KS) has been believed to be XY sperm. Accordingly, in the intracytoplasmic sperm injection treatment of patients with KS, hereditary KS has been a concern. Therefore, this study attempted to estimate the risk before and after the assisted reproductive technology.The main cause of Klinefelter's syndrome  analysis, following an original cell identification method using 1052 testicular gametes of 30 patients, was conducted. Second, in the resultant 45 babies, cytogenetic and physical–cognitive screening data were analyzed. In addition, a first attempt was conducted to investigate the origin of the extra X chromosome in 11 patients with KS by using 12 X‐chromosome short tandem repeat (STR) analysis in order to estimate the paternal contribution to KS.First, in order to validate the safety of the gametes of the patients with FISH analysis and the babies were normal genetically, physically, and cognitively. In the STR, it was confirmed that most (7/11) of the patients with KS resulted from the fertilization of the XX oocytes, suggesting that a baby with KS that had been reported previously might not have resulted from XY sperm.No sex chromosomally abnormal gamete was found in the KS is not as high as previously expected.These results indicate that the risk of assisted reproductive technology for patients with  Its incidence is ~1 in 500‐1000 live births in men.Recently, the authors established criteria to distinguish testicular somatic and meiotic cells without fixation and any staining,22.1This study dealt with 280 men who had been diagnosed previously as having non‐mosaic KS and had consented to receive microsurgical testicular sperm extraction (micro‐TESE) treatment at the institute from 2000 to 2013.2.2Several different sites of each testis were biopsied under an operation microscope (micro‐TESE). The biopsied testicular tissues were prepared in Dulbecco's phosphate‐buffered saline (DPBS) containing 0.125% collagenase and 0.01% DNase in order to free the spermatogenic cells from the seminiferous tubules, as previously described.2.3For the cryopreservation of the sperm, the testis tissue suspension was centrifuged and the pellets were transferred into a droplet of human tubal fluid (HTF) on a Petri dish with a glass pipette under a diverted microscope. Then, the cell suspension was mixed with a very small amount of a freezing medium  and placed on the tip of Cryotop  under an inverted microscope. The Cryotop was exposed to liquid nitrogen vapor for 2 minutes and stored in liquid nitrogen. For the thawing of the frozen cells, after maintaining the Cryotop in air for 5 seconds, it was dipped into a droplet that was covered with warm mineral oil (37°C) to suspend the cells.For ROSI, the spermatids were selected from the testicular cell suspension under an inverted microscope and suspended in 0.15 mL of freezing medium . The suspension was drawn in a 0.25 mL Cassou straw and cooled on ice (4°C). After the straw was maintained at −7°C in a cooling chamber of a programmable alcohol bath freezer for 20 minutes, it was cooled to −30°C at the rate of −0.3°C/min before being plunged into liquid nitrogen. Thawing was carried out by maintaining the straw in air for 5 seconds. The cell suspension then was diluted with HTF containing 10% SPS in a test tube to remove the cryoprotectant.2.4The authors already have established the criteria for identifying biopsied spermatogenic cells morphologically. The characteristics of the testicular cells were examined in detail under a differential interference microscope (10×40) and then their chromosomal constitution was determined by cytogenetic analysis to confirm whether the characteristics used and the meiotic phases correlated with each other.2.52+‐ and Mg2+‐free) on Poly‐L‐Lysine ‐coated slides with a square mark on the back slide. Soon after the PBS was placed, the surrounding cells were completely dried off and covered with a small amount of the fixative of Carnoy's solution (methanol: acetic acid=3:1). The fixative evaporated gradually and the cells became transparent. When the fixative completely disappeared, the cell membrane burst and the nuclei were attached to the glass slide. In order to wash away the phosphate crystals that were derived from the PBS (–), the cells were covered with the fixative several times and dried in air. For the fixed cells, triple‐target FISH was performed by using fluorescence‐labeled DNA probes that were specific for chromosomes X and Y and chromosome 7 . The mixture of the probes was applied to the slide under a cover slip and the nuclear and probe DNA were denatured simultaneously for 5 minutes at 75°C. The slide then was incubated in a chamber  at 42°C for 120 minutes in order to allow hybridization, followed by counterstaining with 4,6‐diamidino‐2‐pheniylindole .Spermatogonia (SG), primary spermatocytes (Pr‐Scs), round spermatids (STs), and elongating or mature sperm that had been selected from enzymatically treated biopsied tissues with a micromanipulator were put into a droplet of HTF with SPS and then placed in a droplet of 10 μL of PBS , according to the method of one particular study.2.9Out of the 45 babies who were born by ICSI or spermatid injection treatment from the patients with KS in the institute, 29 underwent chromosomal analysis by using amniocentesis or peripheral blood samples before or after birth, respectively, along with the compulsory newborn or infant screening for physical and cognitive development in Japan. For the rest, only information in the screening was used to examine the possibility of KS.2.10The clinical application of ROSI and genetic analysis with X‐chromosome STRs were approved by the Institutional Review Board of the Saint Mother Obstetrics and Gynecology Clinic for ART, Kitakyushu, Japan. This clinical study also was registered on the University Hospital Medical Information Network of Japan , adhering to the Recommendations for the Conduct, Reporting, Editing, and Publication of Scholarly Work in Medical Journals criteria.33.1In Figure 3.2In Figures The results of the FISH analysis for the SG, Pr‐Scs, and STs in five men with KS are shown in Table 3.3The success rates of the ICSI and ROSI treatment of patients with KS are shown in Table 3.4In the 29 babies who were cytogenetically analyzed, it was confirmed that they had a normal karyotype. The results of the newborn or infant screening for physical and cognitive development also showed that, in all 45 babies, no abnormality was found.3.5Examples of X‐chromosomal STR DNA profiles are shown in Table 44.1The present study showed that 45 babies were successfully delivered by using oocyte penetration by sperm or spermatid from patients with KS from January 2000 to December 2013 at the institute and, among them, there was neither a case of chromosomal abnormality nor any case of physical or cognitive abnormality. The miscarriage rate (37.3%) in the treatment of patients with KS by using sperm and spermatid was not significantly higher, when compared with patients who do not have KS (20.1% of 134).This clinical result is consistent with the cytogenetic data of the FISH and chromosomal analysis in the gametes from patients with KS. In the 25 patients with KS who were examined, no sex chromosome abnormality was found in 952 ST cells and 100 sperm , suggesting that the contribution of the XX oocyte to the production of XXY embryos might be greater than by the XY sperm, although the sample number that was applied for the X‐chromosomal STR DNA profiling is not large enough. Some studies have previously attempted to determine the origin of the extra X chromosome in patients with KS with X‐chromosome restriction site polymorphism.Conflict of interest: The authors declare no conflict of interest. Human and Animal Rights: All the procedures were followed in accordance with the ethical standards of the responsible committees on human experimentation  and with the Helsinki Declaration of 1964 and its later amendments. Informed consent was obtained from all the patients to be included in the study. All the institutional and national guidelines for the care and use of laboratory animals were followed.


