approaches enables the calculation of the SAR in tissues :(4)SAR=σQr) to the Pennes bioheat model to calculate the temperature distribution [c is the specific heat (J·kg−1·K−1); T is the temperature (K); t is the time (s); k is the thermal conductivity (W·m−1·K−1); Qm is the metabolic heat generation rate (W·m3); ωb is the blood perfusion rate (kg·m−3·s−1); and cb and Tb correspond to the specific heat and temperature of blood, respectively.The RF energy obtained from the EM simulation is given as a heat source (ribution –32:(5)ρcR is the temperature dependence of the rate of cell death , dt is the time interval with which temperature measurements are made (min), and to (min) and tfinal (min) are the initial and final heating periods, respectively.Besides the temperature distribution, thermal dose can be obtained using the cumulative equivalent minutes (CEM at 43°C) :(6)CEM43α (Gy−1) and β (Gy−2) are the radiosensitivity parameters at 37°C, α(T) is the temperature-dependency of α, d is the fractionated dose (Gy), D is the total radiation dose (Gy), and G is the Lea–Catcheside protraction factor.The combined therapeutic outcomes of radiotherapy and hyperthermia can be calculated in terms of the equivalent radiation dose as follows :(7)EQDRTitis.swiss/database) [Tissue properties are important parameters in simulations in determining the temperature distribution of the target and its surrounding tissues. Electrical conductivity, relative permittivity, density, thermal conductivity, specific heat, metabolic heat generation rate, and blood perfusion rate are the major tissue properties associated with the electrothermal simulations of mild and ablative hyperthermia . Severalatabase) . In RF tatabase) –38. Tumoatabase) . Generalatabase) , 42–44. atabase) , 46. A satabase) . Tables Some of the properties displayed in Tables Locoregional therapy is usually applied at hyperthermic temperature of 40°C–45°C. Studies with tissue-mimicking phantom models and 3D human anatomy models have been conducted to demonstrate its efficacy in the treatment of various types of cancer as summarized below.1+ imaging to validate SAR models for RF hyperthermia [Tissue-mimicking phantoms, the physical properties of which are close to human tissues, are important in the development of experimental and numerical techniques. Many studies have been performed to develop phantoms with dielectric and thermal properties similar to those of human tissues –74. An arthermia . SAR disrthermia . The sizrthermia . Temperarthermia . The fearthermia , 50, 77.1+ imaging technique with an accuracy of 3.5%, suggesting that the MR B1+ imaging technique is a valuable technique for obtaining the dielectric interaction between human anatomy and the RF field [1+ is an experimentally validated technique for hyperthermia SAR treatment planning [1+ imaging and SAR determination technique [The accurate prediction of SAR and temperature distribution in human tissues is necessary for the effective use of RF-induced hyperthermia in clinics. By using patient-specific computational models, HTP quality can be improved. Numerical simulations with phantom and human anatomy models can evaluate the efficacy of RF techniques developed for clinical use. A 3D model derived from human anatomical data showed that simulations can assist in the clinical use of RF applicators to heat the region of the thorax . In patiRF field . MR B1+ planning . Given tplanning , patientplanning . The effechnique , 82 withechnique . PatientAmong RF hyperthermia systems, RF phased array applicators are effectively used in clinics for the selective heating of tumor tissues while sparing normal healthy tissues . There hA potential hyperthermia-phased array treatment system for head and neck cancer has been investigated and developed successfully with the assistance of numerical simulations that consider various parameters , and an −2·K−1). The 3D model consisting LCA, water bolus, and a block of tissue was evaluated by comparing simulations with clinical measurements, and the temperature distribution of tissues was predicted well on a global view, but some temperature probes showed a deviation of 1.5°C–2.0°C [Water bolus temperature influences the prediction of tissue temperature in hyperthermia therapy. 3D EM and thermal simulations were performed to develop a guideline for water bolus temperature for the LCA . A conve°C–2.0°C . Water b°C–2.0°C . In HYPE°C–2.0°C , 90, 94.The thermal dose  model is mainly used to calculate tissue damage during hyperthermia therapy . Thermalα and β of the linear-quadratic (LQ) model can effectively express radiosensitization by hyperthermia [Substantial prospective and randomized clinical data show the clear benefits of combined hyperthermia and radiotherapy for various types of cancer . A methorthermia . The LQ rthermia ; howeverrthermia , 110. Nurthermia , 55. Forrthermia  in patierthermia .The X-Term software package was developed to calculate the equivalent radiation dose using an extended version of the LQ model. The software can support decision-making for optimal clinical treatment, enabling the biological evaluation of thermoradiotherapy plans via equivalent 3D radiation dose distributions . It is iFor the effective clinical application of HTP, temperature-dependent blood perfusion and the dielectric properties of tumor tissues that consider variations according to patients and tumor stages require further investigations for various types of cancer. This may be investigated with the development of techniques, such as magnetic resonance electrical properties tomography (MREPT) and dictionary-based electric properties tomography (dbEPT) for measuring dielectric properties , 116 andStudies have demonstrated the importance of simulations in the development of effective HTP techniques for clinical use. Dielectric properties and variations in blood perfusion are important in calculating energy deposition and temperature distribution in target tissues. Based on the accurate numerical modeling for hyperthermia treatment, efficient hyperthermia devices can be developed and the limitations of existing systems can be improved. Tissue damage and thermal dose calculations can predict the hot spots induced in applying RF energy, ensuring the safety and visualization of the lesion volume prior to treatment. Biological modeling for the calculation of an equivalent radiation dose may be effective for the quantification of thermoradiotherapy planning for combined hyperthermia and radiotherapy in clinics. The appropriate modeling and simulation of thermoradiotherapy is likely to contribute to the prediction of the efficacy and toxicity of cancer thermal therapy.


