Expression analysis further revealed that both ligands and receptors were expressed in zebrafish adult testes. Subsequently, we demonstrated that gdnfa is expressed in the germ cells, while Gfrα1a/Gfrα1b was detected in early spermatogonia (mainly in types Aund and Adiff) and Sertoli cells. Functional ex vivo analysis showed that Gdnf promoted the creation of new available niches by stimulating the proliferation of both type Aund spermatogonia and their surrounding Sertoli cells but without changing pou5f3 mRNA levels. Strikingly, Gdnf also inhibited late spermatogonial differentiation, as shown by the decrease in type B spermatogonia and down-regulation of dazl in a co-treatment with Fsh. Altogether, our data revealed that a germ cell-derived factor is involved in maintaining germ cell stemness through the creation of new available niches, supporting the development of spermatogonial cysts and inhibiting late spermatogonial differentiation in autocrine- and paracrine-dependent manners.Glial cell line-derived neurotrophic factor (GDNF) and its receptor (GDNF Family Receptor α1-GFRα1) are well known to mediate spermatogonial stem cell (SSC) proliferation and survival in mammalian testes. In nonmammalian species, Gdnf and Gfrα1 orthologs have been found but their functions remain poorly investigated in the testes. Considering this background, this study aimed to understand the roles of the Gdnf-Gfrα1 signaling pathway in zebrafish testes by combining in vivo, in silico and ex vivo approaches. Our analysis showed that zebrafish exhibit two paralogs for Gndf ( GDNF  is a closely related member of the TGF-β superfamily which belongs to the GDNF family of ligands (GFLs). This family of ligands consists of Gdnf, neurturin, artemin and persephin . The imps), which also expresses the inhibitor of DNA binding 4 (ID4) [pr) and aligned  spermatogonia [GDNF signaling occurs through binding the non-signaling co-receptor of the GDNF Family Receptor α1 (GFRα1), which is attached to the cell membrane by glycosylphosphatidylinositol-anchors ,9,10, pe 4 (ID4) ,15. This 4 (ID4) ,15. Howeatogonia ,18,19,20atogonia , pigs [2atogonia , collareatogonia ,24, buffatogonia , differeatogonia  and primatogonia ,28.Scyliorhinus canicula) [Oncorhynchus mykiss) [Oryzias latipes) [gdnfb mRNA levels increased during the arrest of the spermatogenic cycle (end of germ cell proliferation and differentiation), suggesting that Gdnfb is likely involved in the repression of SSC differentiation rather than proliferation [gdnf (gdnfa and gdnfb) and gfrα1 (gfrα1a and gfrα1b) transcripts in zebrafish testes. Subsequently, we identified the cellular types expressing Gdnf and Gfrα1 and assessed the biological effects of Gdnf through an ex vivo testis culture system. According to Oatley and Brinster [In nonmammalian species, particularly in fish, Gdnf/Gfrα1 homologs have been found in a limited number of species, such as dogfish (anicula) , rainbow mykiss) ,31,32 anlatipes) . In theslatipes) . The phylatipes) . Similarlatipes) , who shoBrinster , the impDanio rerio, outbred) (4–5 months old) were kept in 6 L water tanks in a recirculating system with controlled photothermal conditions (27 °C and 14 h of light and 10 h dark). Parameters such as salinity, pH, dissolved oxygen and ammonia were monitored daily in all tanks. Fish were fed twice a day using commercial food . Handling and experimentation were in accordance with Brazilian legislation regulated by the National Council for the Control of Animal Experimental (CONCEA) and the Ethical Principles in Animal Research of São Paulo State University (protocol no. 666-CEUA). Zebrafish is a tropical freshwater fish species natural to rivers in Southern Asia [Sexually mature zebrafish , GFRA1 of Homo sapiens (P56159), Rattus norvegicus (Q62997) and Mus musculus (P97785) were obtained from the Universal Protein Resource  and aligned using the MEGA algorithm allocated in Geneious Pro 4.8.5 software [GFRA1 (human), Gfrα1 (rat and mouse), gfrα1a and gfrα1b (zebrafish), we used the GenBank database, available at the National Center for Biotechnology Information  (accessed on 25 February 2020) and Ensembl [The predicted amino acid sequences for Gfrα1a and Gfrα1b of software . For thesoftware ). For thsoftware  allocatesoftware . The chosoftware . Phylogesoftware . This stsoftware , with adsoftware  using losoftware  after trsoftware . In the  Ensembl .gdnfa , gdnfb , gfrα1a  and gfrα1b  in zebrafish testes, total RNA from testes  was extracted using an RNAqueous®-Micro kit , following the manufacturer’s instructions. cDNA synthesis and quantitative reverse transcription polymerase chain reaction (RT-qPCR) were performed as previously described [gdnfa, gdnfb, gfrα1a and gfrα1b were determined through a StepOnePlus™ Real-Time PCR System . Primers  were digested with 0.2% collagenase  and 0.12% dispase  [® RNA Mini Kit , following the manufacturer’s instructions. cDNA synthesis was conducted using a SuperScript® II Reverse Transcriptase kit  and random hexamers. The relative mRNA levels of pou5f3  (spermatogonia marker), vasa (spermatogonia marker), gdnfa, igf3 (insulin-like growth factor 3) (Sertoli cell marker),gfrα1a and gfrα1b were determined by qRT-PCR. β-actin and ef1 were used as housekeeping genes. The quantification cycle (Cq) values were determined in a StepOne system  using SYBR Green  and specific primers (To obtain testicular cellular fractions (germ or somatic cell-enriched fractions), a differential plating method was carried out as previously described by Hinfray et al. . To thisMI, USA) . Total cMI, USA) . By usinMI, USA) . RNA fro primers , as descn = 10 males) were fixed with 4% paraformaldehyde in PBS   for 1 h, embedded in paraplast  and sectioned at 5 μm thickness. After deparaffinization and rehydration, sections were submitted to antigen retrieval by heating slides in sodium citrate buffer  until temperatures reached 95–100 °C in a microwave. To reduce background fluorescence, slides were incubated with NaBH4 (sodium borohydride—0.01g dissolved in 1 mL of distilled water)  for 3 min. Subsequently, slides were rinsed with 1X PBS (pH 7.4) and incubated with the biotinylated primary antibody rabbit anti-zebrafish Gfrα1a  at 4 °C overnight. Zebrafish polyclonal biotinylated antibody anti-Gfrα1a was synthesized by Rheabiotech  using the specific antigen sequence ‘RLDCVKANELCLKEPGCSSK’ located at the N-terminus of zebrafish Gfrα1a  (1:400) or Alexa Fluor 594 Streptavidin  (1:400) in 1X PBS (pH 7.4) for 60 min at room temperature. Subsequently, sections were counterstained with Hoechst   or Propidium iodide (PI)  (1 mg/mL dissolved in distilled water) and mounted with ProLong Gold Antifade . Control sections were prepared by preadsorbing the zebrafish Gfrα1a antibody with the corresponding peptide  or by omitting the primary antibody. Slides were photographed using a Leica SP5 laser scanning confocal microscope  from the Electron Microscopy Center, Institute of Biosciences, São Paulo State University , and germ cells were classified according to Leal et al. [Testes  were homogenized in an extraction TBST buffer  containing a cocktail of protease inhibitors . Subsequently, the homogenate was incubated on ice for 15–20 min before sonication (3 × 1 min on ice) and centrifuged at 4000 rpm at 4 °C for 20 min in order to determine the total protein concentration by means of a NanoVue spectrophotometer . A total of 40 µg protein was analyzed by sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE). Protein extracts were blotted onto a nitrocellulose membrane  blocked with 3% non-fat milk diluted in 1X Tris-buffered saline (TBS)  for 1 h, and incubated with the primary antibody rabbit anti-zebrafish Gfrα1a  at 4 °C overnight. The membrane was washed with TBS and incubated with horseradish peroxidase-conjugated anti-rabbit IgG  for 2 h. After washing, blots were developed with a chemiluminescence substrate kit  and the signal was captured by a CCD camera . As controls, some membranes were alternatively incubated with primary antibodies that had been preadsorbed with the respective peptides.For the Western blot analysis, testes  (accessed on 20 February 2020) was used. We used a recombinant human hormone because the recombinant zebrafish Gdnf is not commercially available. In addition, rhGDNF has previously been used in fish [To evaluate the effects of Gdnf on zebrafish spermatogenesis (see below), a rhGDNF purchased from PeproTech in fish . The rhGn = 10 males) were incubated with recombinant zebrafish Fsh (rzfFsh) (100 ng/mL [n = 10) were fixed in 4% buffered glutaraldehyde at 4 °C overnight, dehydrated, embedded in historesin Technovit 7100 , sectioned at 4µm thickness and stained with 0.1% toluidine blue to estimate the frequency of the different germ cell cysts using a high-resolution light microscope . In this analysis, five histological fields for each animal were randomly selected for counting the frequency of germ cell cysts (type A undifferentiated spermatogonia (Aund), type A differentiated spermatogonia (Adiff), type B spermatogonia (SPG B), spermatocytes (SPCs) and spermatids (SPTs)), as previously described [The effects of rhGDNF on zebrafish spermatogenesis were investigated using a previously established ex vivo culture system . In this00 ng/mL )  were fixed at 4 °C overnight in freshly prepared methacarn (60% (v/v) absolute ethanol, 30% chloroform and 10% acetic acid) for 4 h. Subsequently, testes were dehydrated, embedded in Technovit 7100 , sectioned at 4 µm thickness and used for BrdU immunodetection, as previously described [und, Adiff and Sertoli cells was determined by counting the BrdU-positive and BrdU-negative cells in a total of 100 cells for the same cellular type, as described previously [To investigate the effects of rhGDNF on germ cell proliferation, BrdU (100 µg/mL) was added during the final 6 h of incubation. After incubation, zebrafish testes  was extracted using the same method described in gdnfa, gfrα1a, gfrα1b, amh (anti-Müllerian hormone), igf3, fshr (follicle stimulating hormone receptor), pou5f3, dazl (deleted in azoospermia-like) and sycp3l  were evaluated. The mRNA levels of the targets (Cts) were normalized by β-actin levels, expressed as relative values of basal expression levels, according to the 2−(ΔΔCT) method. Primer sequences are indicated in For RT-qPCR, total RNA from testicular explants (GDNF (NM_000514.4), mouse Gdnf (NM_010275.3) and zebrafish gdnfa (NM_131732.2), the transcription start site (TSS) was found in the Eukaryotic Promoter Database (EPD), and the promoter regulatory regions (3’ to 5’) were prospected by means of the flanking regions (2000 bp) extracted from NCBI. The cAMP response elements , the androgen receptor binding site , several NF-kB-binding sites, N-Box, E-Box, TATA-Box and GC-Box  was used for the statistical analysis.Data were initially checked for deviations from variance normality and homogeneity through the Shapiro–Wilk and Bartlett’s tests, respectively. Significant differences between two groups were identified using a paired Student’s Sequence analysis revealed that both predicted zebrafish Gfrα1a and Gfrα1b have sequence characteristics of Gfrα family members, such as the three cysteine-rich domains (D1-3), 28 cysteine residues , and two triplets (MLF and RRR) in the domain D2 . SequencPhylogenetic analysis further confirmed that both zebrafish Gfrα1a and Gfrα1b are related to other fish Gfrα1a and Gfrα1b predicted sequences, respectively, and that these isoforms diverge and form two separate fish-specific subclades (estimated posterior probability = 1) A. On thegfrα1a- and gfrα1b- containing regions are syntenic to human GFRA1- and rodent Gfrα1-containing regions  showed a larger group of syntenic genes  when compared with zebrafish gfrα1a    C.gdnfa and gdnfb) and receptors (gfrα1a and gfrα1b) were expressed in zebrafish testes, although with different numbers of amplification cycles ) ) . As the h testes .gdnfb transcripts in zebrafish testes, we focused our analysis on gdnfa. We tried to identify the cellular types expressing gdnfa mRNA in zebrafish testes by employing in situ hybridization with a specific antisense cRNA probe  and Sertoli cells (igf3). For the germ cells, we used vasa, which is a germ cell marker mostly expressed in early germ cells, including types