Escherichia coli produces enzymes dedicated to hydrogen metabolism under anaerobic conditions. In particular, a formate hydrogenlyase (FHL) enzyme is responsible for the majority of hydrogen gas produced under fermentative conditions. FHL comprises a formate dehydrogenase (encoded by fdhF) linked directly to [NiFe]-hydrogenase-3 (Hyd-3), and formate is the only natural substrate known for proton reduction by this hydrogenase. In this work, the possibility of engineering an alternative electron donor for hydrogen production has been explored. Rational design and genetic engineering led to the construction of a fusion between Thermotoga maritima ferredoxin (Fd) and Hyd-3. The Fd-Hyd-3 fusion was found to evolve hydrogen when co-produced with T. maritima pyruvate :: ferredoxin oxidoreductase (PFOR), which links pyruvate oxidation to the reduction of ferredoxin. Analysis of the key organic acids produced during fermentation suggested that the PFOR/Fd-Hyd-3 fusion system successfully diverted pyruvate onto a new pathway towards hydrogen production. Escherichia coli performs formate-dependent hydrogen production -hydrogenase :: ferredoxin interactions are not common; however, Synechocystis sp. PCC 6803 does contain such a system [Chlamydomonas reinhardtii showed that photosystem I could be coupled directly to H2 production [in vitro [Together, these data demonstrate the successful re-purposing of a system . Physicaoduction . Similaroduction . Functioin vitro ; however


Borealin prevents the association of CHMP4C with membranes, whereas Aurora B interferes with CHMP4C's membrane remodelling activity. Moreover, we show that CHMP4C phosphorylation is not required for its assembly into spiral filaments at the abscission site and that two distinctly localized pools of phosphorylated CHMP4C exist during cytokinesis. We also characterized the CHMP4C interactome in telophase cells and show that the centralspindlin complex associates preferentially with unphosphorylated CHMP4C in cytokinesis. Our findings indicate that gradual dephosphorylation of CHMP4C triggers a ‘relay’ mechanism between the CPC and centralspindlin that regulates the timely distribution and activation of CHMP4C for the execution of abscission.The chromosomal passenger complex (CPC)—composed of Aurora B kinase, Borealin, Survivin and INCENP—surveys the fidelity of genome segregation throughout cell division. The CPC has been proposed to prevent polyploidy by controlling the final separation (known as abscission) of the two daughter cells via regulation of the ESCRT-III CHMP4C component. The molecular details are, however, still unclear. Using atomic force microscopy, we show that CHMP4C binds to and remodels membranes  In addition, these filaments appeared to promote the closure of membrane gaps over time . This behaviour is similar to that observed previously for the C. elegans CHMP4B homologue  Methionine-labelled CHMP4C and MKLP1 polypeptides were prepared from corresponding PCR products amplified, using primers harbouring a T7 promoter and then transcribed and translated in vitro using the TnT T7 Quick Coupled Transcription/Translation System (Promega) in the presence of [35S] methionine (Perkin Elmer). The binding reaction contained 150 mM NaCl and subsequent washes varied from 150 mM to 1 M NaCl. GST pull down assays were carried out as described previously [DNA fragments coding for CHMP4C and MKLP1 fragments were generated by PCR and cloned into pDEST15 (Thermo), using Gateway technology to express N-terminal GST-tagged polypeptides in eviously .


The flexible tactile sensor has attracted widespread attention because of its great flexibility, high sensitivity, and large workable range. It can be integrated into clothing, electronic skin, or mounted on to human skin. Various nanostructured materials and nanocomposites with high flexibility and electrical performance have been widely utilized as functional materials in flexible tactile sensors. Polymer nanomaterials, representing the most promising materials, especially polyvinylidene fluoride (PVDF), PVDF co-polymer and their nanocomposites with ultra-sensitivity, high deformability, outstanding chemical resistance, high thermal stability and low permittivity, can meet the flexibility requirements for dynamic tactile sensing in wearable electronics. Electrospinning has been recognized as an excellent straightforward and versatile technique for preparing nanofiber materials. This review will present a brief overview of the recent advances in PVDF nanofibers by electrospinning for flexible tactile sensor applications. PVDF, PVDF co-polymers and their nanocomposites have been successfully formed as ultrafine nanofibers, even as randomly oriented PVDF nanofibers by electrospinning. These nanofibers used as the functional layers in flexible tactile sensors have been reviewed briefly in this paper. The β-phase content, which is the strongest polar moment contributing to piezoelectric properties among all the crystalline phases of PVDF, can be improved by adjusting the technical parameters in electrospun PVDF process. The piezoelectric properties and the sensibility for the pressure sensor are improved greatly when the PVDF fibers become more oriented. The tactile performance of PVDF composite nanofibers can be further promoted by doping with nanofillers and nanoclay. Electrospun P(VDF-TrFE) nanofiber mats used for the 3D pressure sensor achieved excellent sensitivity, even at 0.1 Pa. The most significant enhancement is that the aligned electrospun core-shell P(VDF-TrFE) nanofibers exhibited almost 40 times higher sensitivity than that of pressure sensor based on thin-film PVDF. With the explosive development of science and technology, widespread attention has been paid to tactile sensors on both the research and applied technology fields ,2. TactiPolymer nanomaterials, especially polyvinylidene fluoride (PVDF), PVDF co-polymers and their nanocomposites with ultra-sensitivity and high deformability, represent the most promising material, which can meet the hot spot of flexibility and the requirements of dynamic tactile sensing in wearable electronics ,28,29. VThe nanofiber materials of PVDF, PVDF co-polymers and their nanocomposites, even randomly oriented PVDF nanofibers, have been successfully fabricated  and usedElectrospinning is a simple, low-cost, and versatile technique to fabricate long and continuous micro/nanoscale fibers (from a few nanometers to submicrometers) ,37. The The schematic illustration of a laboratory electrospinning setup is shown in The morphologies of nanofibers by electrospinning also can be influenced by multiple factors  includind31≈20 pC/N and −20 ≥ d33 ≥ −30 pC/N) [d31 ≈ 25 pC/N and −30 ≥ d33 ≥ −40 pC/N) [Among the electrospun piezoelectric materials applied in tactile sensors, electroactive piezopolymers such as polyvinylidene fluoride (PVDF) (30 pC/N)  and its 40 pC/N)  have bee2–CF2–)n, is a semicrystalline homopolymer, and the crystallite polymorphs have five phases  owing to fabricating conditions [−30 C·m [−30 C·m) [PVDF, whose molecular formula is  . The pol−30 C·m) . Many meVarious efficient techniques have been applied during the fabrication process to achieve dipole alignment of the crystalline structures in β-phase PVDF, such as uniaxial or biaxial stretching ,64,65, tThe nanoscale fibers of α or β or γ-phase PVDF with an increasing content of β-phase could be fabricated directly by electrospinning without any post-treatment. Zheng et al.  found th−1 and the output voltage signal was about 100 mV at 0.025 MPa air pressure. However, the PVDF material shows a susceptibility to temperature [The flexible PVDF material used as a tactile sensor shows several advantages, such as high piezoelectric coefficient, simple processing technology, dimensional stability, and chemical inertness . The typperature ,91, espeperature . So protPVDF composites with nanostructure materials can promote better performance ,92,93, tBaozhang Li et al.  