Remarkably, when B-γ-CsSnI3 perovskite is deposited from a dimethylformamide solution onto a 180–190 nm thick CuSCN film supported on an indium-tin oxide (ITO) electrode, the CuSCN layer is completely displaced leaving a perovskite layer with high uniformity and coverage of the underlying ITO electrode. This finding is confirmed by detailed analysis of the thickness and composition of the film that remains after perovskite deposition, together with photovoltaic device studies. The results of this study show that, whilst CuSCN has proved to be an excellent hole-extraction layer for high performance lead-perovskite and organic photovoltaics, it is unsuitable as a hole-transport layer in inverted B-γ-CsSnI3 perovskite photovoltaics processed from solution.We report the findings of a study into the suitability of copper (I) thiocyanate (CuSCN) as a hole-transport layer in inverted photovoltaic (PV) devices based on the black gamma phase (B-γ) of CsSnI However, the possibility of lead contamination of the environment due to failure of the device encapsulants or improper disposal at the end of life is a serious concern for commercial exploitation6. The latter is because lead is a highly toxic element that accumulates in the food chain7 and lead perovskites decompose upon exposure to moisture and water to form lead compounds with significant solubility in water9. Consequently, there is a need for lead-free alternative matched to the needs of photovoltaic (PV) applications. Recent research has shown that tin (Sn) is a potential replacement for Pb in halide perovskites, an element with much lower toxicity than Pb10. PPVs based on wholly inorganic tin perovskite PVs are however at a very early stage of development and so to date the highest reported power conversion efficiency is only 6.4%11. Much of the dramatic improvement in the power conversion efficiency of lead PPVs has resulted from identification and optimisation of the electron transport layer (ETL) and hole transport layer (HTL)12 which interface the light harvesting perovskite layer with the electrodes. These interfacial layers are critically important because they: (i) enable the optimization of the light distribution in the device; (ii) facilitate efficient and selective charge extraction, by minimizing the barrier to the extraction of one carrier type, whilst presenting a large barrier to extraction of the charge carriers with opposite polarity carrier; (iii) physically separate the metal electrode form the perovskite layer, blocking the adverse reactions between them.Perovskite photovoltaic (PPV) devices using lead (Pb) halides as the light harvesting semiconductor have shown an unprecedented evolution over the span of less than a decade, with the power conversion efficiency increasing from 3.8% in 200913. It is however recognized that the high cost and instability of this material will negatively impact the prospects of commercialization and so there is a need to identify lower cost alternative HTLs. In addition to offering long term stability, the charge transport layer at the transparent electrode must also offer high optical transparency, and so there is interest in using wide band gap wholly inorganic HTLs14 including NiO15, CuI16, Cs2SnI617 and copper (I) thiocyanate (CuSCN)22. Among these CuSCN has proved to be a particularly effective HTL for high performance Pb-PPVs with both a conventional12 and inverted device architecture18, and also for high performance organic PVs22. The success of this material as a HTL is due to its wide band gap (≥3.50 eV), excellent solution processability at room temperature and high hole-mobility combined with an ionization potential suitable for the efficient extraction of holes22. Herein, we report the findings of an investigation into the suitably of CuSCN as a HTL in inverted PV devices based on B-γ-CsSnI3, a semiconductor that is attracting considerable attention because it offers near ideal optoelectronic properties for a single junction PV devices and can be processed at room temperature from dimethylformamide (DMF) solutions of CsI and SnI223.In the context of Pb-PPVs the doped organic semiconductor spiro-OMeTAD  has proved to be the best HTL to date in terms of the device power conversion efficiency22. A solution concentration of 50 mg/ml deposited at room temperature yielded a film thickness of 180–190 nm as measured by step height analysis using atomic force microscopy (AFM): Supporting Information Figure 3 + SnCl2 (10 mol% excess) |phenyl-C60-butyric acid methyl ester (PC61BM)|bathocuproine (BCP)|Al. The B-γ-CsSnI3 layer was deposited from DMF solutions at room temperature, with 10 mol% excess SnCl2 added as a source of excess Sn, according to our previously reported optimized procedure23. In a dry nitrogen-filled glovebox CsI, SnI2 and SnCl2 were mixed together in 1:1:0.1 molar ratio. To this mixture DMF was added to make an 8 wt% solution , which was stirred overnight before use. To deposit films, two drops of solution were cast onto a substrate spinning at 4,000 rpm for 60 s. To confirm that DMF is an orthogonal solvent for CuSCN a 180–190 nm thick film of CuSCN was washed with DMF using the same spin-coating procedure as used for perovskite film deposition. The AFM images in Fig. q), measured over an area of 10 μm × 10 μm is reduced from ∼30 nm before spin casting DMF to ∼10 nm after washing with DMF by spin casting. This reduction in surface roughness is consistent with partial dissolution of the CuSCN layer during DMF washing and its possible  removal. However, it is clear from Fig. 19.In this study diethylsulfide was the solvent of choice for CuSCN deposition because it has been shown to be an excellent solvent for the formation of CuSCN films for electronic applications3 perovskite films deposited from 8 wt% DMF solutions by spin coating directly onto CuSCN supported on ITO glass have a high surface coverage with improved uniformity as compared to perovskite films deposited directly onto ITO glass , open-circuit voltage (Voc), fill factor (FF) or shape of the external quantum efficiency (EQE) spectrum for PV devices with and without a CuSCN HTL. Given that the CuSCN layer increases the total semiconductor thickness in the device by up to a factor of 5, it is surprising that the Jsc remains unchanged (8.1 mA cm−2vs 8.2 mA cm−2) and the shape of the EQE spectrum remains unchanged, since the light distribution in the device would be significantly changed by the inclusion of such a thick additional layer24. It is also unexpected that Voc for the devices with and without CuSCN; 0.31 V and 0.30 V respectively, is essentially unchanged since the CuSCN layer would be expected to reduce the reverse saturation current by blocking the unwanted extraction of electrons by the ITO electrode, giving rise to an increase in Voc23.It is evident from Fig. 3 based PV devices without a HTL23, and so it is unexpected that PV devices incorporating a CuSCN HTL