Aund, Adiff and B spermatogonia [vasa was expressed in the germ cell-enriched population, although with levels not significantly higher as compared to the total cell suspension ), we showed higher mRNA levels in the germ cell-enriched fraction, but no expression in the somatic cell population  as compared to their basal mitotic index  , particularly if the Sertoli cells associated with proliferating types Aund and Adiff spermatogonia  A,B,D. Moctively) C. In thictively) E, reasonectively . Our resatogonia E.gdnfa, gfrα1a and gfrα1b), Sertoli cell growth factors (igf3 and amh), Fsh signaling (fshr) and germ cell markers   .gdnfa and gfrα1a, whereas gfrα1b mRNA levels remained unaltered when compared with basal condition levels , mouse Gdnf (NM_010275.3) and zebrafish gdnfa (NM_131732.2)  of human 31732.2) . The in 31732.2) . The upsman GDNF . For zebF . Moreover, both paralogs have conserved domains and residues which are typical of GFRα1 family members, such as 3 cysteine-rich domains , 28 cysteine residues  and 2 triplets (MLF and RRR) [gfrα1a- and gfrα1b-containing regions are syntenic to human GFRA1- and rodent Gfrα1-containing regions. Altogether, this evidence confirmed that zebrafish gfrα1a and gfrα1b are duplicated genes that diverged from each other after the teleost-specific whole genome duplication. It is well established that, around 320 million years ago, the common ancestor of the teleosts experienced a third round of whole genome duplication [This study demonstrated the involvement of the Gdnf/Gfrα1 signaling pathway in the regulation of the spermatogonial phase in zebrafish. Our first analysis identified two zebrafish paralogs for the Gfrα1-encoding gene, named zebrafish and RRR) ,66,67. Sand RRR) ,67. Thisand RRR) ,68, phyllication ,70. Thislication ,70. In tα1a was mainly detected in early types of spermatogonia (Aund and Adiff), and immunostaining decreased as spermatogonial clones became larger and more differentiated. Likewise, accumulating evidence has shown that GFRA1 is a conserved marker for mammalian type A undifferentiated spermatogonia [s to Aal [und spermatogonia of dogfish (Scyliorhinus canicula) [Oncorhynchus mykiss) [Oryzias latipes) [Oreochromis niloticus) [gfrα1 transcripts decreased throughout spermatogonial development and became undetectable in spermatids and spermatozoa. In medaka, Zhao et al. [gfrα1a and gfrα1b mRNA in spermatocytes, but no expression was found in spermatids and spermatozoa. Altogether this evidence is in agreement with our results and supports our hypothesis that the Gndf-Gfrα1a signaling pathway is important for the regulation of the zebrafish spermatogonial phase but is not required for meiotic and post-meiotic phases. Strikingly, our study also detected the Gfrα1a protein among Sertoli cells associated with different types of germ cells. In rainbow trout, Maouche et al. [gfrα1a1 transcripts were mainly expressed in somatic testicular cells, while gfrα1a2 was restricted to type Aund spermatogonia. To our knowledge, our study and the one of rainbow trout [α1a is not only involved in the control of type Aund spermatogonia but can also modulate the functions of Sertoli cells.When evaluating the expression profiling of Gfrα1a and Gfrα1b, we found that both paralogs are expressed in zebrafish testes. Considering the greater homology with the mammalian GFRA1 and the modulation by rhGDNF, we developed an antibody for zebrafish Gfrα1a . Our data revealed that Gfrα1a was found in all types of zebrafish spermatogonia, although the staining pattern varied among the different generations of spermatogonia. Gfratogonia ,71,72,73anicula) ,53, rain mykiss) ,31,32, mlatipes)  and tilaloticus)  reportedo et al.  showed ae et al.  demonstrow trout  were thegdnfb has shown a Ct value greater than 30. These data suggest that Gdnfa might be the main ligand in zebrafish testes. Further in situ hybridization and RT-qPCR analysis demonstrated that gdnfa is mainly expressed in the germ cells. gdnfa was not expressed in somatic testicular cells. In both analyses, we were not able to identify the germ cell types expressing gdnfa in zebrafish testes. Nakajima and collaborators [gdnf mRNA and protein were expressed in type Aund spermatogonia of immature rainbow trout. Moreover, the same authors showed that gdnf and gfrα1 were co-expressed and that their expression changed synchronously during germ cell development [Investigation of the Gdnf ligands (Gdnfa and Gdnfb) revealed that both are expressed in zebrafish testes, although elopment ,9,10, peelopment ,12 and telopment ), actingelopment ,28,71,72To assess the biological roles of Gdnf in zebrafish spermatogenesis, we used a rhGDNF. There is strong evidence that rhGDNF can bind to zebrafish Gfrα1a and elicit a downstream signal transduction in zebrafish testes. The first item of evidence is the predictive 3D model which examined the interaction sites between human GDNF and zebrafish Gfrα1a based on the binding interaction with human GFRA1. This analysis revealed structural similarities between zebrafish Gfrα1a and human GFRA1 A, box 2,und and Adiff spermatogonia when compared to basal conditions. Consistently, histomorphometric analysis revealed that both types Aund and Adiff became more abundant, while type B significantly decreased following rhGDNF treatment. Altogether, these results indicated not only that Gdnf stimulates proliferation of the most undifferentiated spermatogonia (Aund and Adiff) but that it is also involved in blocking late differentiation into type B spermatogonia. Similar functions have been described in mammalian and non-mammalian species. In mammalian species, particularly rodents, GDNF promotes self-renewing proliferation of SSCs  were up-regulated when the expression of both receptors was lowered. Altogether, this evidence from different species sustains our conclusion that the Gndf-Gfrα1 signaling pathway is associated with maintaining the pool of undifferentiated spermatogonia (Aund and Adiff) through promoting their proliferation and also by inhibiting their differentiation. Moreover, as zebrafish Gdnfa and its receptor (Gfrα1a) are co-expressed, it is important to highlight that the above-mentioned function is an autocrine loop of Gdnf on types Aund and Adiff spermatogonia.With regard to biological functions, our results demonstrated that rhGDNF (100 ng/mL) increased the mitotic index of types Aof SSCs . These data indicate for the first time that a germ cell-derived factor is involved in the creation of new spermatogenic cysts, i.e., new available niches, in addition to supporting the development of early differentiating spermatogonial cysts. In the first case, as Gdnf stimulates the proliferation of type Aund, the newly formed, single spermatogonium must recruit its own Sertoli cells to form a new spermatogenic cyst. Therefore, it is reasonable that new Sertoli cells would be produced to create a niche into which the newly formed, single type Aund can be recruited or attracted (germ cell homing). Consistently, in mice, Gdnf has been shown to be important for germ stem cell homing as it acts as a SSC chemotactic factor [α1a, which is also expressed in Sertoli cells of zebrafish. In agreement with our observation, a study in rodents has shown that Gdnf promoted the proliferation of immature Sertoli cells through its interaction with Gfrα1 and neural cell adhesion molecules (NCAMs), both co-expressed in Sertoli cells [α1a expression in Sertoli cells, we cannot exclude that Gdnf-induced Sertoli cell proliferation may be mediated by other growth factor(s) produced by type A undifferentiated spermatogonia.In this study, we also quantified Sertoli cell proliferation because change in the proliferation of Sertoli cells associated with types Aectively . In fishectively ,71,74. Sc factor . In the li cells ,77. Althα1a). This would be the first demonstration that a germ cell factor can affect the spermatogonial niche through an autocrine and paracrine loop. It seems that Gdnf signaling would enhance its own production and sensitivity to favor the creation of new spermatogonial niches (type Aund spermatogonia and Sertoli cells). Notably, gfrα1b was not modulated by any treatment, which indicates that zebrafish Gfrα1a may be the mammalian GFRα1 homologous form. Moreover, we showed that Fsh did not modulate gdnfa expression in zebrafish testis explants. Similarly, Bellaiche et al. [gdnfb in immature and early maturing rainbow trout testicular explants either. This regulation in fish is different from the one reported in mammals, where Fsh has been shown to stimulate the expression of Gdnf in the testes [gdnfa gene to search cAMP response elements (CREs). As is well known, Fsh stimulates the cAMP-dependent protein kinase A signaling pathway, leading to phosphorylation of the cAMP response element-binding protein (CREB), which is necessary to transactivate several genes containing CREs [Gdnf promoter are directly involved in basal and cAMP-induced expression of Gdnf in Sertoli cells. In our in silico analysis, we demonstrated that the zebrafish gdnfa promoter (−2000 to +1 bp) has fewer conserved DNA binding sites compared with human and mouse GDNF/Gdnf promoters. Moreover, our analysis showed only one CRE site near to the zebrafish gdnfa transcription start site, instead of three CREs, as reported in human and mouse. The difference in the promoter region and the lower number of CRE binding sites could be the reason that Fsh could not stimulate gdnfa expression in zebrafish testes.We further evaluated whether Gdnf could modulate testicular gene expression or affect Fsh-induced gene expression in zebrafish explants. Previous studies have shown that Fsh is the major endocrine player regulating zebrafish spermatogonial development through targeting Sertoli and Leydig cell functions, such as sex steroid and growth factor production ,63,78,79e et al.  demonstring CREs ,81. Lambing CREs  demonstrGDNF/Gdnf promoter region also contains several E- and N-boxes that allow the binding of basic helix–loop–helix proteins with potential repressor activity through Notch signaling [gdnfa expression through the Notch pathway and transcription repressors HES and HEY, which would bind to E- and N-boxes within the zebrafish gdnfa promoter region. Functional studies of the gdnfa promoter region are required to elucidate how Fsh and Gdnf regulate the expression of gdnfa in zebrafish testes.The ignaling . Activatignaling ,84. The ignaling ,86,87. Tignaling . Therefogfrα1a transcripts were up-regulated by Fsh but not with the same intensity as observed in the Gdnf treatment (a three-fold increase as compared to Fsh). In immature rainbow trout, Bellaiche et al. [gfra1a mRNA levels were increased following in vitro treatment with Fsh (100 ng/mL—the same concentration as was used in our work). Moreover, the same authors reported that testicular gfra1a levels increased towards the end of the reproductive cycle, which coincides with the natural elevation of plasma Fsh levels in rainbow trout [GDNF, we have evidence from two teleost species that Fsh modulates the Gdnf-Gfrα1 pathway through stimulating, not ligand, but receptor (gfra1a) mRNA levels. However, there are some questions that remain. The first concerns whether the Fsh-induced expression of gfra1a is mediated by Sertoli cells, germ cells or both. In this work, we have demonstrated that gfra1a is expressed by Sertoli and germ cells, while the Fsh receptor is exclusively expressed by somatic cells (Sertoli and Leydig cells) [gfra1a expression is mediated by germ cells, this indicates that the regulation occurs indirectly through growth factors or androgens released by somatic cells (Sertoli and Leydig cells). Moreover, we cannot exclude that the increase in gfra1a could also be a consequence of the proliferation of spermatogonia or/and Sertoli cells stimulated by Fsh. More studies are necessary to address the nature of Fsh regulation on gfra1a expression in zebrafish testes. Although Gdnf or Fsh independently stimulated gfra1a mRNA levels in zebrafish testes, we observed that co-treatment affected negatively the Gdnf-induced expression of gfra1a. This is also noted for other genes such as pou5f3 or dazl, whose expressions were higher in the Gdnf treatment as compared to co-treatment with Fsh. For pou5f3, a stem cell marker, this