prepared17 to 107 Ω·cm) under 5 MPa compressive stress. The obtained non-woven mats with PVDF/PPy blends can be used in a pressure sensor.The electrospun PPy particle-dispersed nanofiber webs exhibited a high surface area and a presence of piezoelectric β-phase . ConductThe PVDF co-polymer such as Poly (vinylidene fluoride-hexafluoropropylene) (PVDF-HFP), Poly(vinylidene fluoride trifluoroethylene) (P(VDF-TrFE)) , PVDF-T is a kin2 dipoles in the P(VDF-TrFE) nanofiber, which was enhanced by the electrospinning process [−3 under triboelectric mechanism and 5 N pressure force. A maximum sensitivity of 60.5 mV·N−1 for electrospun P nanofibers has been realized, which could be a reliably measured dynamic force up to a frequency of 20 Hz [−1 with a high signal to noise ratio. An ultra-sensitivity pizeoresistive pressure sensor based on 3D layers of the graphene oxide (rGO)-encapsulated P(VDF-TrFE) nanofibers (−1), low detection limit (1.2 Pa), rapid response speed (5 ms), low operating voltage (1 V) at 50 Hz and long-term stability under 100,000 cycles. A super flexible strain sensor based on the nanocomposites of (P(VDF-TrFE)) fibers and ZnO nanowires has been fabricated on PDMS substrate [The preferential orientation of CF process , has bee process . The outof 20 Hz . The obtof 20 Hz  was devenofibers was succeubstrate . The send33 mode has been obtained for non-bent flat sensors, since the dipoles were mainly formed in the vertical direction. The output signals decrease slightly in bent state sensors due to the directions of the dipoles deviating along the direction perpendicular to the bent curve. The further lowered output data was received for finger-like sensors owing to their smaller size and the reduced surface area of the piezoelectric layer. Such 3D flexible customizable sensors (Electrospun P(VDF-TrFE) nanofiber mats used for 3D sensors including non-bent flat sensors, bent state sensors and finger-shaped sensors have been reported by Han Bit Lee et al. . A stabl sensors , consideWith the rapid development of electrospinning technology, the highly aligned nanofibers of P (VDF-TrFE) have been successfully fabricated on flexible substrates by one step and have been used for pressure sensors . The tesThe tested piezoelectric properties of the PVDF, P(VDF-TrFE) and their nanocomposite nanofibers or mats via electrospinning used for flexible tactile-sensing application have been summed up in PVDF nanostructure materials with ultra-sensitivity, high deformability, outstanding chemical resistance, high thermal stability, low permitivities and low acoustic impedances can meet the requirement of flexibility for dynamic tactile sensing in wearable electronics. The electrospinning technique becomes available to fabricate PVDF nanofiber layers with excellent performance for flexible tactile-sensing applications in a one-step, low-cost and versatile style. Moreover, the β-phase content and piezoelectric properties of PVDF can be improved by adjusting the electrospinning technical parameters. It becomes exceedingly essential to design different morphologies of nanofibers or mats during electrospinning in order to properly enhance the performances of tactile sensors. Now the main tactile function layer in 3D pressure sensors is mainly composed by electrospun PVDF and PVDF co-polymer nanofibers mats, which can achieve excellent sensitivity. The tactile performances of PVDF are greatly improved when PVDF and PVDF nanofibers become more oriented or doped with nanofillers and nanoclay. The most significant enhancement is that the aligned electrospun P(VDF-TrFE) core–shell nanofibers were successfully fabricated, and the core–shell nanofibers exhibit almost 40 times higher sensitivity than that of pressure sensors based on thin-film PVDF. Both PVDF nanocomposite and co-polymer nanofibers by electrospinning exhibit excellent piezoresistive performance while working as pressure sensors. PVDF and PVDF co-polymer nanofibers produced by electrospinning represent the most promising materials for flexible tactile-sensing applications.


Litopenaeus vannamei were evaluated by conventional culture characteristics, physical and chemical characteristics, and molecular biology methods. Detection of extracellulase and hemolysin activity shows that the isolated GYX2014-1 has protease, lipase, gelatinase activity, but none of amylase, or lecithinase activity. The 16S rRNA gene (GenBank accession number: KT781675) was analyzed, and a phylogenetic tree analysis showed that the isolated pathogen was most closely related to V. vulnificus (GenBank accession number: NR 118570)—a match of more than 99%. The phenotypic traits and molecular biology of isolated bacteria, determined their identity as Vibrio vulnificus (V. vulnificus). In addition, artificially infected L. vannamei with Vibrio vulnificus appeared with the same disease symptoms as those of naturally infected shrimp. Drug sensitivity tests showed that V. vulnificus is highly sensitive to fosfomycin, cefradine and sinomin, and was resistant to penicillin, amikacin and kanamycin. This experiment is the first to separate V. vulnificus from L. vannamei, and the findings of this study can be used as a reference for disease control and health management.The morphology and the drug sensitivity of the strain GYX2014-1 isolated from the hepatic pancreatic tissue of moribund  Penaeus vannamei Boone, scientific name Litopenaeus vannamei [white-leg shrimp or white shrimp, are eurythermal euryhalinous tropical shrimp. Their appearance resembles Chinese shrimp, Penaeus merguiensis. Their body length measures up to 24 cm and they have a thin, light gray in color shell with no body markings. L. vannamei are consumed for their highly nutritious and delicious meat encased in a thin shell, as a result they are a lucrative crustacean species to farm worldwide [L. vannamei have been successfully artificially bred in China. Because of their rarity in naturally occurring environments they are widely popular among Asian shrimp producers—accounting for more than 77% of the farmed shrimp production in China [Vibriosis, are responsible for the mortality of shrimp culture to the great distress of farmers [L. vannamei was destroyed by Vibrio Parahaemolyticus, causing illness and death [vannamei , commonlin China . However farmers –8. For end death .Vibrio vulnificus, is a prominent invasive species within the Vibrio spp. [Marine Vibrio, they are Gram-negative, halophilic [Vibrios , V. vulnificus can cause human diseases such as gastroenteritis, septicaemia [V. vulnificus sepsis [Nibea albiflora [rio spp. , also knlophilic  and faculophilic . They arlophilic , commonllophilic . As one ticaemia , acute ls sepsis , and thelbiflora .L. vannamei is fish and shrimp polyculture cultivated in higher-place pond and soil pond, and the key to shrimp culturing lies in shrimp disease prevention and control. In May 2016 at a L. vannamei farm in the south of Jiangsu Province, the cultivated shrimp succumbed to mass illness. it was believed that the main infectious agent was from Vibrio sp., and suspected pathogenic bacteria V. vulnificus was isolated from diseased shrimp. At present, research surrounding L. vannamei mainly concern feed nutrition [V. vulnificus infection has not been reported. As L. vannamei farming increase in popularity research on the disease treatment is becoming more and more important. Therefore, in this experiment, L. vannamei carrying Vibrio spp. were thoroughly investigated. We studied the phenotypic characteristics of the isolated bacteria, their main biological characteristics, extracellular enzymes produced, their 16S rRNA gene sequence and conducted phylogenetic analysis which detected the sensitivity of the bacteria to antibacterial drugs in order to provide a reference point for further research on effective inspection of L. vannamei for Vibrio and basis for prevention and control of disease epidemiology.The main artificial breeding model of utrition  and contutrition , but