should exhibit the same evolution in performance with storage.Additionally, devices with and without a CuSCN layer improve significantly with storage under nitrogen: Fig. 2, and the result was the same  analysis  of the films of CuSCN and B-γ-CsSnIs Figure  which pr7 Figure  confirmi7 Figure  is consi7 Figure  and all 3 perovskite does not form directly from DMSO solutions at room temperature, but there is rapid crystallization to form a solvated intermediate29 which must be annealed for conversion to the perovskite. Figure 30 environment  as the solvent for perovskite film deposition. Notably, unlike for DMF, B-γ-CsSnIt Figure  shows tht Figure . Taken t3 perovskite or a solvated intermediate29. Tin perovskites are known to crystallize much more rapidly than their lead analogues due to the high Lewis acidity of Sn2+ 30, and the enthalpy of formation of the B-γ-CsSnI3 perovskite is very low as compared to that of CuSCN (∼0.06 eV31vs 1.14 eV32), so the process of complete ejection of the CuSCN under layer is evidently a strongly kinetically driven process.The complete displacement of the 180–190 nm thick CuSCN film by the perovskite film  is remarkable, not least because of the high speed of film formation during spin-casting. This finding is attributed to a combination of the increased solvation power of DMF and DMSO for CuSCN, due to the high ionic strength associated with halide and metal ions, together with the tendency for very rapid crystallization either directly to the B-γ-CsSnI3 based PPV with an inverted device architecture. Unencapsulated PPV based on B-γ-CsSnI3 with an inverted architecture have been shown to exhibit promising device stability23, although the power conversion efficiency has remained stubbornly low primarily due to a low Voc. The ionization potential of B-γ-CsSnI3 is particularly small amongst tin and lead halide perovskites33 and so in order to achieve a significantly increased Voc, energetic losses that occur during hole-extraction must be minimized. The identification of a suitable HTL layer, which has hitherto proved elusive31, is therefore essential to improve the efficiency of B-γ-CsSnI3 based PPVs, and so represents a fertile area of research.In conclusion, whilst CsSCN has proved to be a low cost HTL for Pb-PPV and high performance organic PVs, here we have shown that is unsuitable as a HTL in solution processed B-γ-CsSnIA solution concentration of 50 mg/ml CuSCN in diethyl sulfide was drop cast onto a freshly cleaned ITO glass substrate spinning at 3000 rpm for 60 seconds.2 and tin(II) halide were mixed together in 1:1:0.1 molar ratio. To this mixture N,N-dimethylformamide (DMF) was added to make an 8 wt% solution , which was stirred overnight before use. To deposit films, two drops of solution were cast onto the substrate (sufficient to cover the whole substrate), followed by spinning at 4,000 r.p.m. for 60 s. The B-γ-CsSnI3 phase forms immediately upon solvent evaporation.In a dry nitrogen-filled glovebox CsI, SnI−1.) were held in vertical slide holders and ultrasonically agitated in an acetone bath, followed by a high purity water bath with a few drops of surfactant, followed by high purity deionized water only bath, acetone and finally an isopropanol bath. Slides were then UV/O3 treated for 15 minutes. Immediately after UV/O3 treatment the slides were transferred into a dry nitrogen filled glovebox for CuSCN film deposition followed by deposition of the perovskite and finally the PC61BM layer from 13 mg ml−1 chlorobenzene solution using a spin speed of 1500 rpm. This was followed by thermal evaporation of 6 nm bathocuproine (BCP) deposited at 0.5 Å s−1 and then 60 nm of Al deposited at 1 Å s−1. Thermal evaporation was performed at a pressure of 1 × 10−5 mbar with substrate rotation. The Al electrode was deposited through a shadow mask to make six devices per slide, each with an area of 6 mm2.Indium tin oxide (ITO) coated glass slides (Thin Films Devices Inc. 15 ± 3 Ω sqJ–V) curves were measured using a Keithley 2400 source-meter under AM1.5 G solar illumination at 100 mW cm2 (1 sun), scanned from 1 V to + 1 V at 0.1 Vs-1. External quantum efficiency (EQE) measurements were carried out using a Sciencetech SF150 xenon arc lamp and a PTI monochromator, with the monochromatic light intensity calibrated using a Si photodiode (Newport 818-UV). The incoming monochromatic light was chopped at 180 Hz. For signal measurement a Stanford Research Systems SR 830 lock-in amplifier was used. J–V and EQE measurements were made using custom LabVIEW programs.Device testing was performed in the same glove box as used for device fabrication using a solar simulator inside the glove box. Current density–voltage , with the photoelectrons being detected at a 90° take-off angle. The sputtering was carried out at room temperature using a Minibeam I ion gun . A beam of 4 keV Ar+ ions was incidenton a 3 × 3 mm area of the sample surface. Curve fitting was performed using the CasaXPS package, incorporating Voigt (mixed Gaussian Lorentzian) line shapes and a Shirley background.XPS analysis was performed using a Kratos AXIS Ultra DLD. Samples were unavoidably exposed to air for approximately 1 min during transfer from an air-tight box to the vacuum chamber of the instrument. XPS measurements were carried out in an ultrahigh vacuum system with a base pressure of 5 × 103 prepared from 8 wt%  DMF solution deposited onto a glass substrate (13 × 13 mm2) spinning at 4000 rpm for 60 seconds. Measurements were made on a Panalytical X’Pert Pro MRD equipped with an Anton Paar DHS 1100 domed stage under a flow of N2. Simulated diffraction patterns were calculated using the program Mercury 3.122 using CIFs from the Inorganic Crystal Structure Database (ICSD).XRD was performed on thin films of CuSCN prepared from diethyl sulphide solution and a bilayer of CuSCN and B-γ-CsSnISupporting Information


With genetics thought to explain only 40–50% of the total risk of type 1 diabetes, environmental risk factors in early life have been proposed. Previous findings from studies of type 1 diabetes incidence by birthweight and gestational age at birth have been inconsistent. This study aimed to investigate the relationships between birthweight, gestational age at birth and subsequent type 1 diabetes in England.Data were obtained from a population-based database comprising linked mother–infant pairs using English national Hospital Episode Statistics from 1998 to 2012. In total, 3,834,405 children, categorised by birthweight and gestational age at birth, were followed up through record linkage to compare their incidence of type 1 diabetes through calculation of multivariable-adjusted HRs.p trend 0.001).Out of 3,834,405 children, 2969 had a subsequent hospital diagnosis of type 1 diabetes in childhood. Children born preterm (<37 weeks) or early term (37–38 weeks) experienced significantly higher incidence of type 1 diabetes than full term children (39–40 weeks) . Children