Allergic rhinitis (AR) is increasingly becoming a patient self-managed disease. Just under 70% of patients purchasing pharmacotherapy self-select their treatment with no health-care professional intervention often resulting in poor choices, leading to suboptimal management and increased burden of AR on the individual and the community. However, no decision is made without external, influencing forces. This study aims to determine the key influences driving patients’ decision-making around AR management. To accomplish this aim, we utilised a social network theory framework to map the patient’s AR network and identify the strength of the influences within this network. Adults who reported having AR were interviewed and completed an AR network map and AR severity and quality of life questionnaires. Forty one people with AR completed the study. The AR networks of the participants had a range of 1–11 influences , with an average number of 4 and a median of 5. The larger the impact of AR on their quality of life, the greater the number of alters within their network. The three most commonly identified alters were, general practitioners, pharmacists and the participants’ ‘own experience’. The strength of the influence of health-care professionals (HCPs) was varied. The proportion of HCPs within the AR network increased as the impact of AR on their quality of life increased. By mapping the AR network, this study demonstrated that there are multiple influences behind patient’s decisions regarding AR management but the role of the HCP cannot be dismissed. In-depth interviews with allergy sufferers about their treatment decisions highlights a need for healthcare professionals to help optimize allergy management. Allergic rhinitis (AR), a set of conditions including hayfever, is often poorly managed by patients, partly due to the growing availability of over-the-counter medications. However, little is known about what influences patients’ self-management decisions. Biljana Cvetkovski at the University of Sydney, Australia, and co-workers interviewed 41 adults with AR. The participants also completed quality of life questionnaires and created network maps of key influencers. Cvetkovski found that patients followed many different influences when making treatment decisions, including online resources, family, friends and healthcare professionals. Three of the key influencers were general practitioners, pharmacists and patients’ own experience. Those with severe AR had a larger, more diverse network of influences and often reported treatment fatigue. Recent Australian research has demonstrated that just under 70% of pharmacy customers purchased a treatment for AR symptoms by self-selecting their treatment without consulting a HCP, only 15% selecting optimal treatment for their symptoms.15There are several factors that contribute to AR being a challenging condition to manage including, miscommunication between health-care professionals (HCPs) and patients about concept of AR control, the co-existence of non-AR and the suboptimal use of medicines leading to inadequate symptom relief.16 but has so far not identified who or what are the key influencers of these decisions, what the relative level of influence is nor whether these influences change depending on the level to which AR impacts on patients’ day-to-day living. By identifying the key influences within patients’ AR networks, we can better understand both the challenges and opportunities for patients, health-care providers and the health-care system to improve AR management.While it is accepted that a majority of people with AR self-manage their condition, little is understood about who or what influences people with AR in their management decisions. Exploring AR management from the perspective of the patient has revealed that patients feel confident in making their own decisions with regards to their AR treatment17 This approach has been used to identify key influences within the networks of people who have asthma and has given us fresh insight into the role that HCPs and family members have on asthma management.18 Utilising a social network approach with people with AR can help us understand who and what influences patient decisions with regards to AR management.Social network theory can help us to identify a patient’s health network and the influences within it.Therefore, the overall aim of this study was to determine the influences driving patients’ decision-making around AR management, to determine their relative degree of influence and to gain an understanding of whether networks vary depending on the impact of AR on patients’ day-to-day living ).Fifty seven potential participants contacted the research team and expressed an interest in participating in this research. Forty seven of these potential participants were eligible to participate and provided signed consent; 87% (41/47) completed the study and were included for further analysis . Data saturation was achieved following the 20th participant, as no new alters were nominated with the name generation technique by the remaining participants. All eligible volunteers who responded to the initial round of recruitment were enrolled and participated. Once it was established that saturation had been obtained, no further recruitment was deemed necessary. The study population were aged between 18 and 86 years with a median age of 38 years. Sixty seven percent were female. Thirty four participants were from metropolitan Sydney and 7 were from regional areas of New South Wales. Data were collected from March 2014 to December 2014.AR severity is summarised in Table ZERO (score 0), 20 (48.8%) in QOLMILD (score >0–2), 12 (29.3%) in QOLMOD (score 3–4), and 8 (19.5%) in QOLSEV (score 5–6).The average score for the mini-RQLQ questionnaire was 2.6 (range 0–5). The number of participants in each category of AR QOL impairment was: 1 (2.4%) in QOLThe participants nominated GPs; pharmacists; allergists/immunologists; respiratory specialists; ear, nose and throat specialists; practice nurses; alternative therapists; parents; partners; siblings; friends/colleagues; media; internet; their own experience; dermatologists; neurologists; optometrists and opthalmologists as individuals or resources who/that have an influence on their AR management decision-making. Dermatologists, neurologists, optometrists and opthalmologists appear on the map under the category ‘other HCPs’. Parents and partners were combined as one category and siblings are represented in the category ‘family’.TOTAL and bar chart is presented in Fig. n = 41). The number of alters nominated by participants ranged from 1 to 11, with an average number of 4 and a mode of 5. The three most commonly nominated alters within the AR Network MapTOTAL were GPs, pharmacists and participants’ own experience.The AR Network MapGPs, pharmacist and ‘own experience’ constituted >50% of the alters in Circle One, being placed in Circle One by 15 (37%), 9 (22%), and 12 (30%) of participants, respectively. While GPs and pharmacists also featured prominently beyond Circle One, ‘own experience’ was almost entirely (except in one case) plotted within Circle One.ZERO) are displayed in Fig. One participant reported that AR had no impact on their QOL. The AR network map and AR network bar chart for the participants who experienced zero AR impairment on their QOL (AR NetworkMILD) are displayed in Fig. Twenty participants reported AR causing mild impairment on their QOL. The AR network map and AR network bar graph for the participants who experience mild impairment due to AR on QOL (AR NetworkMOD) are displayed in Fig. Twelve participants reported AR causing moderate impairment on their QOL. The AR network map and AR network bar graph for participants experiencing moderate impairment due to AR on QOL (AR NetworkSEV) are displayed in Fig. Eight participants reported AR causing severe impact on their QOL. The AR Network map and AR Network bar graph for participants experiencing severe impairment due to AR on QOL (AR NetworkTOTAL) and for the AR networks per QOL category .Figure This research identifies that people with AR report a wide range of influences when it comes to the management of their AR. These influences include HCPs, family and friends and information from the internet and media. When these influences are visually represented in an egocentric network map, it is evident that GPs, pharmacists and the patient’s own experience are consistently regarded as key influences on AR management. It was found that, as the impact of AR on QOL increases, the size of the patient’s AR network also increases. These findings uncover a complex network of influence for people with AR, which needs to be considered in light of the high level of self-management exemplified by this cohort of patients.18 This method enabled us focus on the patient's perspective and to specifically articulate the relative importance placed on the many and varied ‘influences’, as experienced by the patient. However, it should be acknowledged that this method represents a one-dimensional description of the patient’s AR network. To further enhance the interpretation of the data collected through the egocentric social network approach, network alter density calculations were applied. This added a deeper level of understanding to the relative importance of the different influences and adds novelty to this established method of patient-centred data collection.18In order to address the aims of this study, a methodology embedded with social network theory was utilised. The reasons for utilising a patient-centric social network approach was based on two key empirical findings: (a) there is a high level of self-management on the part of the patient and (b) this approach was successfully used to identify novel understanding of the influence on patient self-management in asthma.15 yet these results reveal that AR patients who experience severe impairment on their QOL identify many HCPs to be of influence within their network for AR management. The inclusion of HCPs whose specialties are not normally associated with AR management (e.g. neurologists) by this subgroup of patients suggests either the impact of AR extends beyond the respiratory system or patients feel that they are not receiving sufficient support from their primary HCP and are looking more broadly for assistance. These results clearly articulate that, in an era of treatment self-selection15 and patient empowerment,16 from the patient’s perspective HCPs remain relevant but not exclusive to the management of AR. The challenge for HCPs lies in harnessing this influence and ensuring optimal care is delivered, despite other influences, which in terms of clinical decision-making is yet unknown.This research unequivocally demonstrates that the size and the composition of the AR network changes as impact of AR on QOL increases. Participants experiencing severe impact of AR on QOL have the largest networks. We often associate uncontrolled AR with an absence of HCP involvement,19 that is, it is the subgroup of people with AR who have large health networks and who are likely to be consulting the GP. In thinking about how GPs can potentially amend their approach to AR management to assist the patients with the greatest burden of disease, we need to recognise the challenges they face in managing AR. A key challenge relates to the fact that diagnosis of AR can be complicated22 and many GPs have expressed great