theL. vannamei were selected. The liver and pancreas were sectioned to pieces under sterile operation, and tissue fluid was inoculated on TSA, 5% sheep blood TSA and BHI agar plate medium, and incubated at 28°C for 24h. 10 colonies were randomly selected and repeatedly streak-plated. After the artificial infection, a pure fatal culture strain was obtained for GYX2014-1 and preserved at 4°C on TSB agar medium.10 newly infected The isolates GYX2014-1 were tested for the production of extracellular products such as lipase, lecithin enzyme, protease and amylase. They were inoculated onto LB agar plate containing yolk liquid (10%), Tween 80 (1.0%), skim milk (10%), starch (1%), and observed in 30°C for 24h, after which a hydrolysis ring can be directly observed on the plate containing egg yolk, Tween 80 and skim milk.2-KI solution (Gram staining with Lugol's solution) was added on tablet containing starch before observing, if the bacteria produced amylase, starch is decomposed, thus, there would be no reaction with iodine and the culture medium around the colony becomes transparent. If the bacteria did not produce amylase, the starch in the medium would react with iodine and a purple colour would be observed [They were considered extracellular enzyme positive if a transparent ring formed around the colony . I2-KI sobserved . The detThe experiment was conducted in strict accordance with the US National Institutes of Health  and the regulations for use of animals in experimentation. The study protocol was approved by the Research Ethics Committee, Wuxi Fisheries College of Nanjing Agriculture University .L. vannamei were challenged with pure GYX2014-1 cultures to test bacterial pathogenicity. L. vannamei were raised for three days before being infected by bath immersion. The bacteria were inoculated aseptically in TSB liquid medium at concentrations of 1×108, 5×107, 1×107, 5×106 and 1×106 CFU·mL-1 and incubated for 24 h at 160 rpm. Each concentration was divided into three groups of 20 shrimp each and sterile TSB liquid medium was established as the control group at the same time. After inoculation, L. vannamei were fed in an isolation tank. Dead shrimp were selected as standard isolates to study GYX2014-1 pathogenicity.Healthy 2S generation, glucose gas, nitrate reduction and other tests, in order to determine their physiological and biochemical characteristics.The bacterial isolates were systematically evaluated  for the Pure isolated bacterial cultures were inoculated in nutrient broth, incubated at 30°C for 24h and collected at 12000 rpm for 1min. DNA was extracted and used as a PCR template using the UNIQ-10 column bacterial genome extraction kit (Sangon Biotech (Shanghai) Co., Ltd., China), according to the manufacturer’s instructions.The specific test methods and parameters of 16s rRNA gene sequence analysis from isolates are mentioned in Teng’s method , the reaThe NCBI BLAST database was used to analyse sequence homology for extracted 16S rRNA gene sequences. The software ClusterX2.0 and strain sequences obtained from the GenBank database of nucleic acid sequences which showed high similarity to extracted 16s rRNA were used to perform multiple sequence alignment, following which a phylogenetic tree was constructed using the adjacent method by MEGA5.1 software and tested by bootstrap (1000 repetition).V. vulnificus strains was determined by routine agar diffusion method (K-B) under aseptic technique. After determining the bacterial concentration to be (1×107)-(1×108) CFU·mL-1, the ring of inhibition was used to categorize the unknown bacteria as either susceptible or resistant [Sensitivity to commonly used antimicrobial drugs of esistant . Drug seColony morphology is an important characteristic of the bacteria identification. In this study, we have obtained an advantage growth of monoclonal colony after separation and purification, which is smooth, circular, transparent, central bulge, 2mm in diameter. Colonies were Gram-negative.Vibrio spp. vary in living organisms, and their rapid and accurate identification has been a problem [The phenotypic characteristics of  problem . Strain Bergey’s Manual of systematic bacteriology, Second edition [Common Bacterial System Identification Manual [The results of the physiological and biochemical tests are shown in  edition  and Commn Manual .Vibrio spp., with 99% similarity to V. vulnificus, and 94% similarity to V. cholerae (GenBank accession number: KF386612). Constructed phylogenetic tree analysis showed that the isolated bacteria were most closely related to V. vulnificus (GenBank accession number: NR 118570) and the farthest from V. cholerae (GenBank accession number: KF386612) (The length of the PCR product was 1448 bp (GenBank accession number: KT781675). The results retrieved were 16s rRNA gene sequences of F386612) .In accordance to NCCLS criteria , the diaL. vannamei infected by artificially injecting different doses of isolated bacterium showed different mortality rates, while the control group had no death during the experimental observation period  and V. harveyi (1–7%) which were identified in the coastal farms of India [V. parahaemolyticus was found in aquatic products from hypermarkets in Shanghai [Vibrio species—V. cholera was detected in L. vannamei [Vibrios increases the risk of infection, and even causes severe food poisoning to humans. Therefore, the study of Vibrios isolated from diseased aquatic animal is of great importance.Bacteria of d safety —their prof India . FoodborShanghai  and BeijShanghai , and thevannamei , 33. EatV. vulnificus is one of the most dangerous bacteria [V. vulnificus by eating raw seafood or having contact with seawater via the gastrointestinal mucosa by swallowing or broken skin contact. Based on differences in biochemical, genetic, and serological tests and preferred host for infection, V. vulnificus are divided into three kinds of biological type: biological type I produce indole, biological type II does not produce indole, biological type III [V. vulnificus is an important pathogenic bacterium of "Human and shrimp disease" and have received wide attention in medical science and shrimp disease science. A deeper understanding of the microbiological characteristics of V. vulnificus can assist in prevention and clinical treatment of bacterial diseases infected by V. vulnificus.bacteria , humans type III  all are L. vannamei was confirmed as pathogens, which are highly pathogenic to L. vannamei. The onset of symptoms was the same as the naturally infected shrimp confirming as the identity of the bacteria which caused the devastating deaths of L. vannamei in the Gaoyou area of Jiangsu Province. In this paper, the drug sensitivity test results were generally consistent with previous research [V. vulnificus to be sensitive to cefotaxime, ceftazidime, and cotrimoxazole. However, tetracycline is confirmed as the most effective antibiotic for use in systemic septicemia infections [The dominant bacteria isolated from artificially infected, diseased research , which sfections —inconsisL. vannamei, the morphology, enzymatic activity, physiological and biochemical characteristics 16S rRNA sequence and sensitivity to antibiotics by bacterial isolates, the identity of bacteria extracted from L. vannamei was judged to be highly pathogenic V. vulnificus. This is the first time V. vulnificus from moribund L. vannamei was extracted while the separation and identification of V. vulnificus has been performed in other aquatic animals such as eel [Synechogobius hasta [V. vulnificus disease timely and effectively is required. Other researchers have found that polysaccharides added in the feed could improve the immune function of L. vannamei [Upon considering the histopathological features of dead h as eel , stone fh as eel  and Syneus hasta . The estvannamei , which pS1 Table(PDF)Click here for additional data file.S2 Table(XLSX)Click here for additional data file.S1 Text(DOCX)Click here for additional data file.