born at higher than average birthweight (3500–3999 g or 4000–5499 g) after controlling for gestational age experienced higher incidence of type 1 diabetes than children born at medium birthweight (3000–3499 g) , while children at low birthweight (<2500 g) experienced lower incidence , signifying a statistically significant trend  contains peer-reviewed but unedited supplementary material, which is available to authorised users. With the incidence of type 1 diabetes rising , there iwww.who.int/classifications/icd/en/). The English national HES first became linkable in 1998, with the collection of anonymised encrypted personal data items, and the most recent HES data provided by the national data provider to the Unit of Health-Care Epidemiology, Oxford University, was for 2012; (2) Maternity Hospital Episode Statistics (MHES) for the whole of England, 1998–2012 [This study used three record-linked data sources: (1) English national Hospital Episode Statistics (HES)—admitted patient care data for the whole of England, 1998–2012 . These h998–2012 . These a998–2012 ; (3) NatThese three data resources have been linked together into a multipurpose mother–infant database at the Unit of Health-Care Epidemiology (UHCE), University of Oxford, such that each infant’s MHES record is linked to his or her successive records of hospitalisation and/or death in later life, as well as to the mother’s MHES record and her successive records of prior or subsequent hospitalisation and/or death. The UHCE has longstanding experience of linking routinely collected hospital admissions data to study individuals across time, specifically with the use of linked HES since its introduction and ONS death registration data, methods for which have been documented extensively elsewhere , 18. TheThe data resources were obtained for permitted use in this study and ethics approval was obtained from the Central and South Bristol Multi-Centre Research Ethics Committee (04/Q2006/176) for analysis of the record-linked data. Full access to the database was available for use in this study.In total, 7,335,218 mother–infant pairs were identified through mother–infant linkage of MHES records from 1 April 1998 to 31 March 2012. These pairs were extracted from the database, along with any other HES and/or death records belonging to either the mother or the child that occurred during the same period. The ESM The most recent meta-analysis  of the aThe most recent meta-analysis  of the aIn previous studies BFGA has been measured in quintiles . The samPotential confounders or effect modifiers included maternal age in years ; maternal type 1 diabetes (ICD-10 codes E10 or O24.0); maternal obesity (E66); gestational diabetes (O24.4 or O24.9); infant sex; area deprivation based on the mother’s Index of Multiple Deprivation (IMD) rank (in quintiles); and Caesarean section (elective and emergency combined).Type 1 diabetes diagnoses were identified by searching each child’s subsequent HES records for ICD-10 diagnosis code E10 after the age of 9 months. Type 1 diabetes diagnosis before 9 months is extremely rare and any recorded type 1 diabetes diagnoses at this age, although coded as such, would almost certainly represent neonatal diabetes (ICD-10 P70.2) [The crude incidence rate  of type 1 diabetes was calculated for each category of birthweight, gestational age at birth, and BFGA in quintiles and deciles. Mantel–Haenszel adjusted rate ratios were calculated to control for each of the secondary independent variables in turn, and adjusted HRs were calculated using Cox’s proportional hazards models to compare the groups after multivariable adjustment. Where appropriate, trend tests across exposure groups were conducted by entering the categorical variables into the models as continuous terms and using the likelihood ratio test (LRT) to check that model fit was not compromised. The proportional hazards assumption was tested formally by splitting age–time at 4.5 years so that there were equal numbers of outcomes in each age–time period and then testing for interactions between the primary exposure variables and age–time.The strategy for building the Cox models was based on which other secondary independent variables had the strongest effect on the relationships between the exposure variables and type 1 diabetes . Missing values were always dealt with in multivariable analyses by ensuring that any two models being compared contained the same observations.All analyses were performed using Stata/IC 13.1 for Windows, StataCorp, TX, USA.Table In total, 2969 children received a hospital diagnosis of type 1 diabetes over an aggregate of 24,101,378 person-years, an overall rate of 12.3 per 100,000 person-years. The crude rates of type 1 diabetes by each category of each variable are shown in Table Absolute birthweight was not associated with type 1 diabetes, but BFGA was strongly associated as the rate of type 1 diabetes increased significantly with BFGA Table . ChildreIn Cox regression models, after controlling for infant sex and for the apparent confounding effects of mother’s type 1 diabetes status, children born preterm  or early term  experienced significantly higher incidence of type 1 diabetes than full term children (Table p trend <0.001). Further adjustment for other factors did not materially alter the results and the general pattern of risk remained (p trend 0.01)  Table . There wp trend <0.0001).The significant association between high BFGA and type 1 diabetes persisted after multivariable adjustment Fig. . EnterinExclusion from the dataset of children whose mother had type 1 diabetes and/or gestational diabetes made no material difference to the results. Restricting the study period to 2003–2010 (when linkage of mother–infant pairs was greater ESM ) did notAfter controlling for various potential confounders, children born preterm (<37 weeks) and early term (37–38 weeks) experience an approximately 20–25% higher incidence of type 1 diabetes in early childhood than children born full term. Absolute birthweight, unadjusted for gestational age, is not significantly associated with type 1 diabetes incidence. However, high BFGA is significantly associated with an increased rate of type 1 diabetes and proves a useful measure for describing the adjusted birthweight–type 1 diabetes relationship. After adjusting for gestational age and other factors, children born with higher birthweight (3500–3999 g or ≥4000 g) are approximately 10–15% more likely than children of medium birthweight (3000–3499 g) to be diagnosed with type 1 diabetes. Furthermore, children in the lowest birthweight category (<2500 g) are significantly less likely to be diagnosed with type 1 diabetes, by about 20%.A meta-analysis of preterm birth (<37 weeks) and type 1 diabetes published in 2014 reported that preterm birth was associated with an 18% increased risk of type 1 diabetes  [, 1.25) . The preA meta-analysis of birthweight and type 1 