observation suggested that Gdnf could be more involved in the maintenance of stemness than in increasing the number of stem cells in zebrafish testes. On the contrary, Fsh would be more associated with proliferation towards differentiation, as pou5f3 was significantly decreased following Fsh co-treatment. Therefore, our data indicate that the pro-differentiating effects of Fsh seemed to be more potent over the stem cell maintenance properties of Gdnf. On the other hand, at the level of differentiation, Gdnf decreased the Fsh effects on spermatogonial differentiation, as the expression of dazl, a marker of spermatogonial differentiation, was significantly down-regulated. Altogether, these observations suggest that Gdnf could promote stem cell maintenance through blocking spermatogonial differentiation. This conclusion is also supported by histomorphometrical data showing that Gdnf decreased the frequency of type B spermatogonia and accords with the higher expression of Gfrα1a in type Adiff spermatogonia.In this study, we demonstrated that e et al.  reportedow trout . Therefog cells) . Therefoamh or igf3 mRNA levels in the zebrafish testicular explants. Therefore, Gdnf’s role in inhibiting spermatogonial differentiation is not mediated by Amh or Igf3 and it could occur by acting directly on germ cells (autocrine) or indirectly through a different growth factor released by somatic cells (paracrine).As Gdnf is a member of the TGF-β superfamily, its role in inhibiting spermatogonial differentiation is likely consistent with other TGF-β superfamily members, such as Amh. Amh is a Sertoli cell growth factor which has been characterized as an inhibitor of spermatogonial differentiation in zebrafish ,64,87  and Sertoli cells. The main actions of Gdnf are: (1) the creation of new available niches by stimulating proliferation of both type Aund spermatogonia and their surrounding Sertoli cells. In this context, we highlight that Gdnf stimulates the proliferation of Sertoli cells, which are associated with type Aund undergoing mitosis. As a consequence, Gdnf increases the number of available niches and maintains the stemness pool in the zebrafish testes; (2) support of the development of differentiating spermatogonial cysts through proliferation of type Adiff and their surrounding Sertoli cells; and finally, (3) inhibition of late spermatogonial differentiation, as shown by the decrease in type B spermatogonia and down-regulation of dazl in the co-treatment with Fsh. Altogether, our data indicate that the autocrine and paracrine roles of Gdnf are evolutionary novelties in fish, although some paracrine functions are conserved, being similar to those observed for mammalian GDNF.In summary,


Escherichia coli BSI and higher proportions of b-haemolytic streptococci. Although obese patients had longer hospital admissions and more repeat incident BSI within 1 year, they had lower overall case fatality. In a logistic regression model, obesity was associated with a lower risk for 30-day case fatality . Obesity is associated with significant differences in the determinants and outcome of BSI. Increasing rates of obesity is likely to influence the epidemiology of BSI in populations.Although obesity is a major healthcare problem that is increasing in many populations worldwide, there are limited studies that have examined its contribution to infectious diseases morbidity and mortality. The aim of this study was to examine the clinical determinants and outcomes of bloodstream infections among patients with obesity. All adults within the publicly funded healthcare system in Queensland, Australia, identified with a BSI during 2017–2019 were included and the presence of obesity was based on discharge International Classification of Diseases (ICD-10) codes. Clinical features, microbiology, and outcomes were compared among obese and non-obese subjects. A total of 24,602 incident BSI were identified among 21,613 Queensland residents; of which 4,579 (21.2%) and 17,034 (78.8%) were classified as obese or non-obese, respectively. Obese patients were less likely to have community associated infections and were more likely to be younger, female, have higher comorbidity scores, and have bone and joint or soft tissue infections as compared to non-obese subjects. Obese patients had a lower proportion of  Obesity is recognized as a major risk factor for adverse health effects and outcomes, and is increasing in many populations worldwide –3. ExcesAlthough obesity is common and associated with a range of adverse health effects, there is a limited body of literature investigating obesity in relation to serious infections. Most studies have included only small numbers of subjects or have been limited to highly selected patient cohorts , 11, 12.The study population comprised of all residents of Queensland, Australia, who were identified as having incident BSI and were admitted to a Queensland Health public hospital between January 1st, 2017, and December 31st, 2019. Queensland’s publicly funded health system, Queensland Health, services approximately 1.6 million episodes of care annually across 16 hospital and healthservice (HHS) regions within a population of approximately 5 million residents . ApprovaPathology Queensland performed all statewide blood culture testing for both community and institutional collection sites across Queensland Health. Throughout the study, all processing sites used the BACT/Alert® 3D system  apart from the main central laboratory managing culture submissions from the Greater Brisbane Area and several rural Queensland sites which used the BACT/ALERT® VIRTUO® system  during 2018. All blood cultures were incubated using BacT/ALERT FA plus (aerobic), and FN plus (anaerobic) media bottles for 5 days and subsequently discarded if no growth was detected.The Queensland Health Clinical Information Systems Support Unit (CISSU) retrospectively identified all blood cultures which produced bacterial growth throughout the study period. Culture results  were obtained along with demographic  details. Incident BSIs were differentiated by first and subsequent bacterial isolations per patient, with the first and subsequent isolation of the same species within 30 days deemed to represent the same episode of BSI. Polymicrobial infections were those where a bacterial species was co-isolated with one or more other significant pathogens within a 48-h period with two independent sets required for common contaminants in order to define significance .Once incident episodes were identified, linkages with statewide databases were used to obtain additional clinical and outcome information. Encounters 2 years preceding and 1 year following an index blood culture were identified within Queensland Hospital Admitted Patient Data Collection (QHAPDC) and used to determine hospital admission and discharge dates, discharge survival status, geographical location, and ICD-10-AM diagnostic codes. The diagnosis of obesity was determined using the following codes “E660” or “E661” or “E6610” or “E6611” or “E6612” or “E6613” or “E662” or “E6620” or “E6621” or “E6622” or “E6623” or “E668” or “E669” or “E6690” or “E6691” or “E6692” or “E6693” or “U781.” For the purposes of length of stay, episodes observed within multiple continous hospital admissions  were deemed to represent a single hospital admission. The Registry of General Deaths was queried as of December 31, 2020, to confirm institution-based deaths and those occurring in other settings within Queensland. The Accessibility/Remoteness Index of Australia (ARIA +) was used to determine geographical remoteness of the study population based on their accessibilty to goods, services, opportunities, and road distance measurements from over 12,000 populated localities to the nearest Service Centres in five size categories based on population size .Bloodstream infections were classified as hospital onset, healthcare associated, or community associated as previously described . Comorbip values of < 0.05 were deemed to represent statistical significance.Data was analyzed using Stata 17.0 . Medians with interquartile ranges (IQR) were used to described non-normally distributed continuous variables and were compared using the Mann–Whitney-Wilcoxon test. Categorical data were compare using the Fisher’s exact test. A multivariable logistic regression model was developed to examine factors associated with all-cause 30-day case fatality rates; only first admissions were included in this analysis. Age, sex, onset classification, Charlson score, mono-versus polymicrobial infection, and focus of infection were included in the initial model. Stepwise backward variable elimination was performed in order to develop the most parsimonious model . CalibraThere were a total of 24,602 incident episodes of BSI among 21,613 QLD adult residents; 2,239 had two, 495 had three, and 255 had four or more incident infections during the surveillance period. The overall median age was 64.3 years , and 10,691 (43.5%) were female. The majority of BSIs were community onset  of which 11,224 (45.6%) were community associated, 8,501 (34.5%) were healthcare associated, and 4,877 (19.8%) were hospital onset. Overall, 5,403 (21.9%) episodes were in those classified as obese.p < 0.001) difference in the proportion of obesity by remoteness although this was not across ordered groups. Geographically, the proportion of obesity was 2,786/12,832 (21.7%) for metropolitian areas, 1,570/6,115 (25.7%) for inner regional areas, 825/4,414 (18.7%) for outer regional areas, 93/529 (17.6%) for remote areas, and very remote 97/438 (22.2%).There was an increasing proportion of episodes occuring among obese individuals with advancing age, peaking in the 50–59 age group and nadir in the 80 + age group. Although the distribution of obesity was similar for males and females < 30 years, more males than females were obese beyond the age of 30 years Fig. . There wThere were a number of different clinical features among BSIs occurring in obese and non-obese patients as detailed in Table p < 0.001). Charlson comorbidity scores of 1–2 were similar across both groups ; however, scores of 3 + were much higher in the obese group  compared to the non-obese group .Underlying medical illnesses were common among obese patients with higher median Charlson comorbidity scores compared to non-obese. Almost one-third of non-obese patients had zero comorbidities , whereas obese patients with no comorbidities accounted less than one-fifth . Bone and joint infections were also more frequently obesity associated among males as compared to females , although this did not associate with any age group.Soft tissue infections were comparably higher among obese males than obese female  non-obese patients.The median duration of hospital stay was 10 (IQR 6–25) days and the median length of hospital stay for obese patients was 3 days longer than non-obese patients . Among the obese cohort, those with community-onset BSI, the median length of stay was 2 days longer than non-obese cohort . Among patients incepted in 2017 and 2018, new incident BSI occurred within 1 year in 539 (10.0%) obese and 1,310 . After adjustment for confounding variables in logistic regression analysis, obesity was associated with a lower risk for 30-day case fatality  as shown in Table The crude 30-day case fatality following the initial episode was 7.5%  and was higher for non-obese patients  with first episodes of patients , 12, 23.Although our study benefits from a large cohort of patients, there are some limitations. First, we used discharge ICD-10 codes to identify obesity and did not use actual measured heights and weights in our evaluation. Studies from our region indicate that whilst ICD-10 codes identify obese patients, their sensitivity is low  such that many were likely included within the non-obese cohort . This, hThis study identifes that the clinical characteristics, course in hospital, and outcomes associated with BSI are different among obese and non-obese patients. This study adds to the growing body of literature documenting the adverse effects of obesity on infectious disease mortality. Increasing rates of obesity is likely to influence the epidemiology of BSI in populations, and further efforts to reduce the burden of obesity-associated infections are warranted.