Conceiving the process of biogenesis as the evolutionary development of highly dynamic and integrated protocell populations provides the most appropriate framework to address the difficult problem of how prebiotic chemistry bridged the gap to full-fledged living organisms on the early Earth. In this contribution we briefly discuss the implications of taking dynamic, functionally integrated protocell systems  as the proper units of prebiotic evolution. We highlight, in particular, how the organisational features of those chemically active and reactive protocells, at different stages of the process, would strongly influence their corresponding evolutionary capacities. As a result of our analysis, we suggest three experimental challenges aimed at constructing protocell systems made of a diversity of functionally coupled components and, thereby, at characterizing more precisely the type of prebiotic evolutionary dynamics that such protocells could engage in. Living beings on Earth, even in their simplest prokaryote versions, are extremely complex systems, made of a great diversity of molecular components in continuous transformation and interaction. At the base level, each cell is sustained by means of an impressive biopolymer apparatus, which essentially consists of proteins and nucleic acids carrying out complementary tasks to orchestrate an intricate and heterogeneous dynamic organisation with surprising robustness. In addition, this organisation always involves an endogenously synthesized boundary that protects those components/processes from the surrounding milieu and, not less importantly, provides a selective interface that couples them to that external environment. Indeed, all known organisms  intrinsically depend, both in material and energetic terms, upon a variety of processes that take place across their boundaries – lipid membranes in/on which highly sophisticated mechanisms of transport and energy transduction reside, making possible the maintenance of the system, as a whole, in open, far-from-equilibrium conditions. In a metaphoric sense, a cell is a special type of “nano-factory”, whose molecular machinery conducts chemical syntheses from simpler precursors and uses the products of that complex chemical activity for its continuous reinforcement, managing to re-fabricate the complete synthesis machinery itself.The problem of origins of life consists in finding a plausible sequence of transitions from abiotic physical and chemical processes towards this level of molecular and organisational complexity, unparalleled by any other phenomena that we observe in the natural world. Therefore, facing this challenge always involves making a strong set of simplifying assumptions, both in terms of the molecular and the organisational features of life as we currently know them. The simplifications tried so far have met with limited success, probably because they represent oversimplifications. From a historical perspective, one can say that the extraordinary success of molecular biology led a whole generation of origin-of-life researchers to believe that the initial steps towards life could be performed by molecules of a single kind . Then, for years, a strong debate was established in the field about, precisely, what kind of molecule  came first, analysing either the abiotic pathway of synthesis that could have brought it about, or the reactive processes that it could have provoked . Fortunately, following the advent of systems biology at the turn of the century, an increasing awareness about the irreducibility of living phenomena to a specific type of molecular mechanism is extending throughout a new generation of scientists, including those interested in the problem of origins –2.In this context, we would like to bring to the fore a fundamental but clearly underappreciated aspect of biological phenomenology: namely, the diversity of components and phase heterogeneity it involves. Aqueous solution chemistry is important for life, but one should not forget that all living organisms require additional physicochemical processes that take place in environments where water is excluded, to different extents. Luckily, we are not alone in the recognition of this basic biological feature: researchers exploring ‘molecular crowding’ –5 share Under this general hypothesis, one can distinguish two major avenues of research. According to the first, organic compartments of different types  would initially play the role of harbouring surfaces or hydrophobic domains, on which several prebiotic compounds might be adsorbed, in such a way that their chemical reactivity is promoted, leading to more intricate transformation networks and molecular species of various kinds. Several models have been suggested in this direction, from the classical coacervates of Oparin’s  and moreorganisation and for others trying to determine the first steps of biological evolution.Nevertheless, without denying the important role that all these (hard and soft) surface- or interface-chemistry scenarios could play in order to discover reaction pathways to diverse organic compounds, the majority of ‘compartment-first’ approaches have focused on a second research objective: capturing cell-like behaviours by means of vesicle model systems. Compartmentalization could initially be tried with a two-phase system  but liposome research techniques, developed during the twentieth century, allowed the in vitro exploration of many – both structural and dynamic – properties of supramolecular assemblies that involve, at least, three-phases (water-membrane-water) and show a striking resemblance to biomembranes, despite their much simpler composition and functional capacities  can be brought together by means of a general scheme of prebiotic transitions that puts ‘protocells’ at the very centre, as the prime axis of the process of biogenesis see . FurtherAs Szostak  has alsoChallenge 1: coupling chemistry with vesicle dynamics. A special effort should be made to discover simple reaction networks whose products include amphiphiles or surfactant molecules that can be spontaneously absorbed by pre-existing vesicles, modifying their basic properties  and displacing them, as a result, from their primary quasi-equilibrium states . In turn, vesicle dynamics should prove supportive of – or at least compatible with – that chemistry.Cell physiology shows us that endogenous synthesis is a necessary condition to consider a molecular component functional in the most basic biological sense: that is, functional with regard to the (proto-metabolic) organisation that it belongs to. According to this organisational conception, more extensively argued for in –46, a coCompartmentalized chemistry, fortunately, is very rich in terms of possibilities for coupling different types of processes and, thereby, its careful exploration is bound to lead us towards proper proto-cellular and proto-metabolic systems . The degree of molecular inter-specificity and functional integration achieved in a first protocellular scenario may be modest, but it is important that both kinetic control and spatial control mechanisms are included in the equation from the beginning, so that they can complement each other in their development. For an interesting bottom-up synthetic-biology example of how this can be approached, see .Challenge 2: finding conditions and mechanisms for minimal functional integration. A focused search for the specific experimental conditions and the set of molecular interaction mechanisms  that lead to minimal functional systems should be pushed forward. The proto-cellular scenario proposed in this commentary makes explicit the need to combine, at least, kinetic and spatial control mechanisms in order to achieve this goal – which would certainly be a major breakthrough, even if the robustness of those initial functional systems proved relatively modest with regard to extant cells.Only through time and selection pressure may those initial elementary functions become more refined and intermolecularly specific, leading to stronger modes of functional integration. But in order to walk that pathway, natural selection (NS) and evolutionary dynamics must come to the picture, too. Obviously, it is not legitimate to assume that the exquisite molecular machinery currently responsible for matter transport or energy transduction in cells , even if they constitute a common feature across all living domains , could bCompetition–selection experiments carried out among different vesicle populations –35 have The main advantage of a scheme