diabetes published in 2010 reported that children with birthweight >4 kg had an increased risk of 10% compared with children weighing 3.0–3.5 kg at birth  . This poThe sensitivity analysis suggests that the associations are similar in children diagnosed under 4.5 years and in those diagnosed between 4.5 and 12 years of age. However, the observed associations may not hold for adult-onset type 1 diabetes.A considerable strength of this study is its large size, covering 13 years of prospectively collected record-linked data and comprising nearly four million pairs of mothers and children in an integrated national healthcare system. Such high statistical power enables risk stratification by several categories of birthweight and gestational age while controlling for multiple other factors in a single population. The fact that all data were collected longitudinally removes the possibility of recall bias and selection biases commonly associated with case–control studies. Notwithstanding issues of coverage (below), the accuracy of the data collected has generally been good and the data are well validated for birthweight in the range 500–5499 g and for gestational age in the range 30–43 weeks . HES havHowever, there were limitations to the study. The extent of the linkage between mothers and children was lower for 1999–2002 than 2003–2010 ESM . HoweverThe dataset did not contain information on some important variables which could conceivably confound, modify or mediate the effects of birthweight and/or gestational age at birth. These include early infant feeding , 25, infThe effects of low gestational age and high BFGA appear somewhat contradictory. One hypothesis points to the role of insulin resistance in type 1 diabetes, also known as ‘double diabetes’ . PretermHigh BFGA and preterm or early term birth are independently associated with subsequent type 1 diabetes. As incidence of type 1 diabetes increases, birth cohort studies of type 1 diabetes and early life risk factors help to contextualise the debate about potential mechanisms of action in type 1 diabetes disease pathogenesis. These findings suggest that the still-undefined environmental factors that lead to seroconversion to positivity for diabetes-related autoantibodies in genetically susceptible individuals are rooted in gestation and early life. This study is also an example of what can be done using national routinely collected data to follow mother–infant pairs through record linkage.ESM(PDF 160 kb)


At 11 of the 21 sites, annual nitrate fluxes in the soil were measured using anion exchange resin bags. Soils contained between 2.3 to 29.4 mg N-NO3− kg soil−1. About 86% (±14%) of mineral N was nitrate. The proportion of nitrate increased to almost 100% during incubation. PNN varied from 0.10 mg N kg soil−1 day−1 to 1.05 mg N kg soil−1 day−1 (21 sites). Neither the initial nitrate concentration nor PNN was related to soil chemistry , microbial biomass, texture, past land use or thinning. In situ net nitrate accumulation (NNA) estimated with resins beds varied from 4 to 100 kg N-NO3− ha−1 yr−1 (11 sites). It was positively correlated with base saturation, clay content, ELLENBERG N, temperature and negatively with soil organic N, C/N ratio and precipitation.Douglas fir trees presumable stimulate nitrification in the soil. We studied in 21 French Douglas fir forests if and how nitrification is modulated by soil properties, past land use and current forest management. Soil (0–10 cm depth) was collected and initial concentrations of N-NH Although, availability of mineral nitrogen is still a factor limiting the productivity of forest ecosystems in many biomes6. Especially, tree species with a high biomass increment and thus, a high demand for nitrogen and other nutrients, as Douglas fir (Pseudotsuga menziesii (Mirb.)Franco var. menziesii)) need to apply/develop efficient strategies to match these requirements.Trees are an integral part of nitrogen cycling in forests because trees take up nitrogen, grow, produce litter which decompose and releases nitrogen. Tree species influence nitrogen cycling through uptake of mineral and/or organic N, litter quality and quantity and interactions with microbes at the plant root interface3 ha−1 yr−1 which rank this species among the most productive coniferous species in Europe8. Since its discovery by the Scottish botanist David Douglas in 1824 this forest tree species had been introduced in Europe and contributes now to about 3% or 421000 ha of the French forest cover10. The most commonly cited reasons for this success are (i) rapid initial growth and high production levels11 over a wide range of environments through effective coping strategies12, (ii) efficient nutrient uptake strategies and biomass production13, (iii) absence of major pests and pathogens10 and at last (iv) wood products with rheological qualities that do not deteriorate with the radial growth rate14.Since the late 50’s until the 80′s significant areas in France were afforested with Douglas fir while during the same period broadleaf forests were converted into Douglas fir forests. Under optimal conditions annual increment of Douglas fir may reach 30 m18 or when introduced as alien species in Europe19. In Europe, some studies focused on its impact on the nitrogen cycle23. Among them, Jussy et al. at Vauxrenard (France) and Zeller et al. at Breuil (France), highlighted the dominance of nitrate as main mineral N form in the topsoil when this species was planted on previous farmland or broadleaf forest25. At both sites, soils were acid, nutrient poor with low amounts of plant available Ca and Mg. Such soils are representative for about half of the area of French Douglas fir forests26. In addition, in a common garden experiment with 6 tree species, a fairly rapid and significant increase of the nitrate concentration in soil cores transferred 18 months earlier from 3 low nitrifying tree species into a Douglas fir stand happened27. Based on this experiment Andrianarisoa et al. suggested that Douglas fir triggers nitrification through interactions with nitrifying bacteria at the root – soil interface28. Although the precise mechanism(s) by which Douglas fir may stimulate nitrification and enhance soil nitrate concentrations remain still unknown, as well as a possible modulation by environmental factors .The impact of Douglas fir on biogeochemical cycles have been extensively studied since the 1960’s in its native range29. However, this impact depends on soil conditions e.g. under acidic conditions when nitrate is not immobilized probably in relation to deficient microbial activity or root uptake, a massive leaching of nitrate and monomeric Al3+ occurred in deep drainage solutions30. Such a phenomenon potentially affects the quality of surface waters31.Consequences of high soil nitrate concentrations and resulting leaching of nitrate in Douglas fir forests is loss of cations  and soil acidificationUp to now, almost