Athalia rosae, which can acquire neo-clerodane diterpenoids (clerodanoids) via pharmacophagy when having access to the plant Ajuga reptans. We show that clerodanoid access mediates protection against predation by mantids for the sawflies, both in a no-choice feeding assay and a microcosm setup. Even indirect access to clerodanoids, via nibbling on conspecifics that had access to the plant, resulted in protection against predation albeit to a lower degree than direct access. Furthermore, sawflies that had no direct access to clerodanoids were consumed less frequently by mantids when they were grouped with conspecifics that had direct access. Most, but not all, of such initially undefended sawflies could acquire clerodanoids from conspecifics that had direct access to the plant, although in low quantities. Together our results demonstrate that clerodanoids serve as a chemical defense that can also be transferred by interactions among conspecifics. Moreover, the presence of chemically defended individuals in a group can confer protection onto conspecifics that had no direct access to clerodanoids.Chemical defense is a widespread anti-predator strategy exhibited by organisms, with individuals either synthesizing or extrinsically acquiring defensive chemicals. In some species, such defences can also be transferred among conspecifics. Here, we tested the effects of pharmacophagy on the defense capability of the turnip sawfly,  We expected C− sawflies from mixed group-composition treatments to acquire clerodanoids, but to have lower amounts of clerodanoids compared to C+ sawflies.To test whether C− sawflies in mixed group-composition treatments acquired clerodanoids compared to 6C− replicates, we collected C− sawflies from different group-composition treatments and analysed them chemically. We also collected C+ sawflies to confirm their clerodanoid acquisition. Lastly, we examined if C+ sawflies differed from C− sawflies of mixed group-composition treatments in their amounts of clerodanoids, i.e. if there is a difference between clerodanoid amounts acquired directly from leaves or indirectly from conspecifics. We only collected individuals from replicates that had intact sawflies remaining at the end of the trial and stored them at −80°C until further analysis. The final sample sizes for C− sawflies chemically analysed were six, five, seven, and five samples each of 6C−, 2C + 4C−, 3C + 3C− and 4C + 2C− group-composition treatments, respectively. The final sample sizes for C+ sawflies were one, four and five from 2C + 4C−, 3C + 3C− and 4C + 2C− group-composition treatments, respectively. Individuals were freeze-dried, homogenized and extracted twice in ethyl acetate . After centrifugation, the supernatants of the two extractions were pooled to a final volume of 400 µl for each individual. The extracts were dried in a vacuum centrifuge at 35°C, suspended in 125 µl 100% methanol  in an ultrasonic bath for 15 min, and filtered using syringe filters . The samples were analysed using an ultra high performance liquid chromatograph  with a Kinetex XB-C18 column , coupled to a quadrupole time of flight mass spectrometer , see electronic supplementary material §2 for details. The resulting chromatograms were processed with the software Compass Data Analysis 4.4 . The putative clerodanoids with neutral masses  (f)In experiment 1, we examined whether treatment had an effect on number of attacks, prey rejection, and prey acceptance using a binomial generalized linear mixed-effects model (GLMM), with mantid identity as random effect. As there was quasi-complete separation in our data for two variables (prey rejection and prey acceptance), i.e. the predictor variable could perfectly predict the response variable for a subset of our data, we fitted a Bayesian binomial GLMM using ‘blme’ package (v. 1.0-5)  for all In experiment 2, we examined the effect of treatment, time and their two-way interaction on number of alive sawflies using a Poisson GLMM (‘lme4’ package v. 1.1-27.1 ) with reIn experiment 3, we calculated the proportion of consumed, alive and ‘dead but not consumed’ C− and C+ sawflies with respect to the initial abundance of C− and C+ sawflies, respectively, in that replicate. We examined whether the proportion of consumed, alive and ‘dead but not consumed’ C− individuals differed significantly among the group-composition treatments using a binomial GLMM (‘lme4’ package), with mantid identity and trial number as random effects. Finally, we examined if there was a significant difference in the amount (semi-quantified based on peak area) of the two putative clerodanoids between C− and C+ sawflies of mixed group-composition treatments using a Kruskal-Wallis test. We also tested whether C− sawflies from mixed group-composition treatments had significantly different clerodanoid amounts from C− sawflies of the 6C− treatment using a Kruskal-Wallis test.Post-hoc tests were conducted using ‘multcomp’ package (v. 1.4-17) [All data were analysed using R 4.0.5 (2021-03-31) . We chec 1.4-17) .. 3 (a)χ2 = 5.92, d.f. = 2, p = 0.052; figure 1b). By contrast, prey rejection differed significantly between treatment , with C+ individuals being rejected more often than C− (post hoc test: p < 0.001) and AC+ (post hoc test: p < 0.001). Likewise, treatment had a significant effect on whether an individual was consumed , with C+ individuals (0% consumed) being significantly less consumed compared to C− (100% consumed) (post hoc test: p < 0.001) and AC+ (70% consumed) (post hoc test: p = 0.001). Note that C+ sawflies were usually attacked twice, as they were often initially rejected by mantids (figure 1c) but then re-attacked during the trial. By contrast, C− sawflies were never and AC+ sawflies were infrequently rejected by the mantids, and were consumed within the first attack (figure 1d).All sawflies, irrespective of treatment, were attacked at least once with no significant effect of treatment on number of attacks ( (b)χ2 = 36.76, d.f. = 3, p < 0.001). In the treatment with no mantids, all C− and all but one C+ individuals survived across all replicates (b). In C− treatments with mantids, no individual was alive after three half-days. By contrast, for C+ treatments with mantids, all individuals were alive in two replicates. In the other six C+M+ replicates the number of alive individuals decreased with time, although in no replicate were all individuals killed. The number of ‘dead but not consumed’ individuals significantly differed between C−M+ and C+M+ treatments . Similarly, there was a significant difference in number of consumed sawflies , with all sawflies consumed in the C−M+ treatment while only few sawflies were consumed across three replicates in the C+M+ treatment. In four C+M+ replicates but zero C−M+ replicates, we collected ‘dead but not consumed’ individuals, suggesting that while the mantids attacked C+ individuals, they were not always consumed.There was a significant interactive effect of treatment and time on number of sawflies alive (plicates b. In C−  (c)χ2 = 41.87, d.f. = 3, p < 0.001; electronic supplementary material §4a), with significantly more C− consumed in the 6C- treatment compared to the other mixed group-composition treatments (a). There was no significant difference between the three mixed group-composition treatments (a). The proportion of alive C− sawflies differed between the treatments , with significantly fewer C− alive in the 6C− compared to the 2C + 4C- and 3C + 3C− treatment, while other treatments were not significantly different (b). Similarly, the proportion of ‘dead but not consumed’ C− sawflies differed between the treatments , with significantly more C− sawflies being ‘dead but not consumed’ in the 4C + 2C− compared to the 6C− treatment, but no other significant differences between treatments (c). Similar to experiment 2, C+ sawflies were consumed rarely, although in many replicates there were ‘dead but not consumed’ C+ individuals .Group-composition treatment had a significant effect on the proportion of consumed C− sawflies , occurring as prominent peaks in the chromatograms . All ten (100%) C+ sawflies had acquired both clerodanoids  and 2  than C− sawflies for mixed group-composition treatments. C− sawflies of mixed group-composition treatments had a significantly higher amount of clerodanoid 1  but not of clerodanoid 2  than C− of the 6C− treatment.The chemical analysis revealed that the clerodanoids 1 (482) and 2 (484) could be detected in 16 (approx. 94%) and 14 (approx. 82%), respectively, of the 17 sampled C− sawflies from mixed group-composition treatments a,b, occuodanoids . There wodanoids , possibl. 4A. rosae, which takes up and further metabolizes clerodanoids  from A. reptans plants [A. reptans leaves provides a defense against predation by making the sawflies unpalatable to the predator. We also demonstrated that clerodanoid access provides protection not only to focal individuals but also to conspecifics in mixed groups of C+ and C− individuals.Chemical defense as an anti-predator strategy is widespread and well-documented in animals . An intes plants ,37. HereWhile most sawflies without access to clerodanoids were lethally attacked and consumed by the mantids, only very few sawflies that had taken up clerodanoids from leaves were consumed, as we had predicted. Nevertheless, many sawflies with clerodanoid access were also attacked but then readily rejected by the mantids, as shown by the prey rejection behaviour in experiment 1 and by the higher number of ‘dead but not consumed’ sawflies in experiment 2. This rejection is likely induced by the bitter taste of the clerodanoids that may be deposited on the cuticle and in body tissue of the adult sawfly . When teA. rosae can acquire clerodanoids not only from plants but also from conspecifics via nibbling on their body surface. However, acquiring clerodanoids indirectly from conspecifics resulted in less protection than direct acquisition from the plants in A. rosae in our experiments. Not all sawflies successfully acquire detectable clerodanoid amounts from C+ conspecifics [A. reptans leaves , which might facilitate temporary avoidance learning by mantids. It remains to be tested whether other species or even adults of H. patellifera are likewise deterred by clerodanoids. The effectiveness of chemical defenses can differ depending on the predator species, developmental stage of the predator or prey, prey size etc. [Gallus gallus domesticus, rejected mimics  less frequently when the relative abundance of these mimics compared to the models  increased, but birds only discriminated between the models and mimics when the frequency of mimics was above 25% [Our data from the predation microcosm experiment (experiment 2) demonstrated that the mantids attacked C+ sawflies, with numbers of alive sawflies decreasing over time, but this decline was less rapid than that of C− sawflies in presence of mantids. This suggests that the mantids may learn to avoid C+ sawflies after first encounters, leading to a longer survival period of the sawflies. Learned aversion has been found in the mantid e bitter . Similartogether . Interesidifolia . Moreoveidifolia ,58. Indeidifolia ,59. The ize etc. –62. In lbove 25% . Moreovebove 25% , and thebove 25% .A. rosae, intraspecific variation in clerodanoid uptake could be expected if the distribution of pharmacophagy-suitable plants is patchy, if there is intraspecific variation in the clerodanoid concentrations available from the plants, or if there are associated costs of clerodanoid uptake. Indeed, A. rosae individuals that were exposed to clerodanoids had a shorter lifespan than control individuals [b). Similar costs of chemical defense have been revealed in swallowtail butterflies, which showed reduced larval survivorship [A. rosae.In natural populations of ividuals . This suivorship  or a redivorship  when seqivorship . Future