educational need with regards to allergy management.23 With a limited supply per capita of allergists/immunologists , the role of the GP in treating allergy has never been more important and upskilling our HCPs may be the solution to minimising AR-related impact on QOL in the community.24GPs appear in the AR network of the majority of patients. Following on from this, those with more severe disease consult their GPs and also have larger networks. This is an important finding in light of the fact that people with moderate-to-severe disease represent the majority of people consulting a GP,26 we need to consider pharmacists’ skills and the resources available to them.Another HCP identified as being influential in AR management is the pharmacist. With the pharmacist, there was a high variability in the level of influence, which was noted. While it can be argued that it is the patient’s choice as to how they ‘utilise’ the pharmacist in the management of their AR, it can also be argued that, given the current availability of medicines for AR in the pharmacy, they are the first port of call for AR management. Allergic Rhinitis and its Impact on Asthma (ARIA) guidelines include pharmacists in their integrated pathway as the starting point to treatment and management, but with so many medicines available over the counter,27; however, we are yet to understand the nature of their influence in AR. We need to ensure that patients with AR are themselves equipped with appropriate knowledge and understanding that their AR is more than a trivial condition. The need for patients to be better equipped in decision-making is highlighted in the high level of influence placed on patients’ ‘own experience’ in this study. Our previous findings demonstrate that a subset of people with AR believe they themselves know what works best to control their AR symptoms while experiencing treatment fatigue and disillusionment with HCP encounters.16 Patients need to be provided with tools to assist them and an example of such a tool is The Allergy Diary (ARIA).28 The Allergy Diary is a mobile health application that facilitates self-monitoring and collaboration with their HCPs. Further exploration of how the Allergy Diary could be implemented to address the challenges identified in this research should be undertaken in the future.The inclusion of non-HCPs in the AR network demonstrates that as HCPs we must be conscious that people who are not medically trained may be influencing the decision-making of people with AR. The role of non-HCP influences have previously been identified as important in the management of asthmaThis research leaves us with several unanswered questions. Following on from this research and the identification of patient influences, it is now essential we gain an understanding of the nature of the relationships between the patient and influences and how these relationships are impacting on patient AR decision-making and one another. In particular, we must investigate patient reports of ‘own experience’ as a key influence of their AR management and whether it is a summation of previous encounters with other alters or entirely based on experimentation with over-the-counter treatments. We must also investigate what factors determine perceived level of influence and how we can use this information to optimise AR clinical outcomes. Without further information about the nature of the perceived influences and the reasons behind them, we cannot make direct connections about the nature of these influences and impact of them on AR clinical outcomes.29 i.e. skewed towards mild disease, a greater distribution of AR severities could potentially strengthen our understanding. A further limitation is that AR was self-reported by participants but unconfirmed . While this is consistent with findings in the Australian population, some of which report that 60% of individuals self-diagnose their AR30, ways in which to overcome this limitation should be considered in future. Variation in patient responses to AR severity and impact on QOL questionnaires (>60% of participants reported moderate-to-severe disease severity yet reported even distribution in mild versus moderate–severe categories of QOL impairment) exemplified the challenges and controversies surrounding the use of these clinical tools in AR.31 Having only one patient in the no impact group subsequently limited our understanding of the AR networks of people experiencing no impairment on their QOL due to AR and a larger representation of participants in this subgroup is required in future research.This study was limited by the recruitment of participants solely from New South Wales, Australia. Even though the demographics of the study population are representative of the AR population,In conclusion, this research has delved into the world of the patient with AR and their AR network. The most striking new knowledge generated from this research is the finding that there is a disconnect between the impact of AR on patient day-to-day living and the number of influences on which patients with AR reply. In all of this, we need to understand why the influence of HCPs is not optimising AR control and why patients feel they need so many other influences on their AR management. Understanding the effectiveness of HCPs in AR management and better supporting them to be effective is one key challenge in the real-life management of AR that needs to be addressed as a priority.32 Specifically, this study used an egocentric social network framework; it focused on the network of an individual/‘ego’ (the participant) and the relationships/‘ties’ with individuals or resources/‘alters’.This study used a mixed methods approach based on the theoretical and analytical framework of social network theory as previously developed and utilised by Cheong et al.The target population was people aged ≥18 years who identified themselves as having AR and able to speak English.Advertisements were placed on the Woolcock Institute of Medical Research’s website and Facebook page. Letters were sent to individuals who were on the Woolcock volunteers’ database of patients (i.e. patients with AR who have previously either participated in research or expressed an interest in participating in research). Respondents who registered an interest were asked to contact the research team. Participation was voluntary. Written, informed consent was obtained from participants prior to commencement in the study.alters are identified among individual health network maps.In an egocentric social network analysis, recruitment continues until data saturation is reached, that is no new Determination of AR severity and impact on QOLName generator techniqueDrawing of the AR networkIn order to address the aim, the following methods were implemented during an appointment with a member of the research team:33AR severity and QOL was determined by participant completed questionnaires.34 was a structured interview where the participant was asked to identify alters  with whom they have discussed their AR within the past 5 years. A predetermined list of potential alters, generated from AR literature36 and exploratory inquiry, was used as secondary prompts in this process.The name generator techniqueDrawing the AR network: An adapted concentric circle framework was used as the basis for the generation of each AR network map.37 The participant was asked to visually depict their relationship with each of their alters with respect to their influence on their AR management by plotting them on a concentric circle diagram  who/that were most influential with regards to their AR management. Circle Four, the furthest away, represented the alter(s) who/that were of little influence on their AR management.It was explained to each participant that they are represented by the red spot in the middle of the concentric circles Fig. . FurtherBased on participant responses to the AR severity questionnaire, their AR severity was categorised into one of the respective five AR severity categories: no AR, mild intermittent, moderate to severe intermittent, mild persistent, and moderate to severe persistent.ZERO, score zero), mild impairment , moderate impairment , and severe impairment .Responses to the mini-RQLQ questionnaire were categorised into four groups: no impairment  based on position of alters across the concentric circles, with values assigned to each alter corresponding to the circle in which the alter was plotted. An AR network map collating all participants’ individual maps was drawn (AR Network MapTOTAL). Individual AR network maps for all participants were drawn, as were AR network maps for subgroups of participants, i.e. for participants in each of the four QOL categories . AR network bar graphs were drawn to quantitatively depict these AR network maps.The AR network maps were drawn using NetDraw.ties within a network relative to the total possible number of ties.17 In this egocentric network, network density principles were applied to represent the proportion (or relative influence) of alters within the network. In order to determine the network alter density, the strength of the tie was considered, which in an egocentric network is exemplified by the length of the tie, i.e. the placing of the alter on Circle 1, 2, 3 or 4. In an egocentric network, the strongest tie is that between the ‘ego’ and alters placed on Circle One; the weakest tie is that between the ‘ego’ and alters placed on Circle Four. Therefore, to capture the significance of the positioning of alters (and the strength of the ties), network density was calculated using the following formula:n1C1 relates to the number of participants who placed a particular alter in Circle One; n2C2 relates to the number of participants who placed a particular alter in Circle Two, n3C3 relates to the number of participants who placed a particular alter in Circle Three, and n4C4 relates to the number of participants who placed a particular alter in Circle Four.In social network theory, network density measures the proportion of alters for the participant population as a whole, i.e. the influence of particular individuals or resources for people with AR. The larger the value of density of the alter, the more the influence within the network.In this study, the network alter density enables the determination of the overall influence of TOTAL and the AR NetworkQOLzero, AR NetworkQOLmild, AR NetworkQOLmod and AR NetworkQOLsev subgroup maps and represented in a bar graph.AR network alter density was calculated for the AR Network Map40This study was approved by the University of Sydney Human Research Ethics Committee and was completed in accordance with STROBE guidelines for observational research.Supplementary Information