all studies about nitrate concentrations and potential nitrification were obtained in Douglas fir forests on acid, more or less nutrient poor soils. Thus, the question arises if this tree species affects soil nitrate concentrations and potential nitrification in a generalized way in less acid and more fertile soils. Our hypothesis is that in Douglas fir forest soils in France, nitrate is the dominant mineral N form and that potential nitrification rates were modulated by soil properties. In the light of this hypothesis our objectives were to (1) evaluate the amount and form of mineral N in the mineral soil (0–10 cm depth) in 21 Douglas fir forests in France, distributed all over the distribution area of this species, and assess net mineralization and nitrification potentials under controlled conditions, (2) compare these potentials to their expression under field conditions using ion-exchange resins and (3) tackle how environmental factors  may modulate the availability of mineral nitrogen in the soil of Douglas fir forests.Amongst the studied sites, soil types and their soil physico-chemical characteristics varied broadly. Cambisols formed the biggest group, the other soil types like Podzols, Alfisols, Andosols or Planosols are less abundant (1–2 sites per soil type) (Table 4+ kg soil−1 and the nitrate concentration varied from 2.3 to 29.4 mg N-NO3− kg soil−1 (Table In the 84 soil samples (0–10 cm layer), collected at the 21 sites, the soil pH covered a range from 3.8 to 6.7, the C concentration varied from 2.5% C to 10.9% C, the N concentration varied from 0.2% N to 0.7% N and the C/N varied from 11.0 to 20.1 (Table 3− kg−1 day−1 (SAL-B) till 1.05 mg N-NO3− kg−1 day−1 (ALL)    Table . After t05) Fig. . The few05) Fig. . Neither05) Fig. . Obvious05) Fig. .Figure 13 ha−1 yr−1 at MEY to 101.3 kg N-NO3 ha−1 yr−1 at ROQ. Nevertheless, beside these two extremes, NNA varied in a narrower range among the remaining 9 sites (10.5 kg N-NO3 ha−1 yr−1 to 78.2 kg N-NO3 ha−1 yr−1). NNA was positively correlated to the base saturation        Fig. , the cla05) Fig. , the Ell05) Fig. , the C/N05) Fig.  and mean05) Fig. . NNA was05) Fig. . Excludi05) Fig. .Figure 2mic/Nmic are opposed to C/NhorA, Nmic and soil organic nitrogen (SON) on the principal component 1 (PC1). C/NhorO, duration of the growing season (GW) are opposed to aluminum extracted by the Tamm method (AlTamm), pH, soil organic nitrogen (SON) and phosphorus (P) on the principal component 2 (PC2). The principal plan PC1-PC2 did not allow to discriminate the PNN groups, whereas at least the high NNA group differentiates from the others NNA groups. These findings corroborate previous results presented in Figs A Principal Component Analysis (PCA) has been used to summarize the potential relationship between site characteristics (soil and stand properties) and net nitrification (PNN) or net nitrate accumulation rate (NNA)Fig. . Base sa2 = 0.95, p < 0.05) which follows the 1:1 line, indicating that PNN = PNM. A similar positive correlation is observed for coniferous forests . Compared to Douglas fir, PNN is lower than PNM in coniferous forests, but nitrate is still the dominant mineral N form. Although a large variability, in broadleaf forests, a positive relation between PNN and PNM is observed . Compared to Douglas fir and coniferous forests, PNN is much lower than PNM in broadleaf forests. Mean rates of PNM are 0.54 mg N kg−1 day−1, 0.48 mg N kg−1 day−1 and 0.84 mg N kg−1 day−1 in Douglas fir forests, coniferous forests and broadleaf forest, respectively. Mean rates of PNN are 0.55 mg N-NO3− kg−1 day−1, 0.40 mg N-NO3− kg−1 day−1 and 0.48 mg N-NO3− kg−1 day−1 in Douglas fir forests, coniferous forests and broadleaf forest, respectively.In the selected studies (n = 9), PNM and PNN rates were obtained by incubating mineral soils under fairly similar incubation conditions than ours . Over the panel of published data, large variations in PNM and PNN among coniferous, broadleaf and Douglas fir forests were observed Fig. . In DougOur hypothesis that nitrification is predominant in French Douglas fir forests soils is supported by the initial ammonium and nitrate concentrations measured in the topsoil at the 21 sites.−1) were observed, we show that a dominant share of the mineral N in the 0–10 cm soil (on average 86% ± 14%) was present as nitrate. As this percentage was neither related to soil properties nor forest management, we suppose that the main reason for such an imbalance between ammonium and nitrate is the tree species itself. Climate events (drought or enhanced soil temperature) may reinforce or weaken the amount of residual soil nitrate but this factor will not basically modify this trait. In addition, the average autumnal nitrate concentration in Douglas fir (12 mg N-NO3− kg soil−1) is definitively at the upper boundary compared to nitrate concentrations measured in other temperate forests soils33 and the Ellenberg N values of the forest floor vegetation confirms the long-lasting dominance of nitrate in the studied Douglas fir forests. Usually, the leftover of nitrate in late autumn is a sign that the production of nitrate exceeds the uptake by the trees and the understory vegetation34. Our results are consistent with earlier findings at the Breuil common garden experiment35, where apparently higher soil and soil solution nitrate concentrations were measured in Douglas fir compared to other deciduous or coniferous species. In addition, Douglas fir increased rapidly the soil nitrate concentration in soil cores transferred into the Douglas fir plots from other less nitrifying plots whereas the opposite effect was observed in soil cores from Douglas fir transferred into less nitrifying plots27.Firstly, although large inter-site variations of the initial soil nitrate concentration  is high at all sites, except one and is probably only limited by the bottleneck’s depolymerization of soil organic N and ammonification. These findings illustrate the high potential of nitrifying bacteria to convert ammonium into nitrate and corroborate the dominance of nitrate in French Douglas fir soils. We may suppose that under non-limiting conditions, the potential nitrification rate would be even higher than observed. Positive or negative effects of different tree species on net and gross N mineralization and nitrification had been observed in a certain number of common gardens experiments29. Nevertheless, the absence of any relation between PNN and soil organic C and N suggest that soil organic matter is probably not a principal driver of nitrification at our sites. Moreover, the potential net mineralization and net nitrification measured at the 21 sites cope fairly little with soil chemical parameters. These findings concur with the results of two meta-analysis with numerous tree species44 where a minor part of the observed variability of net mineralization and nitrification was explained by climatic and soil chemical