Recent research has characterized the behavioral defense against disease. In particular the detection of sickness cues, the adaptive reactions (e.g. avoidance) to these cues and the mediating role of disgust have been the focus. A presumably important but less investigated part of a behavioral defense is the immune system response of the observer of sickness cues. Odors are intimately connected to disease and disgust, and research has shown how olfaction conveys sickness cues in both animals and humans. This study aims to test whether odorous sickness cues (i.e. disgusting odors) can trigger a preparatory immune response in humans. We show that subjective and objective disgust measures, as well as TNFα levels in saliva increased immediately after exposure to disgusting odors in a sample of 36 individuals. Altogether, these results suggest a collaboration between behavioral mechanisms of pathogen avoidance in olfaction, mediated by the emotion of disgust, and mechanisms of pathogen elimination facilitated by inflammatory mediators.Disgusting stimuli are associated with an increased risk of infection. We here test whether disgusting odors, can trigger an immune response in the oral cavity. The results indicate an increase level of TNFα in the saliva. This supports that disease cues can trigger a preparatory response in the oral cavity. Upon detection of disgusting objects, a repertoire of autonomic and involuntary behavioral responses is initiated to avoid pathogen-rich objects like feces and rotten food, and to prepare for the possibility of contact. Pathogen avoidance offers a considerable evolutionary advantage by reducing the probability for disease contagion when compared with the exhaustive and cost-intensive mechanisms of pathogen elimination in form of a fully developed immune response , 2.in vitro with lipopolysaccharide  and 15 male [(26.5 (3.9) years] with comparable age  and body mass index BMI . General health was rated as ‘pretty good’ or ‘very good’ by all participants on a five-point scale ranging from ‘very bad’ to “very good. Mean disgust ratings and distribution of individually chosen disgust odors are given in Based on a previous published study that found a moderate effect size of disease-related stimuli exposure on the surge of salivary TNFα , a powerParticipants were recruited via advertisements at Stockholm University, Karolinska Institutet and on student online-platforms. All were offered movie vouchers for their participation. Inclusion criterion were being a non-smoker, reporting being healthy, a functional olfactory sense, and not being pregnant. After giving informed consent, eligible participants were invited for a first screening session to identify for each individual the four most disgusting odors from a sample of twelve. Those four individually selected disgust odors were then to be used during the following exposure session ‘Disgust’ and had to fulfill the requirement that ratings for those four individually most disgusting odors had to be equal to, or exceed, 60 on a disgust visual analogue scales (VAS) ranging from 0 ‘not at all’ to 100 ‘extremely’. Individuals reporting weaker disgust were excluded from the study. This selection procedure was necessary due to the large inter-individual variability in odor evaluation and the need to guarantee successful disgust induction in study participants so as to be able to address our study aim, i.e. to investigate immune system response to olfactory evoked disgust. Participants were informed that the aim of the current study was to investigate how odors, especially unpleasant ones, influence our psychological and physiological well-being. All were given movie vouchers for their participation.Sixteen odors were pre-selected in separate pilot studies (not described here): four neutral blending fluids  and 12 disgust-odorants comprising complex everyday odorants , monomolecular chemicals , and artificial odorant-mixtures . In those pilot studies, well-perceivable, iso-intense odor concentrations using appropriate blending fluid were determined. We also decided upon appropriate odor-object identifier that were chosen either from the identity of the real object , its product name , descriptions in the literature or from the internet and personal associations of how participants in the pilot studies described the odor qualities  were 2-mercaptoethanol (rotten eggs) and fermented herring, whereas only one participant perceived strong disgust from smelling pyridine (gingivitis); indicating considerable individual variation in olfactory perceived disgust between individuals on the one hand, but suggesting conformity of perceived disgust as evoked by rotten food odors.Column We used a within-group design requiring two sessions undertaken on separate visits, one for odor exposure ‘Control’ and one for ‘Disgust’ . For all visits, participants had to abstain from use of perfume and other fragrances. Odor exposure sessions were at least one week apart  to ascertain immune system normalization after disgust stimulation and were scheduled at standardized times for each participant, either between 9–11.30 a.m. or 12–3 p.m. to avoid confounding with immune system analytes’ diurnal cycles. To warrant good analyte quality, participants could only participate if they reported being free from infection and use of anti-inflammatory drugs for at least 14 and 10 days, respectively, and abstinence from physical exercise for at least 24 h and from alcohol for at least 12 h prior to testing.Upon arrival for odor exposure sessions, ‘Control’ or ‘Disgust’, a 30-min resting period was executed for familiarization with the new environment and normalization of physiological and immunological parameters. During this time, several psychometric scales were administrated: the Disgust Scale-Revised (DS-R) ; the pewww.pstnet.com). Odorant presentation was organized in the following way: First, odorant category label (‘Body’ or ‘Food’) were presented, followed by a 5-s countdown for adaptation of breathing pattern and a fixation cross upon which odorants, stored in 160 ml opaque glass jars, were presented by trained investigators quickly opening the jar and placing it in 5 cm distance to the participant’s nose for 3 s of inhalation. After that, participants rated each odorant on 100 step VAS ranging from ‘not at all’ to ‘extremely’ for ‘Intensity’ and ‘Disgust’ ratings, and ranging from ‘extremely unpleasant/-healthy’ to ‘extremely pleasant/healthy’ with ‘neutral’ placed in the middle (50) for ratings of ‘Pleasantness’ and ‘Healthiness’. All odorants were presented in random order with interstimulus intervals of at least 20 s to avoid adaptation and with varying duration due to individual speed of VAS ratings. Each odor exposure session lasted about approximately 20 min with four odorants being presented three times in random order that were unique to each individual (30), corresponding to 65 and 95 min after beginning of each odor exposure session. In addition, at time points pre and post30, blood samples were taken for analysis of a systemic effect of olfactory evoked disgust on level of IL-6 and blood TNFα in the first 21 participants. Pilot whole blood analyses of this sub-sample (Quantikine HS ELISA) showed no variation with odor exposure. Therefore, blood sampling was discontinued.Odor exposure sessions were performed in a quiet well-ventilated room designed for odor perception research purpose, where participants were comfortably seated with his/her chin placed on a chinrest at about 50 cm from a computer screen on which instructions and VAS ratings were presented using E-Prime 2.0  and mounted to target areas. EMG signal was recorded using AD Instruments differential BioAmp amplifier controlled by a PC using LabChart7 pro software (www.ADInstruments.com) with the following settings: input impedance of 200 MΩ, amplification range +/– 5 µV to +/100 mV, gain accuracy +/1.5%, common mode rejection ratio 85 dB @ 60 Hz, 1000 Hz sampling rate, mains filter, first-order 10 Hz high-pass filter, and fourth-order Bessel 500 Hz low-pass filter at –3 dB .Two salivary immune markers were measured in the current study: Tumor necrosis factor α(TNFα) and secretory immunoglobulin A (sIgA). To do so, 3 mL whole saliva samples were collected using passive drool technique through clean 5 cm plastic straws into 10 ml screw-lid plastic centrifuge test tube vials while recording sampling time for later correction for salivary flow. Participants were instructed to imagine eating their favorite dish to increase salivary flow, and to then carefully extrude the accumulating saliva with their tongue into the straw. After sampling, saliva was centrifuged, aliquoted, bar-code labeled, and frozen to –80 °C within one hour. After collecting all samples from all participants, saliva aliquot was thawed for analysis of TNFα and sIgA using Invitrogen’s UltraSensitive TNFα (KHC3013) and Salimetrics’ salivary secretory IgA (1-1602) enzyme immunoassay kits, respectively, and results were reported in pg/mL for TNFα and in ug/mL for sIgA. Analyses with ELISA were performed in duplicate; thus 432 data points were available per measure [36 participants * 2 odor exposure sessions (control vs. disgust) * 3 time points .The following analyses were performed using IBM-SPSS 22: Baseline-corrected scores of state disgust and stress were used for analysis and repeated measures ANOVAs were calculated including the within-subject factors ‘Odor condition’  and ‘Time’  data were analyzed using mixed model analyses. A mixed effect approach was used including the fixed factor ‘Odor condition’ and ‘Time’ and the random factor ‘Subject’, allowing intercepts to vary between participants. A stepwise elimination procedure was followed by a chi-square test comparing a model with and without the critical effect and those effects significantly improving the model fit were kept and effect size b reported.lmer function in the lme4 R package). Our dependent variable was either TNFα or sIgA levels. Our exploratory variables were ‘Odor condition’ , ‘Time’  and their interaction. Finally, we included a random intercept for each subject’s ID and random slopes for odor condition by subject . We also controlled for the robustness of our results by doing the same models but controlling for several confounding factors such as sex, BMI, and disgust sensitivity .To examine whether the levels of immunological markers  were influenced by the odor condition we used a Linear Mixed-Effects Model, LMM (30) within each condition. In the latter model, we included a random intercept for each subject’s ID and random slopes for time by subject.Based on reviewers’ comments we also completed a Linear Mixed-Effects Model exploring how the levels of immunological markers (dependent variables) are influenced by ‘Time’  = 27, P < 0.01), in addition to significant main effects of Time and Odor condition  = 56, P < 0.01 and F = 40, P < 0.01, respectively). These results confirm our intended manipulation of olfactory evoked disgust which was most evident at time point Post but that had dissipated by time point Post30.Ratings of state disgust  showed a30 being 1.0 (1.2) versus 1.8 (2.3). Repeated measures ANOVA on baseline-corrected state stress confirmed this impression showing no significant changes, over time, between exposures, and no significant interaction either  < 2 and ps >.10).Levels of state stress, however, differed only marginally between Control and Disgust conditions with corresponding means (and SD) at time point Pre being 1.5 (1.4) on a 10-point scale versus 2.0 (2.0), at time point Post being 1.3 (1.6) versus 2.0 (2.0), and at time point Postχ2(1) = 252.2, P < 0.001) with