Elucidation of mechanisms underlying the increased androgen receptor (AR) activity and subsequent development of aggressive prostate cancer (PrCa) is pivotal in developing new therapies. Using a systems biology approach, we interrogated the AR-regulated proteome and identified PDZ binding kinase (PBK) as a novel AR-regulated protein that regulates full-length AR and AR variants (ARVs) activity in PrCa. PBK overexpression in aggressive PrCa is associated with early biochemical relapse and poor clinical outcome. In addition to its carboxy terminus ligand-binding domain, PBK directly interacts with the amino terminus transactivation domain of the AR to stabilise it thereby leading to increased AR protein expression observed in PrCa. Transcriptome sequencing revealed that PBK is a mediator of global AR signalling with key roles in regulating tumour invasion and metastasis. PBK inhibition decreased growth of PrCa cell lines and clinical specimen cultured ex vivo. We uncovered a novel interplay between AR and PBK that results in increased AR and ARVs expression that executes AR-mediated growth and progression of PrCa, with implications for the development of PBK inhibitors for the treatment of aggressive PrCa. Prostate cancer (PrCa) is a major cancer responsible for male fatalities worldwide . The groAR gene, gain-of-function mutations in the androgen signalling pathway [ADT is initially effective but resistance is common and this leads to the development of aggressive incurable disease known as castration-resistant prostate cancer (CRPC) . CRPC is pathway , and the pathway , 9. Nota pathway , 11.AR gene [In addition to direct changes to the AR, another mechanism underlying CRPC growth is increased activity and/or expression of AR co-activators –14. Yet AR gene , 18. DesIn order to understand how AR is stabilised and promotes PrCa growth, it is imperative to identify clinically relevant AR targets, both up- and downstream of AR signalling. Here, we generated androgen-regulated proteome data sets to comprehensively identify effectors of androgen signalling and identified PDZ binding kinase (PBK) as an AR-regulated factor in vitro and in vivo in PrCa that integrates AR signalling with PrCa growth. In men with PrCa, PBK is androgen-regulated and localised in the tumour cell nucleus. PBK overexpression is associated with poor disease outcome and clinical progression. We further uncover PBK interactome and identify a crucial reciprocal feedback between PBK and AR, whereby PBK interacts with both the NTD and LBD of AR to directly regulate the stability and function of both full-length AR and ARVs. Inhibition of PBK activity destabilises AR and decreases PrCa growth and metastasis. These results provide novel insights into the role of androgen-induced pathways in PrCa revealing PBK as a key effector through which AR manifest its oncogenic function in PrCa.r2 = 0.51). The protein levels of known androgen-upregulated targets were downregulated by both AR knockdown and bicalutamide treatment, whereas androgen-repressed proteins were upregulated by both AR treatments (n = 514)  Fig. .Fig. 1IdPBK gene  or those treated with androgen inhibitor degarelix (a LHRH agonist that blocks testicular androgen synthesis) for 7 days (n = 27)  , with 45% of degarelix-treated cases having no detectable expression of PBK in comparison to 15% of untreated cases. Overall, cytosolic PBK levels were lower compared to nuclear levels in all tissues tested, whereas there was no significant difference in cytosolic PBK levels between tumours or benign tissue or in response to degarelix treatment  Fig. . Nuclear01) Fig. . Degarel Figures , S1E.FigTaken together, these novel in vitro and in vivo data reveal that PBK is an AR-regulated factor whose expression is elevated in PrCa by androgen signalling. Given this knowledge and the amenability of kinases as potential drug targets, the role of PBK was further investigated in disease relevant models of PrCa.p = 0.0002, Grasso; [p = 4.3e-14, Taylor; [p = 6.3e-10, Varambally [p = 3.2e-05 and p = 0.05)   Fig. .n = 50) and metastatic PrCa (n = 50) tissues. Whereas PBK expression was low in benign tissue, metastatic tissue had significant higher PBK expression, which predominantly localised in the nucleus of tumour cells (p = 6.4e-08)  Fig.  consiste08) Fig. . No diffPBK is known to be an important regulator of cellular processes such as transcription and mitosis –26, but NTD) and the ligand-binding domain (ARLBD) of AR  experiments further validating the interaction between PBK and AR Fig. . To map  AR Fig. .p = 0.000; over 90% decreased PBK transcript abundance) or treated with PBKi (p = 8.24e-06)  and significantly greater compared with bicalutamide.Given their direct interaction, we tested the impact of PBK inhibition either by PBK knockdown using a pre-validated pool consisting of four different siRNAs targeting distinct regions on the PBK mRNA or its chemical inhibition using HI-TOPK32 compound (PBKi)  as a pro Figures A, S2B. P Figures . The extp < 0.05)  and PBKi (p < 0.01) decreased AR transcriptional activity   to test the global impact of PBK inhibition by either siPBK or PBKi. A significant overlap in the gene transcripts affected by PBK knockdown and PBKi was observed  for genes downregulated following PBK inhibition (hypergeometric ) Figure . Functiop < 0.01; Fig. Many classic AR-regulated genes showed altered expression following PBK inhibition , indicating delayed migration of cells in scratch–wound assays    as assessed by Ki67 staining. AR levels were reduced by bicalutamide and PBKi, in both cases to levels approximately threefold lower than the control treatment (p < 0.001)  Fig. D, S4E. T) Figure . Next, w01) Fig. . These eWe performed mass spectrometry of PrCa cells to identify AR-regulated proteome, with a view to identifying novel effectors downstream of this key oncogene that promote PrCa progression in response to androgen signalling. Among these, we uncovered PBK as a novel AR-regulated protein whose expression is directly regulated by androgens in vitro and in men with PrCa. Interestingly, PBK expression was predominantly nuclear in PrCa and identified aggressive disease subtype suggesting its potential as a prognostic biomarker for cancer progression. Mechanistically PBK forms a feed-forward AR-PBK signalling loop whereby PBK binding to the NTD and LBD of the AR promotes its stability and activity. As a consequence, PBK overexpression observed in aggressive disease could potentially serve as a survival strategy in promoting AR stability, stimulating growth, migration and invasion of PrCa. These findings are summarised in Fig. pbk can exploit other oncogenic triggers to enhance its own expression. For example, the cytokine IL-6, which is overexpressed and promotes PrCa progression can upregulate PBK expression [PBK has emerged as a key player in multiple tumour types, including breast cancer , haematopression . Likewispression –40.In advanced PrCa, AR is the major therapeutic target, and its point mutations such T878A and F876L, as well as the LBD deleted splice variants can lead to a constitutively active AR leading to failure of ADT. There is evidence that reducing AR protein levels may be more effective in treating CRPC than inhibiting its activity , 41. As Our findings suggest that AR promotes PrCa growth via upregulation of PBK and the therapeutic benefits of anti-androgens could result from inhibition of PBK in primary PrCa. We believe that the primary reason for the development of CRPC could be the loss of regulatory axis whereby, instead of AR, PBK expression is regulated by other oncogenic transcription factors such as E2F and c-myc , 40 as aMethyltrienolone was obtained from Perkin Elmer, enzalutamide was obtained from Axon Medchem and bicalutamide was obtained from Sigma chemicals. Dihydrotestosterone, dimethyl sulfoxide (DMSO) were obtained from Sigma chemicals . The PBK inhibitor HI-TOPK-032 (PBKi) was purchased from InterBioScreen, Russia. Life Technologies  provided cell culture media, fetal bovine serum (FBS), antibiotics etc.2.Genetic profiling of polymorphic short tandem repeat loci was used to verify cell lines in accordance with ATCC guidelines. AmpFISTR test or GenePrint10 test  was used, and data were analysed using GeneMapper v4.0. LNCaP, C4-2, VCaP, PC3, DUCaP, 22Rυ1 and DU145 cells were procured through commercial suppliers. These cell lines were grown in Roswell Park Memorial Institute media that contained 10% FBS and 1% penicillin/streptomycin in a humidified incubator at 37 °C with an atmosphere of 5% COAR gene. PCR and Sanger sequencing methods were also used to verify the identity of R1-D567 cell line to detect the transcription activator-like effector endonuclease-based genome engineering-induced signature break fusion junction.R1-AD1 is a CWR-R1 subline whose identity was verified using polymerase chain reaction (PCR) and Sanger sequencing (positive for the H874Y point mutation in the AR ligand-binding domain). Multiple ligation-dependent probe amplification assay was used to rule out copy number imbalances along the entire length of the oC. Cells were mixed together . Supernatant was discarded and cells were lysed using lysis buffer . Protein lysates (~30 µg in 8 M urea buffer) were loaded onto one-dimensional sodium dodecyl sulphate gel and run ~ 1.5 h to get a full-length gel with complete separation. For in-gel digestion, the gel was cut into 18 pieces, which were briefly washed with ammonium bicarbonate buffer, and further reduction was carried out with dithiothretol and alkylation with Iodoacetamide, which was followed by trypsin digestion  at 37 °C overnight. 0.4% of trifluoroacetic acid was used to stop the digestion reaction and the supernatant was transferred to a reaction tube following by drying using speed vac. Peptides were re-dissolved in 6 µl of 2% acetonitrile/0.1% formic acid solution, and 5 µl was loaded with auto sampler  onto a trapping column , separation was achieved with an Easy-spry Pep map analytical column . Both were packed with C18 resin . Peptides were separated with an Ultimate3000 nano RSLC (Dionex) HPLC with in-line flow rates of 4.0 and 0.35 µl/min, respectively). The LC gradient range was from 5 to 35%B in 100 min . The eluted peptides were analysed using the Q Exactive Hybrid Quadrupole-Orbitrap Mass Spectrometer (Thermo-Scientific). One full MS scan  target of 106) for each cycle was performed. This was followed by 10 data-dependent MS/MS spectra . Selected ions were dynamically excluded for 30 s and singly charged ions were rejected using charge-state screening.C4-2 cells were labelled with either with heavy or light amino acids, and transfected with ON-TARGET plus siRNA pool (and non-targeting control siNT) for 72 h or treated with anti-androgen Bicalutamide or DMSO (24 h). Cells were washed twice with cold PBS, lifted, and were centrifuged (300–400 g) at 4 http://www.uniprot.org/). Search parameters included partially tryptic specificity; fragment mass tolerance of 0.05 Da; a precursor mass tolerance of 20 ppm; a static modification of carboxy amidomethylation; and dynamic modifications of oxidation and de amidation. Results were filtered to only include fully tryptic peptides. Other cutoffs were established to achieve maximum sensitivity levels at < 0.1% false-positive rate (one reversed sequence hit for every 1000 forward sequence hits).The RAW files were processed with Thermo Proteome Discoverer 1.4. The MS/MS spectra were searched using both Sequest and Mascot against a reference composite database that contained the Human Uniprot protein database (downloaded April/2014 from This was performed on C4-2 cells using a PBK antibody (Novus) following a recently developed RIME method .All plasmids were sequence verified. Four different and highly target specific siRNA sequences (ON-TARGET plus smart pool of four-independent siRNAs) were used to achieve potent knockdown of AR and PBK . Lipofectamine RNAiMAX transfection reagent (Life Technologies) was used to perform transient transfections with siRNA. Lipofectamine2000 transfection reagent (Life Technologies) was used to perform DNA transfection following manufacturer’s protocols. Reverse