parameters (33% by MAP + %C + %N + clay content) but both studies supposed that biological parameters like soil organic matter quality and microbial community composition strongly increase this percentage.Litter (needle and roots) is the most important source of recent soil organic matter in the studied Douglas fir forests and the thin organic layers in all studied stands indicated a highly efficient team constituted by fauna, fungi and bacteria that decomposes litter thus creating a continuous flux of soil organic matter into the topsoil. Some authors also reported a positive effect of Douglas fir on the humus C:N ratio, soil pH and base saturation46, past land use32 and forest management practices49. In the present study, recognized drivers of nitrification in forest ecosystems like past land use and forest management practices did not mark net nitrification and nitrate accumulation in resins in the Douglas fir stands. Thus, other intrinsic parameters seem responsible for the predominance of nitrate in French Douglas fir soils. Different kinds of interactions at different levels  between the tree species and microbes and/or soil parameters are appropriate to affect soil N transformations and nitrification51.Nitrification had also been related to the tree species54 while the absence of monoterpenes was observed in Douglas fir stands52. Moreover, Nugroho et al. suggested that Douglas fir could even up regulate the number of nitrifying bacteria: although the mechanism is not well understood, a positive correlation between AOB’s like Nitrosospira and nitrate production was observed39. Andrianarisoa et al. revealed that interactions at the root-soil-interface leading to a rapid up regulation of the number of ammonium oxidizing bacteria (AOB) in soils cores transferred from two low nitrifying species  into a Douglas fir plot28. According to these studies there is some evidence that Douglas fir stimulate AOB’s, but how is still an open question. Nugroho et al. supposed that tree species regulate AOB’s through their effects on the soil C/N ratio, but Zeller et al. observed a clear difference between different species in net and gross nitrification in a common garden experiment where soils had a similar C/N ratio39. As previously detailed, neither the humus nor the soil C/N ratio was a primary determinant of PNN or NNA in our study. As at our sites climate and soil chemistry varied largely, the high PNN and soil nitrate concentrations suggests a straight stimulating effect of Douglas fir on nitrifying bacteria39. In addition, Douglas fir is a neophyte in Europe, young trees were often inoculated with north American mycorrhizal strains as Laccaria laccata S238N55. Probably, Douglas fir fine roots are not familiar to most of the ectomycorrhizal fungi (ECM) present in European forest soils which may affect the interactions between microorganisms and fine roots. In the light of such a scenario it could be possible that with ongoing time the ectomycorrhizal diversity increases thus inducing a switch towards a more conservative N cycling.Some tree species like Norway spruce or birch produce monoterpenes or diterpenes as agents to down regulate nitrifying bacteria56. IER have the big advantage to investigate under real field conditions  soil mineral nitrogen fluxes with a very limited initial soil disturbance57. The availability of mineral nitrogen in the nitrate form, as measured by the resins bags is the expression of the difference between the production by nitrifying bacteria, the immobilization by microorganisms and the vegetation and finally loss by leaching of excess nitrate. The negative correlation between NNA and PNN reflects the complexity of the N cycle in Douglas fir forests and underlines that the potential is not expressed in situ. Contrary to PNN, NNA was related to the S/T ratio, the clay content and the soil organic N concentration. Interestingly, less nitrate was accumulated in soils with higher soil organic C and N contents, which is somewhat surprising and opposite to observations made in other forests34. Sites characterized by higher soil fertility  sustained nitrification but also loss of nitrate. Such a behavior suggest/indicate that even under conditions of optimal growth  for Douglas fir a substantial proportion of nitrate is probably transferred into deeper soil layers and/or lost to the ground water58. The greater amount of clay at these sites could result in more fine porosity, which would be a suitable habitat for nitrification for much of the year. Leaching of excess nitrate will result in loss of cations, acidification and in fine deterioration of drinking water quality59. At least, two forest management measures could reduce nitrate leaching: mixed stands composed of beech and Douglas fir60 and fertilization with Ca -Mg –P for acid nutrient poor soils, because such a treatment reduced the nitrate concentration significantly in soil solutions collected at 0.6 m soil depth in a so treated Douglas fir stand35. Nevertheless, further experiments are necessary to evaluate the impact of fertilization on soil nitrate fluxes in other acid contexts and along a soil fertility gradient.Ion exchange resins (IER) have been recognized as a relevant tool for the assessment of the availability of mineral nitrogen in soils3− concentrations either in situ and ex situ. This effect comes first into sight in the field fresh soil samples (collected in autumn) from all 21 sites. Potential net nitrification rates (PNN) in incubated soils but also the net nitrate accumulation (NNA) in the field corroborate the domination of nitrate in French Douglas fir soils. Net nitrate accumulation is higher in more fertile soils and at warmer sites. This suggests that even under optimal conditions for tree growth (high biomass increment) an excess of nitrate remains in the soil with a peak in autumn. As nitrate is highly mobile in the soil profile, leaching loss of nitrate and cations may affect surface and groundwater quality, as well as the sustainability of soils by an acidification process. Future studies are needed to assess the environmental impact of Douglas fir by evaluating properly the leaching losses of nitrate at the plot scale and at larger scales (watersheds etc.) in monospecific Douglas fir forests. Another perspective, which seems the most difficult, is to understand the mechanism(s) by which Douglas fir stimulates the activity of nitrifying bacteria. Lastly, further research should focus on how forest management measures may mitigate nitrate fluxes, probably by the set up of mixed stands and through liming/fertilization.All results converge to the same conclusion, that namely Douglas fir, an alien tree species in Europe, has a strong encouraging/stimulating effect on nitrification and top soil N-NO61. Climatic parameters like annual rainfall, air temperature and length of the growing season were recorded but not included into the site selection