effect size b = 0.16 and standard error SE = 0.07 (2(1) = 3.6, P < 0.057, b = –0.076, SE = 0.03) indicating enhanced increase of levator labii activation during disgust odor inhalation as compared to neutral ones.At the levator labii region, mean EMG amplitudes over the whole –3 to 3 s time window were significantly increased during exposure to disgusting odors (E = 0.07 . This ovE = 0.07 . At this2(1) = 90.4, P < 0.001, effect size b = –0.15, SE = 0.09). Possibly, this increased activation with neutral odors may be related to higher sniff vigor during ‘Control’ conditions due to the neutral odorants’ relatively weaker or less unpleasant percept [2(1) = –0.146, P < 0.70, b = –0.019, SE = 0.05).Investigation of the corrugator supercilii region revealed a significant effect of exposure but this time larger EMG amplitudes occurred after exposure to neutral odors  = 2.17, P = 0.03) and from pre to post30  = 5.77, P < 0.001; see b = –0.01, SE = 0.13, t = –0.05, P = 0.96). Moreover, we found a significant interaction between Time and Odor condition from pre to post  = 2.86, P = 0.005) showing a stronger rise in TNFα levels after disgust as compared to neutral odor exposure at post but not at post30  = 0.12, P = 0.90). Corresponding analysis of sIgA showed significant increase of sIgA only at time point post30  = 6.30, P < 0.001) but with no effect of Odor condition or interaction between Time*Odor condition . The results found were robust to the inclusion of the confounding variables  and none of the confounding variables significantly influenced the outcome variables .The LMM for TNFα showed significant main effects of Time from pre to post  = 2.55, P = 0.02; disgust: b = 0.43, SE = 0.09, t = 4.96, P < 0.0001) and pre to post30  = 3.091, P = 0.004; disgust: b = 0.41, SE = 0.10, t = 4.21, P < 0.001). IgA levels significantly increased within both conditions from pre to post30  = 3.005, P = 0.005; disgust: b = 0.08, SE = 0.03, t = 2.91, P = 0.006) but not from pre to post  = 1.32, P = 0.20; disgust: b = 0.06, SE = 0.03, t = 1.78, P = 0.08).The LMM exploring how Time affects levels of the immunological markers within each condition revealed that TNFα levels significantly increased from pre to post  and pathogen elimination via the immune system.Our finding that salivary TNFα levels increase upon olfactory evoked disgust corresponds well with the consistent findings reported , 5, 31 sBehavioral conditioning of immune functions can potentially explain how oral immune markers are produced upon smelling of disgusting odors : A substThe effect of disgust stimuli on sIgA seems more complex than previously thought. Whereas , 5 foundMoreover, visually and olfactory evoked disgust may have differing effects on the salivary immune response because odors, but not pictures, directly activate the salivary reflex  which ret-test comparing the difference pre to post of TNFα levels between the two conditions  is d = 0.52 (cohen’s d function of the effect size package in R), thus higher than the minimal theoretical effect size (d = 0.48) we would be able to detect for a similar test with our achieved sample size (n = 36) at 80% power.Although our sample size is higher than several previous published studies that found a significant increase of immuno-markers after exposure of disease-related stimuli, our achieved sample size is relatively modest. Based on , a powern = 21) blood samples were taken for analysis of a systemic effect of olfactory evoked disgust on level of IL-6 and blood TNFα that showed no variation with odor exposure. Future studies should investigate whether disgust stimuli drive systemic and local immune responses differently depending on the sense modality used for triggering the experience of disgust.As noted, for a subset of participants , which made it necessary to use individually matched disgust odors. We believe this led to a distinct manipulation of olfactory disgust between odor conditions. Difficulties in evoking olfactory disgust have been reported by others, resulting in the need to provide additional cues together with disgust odors in order to enhance ratings of olfactory evoked disgust [We found large inter-individual variability in stimulus disgust  and state disgust ratings (disgust induction in odor exposure session disgust  disgust . These f disgust , 43. WitWe used EMG as an objective measure of olfactory evoked disgust and found an overall increased activation in the levator labii region during disgust as compared to control odor exposure. This finding, in parallel to subjective disgust ratings, further confirmed that our experimental design successfully manipulated odor-evoked disgust. This observation is well in line with other studies that often choose the levator labii region as the only EMG indicator of distaste and disgust . In our It is important to note that disgust odor exposure did not significantly alter the level of perceived stress in our volunteers. Stress, being a well-established behavioral effector on the immune system , is therWe show that individually tailored odors can be potent stimuli to evoke state disgust in healthy volunteers. Interestingly, disgusting smells induced increased levels of the pro-inflammatory cytokine TNFα. These results are a first demonstration of chemosensory pathogen avoidance, in the form of disgust, being linked to immunological pathogen elimination. Altogether the results indicate that human olfaction, akin to animal studies, may have an active part in the defense against disease; not only as a keen detector of early sickness cues but also in launching a preparatory immune response in response to disgusting stimuli.eoac042_suppl_Supplementary_Figure_S1Click here for additional data file.


Furthermore, higher antioxidant activity in ‘Herskawitz’ blanched peel extracts using 2,2-diphenyl-1-picryl hydrazyl (DPPH) antioxidant activity, ferric ion reducing antioxidant power (FRAP), and 2,2-azino-bis(3-ethylbenzothiazoline-6-sulphonic acid (ABTS) radical scavenging activity at 567.78 ± 9.47 µmol Trolox/g DM, 800.05 ± 1.60 µmol Trolox/g DM, and 915.27 ± 0.61 µmol Trolox/g DM, respectively, was noted. ‘Herskawitz’ blanched peel extracts were recorded with the lowest minimum inhibitory concentration (MIC) value of 80 µg/mL for Gram-positive Bacillus subtilis and Gram-negative Klebsiella pneumoniae bacteria strains. A total of 30 metabolites were present in ‘Acco’ and ‘Herskawitz’ peel extracts and were tentatively identified after LC-MS profiling. This study demonstrates that blanched peel extracts from ‘Herskawitz’ cultivar have great potential for commercial use in value-added products in the nutraceutical, cosmeceutical, and pharmacological industries.Hot water blanching at 80 °C for 3 min can be used as a novel pre-treatment step in pomegranate peel to preserve the integrity of the phytochemical content within the peel extracts by lowering or inactivating enzymes such as polyphenol (PPO) oxidase and peroxidase (POD) that are responsible for the break-down of phytochemicals within the peel. The aim of this study was to investigate the effect of hot water blanching pre-treatment on yield, bioactive compounds, antioxidants, enzyme inactivation, and antibacterial activity of ‘Wonderful’, ‘Acco’, and ‘Herskawitz’ pomegranate peel extracts. We used a variety of spectrophotometric-based assays and liquid chromatography mass spectrometry (LC-MS)-based approach to characterize and quantify metabolites within the peel extracts. Blanching significantly ( Punica granatum L.; Lythraceae) is a fruit-bearing deciduous tree or evergreen shrub extensively grown in many parts of the world, including South Africa -s-triazine (TPTZ) solution (10 mM TPTZ in 40 mM HCl), and 2.5 mL of FeCl3) solution (20 mM FeCl3·6H2O in water). The mixture was vortexed for 30 s and later incubated in the dark at room temperature for 30 min. The absorbance was taken at 593 nm using a UV-vis spectrophotometer . Each sample was tested in triplicate, with the results expressed as µmol Trolox/g DM. The ABTS radical cation (ABTS+) stock solution was prepared according to Chirinos et al. [v/v) methanol. A 15 µL peel extract was added to 200 µL of the ABTS+ working solution, followed by incubation in the dark for 6 min. The absorbance was recorded at 750 nm using a microplate reader . The results were expressed as µmol Trolox/g DM. Measurement of the antioxidant activity of different peel extracts was performed in triplicate.The method described by Karioti et al. , with sls et al. , with mis et al. . Brieflyg rpm for 25 min at 4 °C, before the supernatant was carefully collected into clean vials and used as crude enzyme extract.Preparation of samples for polyphenol oxidase and peroxidase enzyme extraction were determined according to the method of Magangana et al. . BrieflyThe activity of PPO enzymes was measured using a method by Gonzalez et al. , with miPeroxidase enzyme activity was carried out using a spectrophotometric method employing a UV-vis spectrophotometer  at 470 nm absorbance. In this study, guaiacol and hydrogen peroxide were used as substrates as described by Meighani et al. , with miAnalyses were carried out on a Waters Synapt G2 quadrupole time-of-flight mass spectrometer  according to the method by Magangana et al. . BrieflyCompound detection and confirmation were performed as previously discussed by Magangana et al. . This inEscherichia coli ATCC 11775 and Klebsiella pneumoniae ATCC 13883, and two Gram-positive bacteria, Bacillus subtilis ATCC 6051 and Staphylococcus aureus ATCC 12600. Streptomycin  was used as a positive control and bacteria-free broth, 70% (v/v) ethanol, and sterile distilled water were used as negative controls. The final concentration of peel extracts ranged from 19.53 to 2500 µg/mL, while streptomycin concentrations ranged from 0.20 to 25 µg/mL in the respective wells. The plates were left for 18 h at 37 °C for incubation purposes. After this period, 40 µL of p-iodonitrotetrazolium chloride  was added to the well plates to show bacterial growth. The results were expressed in terms of the MIC value, with this test performed in triplicate.Determination of MIC was performed according to a method described by Eloff , with sop ≤ 0.05). All statistical analyses were conducted at the 95% confidence level.All data for phytochemical, antioxidant, and quantitative measurements of the biomarker phenolics were subjected to normality testing, preceding analysis of variance (ANOVA). Data that had a normal distribution were then subjected to a post-hoc analysis according to Duncan’s multiple range test to separate the means. Kruskal–Wallis analysis was used to separate the means as a post-hoc test for data that were not normally distributed. SAS Software  was used to calculate the statistical significance, with the results of all of the studied variables presented as mean ± S.E . Pearson’s correlation matrix was constructed using GraphPad Prism software 4.03  to visualize relationships between phytochemical colourimetric analyses, antioxidant enzyme, and antibacterial assays plus biomarker phenolic metabolites in the data matrix.For metabolomic analysis, the data were normalized using the sample median and transformed by log normalization, while data scaling was performed using the Pareto scaling algorithm prior to multivariate statistical analyses. A heat map, two-dimensional (2D) principal component analysis (PCA) score plot, variable importance in projection (VIP) plot, and orthogonal partial least squares discriminant analysis (OPLS-DA) were generated. In addition, a PCA biplot showing phenolic compound distribution and concentrations between the cultivars, namely ‘Wonderful’, ‘Acco’, and ‘Herskawitz’ pomegranate peel extracts, was also generated. All of the above plots were constructed using