transfections were performed using 25 nM siRNA in all knockdown experiments except for RNAseq, where 50 nM siRNA was used to attain a near complete depletion of endogenous PBK. MMTV-Luc and AR-Luc reporter plasmid have described earlier , 48.Cells treated with androgens were grown in medium containing hormone-depleted  FBS. Renilla luciferase  was used as an internal control in all luciferase assays. Following 48 h transfection, cells were harvested in passive lysis buffer (Promega) and then luciferase assay buffer was used to measure both luciferase/Renilla luciferase activity.Cells were transiently transfected using RNAiMAX reagent with siRNA (25 nM) for 48 h. Cells were then grown in androgen-deprived charcoal-treated RPMI medium and treated with R1881 (1 nM) for 24 h. High Capacity cDNA Reverse Transcription Kit  was form for cDNA preparation. For PCR, we used Taqman quantitative real-time probes (Applied Biosystems) to quantify gene expression changes in TMPRSS2 and NKX3.1 relative to 18 S expression, which served as the internal control. AR knockdown was used as the positive control; experiments were carried out with nine replicates.To determine cell viability, cells were incubated with 3--5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium) reagent. This reaction was followed by colorimetric assay using Promega’s cell viability kit protocol. Clonogenic assays were performed using the exact methodology, which has been described earlier .AR domains were purified as described previously . In totat test when n = 3 or more.These experiments were performed as described earlier . For GSTDESeq v1.10.1 [C4-2 cells were treated with PBKi for 6 h or transfected with PBK siRNA for 72 h. Qigen Allprep kit  was used to isolate total RNA, which was quantified using Qubit (Life technologies) and quality (RIN > 8) was confirmed using the Bioanalyzer 2100 (Agilent). TruSeq® mRNA HT Sample Prep Kit was used for RNAseq, which was performed with a 500 ng of total RNA as input. Illumina HiSeq generated SE40 reads were aligned to the human reference genome version GRCh37.64 using TopHat v2.0.4 . HTSeq-c v1.10.1 . Multipl v1.10.1 . Genes w v1.10.1 .Paraffin-embedded tissues were used to perform immunohistochemical staining to detect AR and Ki67. The methodology to detect AR  and Ki67https://sbb.nds.ox.ac.uk/camprompt).All samples were obtained from the Addenbrooke’s Cambridge University Hospital from patients who attended the Urology clinic. Hospital records were used to identify clinical data, which were contained in a prospectively maintained database . For histology, tissue was fixed in 10% neutral buffered formalin. Haematoxylin and eosin (H&E) analysis was performed by the uropathologist on 5-micron thick sections. Patients with hormone refractory tumour/CRPC were defined as those who had a sustained rise in prostate specific antigen from nadir despite undergoing ADT treatment. Benign tissues obtained from prostatectomy or from primary PrCa (matched benign) was used as control. Formalin fixed paraffin-embedded tissue retrieved from the pathology archive was used as control for the chTURP specimens. The original H&E sections were reviewed by a uropathologist. Suitable areas of tumour tissue were included in the TMA were marked on the slides and corresponding paraffin blocks. Cores were removed from the donor blocks using a 2 mm skin biopsy punch and incorporated into recipient TMA blocks with pre-defined layout. For each sample two tumour cores and one benign adjacent core were incorporated. Immunohistochemistry was performed on 3.5-micron sections and was also blind reviewed blinded by the uropathologist to verify the pathology and suitability of the included tissue cores for scoring.Both Boyden chamber and matrigel invasion assays were performed as previously described .3 pieces, which were mounted on collagen cushions, kept on steel grids for 3 weeks to grow as explants. The tissue was treated as indicated with drugs in RPMI with 10% FBS, 1% penicillin, streptomycin and gentamycin. To prepare collagen cushions, 250 μl of collagen mix  was solidified on a nylon membrane. Tissue were harvested by fixation in formalin for 20 h and then transferred to 70% ethanol prior to paraffin embedding for immunohistochemistry.PrCa tissue was obtained with informed consent in accordance with the institutional policy. Using a sterilised knife, the tissue was cut into 1–2 mmVCaP cells were selected for the scratch–wound assay on account of their strong adherence to tissue culture plates. Cells were transfected with 25 nM siRNA for 24 h using RNAiMAX reagent, by which time nearly confluent layers of VCaP cells had formed in a 24-well tissue culture plate. The scratch was introduced using a wound scratch instrument (Essen Bioscience) with a micropipette tip (1–2 µl capacity). The cells were washed with PBS, given fresh medium and treated with the indicated drugs. The culture plate was placed inside the Incucyte instrument and monitored for the required time.t test where applicable. P value of 0.05 or less was considered significant. Appropriate nonparametric tests such as Mann–Whitney U test were used to analyse various datasets. Kaplan–Meier survival curves were generated by recursive partitioning analysis. KM curves are predictive of recurrence-free survival . *p < 0.05, **p < 0.01, ***p < 0.001.Statistical analyses were reported as mean ± SEM for continuous variables. We used Student’s http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?token=ctgjggwqhlqbvod&acc=GSE63701 & http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?token=cparuuusjtcnlun&acc=GSE64341The RNA-sequencing data have been submitted to Gene Expression Omnibus. It is available at the following links Fig S1 WarrenFig S2 WarrenFig S3 WarrenFig S4 WarrenFig S5 WarrenTable S1 WarrenTable S2 WarrenTable S3 Warren


The spermatophyte root system is composed of a primary root that develops from an embryonically formed root meristem, and of different post-embryonic root types: lateral and adventitious roots. Adventitious roots, arising from the stem of the plants, are the main component of the mature root system of many plants. Their development can also be induced in response to adverse environmental conditions or stresses. Here, in this review, we report on the morphological and functional diversity of adventitious roots and their origin. The hormonal and molecular regulation of the constitutive and inducible adventitious root initiation and development is discussed. Recent data confirmed the crucial role of the auxin/cytokinin balance in adventitious rooting. Nevertheless, other hormones must be considered. At the genetic level, adventitious root formation integrates the transduction of external signals, as well as a core auxin-regulated developmental pathway that is shared with lateral root formation. The knowledge acquired from adventitious root development opens new perspectives to improve micropropagation by cutting in recalcitrant species, root system architecture of crops such as cereals, and to understand how plants adapted during evolution to the terrestrial environment by producing different post-embryonic root types. The root system of spermatophytes is composed of a primary root that develops from the radicle formed during embryogenesis. Post-embryonically, the primary root can branch and form lateral roots. Post-embryonic roots can develop from stems, leaves or other vegetative non-root organs, either constitutively or in response to stress. Such roots are referred to as adventitious, a term that etymologically indicates their unusual and surprising origin  1]. Adv. Adv1]. Ficus sp. produce many hanging AR that allow exploring and exploiting the aerial canopy where organic substrate-rich niches are frequent in cavities formed at tree branching sites , which plays a key role in root stem cell niche specification and maintenance, suggesting that callogenesis and rhizogenesis share, in part, genetic elements [aberrant lateral root formation 4  mutant, impaired in lateral root formation, suggesting that both AR and induced calli derive from the xylem and the stem pericycle-like cells [AFL4 orthologs could be used in other species to determine whether the cell layers from which AR initiate possess a pericycle-like identity or not.AR always develop from cells neighbouring vascular tissues . In Arabelements . This iske cells ,18,19,20In rice, the plant model for monocots, CR differentiate from a cell layer called the ground meristem that has been assimilated to a stem pericycle-like tissue ,21,22,23In woody species, AR primordia also initiate from cells located between the vascular bundles and the starch sheath layer . In cuttBesides their pericycle-like cell origin, AR can also initiate in Arabidopsis, petunia or woody species from phloem or xylem parenchyma cells, young secondary phloem cells, cambium cells close to the phloem cells, cotyledon parenchyma cells, leaf, and procambium ,18,32,33Altogether, regardless of the species, tissue or organ, AR initiation occurs from pericycle-like cells and can associate vascular tissues and starch sheath, suggesting a common origin of AR formation in monocots and dicots, including woody species. Interestingly, callogenesis and rhizogenesis share genetic characteristics. This process resembles the two-step mechanism observed during hormone-induced organogenesis, previously proposed as an indirect pathway for AR induction in difficult-to-root woody species .−3 phytomer  to low oxygen (hypoxia). A common adaptation to flooding is the formation of AR with aerenchym. In some species, such as tomato, AR are formed de novo upon flooding; in other species, such as rice or bittersweet, the primordia are constitutively preformed in the stem and their emergence is induced by flooding ,58,61. W2+, nitrogen, zinc, phosphorus, iron and manganese, influences AR development of cuttings and the survival capacity in adverse conditions [2 increases AR formation in Arabidopsis, most likely via the activation of mitogen-activated protein kinases. Similarly, the application of Ca2+ chelators and a Ca2+ channel blocker inhibits AR formation [The availability of water and macronutrients also regulates AR development  Figure . Under nnditions . In petunditions . An exogormation . The micormation .Phaseolus vulgaris L.), the limitation of phosphorus stimulates adventitious rooting, allowing topsoil foraging [Whereas phosphorus is a crucial macronutrient for plant growth and development, its availability in soils is well below the concentration required for proper plant development. Moreover, in most soils, the phosphorus available to plants is present primarily in topsoil horizons, decreasing with soil depth. Its fast-chemical immobilization makes fertilization inefficient to overcome phosphorus deficiency ,65,66. Iforaging . NeverthThe understanding of how external signals are perceived, conveyed, and interpreted to drive root adaptive developmental processes are still poorly known and should be further studied.Hormones are important regulators of the plant response, transducing external signals into physiological behaviour. Our current knowledge of the signals interplay involved in constitutive or inducible AR formation is summarized in Auxin is the major growth-promoting hormone for AR initiation. Auxin such as indole-3-acetic acid (IAA) promotes AR formation, and auxin homeostasis is associated with different developmental steps of the rooting