of transitions like the one portrayed in A possible – though still tentative – narrative would proceed as follows: initially,  fatty acChallenge 3: characterizing the evolutionary dynamics of pre-Darwinian protocells. Rather than focusing on the reaction kinetics and evolutionary dynamics of populations of naked nucleic acid molecules (the core idea underlying the ‘RNA world’ hypothesis), or even compartmentalised chemistries run by poly-nucleotides , protocell systems with molecular components of much lower molecular complexity should be investigated as units of pre-Darwinian evolution. The overarching question then becomes: how can far-from-equilibrium chemical assemblies that involve low-molecular-weight species be launched in the lab, so that they manage to divide with regularity, explore an ample range of – sufficiently robust – phenotypes, and have potential to set up mechanisms for increasingly reliable heredity?the answer . It is probably too early to draw conclusions and try to make generalizations when we still lack the relevant empirical results .Elucidating the molecular, organisational and evolutionary innovations leading to the major transitions in the process of origins of life will surely require the effort of many research groups in the future. To our eyes, at least, the bottlenecks represented in


The prefrontal cortex (PFC) is divided into subregions, including the medial and orbital prefrontal cortices. Dopamine connectivity in the medial PFC (mPFC) continues to be established throughout adolescence as the result of the continuous growth of axons that innervated the nucleus accumbens (NAcc) prior to adolescence. During this period, dopamine axons remain vulnerable to environmental influences, such as drugs used recreationally by humans. The developmental trajectory of the orbital prefrontal dopamine innervation remains almost completely unstudied. Nonetheless, the orbital PFC (oPFC) is critical for some of the most complex functions of the PFC and is disrupted by drugs of abuse, both in adolescent humans and rodents. Here, we use quantitative neuroanatomy, axon-initiated viral-vector recombination, and pharmacology in mice to determine the spatiotemporal development of the dopamine innervation to the oPFC and its vulnerability to amphetamine in adolescence. We find that dopamine innervation to the oPFC also continues to increase during adolescence and that this increase is due to the growth of new dopamine axons to this region. Furthermore, amphetamine in adolescence dramatically reduces the number of presynaptic sites on oPFC dopamine axons. In contrast, dopamine innervation to the piriform cortex is not protracted across adolescence and is not impacted by amphetamine exposure during adolescence, indicating that dopamine development during adolescence is a uniquely prefrontal phenomenon. This renders these fibers, and the PFC in general, particularly vulnerable to environmental risk factors during adolescence, such as recreational drug use. Dopamine function in the orbital prefrontal cortex (oPFC) underlies many complex cognitive tasks and is disrupted by drugs of abuse. However, the developmental trajectory of the dopamine innervation to this portion of the PFC remains almost completely unstudied. We show that dopamine axons continue to innervate the oPFC during adolescence. This renders these axons particularly vulnerable to environmental influences. Exposure to amphetamine, at doses equivalent to those used recreationally by adolescent people, reduces the number of dopamine connections in the oPFC. This effect is selective; it also occurs in the medial PFC (mPFC) but not in the piriform cortex. The impact of amphetamine on cortical dopamine development in adolescence appears to be a uniquely prefrontal phenomenon.The prefrontal cortex (PFC) is one of the last brain regions to mature, with changes in structure and connectivity continuing through adolescence and into early adulthood . In paraDopamine connectivity in the mPFC continues to be established throughout adolescence and into early adulthood in both rodents and primates . In miceWhether the dopamine innervation to the orbital PFC (oPFC) also continues through adolescence remains understudied but see . In rodeThere is a longstanding controversy surrounding the designation of the PFC in the rodent and whether it is truly homologous to the PFC in the primate . HoweverIn this study, we first characterized the adolescent dopamine innervation to the oPFC in mice. We then examined whether exposure to amphetamine in adolescence affects oPFC dopamine development. To determine if the adolescent trajectory of the dopamine innervation to the PFC is unique, we conducted parallel studies in the adjacent piriform cortex, which is not part of the PFC.Experiments and procedures were performed in accordance with the guidelines of the McGill University animal care committee’s regulations. Mice were received from Charles River Canada and housed with same-sex littermates at the McGill University Neurophenotyping Center on a 12/12 h light/dark cycle with ad libitum access to food and water. In this study we define “early adolescence” in C57/BL6 mice as between the weaning day [postnatal day (PND)21] and PND32 . Male miD-amphetamine sulfate  was dissolved in 0.9% saline. Mice were assigned to “drug” and “saline” groups and received one injection of either amphetamine (dose: 4 mg/kg) or saline via intraperitoneal injection once every other day for a total of five injections. This treatment regimen was administered during early adolescence, commencing on PND22 ± 1 and terminating on PND31 ± 1. This regiment has previously been shown to alter mPFC development when administered in early adolescence but not adulthood .We chose a dose of amphetamine that would achieve a blood plasma concentration in rodents  within tMice were euthanized with an intraperitoneal injection of 50 mg/kg ketamine, 5 mg/kg xylazine, and 1 mg/kg acepromazine. They were then perfused intracardially with 10 IU/ml heparinized saline followed by 4% paraformaldehyde. Both perfused solutions were pH adjusted to between 7.2 and 7.4 with dilute hydrochloric acid and sodium hydroxide. After perfusion, brains were dissected from the skull, placed in 4% paraformaldehyde overnight at 4°C, and then stored in phosphate-buffered saline at 4°C. After up to 2 d in storage, brains were cut coronally into 35-μm-thick sections on a vibratome.Every second section was processed for immunofluorescence. A polyclonal rabbit anti-tyrosine hydroxylase  antibody  and an Alexa Fluor 594-conjugated polyclonal donkey anti-rabbit antibody  were used as primary and secondary antibodies. The manufacturer’s certificate of analysis reports that the immunogen for the primary antibody is denatured TH from rat pheochromocytoma. Its specificity has been verified by Western blotting (Millipore) and immunoprecipitation . The fibTo prove conclusively that the protracted dopamine innervation to the oPFC during adolescence is due to new axon growth and not the branching of fibers that reached the oPFC earlier in life, we adapted an axon-initiated viral transduction technique  to track2O) throughout recovery for pain management.Early adolescent (PND22 ± 1) wild-type mice were anesthetized with isoflurane. Simultaneous unilateral stereotaxic infusions of DIO-eYFP into the VTA and CAV-Cre into the NAcc were performed using Hamilton syringe needles. Coordinates were previously verified by viral and/or dye injection . The cooContours of oPFC subregions and the piriform cortex were delineated on sections corresponding to plates 14–20 of the mouse brain atlas, resulting in delineations on five sections per region per mouse . We deliPrevious work in the mPFC that uses similar methods delineates only the dense dopamine innervation present in the deep cortical layers . However2 was superimposed on each contour, starting at a random point within the contour. Unbiased counting frames (25 μm2) were placed in the top left corner of each grid square. Depending on the area of the region of interest, between 10 and 35 counting frames were quantified per delineation. Counting was conducted at 100× magnification on every other mounted section using a counting depth of 10 μm and a guard zone of 5 μm. Section thickness was measured while counting and counts were performed blind by a single individual. To assess the volume of each delineated region we used the Cavalieri volume estimation method in Stereoinvestigator, with a grid of 100 μm2. To calculate varicosity density for