MetaboAnalyst 5.0 , phenolic acids (ellagic acid), and flavonoids  to blanch ‘Herskawitz’ peel extracts. While blanching of ‘Acco’ and ‘Wonderful’ pomegranate peel extracts may also increase the recovery of these key metabolites, they cannot be compared to the superior phytochemical profile obtained in blanched ‘Herskawitz’ peel extracts. This could result from inter-genetic cultivar variability, which may also be responsible for the thermal response of the cultivar during blanching. We recommend utilizing hot water blanching at 80 °C for 3 min as a pre-treatment step before processing the pomegranate peel. This study successfully preserved and recovered key metabolites from the peel extracts of three cultivars, namely ‘Acco’, ‘Herskawitz’, and ‘Wonderful’, by using hot water blanching at 80 °C for 3 min. We also recommend the application of ultrasonic extraction to those in the processing industry for faster results. Interestingly, although blanched ‘Wonderful’ peel extracts were reported with the highest extract yield, blanched ‘Herskawitz’ peel extracts were reported with the highest phytochemical and biological activity. Insights into the biochemical and genetic pathways using proteomic- and transcriptomic-based studies could provide an explanation. In addition, future studies should focus on the isolation of active compounds recovered in blanched ‘Herskawitz’ peel extracts and investigate more pharmacological activities (both in vitro and in vivo). We also recommend optimizing blanching temperature and time for ‘Herskawitz’ peel extracts using response surface methodology (RSM) and determining toxicity effects in the blanched peel extracts. In addition, a study of genetic variability between or within cultivars could provide significant information as to its potential for breeding purposes and novel drug discoveries.


Additionally, process-related tests were carried out using lab (N2 emissions), pot and lysimeter experiments (nitrate leaching). In total, 2.5 million records have been stored in a Microsoft Access database (StaPlaRes-DB-Thuenen). The database is freely available for (re)use by others  on the publication server and data repository OpenAgrar for meta-analyses, process modelling and other environmental studies.The purpose of the StaPlaRes project was to evaluate two innovative techniques of urea fertiliser application and to quantify greenhouse gas (GHG) emissions. All GHG emissions, as well as other gaseous emissions, agronomic and environmental variables were collected for three years (2016/2017–2018/2019) at three experimental field sites in Germany. All management activities were consistently documented. Multi-variable data sets of gas fluxes (N  The global urea market demand reached a volume of nearly 187.8 million metric tons in 2020. From 2021 to 2026 the demand is expected to grow by 2% annually2. A large percentage of urea-N used for food production is lost to the environment in many different forms, including NH3, N2O and N2 emissions7. Nitrous oxide contributes to both, the greenhouse effect8 and stratospheric ozone depletion10. More than half of the entire anthropogenic N2O emission originates from agricultural soils11. Ammonia (NH3) emission from agricultural sources significantly contributes to air pollution, soil acidification, water eutrophication, biodiversity loss, and declining human health12. There are numerous options for reducing NH3 emission from urea-fertilised agricultural systems. Inhibitors, for example, are a promising tool for N2O and NH3 mitigation. However, the effectiveness is highly variable and some measures depend widely on site-specific conditions such as weather, soil properties and management practices13. Moreover, there can be trade-offs such as simultaneous NH3 reduction and N2O increase.Worldwide use of urea has increased more than 100-fold in the past four decades and now constitutes more than 50% of global nitrogenous fertiliser usage3 and N2O measurements, yield analyses, and soil sampling, a three-part experimental setup (see detailed explanation in Methods) was designed at three experimental field sites in Germany.In order to combine NH14.During the project period (autumn 2016 to autumn 2019) the weather was exceptionally warm and dry. The average annual temperature was 3 K higher compared to the long-term annual temperature at all experimental sites. A high deficit in annual precipitation occurred also at all sites, which was mainly caused by the lack of precipitation in spring. The second and third investigation years were significantly drier than the first one 16 at the sites (EF 0.67–0.77%) and significantly lower than the default value of 1.0% according to the IPCC Refinement17. The trial-specific EFs fall within the lower uncertainty range of the aggregate N2ON- EF according to IPCC Refinement, which is reported to be 0.1–1.8%.Overall, the site-specific emission factors (EFs) for N3-N emission factor average over the three trial years and the three crops for the benchmark treatment “surface” is highest in Cunnersdorf (0.032 kg NH3-N kg N−1) and lowest in Roggenstein (0.012 kg NH3-N kg N−1). Overall, the specific measured NH3-N emission factors at all experimental sites during the project period from 2016 to 2019 are significantly below the default values for urea according to EMEP/EEA18 or Rösemann, et al.19 .The NH20 (10.3220/DATA20220119144442). A virtual final event was organised, where project results were presented. The final report21, posters and presentations of the event are available at the website22. Some project results have already been published25.We introduce multi-variable datasets of GHG emissions as well as other gaseous emissions and agronomic variables. All variables were collected for three years (2016/2017–2018/2019) at three experimental field sites in Germany. In total 2.5 million records have been stored and archived in the database StaPlaRes-DB-Thuenen to quantify and to evaluate GHG for winter oilseed rape, winter wheat and winter barley. The database is publicly available at the OpenAgrar repositoryThe StaPlaRes project consists of three sites spread across Germany. The main soil characteristics of each field site are shown in Table Avena sativa L.) was cultivated as the preceding crop to achieve comparable conditions. The experiment at each field site was designed as a uniform field trial with an identical crop sequence consisting of winter oilseed rape  – winter wheat  – winter barley . The experiment was divided in three plot experiments: plot experiment I (short: PVI), large plot experiment (short: GPV) and plot experiment II (short: PVII)  with an area of 9 m × 9 m each for every treatment . Each plot contained three separate areas (3 m × 9 m) for (a) yield evaluation, (b) gas measurements, and (c) other samplings. In accordance with the requirements of the NHThe whole experiment was set up as a randomized design with four replicated plots and four treatments (T): (T1) Control - No N fertilization, (T2) Stabilised – double stabilised urea fertilization, (T3) Incorporated – subsurface placement, and (T4) Surface – granular urea surface application without UI + NI, without. All activities on the fields were conducted according to best agricultural management practices.All management activities at each field plot were documented from late summer 2016 until late summer 2019. Mandatory data on management events were emergence, sowing, harvest with crop name, soil tillage with soil depth and type, applications of mineral and/or organic fertilization  as well as crop protection. Each activity and the associated device were described. Additionally, dates of crop development, damages as well as nutrition supply and previous crop were reported.27 was used as urease inhibitor (UI) in the experiment, and the nitrification inhibitor (NI) was N-[3(5)-methyl-1H-pyrazol-1-yl) methyl] acetamide (MPA)28. (T3) subsurface placement is a special side dressing technology incorporating granular urea (PIAGRAN® 46) in combination with mechanic weed control (short: incorporated). This innovative technology was developed within the StaPlaRes project. (T4) granular urea surface application (PIAGRAN® 46) without incorporation (short: surface).The amount of fertiliser applied was determined by the site-specific N requirement for each crop following the fertilisation recommendation of the associated Federal State ; relevant details are summarized in Table For cereals, the first fertiliser application took place at the same time in all fertilised treatments. The number of split applications was reduced from three to two in winter wheat and from two to one in winter oilseed rape and winter barley for (T2) Stabilised. The stabilised one-time fertilisation for OSR was applied approx. two to three weeks earlier. The scheduling of the application of stabilised urea was studied with two fertiliser treatments: (a) granular stabilised urea (ALZON® neo-N – combined use of urease and nitrification inhibitors (short: stabilised) also as surface application without incorporation, (b) granular stabilised urea using ALZON® neo-N as a very early initial application (before the beginning of vegetation) and a flexible timing of the second dressing (shoot). An additional experiment was conducted in Cunnersdorf and Roggenstein for winter wheat and winter barley to optimise the timing of N-stabilised fertilisation (T2).All meteorological parameters were measured in 60-minute resolution by different weather stations at each experimental site  and straw (for winter wheat and winter barley) were harvested on each field plot. All crop materials were weighed. Subsequently, quality parameters such as the nitrogen or crude protein content as well as dry matter content of all grain samples were determined. For winter oilseed rape, the oil content was also analysed. Furthermore, crop development parameters like BBCH, grains per ear, plants per m², etc. have been recorded. All crop parameters  were determined by methods as specified in Table 4-N and NO3-N before the beginning of vegetation and after the harvest at 0–30 cm and 30–60 cm soil depth. After the first fertiliser application, mineral nitrogen in the soils was measured weekly and simultaneously with the gas flux measurements. Thus, with each gas flux measurement campaign, soil ammonium-N and soil nitrate-N content are related. All soil samples were stored at −20 °C until lab analysis (see Table The topsoil (0–30 cm) was analysed at the beginning of the experiment. For each site, soil moisture data were collected hourly beside the field plots on a grass covered plot using SENTEK sensors based on the FDR methodology. The soil moisture was also directly measured during the Large plot experiment (GPV) in Cunnersdorf. Additionally, every month, soil samples were determined gravimetrically to calibrate the sensors. Soil samples were taken to determine NHet al.29. Several pot experiments with oat, silage maize, spring barley, spring wheat and summer oilseed rape using Mitscherlich containers were installed to analyse the nitrate leaching potential and/or ammonia volatilization potential. Lysimeter experiments served to quantify the amount of nitrate leaching for two fertiliser treatments (T2 and T3).In addition to the field experiments, process-related investigations were conducted. Under standardized laboratory conditions (20 °C) without plants, soil tests were applied to investigate effects of urea with or without inhibitors on the nitrogen turnover dynamic and urease activity. Furthermore, ammonia volatilization potential (AVP) was also tested under different temperature regimes (5 °C and 20 °C). All methodological details about AVP have been described by Ohnemus, 32) was installed at all three sites to measure N2O, CO2 and CH4 during