process . In variCytokinins (CK) and auxin act antagonistically in a wide array of physiological responses, including AR formation. In fact, an increase in auxin and the concomitant CK depletion are necessary for adventitious rooting in cuttings and often enough for AR in easy-to-root species . ExogenoIn response to wounding, wounding-related compounds, such as ethylene, jasmonate and nitric oxide, in association with auxin can promote cell division leading to AR formation ,44,75.PIN3 and PIN7, resulting in the modification of auxin transport [In Arabidopsis, tomato and rice, flooding conditions induce the formation of AR via the local accumulation of ethylene that inhibits auxin transport, leading to an auxin accumulation that, in turn, induces ethylene production and increases the process of AR formation ,53,58. Iransport ,78. Due ransport . Moreoveransport .Ethylene may also represent the first warning signal indicating hypoxia and anoxia provoked by submergence . In Arab2+) are involved in promoting AR development [In mung bean, ethylene promotes AR formation by increasing cells responsiveness to auxin . Contrarelopment .Gretchen Hagen3 (GH3) gene family, which encodes enzymes responsible for the conjugation of various amino acids to auxin and jasmonate, leading to their activation, inactivation, or degradation (see hereafter) [2+)-dependent way [2+ accumulation into the cytosol that activates both calcium-dependent protein kinases and mitogen-activated protein kinases, leading to cell division involved in AR development [2+ in AR development in response to nitric oxide has been also observed in cucumber submitted to osmotic stress [2+ in the mechanism and to unveil the conserved processes among several species.Jasmonate and auxin crosstalk controls the AR initiation via AUXIN RESPONSIVE FACTOR (ARF) proteins and the reafter) ,88,89. Areafter) . In addireafter) . Nitric reafter) . Nitric reafter) . In ricereafter) . In cucureafter) ,47. The dent way ,49,50. Aelopment ,44,94. Ic stress . A studyc stress . Further2O2). In mung bean, H2O2 stimulates the expression of many genes involved in AR development [2O2 is a signal involved in AR formation after cucumber de-rooting, and the inhibition of H2O2 suppresses AR formation [2O2, has been correlated with AR formation in a dose-dependent manner, particularly during the early steps of initiation. The depletion of peroxidase activity is related to the auxin-dependent inhibition of the peroxidase isozyme de novo synthesis [Salicylic acid that is involved in various biotic and abiotic stress responses promotes AR formation . Salicylelopment . A high ormation . In thisynthesis .In conclusion, phytohormone crosstalk, with auxin as a hub, occurs in response to environmental signals in order to tightly and spatiotemporally control the AR development. Nevertheless, the major part of the cited studies focused on the characterization of one specific hormonal pathway during AR formation.tryptophan aminotransferase of arabidopsis (taa1) [crown root less 4 (crl4)/Osgnom1 [As already mentioned, cereals constitutively produce AR. Based on the analysis of rice and maize mutants impaired in CR development, genes involved in polar auxin transport and auxin signalling pathways were identified as major genetic components controlling CR formation ,101,102 /Osgnom1 ,105, resOsLBD3-2 and CROWN ROOT LESS1 (CRL1) are very close to the maize ROOTLESS CONCERNING CROWN AND SEMINAL ROOTS (RTCS) that is involved in CR and brace roots formation [CRL1 induction is lost in plants overexpressing a non-degradable modified form of OsIAA3 [CRL6, a gene encoding a chromatin remodelling factor involved in CR formation, stimulates the expression of several OsIAA genes [CRL1 inducible overexpression in the crl1 mutant background [QUIESCENT-CENTER SPECIFIC HOMEOBOX (QHB), the rice orthologue of AtWOX5. A quarter of these genes have no homologs with Arabidopsis genes with a role in lateral roots initiation, suggesting that specific mechanisms regulate CR formation. In situ hybridisation localized CRL1 expression pattern with some of these genes in CR initia and primordia [A phylogenetic analysis of the ASYMMETRIC LEAVES 2-like (ASL)/LBD family showed that the rice genes ormation ,106,107.f OsIAA3 . CRL6, aAA genes . In riceckground . Among trimordia .CRL5, which encodes an AP2/ERF family transcription factor, is induced by auxin, likely via OsARF1, and positively regulates the cytokinin-responsive regulator gene OsRR1, an inhibitor of the CK pathway [crl1/crl5 double mutant suggests that CRL5 acts through an auxin-related pathway distinct from CRL1 to control CR initiation. Another transcription factor, the WUSCHEL-Related Homeobox 11 (OsWOX11) gene, is induced by auxin and CK, affecting auxin- and cytokinin-responsive gene expression. In the auxin biosynthesis yucca and taa1 mutants, OsWOX11 is downregulated and its overexpression can partially restore the formation of CR that is impaired in both mutants [OsWOX11, required for auxin-dependent CR development [ERF3 regulates OsRR2 expression and is involved in CR initiation, whereas when OsWOX11 is expressed after the CR primordia formation, the ERF3/OsWOX11 interaction likely represses OsRR2 during CR elongation [CRL5 and OsWOX11 do not interact, which suggests different regulatory pathways of CR development integrating auxins and CK [OsWOX11 demonstrate its key role in CR development. OsWOX11 regulates approximately 700 genes involved in root development, stress response, hormone signalling, and redox metabolism. Of them, 34% contain at least one WOX cis-regulatory motif TTAATGG/C [OsWOX11 binds the promoter of OsLOB16, homologous to CRL1 [AtWOX11, orthologous to OsWOX11, also binds the AtLBD16 promoter, promoting the root primordium identity during Arabidopsis adventitious rooting in vitro [METALLOTHIONEIN2b (OsMT2b) is downregulated by RNA interference, the CK concentration increases and the number of CR decreases, whereas OsMT2b-overexpressing lines are characterised by an increase in CR and a lower amount of endogenous CK [cis-zeatin, negatively regulates the CR development formation [In rice, several genes controlling CR formation are involved in auxin and CK signalling crosstalk. First,  pathway . The add mutants . OsWOX11elopment ,111, intongation . The pats and CK ,112. FurTAATGG/C ,114. Thein vitro . Other genous CK . Similarenous CK , whereasormation .The characterisation of rice, maize and Arabidopsis mutants altered in the CR or lateral root formation shows that a core regulatory network involving auxin-signalling pathways and LBD transcription factors is conserved during CR and lateral roots initiation, independently from the stem or root origin of the newly form post-embryonic root, respectively .Taking into consideration these recent advances in the deciphering of genetic elements controlling AR, this confirms that auxin and CK pathways represent the main genetic control of AR formation. Nevertheless, as discussed previously, the role of other hormones should not be underestimated. Therefore, further genetic and functional genetic studies will undoubtedly help to clarify the hormonal crosstalk involved in the regulation of AR formation.Eucalyptus globulus showed that in cuttings, the endogenous content of auxin was two-fold higher in the easy-rooting line, confirming the importance of the hormone in AR induction [SUPERROOT (sur1 and sur2) and transgenic lines overexpressing the YUCCA gene involved in auxin biosynthesis spontaneously produce AR from hypocotyls because of auxin overproduction [GH3 genes [ARF and miRNA genes in the regulation of GH3 genes and AR formation [(Juglans nigra L.), the same three ARFs are involved in AR formation [RING E3 ubiquitin ligase CONSTITUTIVE PHOTOMORPHOGENIC1 (COP1) controls the transcription of the auxin efflux carrier gene PIN1 that tightly regulates the distribution of auxin across the plant and influences, in particular, AR initiation [sur2-1 double mutant, the AR are suppressed by the mutation of COP9 signalosome subunit 4 (CSN4), controlling the activity of CULLIN-RING E3 ubiquitin ligases (CREL). CREL ubiquitinated proteins are then targeted to proteasomal degradation. The defect in AR formation in the sur2-1/csn4 mutant is the result of the partially impaired degradation of the TIR1/AFB-auxin receptor, which alters auxin signalling and the ARF6/ARF8 regulatory module [gh3.3-1, gh3.5-2 and gh3.6-1 triple mutant, developing few AR compared to the wild-type, is characterized by a two-fold increase of endogenous free active jasmonate [GH3 genes, whose corresponding enzyme might conjugate jasmonate with the Asp, Met or Trp, leading to its inactivation and release of its inhibitory effect on AR initiation [GH3 transcripts and stimulate AR formation [In cuttings, endogenous auxin accumulation at the basal cut site is enough for AR formation induction in easy-to-root species, whereas exogenous auxin treatments are essential to stimulate AR formation from difficult-to-root species . Comparinduction . Moreoveoduction . In ArabH3 genes ,90. The ormation . This obormation . Light-iormation ,44. For itiation . In the y module . Additioormation , underlyormation . In cuttormation . The comormation . The genJASMONATE-ZIM DOMAIN1 (OsJAZ1)/EXTRA GLUME2 (EG2), induces the production of more, larger and longer CR. OsJAZ1 was retrieved from a Quantitative Trait Locus for drought resistance, suggesting for the first time that the JAZ protein belongs to the determinants of the root traits both under normal and drought stress conditions in rice [The study of rice growing in adverse conditions, such as drought stress, allowed the identification of other genes involved in hormone-regulated CR development. For example, the overexpression of the  in rice .expansin (EXP) family, also involved in post-embryonic root formation in Arabidopsis, are among the early auxin-induced genes activated before cell divisions and AR formation [AtWOX11, an Arabidopsis ortholog of OsWOX11, promotes the root primordium identity during Arabidopsis in vitro adventitious rooting [OsWOX11 have been identified. The constitutive overexpression of PtWOX11 enhanced the rate of rooting and increased the numbers of AR per cutting [WOX11 likely controls a well-conserved mechanism for AR formation in monocots and dicots [In pine cuttings, the genes of the ormation . AtWOX11 rooting . In popl cutting . This sud dicots ,127.9 guided RNA, and the genome sequences of diverse taxa will help to validate the conservation of these mechanisms in non-model plants.In conclusion, at the molecular level, the understanding of AR development in model species suggests the conservation of some genetic determinants of AR formation. The availability of genome editing tools such as CRISPR-CasIn rice, after initiation, CR develop inside the stem and stop growing. Later, CR growth restarts, allowing their emergence from the stem epidermis. This mechanism might be involved in the synchronization of CR emergence and shoot development, as mentioned before. The emergence of CR corresponds to the development of CR primordia through the stem tissues, through cells that have suffered programmed cell death. The polar auxin transport controls AR elongation and regulates the growth direction of emerging AR .cullin-associated and neddylation-dissociated 1 (Oscand1) mutants show normal CR primordia formation but no CR emergence [OsCAND1 regulates CR growth through the stem by the control of the cell