process. Among these 21 sites, a sub-network of 11 sites was set up with the objective to monitor continuously soil moisture, fluxes of nutrients and litter fall.All over France, 21 Douglas fir forests (private and public forests) were selected from a larger number of sites Table , Fig. S12, put into a big box, passed through a 4 mm sieve, mixed and finally a representative sample of about 3 kg soil per subplot was shipped in a cooled container to the laboratory. Mineral N concentrations were measured in all soil samples immediately after their arrival in the laboratory. Then, the soils were stored at 4 °C, until the soil sampling campaign was completed and all soils were available for the laboratory incubation. This short storage period (3 weeks) was necessary in order to setup and start the incubation experiment with all soil samples at the same time. Potential net mineralization and nitrification rates were obtained at 20 °C and 60% water holding capacity (WHC). To meet the later criteria for each site the water holding capacity was measured in all soils before the set-up of the incubations and, if necessary, deionized water was added. Soil from each of the four subplots per site (300 g) were put into 2L Mason jars, pre – incubated during 10 days, followed by an incubation period of 42 days. During the whole period, jars were opened twice a week for about 15 minutes, the soil mixed with a spoon to assist the evacuation of accumulated CO2. Subsamples were collected from each jar at the end of the pre – incubation period (T0) and after 21 days (T1) and 42 days (T2) of incubation. Each sample of 40 g of soil was extracted with 200 ml of 0.5 M K2SO4, shaken during 1 hour, filtered and finally the concentrations of N-NH4+ and N-NO3− in the extracts were measured using continuous flow analysis (SKALAR San +  + ). Potential net N mineralization  was the amount of total inorganic N accumulated during the incubation period and PNN  was the amount of N-NO3− formed from the nitrification of the NH4+ already present in the soil core before the incubation as well as that mineralized during the incubation. Both were calculated as mg N kg−1 soil d−1. All concentrations and rates are presented on a dry weight basis. Microbial biomass C and N was measured after 3 weeks of incubation using the fumigation extraction method. Concentration of soil organic C and N were measured using a CHN analyzer (Carlo Erba). In addition, basic soil parameters like soil texture, pH, concentration of P and the CEC were measured at the soil analysis laboratory (LAS) of INRA in Arras.At each of the 21 sites, mineral soil samples (0–10 cm depth) were collected from 4 random subplots situated at 0°, 90°, 180° and 270° about 3 m around an anchor point. The more or less thin humus layer was carefully removed, then all soil (0–10 cm depth) was collected from a surface of 0.25 min-situ N mineralization and nitrification we set up a batch of ion exchange resin traps (anionic and cationic) at 10 cm soil depth and measured over one year at 4, 8, and 12 months the amounts of ammonium and nitrate captured by the resins.In order to evaluate the −1 dry resin, 20–50 mesh) were used to catch anions (nitrate and others) Anionic resins were first rinsed under a slow stream of distilled water and then saturated with Cl− from 1 M HCl (hydrochloric acid) at a ratio of 1000 ml HCl per 100 g of dry resin. Then, 20 grams of wet resin representing about 36–40 meq for anionic were introduced into traps made of PVC rings (Ø 50 mm and 10 mm in height), closed, from both sides by a nylon mesh (20 µm mean mesh size), allowing free percolation of water. At each of the 11 sub-sites, 6 sets of 10 resin traps were set up . After opening a pit of about 3 m long, 0,4 m large and 0,15 m deep, the traps were carefully introduced horizontally into the undisturbed soil (at a depth of 10 cm and with a minimum distance of 25 cm between two traps). Each trap was marked with dyed rope and the trench carefully refilled with the excavated soil, slight compacted and finally the organic layer was restored. In total 6 independent pits were set up per site and two pits were sampled every four months between June 2012 and June 2013.DOWEX 21 K . Net nitrate accumulation rate (NNA) measured by resins is the amount of NO3–−N fixed by the resins during the time of incubation in the field, divided by the number of days between installation and collection. We computed only the mean annual rates of NNA. Net nitrate accumulation was expressed as kg N-NO3− ha−1 y−1.Each resin trap was first rinsed three times with distilled water (10 ml applied with a syringe) for eliminating soil particles. Then each resin trap was weighed and stored at 4 °C until extraction. N-NOpH, silt, Clay, SOC, SON, Nmic, Cmic:Nmic, S, S:T, AlTamm, P, C:NHorO, C:NHorA) and site characteristics . The global idea of sPCA method is to project the standardized data onto a lower dimensional linear space generated by uncorrelated variables, named principal components (PC), such as the variance of the projected data is maximized. The first step is to select a minimal number of PCs while keeping a large part of the explained variance in the new PC subspace. For this, we decided (1) to retain a number of PCs explaining at least 50% of the total variance and (2) to stop introducing new PCs when the fraction of the explained variance decrease sharply. Once the PC subspace considered, the second step is to detect outliers into this subspace. For the outlier detection, we are calculated the Hotelling’s T2 statistic . The T2 statistic is distributed according to a F distribution and the upper 95% confidence limit of this statistic is determined as the maximal accept limit. In case where outliers are detected, a second application of the sPCA method is required after deleting these ones. The retained PCs are interpreted from the correlation circle and the contribution of individual quantitative variables. Moreover, the quality of representation (squared cosine) is calculated for each variable in order to evaluate which variables are well represented onto different principal plans. Thus, a variable with a contribution superior to the uniform contribution and a high quality of representation has a large impact for the considered PC. The dispersion of sites into principal plan is then illustrated for the variables PNN and NNA transformed in qualitative variables: the variable PNN was divided into 4 groups  while the variable NNA was divided in 3 groups .Single and multiple regression analysis were used to detect significant relationship among potential net nitrification and soil and forest management parameters. The same approach was used for the net nitrate accumulation rate. A standardized Principal Component Analysis (sPCA) has been used to analyze the data collected from the 21 sites. This data comprised 17 quantitative variables based on soil physical and chemical properties (Supplementary