each region of interest in each brain, we divided the total varicosity estimates obtained using the optical fractionator by the estimated volume obtained using the Cavalieri estimator.Each cortical subregion was traced at x 5 magnification with a Leica DM400B microscope and Stereoinvestigator software (MicroBrightField). To estimate the number of labeled varicosities, we used the optical fractionator probe function of Stereoinvestigator. We counted TH+ and eYFP+ varicosities, as well as double-labeled varicosities, as appropriate for each experiment. Varicosities were defined as dilated elements associated with axonal processes and were thus only counted if they were clearly associated with an axon . A grid Varicosities were used as the counting unit to obtain a measure of dopamine presynaptic density because nearly every dopamine varicosity in the PFC forms a synapse . Varicost tests, corrected for multiple comparisons using the Hochberg-Bonferroni procedure  or treatment  as fixed factors, mouse as the random factor, and varicosity density as the response variable. Each age and treatment group had a sample size of four mice. Subsequently, we conducted Student’s rocedure , between10.1523/ENEURO.0372-17.2017.ed1Extended Data LegendsExtended Data Figure 1-1. Dopamine (TH-immunopositive) varicosity density estimates for four subregions of the oPFC in adult and early adolescent mice. Varicosity density was estimated by combining the optical fractionator and Cavelieri estimator methods of the software program Stereoinvestigator . These data were used to generate the results presented in Results, Dopamine innervation to the oPFC is protracted across adolescence, and Figure 1.Extended Data Figure 2-1. Density estimates of dopamine  varicosities that have been infected with a fluorescent protein-expressing virus for four subregions of the oPFC in adult and early adolescent mice. Varicosity density was estimated by combining the optical fractionator and Cavelieri estimator methods of the software program Stereoinvestigator . These data were used to generate the results presented in Results, Delayed dopamine innervation to the oPFC results from ongoing axon growth, and Figure 2.Extended Data Figure 3-1. Dopamine (TH-immunopositive) varicosity density estimates in four subregions of the oPFC in adult mice treated with either saline or amphetamine in early adolescence. Varicosity density was estimated by combining the optical fractionator and Cavelieri estimator methods of the software program Stereoinvestigator . These data were used to generate the results presented in Results, Amphetamine in adolescence reduces dopamine varicosity density in the adult oPFC, and Figure 3.>Extended Data Figure 4-1. Dopamine (TH-immunopositive) varicosity density estimates for the piriform cortex in adult and early adolescent mice. Varicosity density was estimated by combining the optical fractionator and Cavelieri estimator methods of the software program Stereoinvestigator . These data were used to generate the results presented in Results, Dopamine innervation to the piriform cortex is not protracted nor influenced by amphetamine in adolescence, and Figure 4B.Extended Data Figure 4-2. Dopamine (TH-immunopositive) varicosity density estimates for the piriform cortex in adult mice treated with either saline or amphetamine in early adolescence. Varicosity density was estimated by combining the optical fractionator and Cavelieri estimator methods of the software program Stereoinvestigator . These data were used to generate the results presented in Results, Dopamine innervation to the piriform cortex is not protracted nor influenced by amphetamine in adolescence, and Figure 4C. Download Tables, DOCX file.F = 9.904, p = 0.019, no significant effect of region, F = 1.30, p = 0.305, or age × region interaction, F = 2.47, p = 0.095). Post hoc Hochberg-corrected t tests revealed that dopamine innervation increases during adolescence in the loPFC (t(6) = 3.091, p = 0.021), daiPFC (t(6) = 3.062, p = 0.022), and vaiPFC (t(6) = 6.282, p = 0.0008), but not in the voPFC (t(6) = 1.495, p = 0.186). Visual comparison of densities between adolescence and adulthood in the voPFC  = 15.12, p = 0.008, no significant effect of region, F = 0.42, p = 0.670, or age × region interaction, F = 3.68, p = 0.057). Post hoc Hochberg-corrected t tests revealed that dopamine varicosities were reduced in the daiPFC (t(6) = 4.987, p = 0.003) and vaiPFC (t(6) = 3.630, p = 0.011), while the effect in the loPFC was marginal (t(6) = 2.370, p = 0.056).Amphetamine in adolescence has been found to reduce the number of presynaptic sites from mPFC dopamine axons, measured as a significant reduction in dopamine varicosity density . Here, wt(6) = 8.256, p = 0.0002).We measured dopamine varicosity density in the piriform cortex, a cortical region that is not part of the PFC, in adolescent and adult mice. In contrast to the mPFC  and oPFCt(6) = 0.7985, p = 0.455). This indicates that it is specifically the dopamine innervation to the PFC that is sensitive to amphetamine during adolescence.In addition, amphetamine during adolescence does not alter dopamine varicosity density: levels are similar between adult mice treated with drug or saline in adolescence  is responsible for coordinating dopamine axon structure and function in the mPFC . ReducinThe piriform cortex, part of the mammalian olfactory cortex, is structurally and functionally linked to the oPFC in rodents and humans  and in rTaken together, our results show that dopamine development to the oPFC is delayed across adolescence. Importantly, we have found that this delayed growth is due to axons that previously innervated the NAcc leaving this region and growing to the oPFC during this period. Furthermore, we show that these axons are vulnerable to environmental influences such as exposure to addictive drugs. Amphetamine exposure during early adolescence results in reduced synapse formation in the oPFC. Finally, dopamine innervation to the piriform cortex reaches adult densities before adolescence, indicating that delayed growth of dopamine axons, and the associated vulnerability to environmental influences, is specific to the PFC.


Scientific Reports6: Article number: 34920; 10.1038/srep34920 published online: 10112016; updated: 02102017.The affiliations for authors Valentin Le Douce, Sebastian Eilebrecht, Benoit Van Driessche, Roxane Verdikt, Yoshihito Kurashige, Céline Marban, Virginie Gautier, Arndt G. Benecke, Carine Van Lint and Olivier Rohr were incorrect in the original version of the article. The correct affiliations are listed below.Valentin Le DouceUniversité de Strasbourg, DHPI EA7292, F-67000 Strasbourg, FranceUniversité de Strasbourg, IUT Louis Pasteur, Schiltigheim, FranceUCD Centre for Research in Infectious Diseases (CRID) School of Medicine and Medical Science, University College Dublin, IrelandSebastian EilebrechtInstitut des Hautes Etudes Scientifiques—Centre National de la Recherche Scientifique, 35 route de Chartres, 91440 Bures sur Yvette, FranceDeutsches Krebsforschungszentrum, Im Neuenheimer Feld 242, Heidelberg 69120, GermanyBenoit Van DriesscheUniversité Libre de Bruxelles (ULB), Service of Molecular Virology, Institute for Molecular Biology and Medicine (IBMM), 12 rue des Profs Jeener et Brachet, 6041 Gosselies, BelgiumRoxane VerdiktUniversité Libre de Bruxelles (ULB), Service of Molecular Virology, Institute for Molecular Biology and Medicine (IBMM), 12 rue des Profs Jeener et Brachet, 6041 Gosselies, BelgiumYoshihito KurashigeUniversité de Strasbourg, Inserm UMR 1121, place de l’Hôpital Strasbourg, FranceCéline MarbanUniversité de Strasbourg, Inserm UMR 1121, place de l’Hôpital Strasbourg, FranceVirginie GautierUCD Centre for Research in Infectious Diseases (CRID) School of Medicine and Medical Science, University College Dublin, IrelandArndt G. BeneckeInstitut des Hautes Etudes Scientifiques—Centre National de la Recherche Scientifique, 35 route de Chartres, 91440 Bures sur Yvette, FranceUniversité Pierre et Marie Curie, CNRS UMR 7224, 7 quai Saint Bernard, 75005 Paris, FranceCarine Van LintUniversité Libre de Bruxelles (ULB), Service of Molecular Virology, Institute for Molecular Biology and Medicine (IBMM), 12 rue des Profs Jeener et Brachet, 6041 Gosselies, BelgiumOlivier RohrUniversité de Strasbourg, DHPI EA7292, F-67000 Strasbourg, FranceUniversité de Strasbourg, IUT Louis Pasteur, Schiltigheim, FranceInstitut Universitaire de France, Paris, FranceThese errors have now been fixed in the HTML and PDF versions of the Article.