cycle at the transition G2/M in CR meristem initial cells. In Arabidopsis, the root meristemless (rml) mutant is impaired in lateral roots and AR emergence and elongation, suggesting the role of RML in post-embryonic root elongation [RML encodes a γ-glutamylcysteine synthetase involved in glutathione biosynthesis [OsWOX11. After initiation, OsWOX11 is expressed in emerging CR in division regions of the root meristem where, in association with OsERF2, it activates CK signalling by downregulating OsRR2 [OsRR2 is expressed in CR primordia and its repression by OsWOX11/OsERF2 may be necessary to promote the emergence of CR [In addition to this constitutive development, CR emergence can be induced by external signals, such as flooding or exogenous ethylene but not by gibberellins, auxin, or CK treatment . In CR pmergence . OsCAND1ongation . RML encynthesis . The inhynthesis . Some geng OsRR2 . OsRR2 ice of CR . OsWOX11ce of CR  and thatce of CR . Some ofce of CR ,132. Ricce of CR ,134,135.YUC4 gene to block its activation, repressing auxin biosynthesis, again underlying how CK regulates auxin homeostasis to inhibit AR formation [PLEIOTROPICDRUGRESISTANCE TRANSPORTER9 (PtPDR9) [Many hormones play a role in the negative control of AR development to maintain the trade-off between carbon cost and development . As prevormation . The inh(PtPDR9) . Exogeno(PtPDR9) .ARF6, GH3.3, GH3.5, and GH3.6 genes that are involved in the auxin and jasmonate homeostasis regulation [Juglans nigra L.), ARF17 seems to have a conserved function; nevertheless, further study would be required to confirm the conserved mechanism across diverse taxa [JA inhibits AR initiation in etiolated Arabidopsis hypocotyls through the COI1 signalling pathway. As already mentioned, COI1 is controlled by complex crosstalk between the miRNA, ARF and GH3 proteins that regulate jasmonate conjugation and the subsequent effect of jasmonate on AR development . ARF17 ngulation . In stemrse taxa .flacca and notabilis mutants produce additional AR. In the notabilis mutant, the phenotype of the WT could be rescued by expressing the 9-cis-epoxycarotenoid dioxygenase1 (SpNCED1) gene involved in abscisic acid biosynthesis [Abscisic acid is also a negative regulator of AR development in tomatoes . The absynthesis . In riceynthesis .gibberellins insensitive (gai) and repressor of GA1-like1 (rgl1), affected in gibberellins perception and responses to gibberellins, AR formation was unaffected [procera had a low capacity to produce AR in a root-inducing medium [Gibberellins also have a negative effect on AR formation. In the poplar mutants affected . In tomag medium . Gibbereg medium . Surprisg medium .Strigolactones repress the AR development by inhibiting the first divisions of founder cells in different species, including Arabidopsis, tomato, pea, and maize ,146. TheAlthough our knowledge on the mechanisms of AR formation and their regulation by environmental signals has increased in the last past few years, it remains limited compared to information related to mechanisms involved in primary root and lateral root formation and development. In this regard, several questions must be addressed. For example, what are the common or different developmental pathways involved in AR, primary root and lateral root development? Why are AR constitutively formed in some species but inducible in others? Would a species with a taproot system benefit from evolving a fibrous system and vice versa?ROLB gene from A. rhizogenes has been described as the most effective gene in promoting root formation, and the use of this gene in genetic transformation to improve the AR of some recalcitrant plants [Studies of species such as maize and rice provide clues concerning AR regulatory networks and are useful to complete our understanding of AR constitutive development. Genetic and molecular studies related to AR development allow the initiation of a model of AR formation regulation in rice . This knt plants , such ast plants  and peart plants , is one OsERF3, which plays a role in AR development, increased grain yield under severe drought conditions but not under normal conditions [Root adaptive development in response to drought that limits the AR formation in the topsoil while promoting already formed AR development in deep soil horizons in maize ,155 may nditions . Most ofnditions . Dicot a


Rehabilitation tailored to older adults’ needs might improve their functional performance and quality of life, as well as increase social participation. The aim of the study was to evaluate the use of medical rehabilitation services among older Poles in relation to socio-economic and health-related determinants.Data regarding medical rehabilitation were obtained from the nationwide, multidisciplinary PolSenior project (2007–2012) conducted on representative sample of 4813 respondents (48.3% women) aged 65+ years. Socio-economic status, physical functioning, falls, chronic pain, and formal disability occurrence, as well as self-rated health were accounted for.p < 0.005) underwent medical rehabilitation during 12 months prior to the survey. Respondents mostly received electrotherapy or light radiation therapy (61.3%). Multivariate logistic regression analysis revealed that women aged 80+ years and men aged 90+ years had a significantly lower chance of using rehabilitation services compared to the youngest study participants (65–69 y.o.). City dwellers used rehabilitation services nearly twice as frequently as rural dwellers. Respondents with university education level were most likely to take part in these services. Dependence in IADL decreased participation in medical rehabilitation, while formal disability and chronic pain promoted utilization of rehabilitation services.One in six respondents (18.9% women vs. 15.8% men, Younger age, city dwelling, higher education, functional independence, formal disability certificate, and chronic pain increased participation in medical rehabilitation. Such results of the study should be considered in planning actions towards reducing health inequalities at the national level and promoting health and well-being among older adults. Aging of developed societies is a burden for health care systems, including rehabilitation services designed to optimize functioning and reduce disability in individuals with health conditions in interaction with their environment .Effective rehabilitation and reablement are mentioned as one of ten components of care for older adults , 3. PrevRehabilitation services for prevention of frailty and disability are of special importance for public health in aging societies. Positive outcomes of rehabilitation on older individuals’ activities of daily living and quality of life have been shown in different settings and cultural backgrounds –9. EarlyNumerous authors underline the importance of inequalities in health particularly among older adults, both in macro and micro scale –15. In PMedical rehabilitation services in Poland are financed from public and private resources. Insurance-covered services are provided by the National Health Fund and the State Fund for Rehabilitation of Disabled Persons. However, this system is not sufficient and, due to long waiting lists, a significant number of patients utilize commercial rehabilitation services.The purpose of the study was to evaluate utilization of medical rehabilitation, its socio-economic correlates, and potential determinants of inequality in health of Polish older adult population.Data regarding medical rehabilitation services were obtained from the nationwide, multidisciplinary PolSenior project titled “Medical, psychological and socioeconomic aspects of aging in Poland” conducted from 2007 to 2012. Study cohort, representative for the Polish population aged 65 years and over, comprised 4979 participants. The representativeness of the sample recruited using three stage stratified, proportional draw, was obtained by weighting for demographic structure of the older Polish population. The fieldwork was conducted in respondents’ homes by trained nurses. Ethical approval (no. KNW-6501-38/I//08) was obtained from the Bioethics Commission of the Medical University of Silesia in Katowice. All study participants or their proxies signed informed consent forms. The design of the PolSenior project was described previously .http://polsenior.iimcb.gov.pl/en/questionnaire). Sources of financing of medical rehabilitation services (insurance-covered vs. private resources) were not analyzed. Socio-demographic variables included in the analyses were: age, place of residence, education level, type of work before retirement, self-assessed economic status, and having formal disability certificate . Other analyzed variables were: functional status, chronic pain occurrence, and its intensity, falls within 12 months prior to the survey and self-rated health (SRH).Data regarding utilization of medical rehabilitation within 12 months prior to the survey and types of services were drawn from the socio-economic questionnaire  and the Lawton Instrumental Activities of Daily Living Scale (IADL) , 20. BasSelf-rated health was measured using 0–10 pt visual analog scale  and scorThe PolSenior project questionnaires included two types of questions: regarding facts (addressed to respondents and/or their proxies) and regarding opinions (addressed only to respondents) . In the χ2 and Cochran-Armitage for trend tests were performed to identify factors related to utilization of medical rehabilitation in the study group.Statistical analyses were performed using Statistica 10.0 software . The Variables significantly associated with rehabilitation use were subsequently included into a multivariate logistic regression model. In the model, IADL was chosen as determinant of functional status, and, consequently, ADL was excluded as dependent variable. Data were presented as odds ratios (ORs) with 95% confidence intervals (95%CIs).Presented analyses differed in terms of the number of observations because of some missing data.p value < 0.05 was considered as statistically significant.In all analyses, p < 0.005), took part in medical rehabilitation during 12 months prior to the study. After weighting for demographic structure of the older Polish population, the utilization of rehabilitation services was higher than in the PolSenior study group (22.3 vs. 17.3%), with greater difference between women and men .Data regarding medical rehabilitation were collected from 4813 participants, constituting 96.7% of the PolSenior study cohort aged 65 years and over. One in six respondents (17.3%), 18.9% women and 15.8% men (Rehabilitation services utilized most frequently by the PolSenior study respondents were: electrotherapy and light radiation therapy 61.3%), massage therapy (52.0%), or passive exercises (51.4%). Distribution of the type of medical rehabilitation services according to gender is presented in Fig. .3%, massp < 0.001). In younger age cohorts (up to 84 y.o.) women, while in older age cohorts (85 y.o. and over) men, dominated as beneficiaries of the services—p < 0.001 (Table p < 0.001). Respondents with university education level were more than 2.5 times as often as those with primary education among rehabilitation users  and, respectively, more than 5 times as often as those without formal education . Notably, respondents with vocational education were the second subgroup after those with higher education , which used the rehabilitation services most frequently.The