the crop cultivation period of winter oilseed rape, winter wheat and winter barley only for the “Large plot experiment”  and the GHG flux calculation  and Passive Samplers36. The basic idea of this approach is to combine a simple qualitative measurement method on many field plots with a quantitative method with parallel measurements on a few plots. I.e. passive samplers37 filled with diluted sulphuric acid continuously absorb ammonia. DTM40 was applied in short measurement periods throughout the day. All details about the experimental design, operational instructions, preparations and flux calculation have been described with video instructions and material list by Pacholski36.Emissions of NH2 and N2O flux in a fully automated system with the N2-free helium-oxygen incubation method. Previous N2 studies by Fiedler, et al.41, Butterbach-Bahl, et al.42, Buchen-Tschiskale, et al.43. outlined the principle of the investigation. The described procedure has been applied here for the first time.For each field site, soil samples were taken to conduct experiments under different boundary conditions , at the peak of the N2O release (t1), at the peak of the N2 release (t2) and at the end of the gas flux measurement.This method includes three soil cores with a volume of 250 cm³ for the incubation and nine soil cores with a volume of 100 cm³ for N2 concentration was measured for two to three days. When consistently low N2 values were reached, the helium-oxygen mixture was replaced by a more complex N2-free gas mixture (He/O2/trace gases). After that the temperature in the system was increased to 20 °C. The measurements of N2 and N2O were carried out up to two weeks until concentrations had levelled off again, i.e. the measured concentrations were similar to the level of the He/O2/trace gas mixture used for incubation. A detailed description of the preparation and incubation is stored with StaPlaRes-DB-Thuenen.Dry soil and water were mixed to obtain a water filled pore space (WFPS) of 70% (TR1) and 90% (TR2) for experiment 1 and 2. For 2 days, the soil cores (250 cm³) were left at 20 °C. Subsequently, the soil cores and fertiliser solution were cooled down to 1 °C and then the fertiliser solution (TR3 and TR4) was injected with five punctures (250 cm³) and four punctures (100 cm³) by a hole template. Soil samples were placed in a helium incubation system and incubated at 1 °C. The normal air was removed from the system and replaced by a helium-oxygen mixture three times. The change in Net al.44.Soil moisture and seepage of each experimental site was modelled using the agricultural meteorological hydrologic budget model METVER. Meteorological and soil physical data as well as data on the crop phenological development is required for METVER. The meteorological data include daily mean air temperature, daily sunshine duration and daily precipitation. Further information about METVER is published by Böttcher, 20 (10.3220/DATA20220119144442). OA is the collective open access repository of research institutions affiliated with the Federal Ministry of Food and Agriculture (BMEL) in Germany. The open access repository publishes, stores, archives and distributes publications, publication references and research data. Its resources can be searched and used by everyone. It contains theses, reports, conference proceedings, journal articles, books, institutional documents, research datasets, videos and interviews. The repository is registered in re3data.org to improve data finding.All data are stored in the relational database StaPlaRes-DB-Thuenen and are available on the publication server and data repository OpenAgrar (OA)StaPlaRes-DB-Thuenen has been designed with Microsoft Access 2019. The database provides stored and archived data  spread over 38 separate tables . The table “5_Plot” represents the organizing principle of the database and contains a Plot_ID (the primary key) describing the unique positioning or affiliation of each measured value and the associated information of the database. For each “Measurements” table in the StaPlaRes-DB-Thuenen there is a 1:n relation to the table “5_Plot”. This means that the tables are linked by the foreign key Plot_ID (with the exception of the tables “R_Conc_incubation” and “P_Flux_incubation”). These measurements-tables and the metadata-tables “M_Site_info”, “M_Straw_info”, “M_BelowLOQ_info”, “M_Yield_info”, “M_P_and_K_info”, “M_Soilprofile_info” and “D_Soil_profile” (Driving forces) are linked to the table “1_Site” via the Site_ID as a foreign key.A dataset in the table “D_Management” describes what event or what activity (Management_Name) was performed on a specific plot for a particular crop, at a given time (as date) with a certain intensity (Intensity), the used device and the amount of N in case of nitrogen fertilisation. The columns Intensity and N_amount are complemented by a unit as index.“D_Soil_profile” describes the composition of the soil profile at each site (location) consisting of horizons  and relevant parameters . All meteorological parameters, displayed in Table 5, are stored in the table “D_Meteo”.All “measurements” tables are structured with the following eight columns. If necessary each table can be complemented by more columns.Column names are sometimes underlined at the end because they differ from the reserved words in the Access database and to avoid problems/error messages. Reserved words are words and symbols with a special meaning for Microsoft Access. The metadata tables “M_Variables”, “M_Units” and “M_Methods” are always linked to each “measurements” table. Please note that not all measurements are available across all field sites.The tables “R_Plant” and “R_Soil_periodic” contain all event-related plant and soil field samples. “R_Soil_periodic” is additionally equipped with “soil depth from” and “soil depth to” as well as with three Boolean columns (switching variable). “Aggregated” column indicates whether a measured value was aggregated based on several values or not. Whether a measured value was adopted from another plot or not will be shown by “Inherited” as a second Boolean column . A further Boolean column “Below_LOQ” in this table indicates whether a measured value is below the limit of quantification (LOQ) or not. “R_Soil_continuous” stores all soil sensor values which were measured in an hourly interval. In addition to field samples, laboratory samples for soil tests and pot experiments were conducted. For a clear differentiation of the different “scale” of measurements, all lab or pot measured values are stored in the table “R_soil_lab_pot” and “R_Plant_pot”.2O, CH4 and CO2 are stored in the table “P_N2O_flux”. “P_N2O_flux_daily” provides interpolated and aggregated daily N2O fluxes. “P_NH3_flux” table contains NH3 fluxes.The database contains raw data of gas flux measurements (table “R_Conc”) and processed data (“P_N2O_flux” and “P_NH3_flux”). Table “R_conc” lists the specific concentration of the gases measured by gas chromatography and used for the calculation of the respective gas fluxes. table is supplemented by the columns “time step”, “chamber area”, “chamber volume” and “vial number”. The gas fluxes of N2, N2O, CO2 and CH4 were quantified using the described incubation method. The experimental results are displayed in the table “R_Conc_incubation” and “P_Flux_incubation”. Modelled values of soil moisture and seepage are stored in the database table “P_Modelled_SM_SP”.In additional laboratory experiments concentrations and fluxes of Nsites - All field sites are described with general information about the site, such as coordinates, altitude above NN, slope, climate type (USDA Plant Hardiness Zones), mean annual temperature, etc.experiments – Field experiments are described by general information about the experiment, such as soil type, soil texture, plot size, etc.crop yield – Residual moisture content of the grain yield for the investigated crops.straw yield – the handling of straw after the harvest (whether the straw was incorporated or removed from the field).fertiliser application – Due to weather conditions, it was not always possible to apply the urea with subsurface placement. Plot by plot it is described on which fertilisation date the fertilisation was “incorporated” or defined as “surface” fertiliser application. If the table does not contain an entry there was no deviation in fertiliser application from the treatment.phosphor & potassium fertilization – the handling of phosphor and potassium fertiliser application at each field site .limits of quantification – for different measured variables (e.g. NH4-N) limits of quantification (LOQ) are documented.All variables, units and methods used in the StaPlaRes-DB-Thuenen are listed in the metadata tables “M_Variables”, “M_Units” and “M_Methods”. “M_Variables_info” displays all variables used. The information about variables contains a brief description and is supplemented by value plausibility and reference to time and space. The data type of each variable is also defined . The table “M_Information” defines descriptive information on all columns of the StaPlaRes-DB-Thuenen, except for the column “Variable_“. All table names include “info” at the end. Further metadata tables provide additional information; which is described below.Data have been collected by tailored data templates which have been compiled in an iterative manner. By pre-defining experiment names, treatment names, measurement variables, units and methods in the data templates, it was possible to reduce errors. In addition, a two-level data quality control was elaborated. The flow chart in Fig. A document was provided with detailed explanations on the procedure for data delivery and data quality control. Moreover, we plotted each variable to identify and correct errors in data entry, as well as to identify and remove potential erroneous measurements.2O have been conducted at all laboratory.Multiple steps were taken to ensure the technical quality of the dataset. Most importantly, consistent field and laboratory protocols were employed. For example, ring tests for gas chromatograph analysis of N2 and N2 concentration values, deviations between the measured and expected concentration values for internal gas standards.The results from helium incubations were specifically checked for the following measurement errors: erratic, synchronous changes in all gas concentrations, measurement gaps, negative COCrop yield data were compared to yield from other experiments conducted at the same location or to yield data from national variety trails. A one-way ANOVA was conducted to compare the mean crop yield of each treatment. A Tukey’s post-hoc test was performed for a pairwise comparison of the treatments with a statistical difference at p < 0.05.Due to irregularities in the hourly precipitation data from the measurement technology at the CUN and BER sites, daily precipitation data from parallel existing weather stations were supplemented (see Table 20 (10.3220/DATA20220119144442).The data described are stored in the database StaPlaRes-DB-Thuenen and will be freely available for (re)use by others at the publication server and data repository OpenAgrarDatabase protection and data reproducibility was guaranteed by dividing the StaPlaRes-DB-Thuenen into a frontend database (FE) and a backend database (BE). The frontend (labelled with “fe” in the database name) represents the application database. The backend (labelled with “be” in the database name) embodies the base of the data in the background and is not intended for application. StaPlaRes-DB-Thuenen has been developed in Microsoft Access 2019 and tested for program version 2016, 2019 and 365. The download of the database contains detailed instructions, which describe how to open and use the StaPlaRes-DB-Thuenen.