utilization of rehabilitation services decreased with age. Participation in medical rehabilitation was declared by every fourth respondent in the youngest age cohort (65–69 y.o.), every fifth aged 75–79 years, and every sixteenth aged 90 years and over p < 0.00. In younp < 0.001).Among white-collar workers, the utilization was nearly 2 times higher than in blue-collar workers and nearly 4 times higher than among farmers . Respondents with formal status of moderate disability were most frequent rehabilitation users .Disability certificate holders used rehabilitation services nearly 2 times more often than those without formal disability status . This proportion was less visible for independent vs. dependent in ADL, 1.5 times difference . In the last case, the difference among men was not statistically significant.In addition, respondents independent in IADL utilized rehabilitation services over 2.5 times more often than dependent ones . However, association between intensity of chronic pain and utilization of rehabilitation services was statistically significant only in men.Respondents who have reported chronic pain were more likely to use rehabilitation services , and among women . In men, a significant difference was noted only between the youngest and the oldest (90 y.o. and over) male cohort. City dwellers were more likely to use rehabilitation services compared to village inhabitants. University level education promoted participation in rehabilitation in both genders. Dependence in IADL was inversely associated with utilization of the analyzed services among women and men. Disability certificate holders and those who reported chronic pain were more likely to take part in medical rehabilitation Table .Table 2FThe present study describes the socio-economic and health-related determinants of rehabilitation use among older Poles and characterizes the inequalities in the access to these services. Responding adequately to the demographic and epidemiological trends and tailoring the health care systems including rehabilitation to the patients’ needs has been reflected in recommendations and good practices formulated by international bodies , 23–26. In our study, one in six respondents participated in medical rehabilitation during 12 months prior to the survey. Electrotherapy and light radiation therapy, massage therapy, or passive exercises were among the most commonly used services. Beneficial effects of these therapies on age-related health problems have been previously demonstrated –30.Results of the PolSenior study showed that the use of rehabilitation services decreased with age, from one in four in the youngest to one in sixteen in the oldest age cohort. Notwithstanding, published data indicate that rehabilitation might be useful and cost-effective in advanced age as shown by Davis et al.  regardinp < 0.005). Notably, when separate age cohorts were analyzed, the opposite was noticed in the oldest old, above the age of 85 years  aged 50 years and over, were more likely to contact the specialist, visit the dentist or be hospitalized in comparison to less educated ones . Rural dSurprisingly, we did not observe any relationships between the self-rated economic status and the utilization of rehabilitation services. However, objective measures of the incomes were not included in the analysis because of high rate of refusal to reveal financial data. A study carried out in USA showed positive correlation of personal income and massage therapy use among adults aged 60 years and over . Based oIn the current study, respondents holding a formal disability certificate had higher participation in medical rehabilitation independently of functional performance. We speculate that formal disability holders acquired experience with certain bureaucracy, and this might have facilitated their access to limited services in an inefficient health care system . PreviouOur study indicated no association between SRH and participation in medical rehabilitation, whereas Figueiredo et al.  found SRThe strength of the present study was providing data for a large group of older community dwellers with high proportion of men, as well as very old individuals who are underrepresented in most gerontological studies. Weights’ adjustment for demographic structure of the older Polish population enabled generalization of the obtained results to the nationwide perspective. The authors perceive that the limitation of this study is lack of data concerning resources of financing of medical rehabilitation services, as well as unknown reasons for rehabilitation (preventive or therapeutic) in the PolSenior respondents.In conclusion, determinants related to the utilization of medical rehabilitation services were: younger age, city dwelling, higher education, independence in IADL, formal disability, as well as chronic pain. Healthy and active aging, as well as reducing inequalities is emphasized as a priority of the European policy framework Health 2020 , 40. The


SSR) and expressed sequence tag (EST)–SSR markers were developed as tools for marker‐assisted selection of Chamaecyparis formosensis and for the molecular differentiation of cypress species.Simple sequence repeat (SSR‐enriched genomic libraries and transcriptome data of C. formosensis, 300 primer pairs were selected for initial confirmation, of which 19 polymorphic SSR and eight polymorphic EST‐SSR loci were chosen after testing in 92 individuals. The number of alleles observed for these 27 loci ranged from one to 17. The levels of observed and expected heterozygosity ranged from 0.000 to 1.000 and from 0.000 to 0.903, respectively. Most markers also amplified in C. obtusa var. formosana.Based on the SSR and EST‐SSR sequences are the first reported markers specific to C. formosensis. These markers will be useful for individual identification of C. formosensis and to distinguish cypress species such as C. obtusa var. formosana.The developed  Chamaecyparis formosensis Matsum., known as cypress, is a coniferous plant species in the Cupressaceae that is endemic to Taiwan. Although several simple sequence repeat (SSR) markers of Chamaecyparis Spach have been reported  SSR markers  were developed from noncoding regions, and (2) expressed sequence tag (EST)–SSR markers (which are thought to be highly conserved in closely related species) were derived from functional sequences. Compared to SSR markers, EST‐SSR markers demonstrate a higher level of transferability across related species  Endl. var. formosana (Hayata) Hayata to effectively distinguish C. formosensis and C. obtusa var. formosana, which are currently difficult to differentiate by phenotype.The logging of illegally sourced timber poses a great threat to biodiversity. To address this problem, scientists and forestry experts have been developing methods to identify individual trees  from two localities in Taiwan . The concentration and quality of SSR‐enriched libraries were measured using a NanoDrop 2000  and Qubit 2.0 Fluorometer (Thermo Fisher Scientific), respectively, and then the DNA libraries were sequenced using the Illumina MiSeq System  at Tri‐I Biotech . A total of 13,653,074 raw reads were produced. The raw reads were quality‐trimmed and merged using CLC Genomics Workbench version 7.5 . All sequence information has been uploaded to the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRP145153). The contigs ranging from 80 to 530 bp in length were merged, and a total of 10,487,858 contigs were assembled. These contigs were screened using the Simple Sequence Repeat Identification Tool  method  using the CTAB method  was detected between Cred35 and Cred229, Cred281 and Cred297, Cred249 and Cred298, and Cred260 and Cred298. The putative functions of EST‐SSR sequences were determined by BLASTX against the non‐redundant GenBank database. Thirteen SSR and four EST‐SSR loci were successfully amplified in C. obtusa var. formosana  Sequence Read Archive . Sequence information for the developed SSR and EST‐SSR primer pairs has been deposited to NCBI (BioProject ID PRJNA454510); GenBank accession numbers are provided in Tables


E. coli Dxr, M. tuberculosis Dxr and the growth of P. falciparum K1 in human erythrocytes. None of the synthesized compounds showed activity against either enzyme or the Plasmodia. This study further underlines the importance of the hydroxamate functionality and illustrates that identifying effective alternative bidentate ligands for this target enzyme is challenging. Fourteen new fosmidomycin analogues with altered metal chelating groups were prepared and evaluated for inhibition of  Plasmodium species, with P. falciparum being responsible for the most severe cases , 424.1672; found 424.1698.Dibenzyl 3-(o-tolylcarbamoyl)propylphosphonate (12b). 1H-NMR  δH ppm 1.70–2.12 , 2.24 , 2.51 , 4.87–5.12 , 7.00–7.23 , 7.28–7.38 , 7.55 , 7.78 . 13C-NMR  δC ppm 18.18 (PhCH3), 19.16 , 24.75 , 36.87 , 67.52 , 123.35 (Ar-C), 125.32 (Ar-C), 126.85 (Ar-C), 128.18 (Ar-C), 128.74 (Ar-C), 128.86 (Ar-C), 130.70 (Ar-C), 136.00 (Ar-C), 136.43 , 170.70 (CO). 31P-NMR : δP ppm = 33.77. HRMS (ESI): calculated for C25H29NO4P [(M+H)+], 438.1829; found 438.1831.Dibenzyl 3-propylphosphonate (12c). 1H-NMR  δH ppm 1.69–2.12 , 2.17 , 2.17 , 2.49 , 4.86–5.14 , 7.02–7.14 , 7.29–7.38 . 13C-NMR  δC ppm 18.79 (Ph-CH3), 19.22 , 25.20 , 36.24 , 67.49 , 127.47 (Ar-C), 128.28 (Ar-C), 128.38 (Ar-C), 128.74 (Ar-C), 128.87 (Ar-C), 134.14 (Ar-C), 135.53 (Ar-C), 136.48 , 170.57 (CO). 31P-NMR : δP ppm = 33.63. HRMS (ESI): calculated for C26H31NO4P [(M+H)+], 452.1985; found 452.1990.Dibenzyl 3-(2-methoxyphenylcarbamoyl)propylphosphonate (12d). 1H-NMR  δH ppm 1.74–2.12 , 2.47 , 3.83 , 4.91–5.10 , 6.86 , 6.94 , 7.03 , 7.26–7.40 , 7.82 , 8.33 . 13C-NMR  δC ppm 18.61 , 25.09 , 37.48 , 55.67 (Ph-O-CH3) 67.23 , 109.97 (Ar-C), 119.98 (Ar-C), 121.08 (Ar-C), 123.76 (Ar-C), 127.61 (Ar-C), 127.99 (Ar-C), 128.46 (Ar-C), 128.65 (Ar-C), 136.41 , 147.889 (Ar-C), 170.03 (CO). 31P-NMR : δP ppm = 33.52. HRMS (ESI): calculated for C25H29NO5P [(M+H)+], 454.1778; found 454.1791.Dibenzyl 3-propylphosphonate (12e). 1H-NMR  δH ppm 1.85–2.11 , 2.33–2.59 , 3.75  4.86–5.12 , 6.55 , 7.17  7.27–7.36 . 13C-NMR  δC ppm 18.12 (Ph-CH3), 22.26 , 25.28 , 36.21 , 67.38 , 127.39 (Ar-C), 128.20 (Ar-C), 128.32 (Ar-C), 128.45 (Ar-C), 128.92 (Ar-C), 129.13 (Ar-C), 135.51 (Ar-C), 136.97 , 165.22 (CO). 31P-NMR : δP ppm = 33.07. HRMS (ESI): calculated for C26H31NO6P [(M+H)+], 484.1884 ; found 484.0402.Dibenzyl 3-(2-fluorophenylcarbamoyl)propylphosphonate (12f). 1H-NMR  δH ppm 1.76–2.01 , 2.50 , 4.88–5.15 , 6.96–7.16 , 7.28–7.39 , 7.84 , 8.25 . 13C-NMR  δC ppm 18.64 , 24.71 , 36.85 , 67.29 , 114.86 , 122.02 (Ar-C), 124.36 , 124.49 , 128.00 (Ar-C), 128.49 (Ar-C), 128.62 (Ar-C), 136.26 , 152.42 , 170.43 (CO). 31P-NMR : δP ppm = 33.60. HRMS (ESI): calculated for C24H26FNO4P [(M+H)+], 442.1578; found 442.1586.Dibenzyl 3-(2-acetylphenylcarbamoyl)propylphosphonate (12g). 1H-NMR  δH ppm 1.80–2.12 , 2.49 , 2.65 , 4.93–5.11 , 7.11 , 7.29–7.38 , 7.54 , 7.88 , 8.72 , 11.70 . 13C-NMR  δC ppm 18.59 , 25.45 , 28.69 (PhCOCH3), 38.45 , 67.25 , 120.82 (Ar-C), 121.90 (Ar-C), 122.45 (Ar-C), 128.01 (Ar-C), 128.45 (Ar-C), 128.70 (Ar-C), 131.79 (Ar-C), 135.30 (Ar-C), 136.45 , 141.07 (Ar-C), 174.24 (CO), 202.91 (PhCOCH3). 31P-NMR : δP ppm = 33.43. HRMS (ESI): calculated for C26H29NO5P [(M+H)+], 466.1778; found 466.1779. Dibenzyl 3-(2-(methylsulfonyl)phenylcarbamoyl)propylphosphonate (12h). 1H-NMR  δH ppm 1.74–2.12 , 2.50 , 2.99 , 4.92–5.11 , 7.21–7.29 , 7.30–7.37 , 7.62 , 7.90 , 8.45 . 13C-NMR  δC ppm 18.56 , 25.42 , 37.92 , 44.41 (-PhSO2CH3), 67.47 , 123.06 (Ar-C), 124.40 (Ar-C), 127.28 (Ar-C), 128.21 (Ar-C), 128.68 (Ar-C),128.85 (Ar-C), 129.54 (Ar-C), 135.54 (Ar-C), 136.53 , 137.11 (Ar-C), 170.66 (CO). 31P-NMR : δP ppm = 33.10. HRMS (ESI): calculated for C25H29NO6PS [(M+H)+], 502.1448; found 502.1470. Dibenzyl 3-(2-(dimethylamino)phenylcarbamoyl)propylphosphonate (12i). 1H-NMR  δH ppm 1.75–2.12 , 2.49 , 2.60 2), 4.92–5.10 , 7.00–7.18 , 7.27–7.38 , 8.33 , 8.43 . 13C-NMR  δC ppm 18.80 , 25.51 , 37.89 , 45.00 (N-CH3), 67.41 , 119.72 (Ar-C), 120.12 (Ar-C), 123.92 (Ar-C), 125.26 (Ar-C), 128.15 (Ar-C), 128.63 (Ar-C), 128.82 (Ar-C), 133.53 (Ar-C), 136.58 , 142.87 (Ar-C), 170.16 (CO). 31P-NMR : δP ppm = 33.53. HRMS (ESI): calculated for C26H32N2O4P [(M+H)+], 467.2094; found 467.2330. Dibenzyl 3-(2-(tert-butoxycarbonyl)phenylcarbamoyl)propylphosphonate (12j). 1H-NMR  δH ppm 1.59 , 1.77–2.13 , 2.50 , 4.93–5.11 , 7.05 , 7.25–7.38 , 7.49 , 7.97 , 8.67 , 11.20 . 13C-NMR  δC ppm 18.66 , 25.54 , 28.41 (PhCOOCCH3), 38.55 , 67.38 , 82.66 (Ar-C), 116.62 (Ar-C), 120.47 (Ar-C), 122.48 (Ar-C), 128.15 (Ar-C), 128.57 (Ar-C), 128.79 (Ar-C), 131.24 (Ar-C), 134.31 (Ar-C), 136.63 , 141.71 (Ar-C), 167.91 (COOtBu), 170.96 (C0). 31P-NMR : δP ppm = 33.41. Dibenzyl 3-(2-(benzyloxy)phenylcarbamoyl)propylphosphonate (12k). 1H-NMR  δH ppm 1.74–2.10 , 2.40 , 4.86–5.16 , 5.10 , 6.88–7.05 , 7.24–7.43 , 7.79 , 8.35 . 13C-NMR  δC ppm 19.25 , 25.66 , 38.00 , 67.54 , 71.50 (NH-Ph-O-CH2-Ph), 112.35 (Ar-C), 120.72 (Ar-C), 122.04 (Ar-C), 124.28 (Ar-C), 128.09(Ar-C), 128.49(Ar-C), 128.90 (Ar-C), 128.95 (Ar-C), 129.14 (Ar-C), 129.35 (Ar-C), 136.91 , 136.97 (Ar-C), 147.66 (Ar-C), 170.49 (CO). 31P-NMR : δP ppm = 33.55. HRMS (ESI): calculated for C31H33NO5P [(M+H)+], 530.2091; found 530.2122.Dibenzyl 3-phenylcarbamoyl)propylphosphonate (12l). 1H-NMR  δH ppm 1.69–1.98 , 2.38 , 5.82–5.01 , 5.06 , 6.62 , 7.12 , 7.21–7.45 . 13C-NMR  δC ppm 18.19 (C2), 24.49 , 36.07 (C3), 67.02 , 70.71 (NH-PhOCH2Ph), 106.08 (Ar-C), 115.21 (Ar-C), 127.33 (Ar-C), 127.89 (Ar-C), 128.31 (Ar-C), 128.53 (Ar-C), 136.39, , 138.81 (Ar-C), 154.92 (CO). 31P-NMR : δPppm = 34.16. Dibenzyl (4-(methylsulfonamido)-4-oxobutyl)phosphonate (12m). 1H-NMR  δH ppm 1.75–2.04 , 2.47 , 3.21 , 4.89–5.11 , 7.28–7.40 , 10.63 . 13C-NMR  δC ppm 17.79 , 24.46 , 35.84 , 41.61 (SO2NHCH3), 67.93 , 128.14 (Ar-C), 128.88 (Ar-C), 128.93 (Ar-C), 136.18 , 172.17 (CO). 31P-NMR : δP ppm = 33.41. HRMS (ESI): calculated for C19H25NO6PS [(M+H)+], 426.1140; found 426.1162. 2-(4-(Bis(benzyloxy)phosphoryl)butanamido)benzoic acid (12n). Compound 12j (0.416 g) was dissolved in a dichloromethane/TFA mixture  at 0 °C. After stirring for an hour, TLC analysis showed a completed reaction. Toluene (15 mL) was then added to the reaction mixture before concentration in vacuo. Column chromatography (97.5% CH2Cl2/2% MeOH/0.5% CH3COOH) yielded 272 mg of 12n as an oil (73% yield). 1H-NMR  δH ppm 1.94–2.17 , 2.52 , 4.87–5.14 , 7.06 , 7.27–7.35 , 7.51 , 8.10 , 8.66 , 11.44 . 13C-NMR  δC ppm 18.25 , 25.22 , 38.52 , 67.96 , 115.55 (Ar-C), 120.23 (Ar-C), 122.72 (Ar-C), 128.21 (Ar-C), 128.77 (Ar-C), 128.86 (Ar-C), 131.81 (Ar-C), 134.71 (Ar-C), 136.14 , 141.89 (Ar-C), 170.90 (CO), 170.98 (CO). 31P-NMR : δP ppm = 26.02.Diethyl 3-(2-cyanophenylcarbamoyl)propylphosphonate (13q). 1H-NMR  δH ppm 1.34 , 1.79–2.17 , 2.64 , 4.01–4.23 , 7.19 , 7.51–7.66 , 8.14 , 8.28 . 13C-NMR  δC ppm 16.49 , 18.58 , 24.43 , 37.02 , 61.75 , 102.97 (Ar-C), 116.46 (CN), 122.10 (Ar-C), 124.39 (Ar-C), 132.46 (Ar-C), 134.04 (Ar-C), 140.37 (Ar-C), 170.86 (CO). 31P-NMR : δP ppm = 32.14. HRMS (ESI): calculated for C25H22N2O4P [(M+H)+], 325.1317; found 325.1317.in vacuo, re-dissolved in a mixture of water and ter-butanol, frozen and lyophilized to afford the desired targets compounds 8a–i, m–p as a white powder in quantitative yield.The amide (100–150 mg) was dissolved in MeOH (10 mL) and Pd/C (10%) was added under inert atmosphere. The resulting mixture was then stirred under hydrogen atmosphere for 10 min and the progress monitored by mass spectrometry. At completion, the reaction mixture was filtered and neutralized with 1 eq. of a NaOH. The mixture was concentrated Sodium hydrogen 3-(phenylcarbamoyl)propylphosphonate (8a). 1H-NMR  δH ppm 1.40–1.56 , 1.78–1.93 , 2.46 , 7.24 , 7.34–7.46 . 13C-NMR  δC ppm 21.13 , 28.55 , 38.10 , 122.45 (Ar-C), 125.79 (Ar-C), 129.33 (Ar-C), 136.92 (Ar-C), 176.00 (CO). 31P-NMR : δP ppm = 22.06. HRMS (ESI): calculated for C10H13NO4P [(M−H)−], 242.0588; found 242.0061. Sodium hydrogen 3-(o-tolylcarbamoyl)propylphosphonate (8b). 1H-NMR  δH ppm 1.47–1.62 , 1.70–1.90 , 2.10 , 2.40 , 7.18–7.35 , 8.42 . 13C-NMR  δC ppm 17.14 (Ph-CH3), 21.06 , 28.42 , 37.68 , 126.76 (Ar-C), 127.21 (Ar-C), 127.81 (Ar-C), 130.89 (Ar-C), 134.56 (Ar-C), 137.97 (Ar-C), 176.47 (CO). 31P-NMR : δP ppm = 23.60. HRMS (ESI): calculated for C11H15NO4P [(M−H)−], 256.0744; found 256.0322. Sodium hydrogen 3-propylphosphonate (8c). 1H-NMR  δH ppm 1.47–1.65 , 1.80–2.20 , 2.17 , 2.54 , 7.07–7.25 . 13C-NMR  δC ppm 17.44 (Ph-CH3), 21.11 , 28.68 , 37.24 , 128.21 (Ar-C), 133.48 (Ar-C), 136.31 (Ar-C), 176.37 (CO). 31P-NMR : δP ppm = 22.47. HRMS (ESI): calculated for C12H17NO4P [(M−H)−], 270.0901; found 270.0319. Sodium hydrogen 3-(2-methoxyphenylcarbamoyl)propylphosphonate (8d). 1H-NMR  δH ppm 1.37–1.52 , 1.77–1.92 , 2.47 , 3.83 , 7.00 , 7.09 , 7.20–7.32 , 7.52 . 13C-NMR  δC ppm 21.40 , 28.94 , 38.04 , 56.01 (-Ph-O-CH3), 112.30 (Ar-C), 121.07 (Ar-C), 125.20 (Ar-C), 125.53 (Ar-C), 127.65 (Ar-C), 152.22 (Ar-C), 176.45 (CO). 31P-NMR : δP ppm = 21.28. HRMS (ESI): calculated for C11H15NO5P [(M−H)−], 272.0693; found 272.0129.Sodium hydrogen 3-propylphosphonate (8e). 1H-NMR  δH ppm 1.42–1.57 , 1.69–1.88 , 2.40 , 3.71 , 6.66 , 7.33 . 13C-NMR  δC ppm 20.82 , 28.05 , 37.12 , 56.34 (PhOCH3), 105.38 (Ar-C), 113.06 (Ar-C), 129.44 (Ar-C), 155.33 (Ar-C), 176.72 (CO). 31P-NMR : δP ppm = 24.34. HRMS (ESI): calculated for C12H17NO6P [(M+H)+], 302.0799; found 302.0074. Sodium hydrogen 3-(2-fluorophenylcarbamoyl)propylphosphonate (8f). 1H-NMR  δH ppm 1.44–1.61 , 1.80–1.94 , 2.51 , 7.13–7.33 , 7.53 . 13C-NMR  δC ppm 20.89 , 28.30 , 37.50 , 116.05 , 124.03 , 124.71 , 126.62 (Ar-C), 128.08 , 157.44 (Ar-C), 176.42 (CO). 31P-NMR : δP ppm = 22.63. HRMS (ESI): calculated for C10H12FNO4P [(M−H)−], 260.0494; found 260.0001.Sodium hydrogen 3-(2-acetylphenylcarbamoyl)propylphosphonate (8g). 1H-NMR  δH ppm 1.24 , 1.40–1.58 , 1.84–1.99 , 2.51 , 7.20–7.43 , 13C-NMR  δC ppm 21.43 , 29.10 , 29.71 (PhCOCH3), 37.69 , 126.83 (Ar-C), 127.98 (Ar-C), 128.23 (Ar-C), 129.40 (Ar-C), 133.94 (Ar-C), 141.189 (Ar-C), 177.12 (-CO-), 177.20 (-COCH3). 31P-NMR : δP ppm = 22.19. HRMS (ESI): calculated for C12H15NO5P [(M−H)−], 284.0693; found 284.0693. Sodium hydrogen 3-(2-(methylsulfonyl)phenylcarbamoyl)propylphosphonate (8h). 1H-NMR  δH ppm 1.40–1.58 , 1.81–1.98 , 2.57 , 3.23 , 7.57 , 7.65 , 7.79 , 8.01 . 13C-NMR  δC ppm 20.97 , 28.89 , 37.91 , 43.14 (-Ph-SO2CH3), 128.31 (Ar-C), 129.60 (Ar-C), 129.83 (Ar-C), 133.81 (Ar-C), 134.67 (Ar-C), 135.82 (Ar-C), 177.16 (CO). 31P-NMR : δP ppm = 22.51. HRMS (ESI): calculated for C11H15NO6PS [(M−H)−], 320.0363; found 319.9703.Sodium hydrogen 3-(2-(dimethylamino)phenylcarbamoyl)propylphosphonate (8i). 1H-NMR  δH ppm 1.37–1.56 , 1.79–1.96 , 2.51 , 2.62 , 7.07–7.15 , 7.22–7.29 , 7.45 . 13C-NMR  δC ppm 21.31 , 29.11 , 38.17 , 43.71 (Ph-N-CH3), 120.11 (Ar-C), 123.95 (Ar-C), 126.90 (Ar-C), 127.79 (Ar-C), 129.99 (Ar-C), 147.99 (Ar-C), 176.57 (CO). 31P-NMR : δP ppm = 24.24. HRMS (ESI): calculated for C12H18N2O4P [(M−H)−], 285.1010; found 285.0459. Sodium hydrogen (4-(methylsulfonamido)-4-oxobutyl)phosphonate (8m). 1H-NMR  δH ppm 1.55–1.69 , 1.78–1.92 , 2.40 , 2.39 . 13C-NMR  δC ppm 19.78 , 27.41 , 38.62 , 40.10 (-N-SO2CH3), 180.33 (CO). 31P-NMR : δP ppm = 25.22. HRMS (ESI): calculated for C5H11NO6PS [(M−H)−], 244.0050; found 244.0611. Sodium hydrogen 3-(2-carboxyphenylcarbamoyl)propylphosphonate (8n). 1H-NMR  δH ppm 1.55–1.70 , 1.81–1.98 , 2.51 , 7.22 , 7.50 , 7.85 , 8.01 . 13C-NMR  δC ppm 19.97 , 27.37 , 38.45 , 121.99 (Ar-C), 124.67 (Ar-C), 125.10 (Ar-C), 130.71 (Ar-C), 132.22 (Ar-C), 137.17 (Ar-C), 173.83 , 174.88 . 31P-NMR : δP ppm = 24.98. HRMS (ESI): calculated for C11H13NO6P [(M−H)−], 286.0486; found 286.0268.Sodium hydrogen 3-(2-hydroxyphenylcarbamoyl)propylphosphonate (8o). 1H-NMR  δH ppm 1.46–1.61 , 1.79–1.96 , 2.51 , 6.88–7.03 , 7.18 , 7.35 . 13C-NMR  δC ppm 20.85 , 28.25 , 37.47 , 116.89 (Ar-C), 120.73 (Ar-C), 124.10 (Ar-C), 126.37 (Ar-C), 128.15 (Ar-C), 149.83 (Ar-C), 176.39 (CO). 31P-NMR : δP ppm = 22.85. HRMS (ESI): calculated for C10H13NO5P [(M+H)+], 258.0537; found 258.0058. Sodium hydrogen 3-propylphosphonate (8p). 1H-NMR  δH ppm 1.48–1.66 , 1.78–1.99 , 2.54 , 6.52 , 7.07 . 13C-NMR  δC ppm 20.63 , 28.12 , 37.02 , 108.25 (Ar-C), 111.93 (Ar-C), 129.19 (Ar-C), 152.84 (Ar-C), 177.01 (CO). 31P-NMR : δP ppm = 22.22. HRMS (ESI): calculated for C10H13NO6P [(M−H)−], 274.0486; found 273.9962. Bisammomium 3-(2-cyanophenylcarbamoyl)propylphosphonate (8q). Intermediate 13q  was dissolved in dry dichloromethane (6 mL) under inert atmosphere and cooled to 0 °C. TMSBr  was added dropwise while stirring. The icebath was removed after 10 min and the reaction stirred at room temperature for 24 h. 31P-NMR confirmed that the starting phosphonate was completely deprotected (shift from δ = 32–25 ppm). The volatiles were removed in vacuo, the crude material was dissolved in 5% aqueous ammonia and washed with diethyl ether. Lyophilisation of the ammonia solution yielded the product as a brown solid in quantitative yield. 1H-NMR  δH ppm 1.50–1.65 , 1.85–2.20 , 2.68 , 7.45 , 7.60 , 7.77 , 8.08 . 13C-NMR  δC ppm 21.55 , 27.80 , 35.65 , 121.59 (Ph-CN), 126.40 (Ar-C), 126.65 (Ar-C), 127.45 (Ar-C), 134.95 (Ar-C), 149.45 (Ar-C), 157.68 (Ar-C), 162.45 (CO). 31P-NMR : δP ppm = 25.00. HRMS (ESI): calculated for C11H13N2O4P [(M−H)−], 267.0540; found 267.0823.14  in MeOH (100 mL) was added formalin (14 mL), Pd/C 10% (160 mg) and formic acid (1 mL). The resulting mixture was allowed to stir under a hydrogen atmosphere for 3 h, after which, the mixture was filtered over a celite path and the filtrate concentrated to about 25 mL. The mixture was then basified by adding NaHCO3 and the water layer was extracted three times with EtOAc (3 × 50 mL). The combined organic phase was washed once with brine and dried over Na2SO4. Column chromatography (hexane/EtOAc 95:5) yielded 15  as a colorless oil. Subsequent treatment of 15 with 30% TFA in dichloromethane at 0 °C afforded 11i which was used for the next step without further purification.To a solution of tert-Butyl 2-(dimethylamino)phenylcarbamate (15). 1H-NMR  δH ppm 1.54 , 2.62 , 6.96 , 7.05–7.16 , 7.70 , 8.07 . 13C-NMR  δC ppm 28.93 (CH3 of tert-Bu), 44.83 (N-CH3), 80.27 (Cq of tert-Bu), 117.97 (Ar-C), 120.16 (Ar-C), 122.51 (Ar-C), 125.22 (Ar-C), 134.13 (Ar-C), 142.35 (Ar-C), 153.29 (CO). HRMS (ESI): calculated for C13H21N2O2 [(M+H)+], 237.1598; found 237.1602. E. coli Dxr, Mtb Dxr and P. falciparum K1 possibly due their inability to adopt a favorable conformation necessary for the Dxr active site metal chelation. Replacing the hydroxamate group of fosmidomycin with an alternative and efficient bidentate metal binding group in Dxr inhibitors, remains a daunting challenge as previously noted [In conclusion, amide derivatives of fosmidomycin were synthesized from simple starting materials. These analogues were inactive against ly noted .