We built and validated a conceptual system dynamics model based on these data that explained 79% of the variance in the hiring of assistant professors and posited no hiring discrimination. Simulations show that, given current transition rates of scientists from URM backgrounds to faculty positions, faculty diversity would not increase significantly through the year 2080 even in the context of an exponential growth in the population of PhD graduates from URM backgrounds, or significant increases in the number of faculty positions. Instead, the simulations showed that diversity increased as more postdoctoral candidates from URM backgrounds transitioned onto the market and were hired.Faculty diversity is a longstanding challenge in the US. However, we lack a quantitative and systemic understanding of how the career transitions into assistant professor positions of PhD scientists from underrepresented minority (URM) and well-represented (WR) racial/ethnic backgrounds compare. Between 1980 and 2013, the number of PhD graduates from URM backgrounds increased by a factor of 9.3, compared with a 2.6-fold increase in the number of PhD graduates from WR groups. However, the number of scientists from URM backgrounds hired as assistant professors in medical school basic science departments was not related to the number of potential candidates (RDOI:http://dx.doi.org/10.7554/eLife.21393.001 Enhancing the diversity of the research workforce has been a longstanding priority of scientific funding agencies . ScientiFaculty members play critical and unique roles within the scientific enterprise, shaping the national research agenda, and cultivating the next generation of scientists and scholars . HoweverThis work focuses on three possible reasons for the low number of scientists from URM backgrounds in the professoriate relative to their peers from well-represented (WR) backgrounds  that are amenable to intervention by the scientific community: (i) the size of the URM PhD talent pool, (ii) the number of available faculty positions, and (iii) the transition of the available URM PhD and postdoctoral talent pool onto the faculty job market, and their subsequent hiring. Educational disparities between students from URM and WR backgrounds begin early in life, and accumulate from K-12 through early independence . Thus, iAdditionally, current faculty diversity efforts occur against the backdrop of systemic changes within biomedicine. Following the doubling of the NIH budget between 1998 and 2003, there was a significant increase in the number of PhDs awarded, without commensurate increase in the number of faculty positions . This leBeyond the number of faculty positions available, there is evidence that graduate students and postdocs from all backgrounds lose interest in faculty careers in research-intensive universities as their training progresses . MoreoveIncreasing diversity in the applicant pool and equitable evaluation in the hiring process are strategies that promote faculty diversity . While sThe static nature of faculty diversity, especially in research-intensive environments, suggests that new approaches are necessary for achieving the goal of workforce diversity. In particular, computational modeling approaches such as System Dynamics (SD) have been used to examine the macro-scale impacts of potential policy interventions on the biomedical postdoctoral workforce , and newProvide a systematic and quantitative perspective on changes in the numbers of biomedical PhDs and assistant professorships in medical school basic science departments by scientists from URM and WR backgrounds between 1980-2014.Build and validate a System Dynamics (SD) model that can capture major trends in the career progression of PhD scientists from URM and WR backgrounds into this segment of the professoriate.Utilize the SD model to test the impact of various intervention strategies to faculty diversity in the short-term (through 2030) and long-term (through 2080). Specifically, we model the impact on faculty diversity at the assistant professor stage by increasing: (i) the size of the talent pool of PhDs from URM backgrounds, (ii) the number of assistant professor positions available, or (iii) the rate of transition of PhDs from URM backgrounds into the applicant pool of assistant professorships.We focus on medical school basic science departments because of the availability of comprehensive, longitudinal demographic data . Our go−7; PhD graduates relative to assistant professors), above the impacts URM status , position alone , or the increases that occurred as the system grew through time .For both URM and WR populations, there was significant growth in the number of PhD graduates, and significant yet slower growth in the population of assistant professors . Howeverfewer URM assistant professors in basic science departments in 2014 than in 2005 (n=341 in 2014 versus 347 in 2005). For scientists from WR backgrounds, there was 31% growth in the annual number of PhD graduates (n=8789 in 2013 compared to n=6703 in 2005) and 8.6% growth in the population of assistant professors (n=5562 in 2014 compared to n=5122 in 2005). Thus, while the populations of PhD graduates and assistant professors has grown since 1980 for scientists from all backgrounds, the magnitude of the growth of PhD graduates relative to assistant professors differed greatly between URM and WR scientists.Between 2005-2013, a total of 5,842 biomedical PhDs were awarded to scientists from URM backgrounds; however, there were six 2=0.12, p=0.07; 2=0.48, p=2.54*10−5; −4), while for scientists from WR backgrounds the proportion of the potential candidate pool hired did not change significantly over time . Thus, despite growth in the pools of potential URM and WR candidates, the nature of entry into assistant professor positions differed significantly between the two populations, with little connection between the size of the URM available candidate pool, and the numbers entering into assistant professor positions  the number of positions available, and 2) the number of candidates pursuing these positions. Candidates on the market are composed primarily of the subset of postdoctoral scientists pursuing faculty careers in medical school basic science departments . Based The model also posits that URM and WR candidates are hired in direct proportion to their representation on the market. That is, the model’s output assumes that that racial bias does not impact hiring. Further, the model assumes that differences in relative strength on the job market across URM status do not impact hiring, because URM PhD graduates have lower interest in faculty careers in research-intensive environments than WR PhDs graduates even if they have graduated from the same institutions and have the same levels of scholarly productivity .Based on the analyses presented above, the career pathways for scientists from URM and WR backgrounds were represented separately, but were linked based on the total number of assistant professor slots available. Within each population, we assumed a fixed proportion of graduates would pursue and enter faculty positions in research-intensive environments (i.e. "faculty aspire”). The size of the “faculty aspire" pool was based on hiring trends 1980-1997, before the NIH budget doubling and subsequent expansion of the biomedical PhD pool. All other PhDs would pursue other careers (i.e. “other aspire”). Without intervention, the “faculty aspire” and “other aspire” populations grow in proportion to the total number of PhD graduates (i.e. “baseline PhD graduate growth rate”). We further assumed that efforts by the scientific community to enhance the diversity of the PhD pool (“URM target growth rate”) would increase the pool of URM “other aspire” PhDs, some of whom will then transition to the faculty market. Key variables—including baseline PhD graduate growth rate, URM target growth rate, proportions of URM or WR scientists pursuing faculty positions, and the number of positions available—were derived from national survey data, while the transition rate represented a free parameter for analysis. Full details of the model are provided in the methods section and model equations and parameter values are presented in Appendix-Tables 1 and 2.2=0.99, p<0.0001; 2=0.96, p<0.0001; 2=0.79, p<0.0001; 2=0.51, p<0.0001), and 78% of the variance in WR assistant professor hiring . The model predicted if the URM PhD population continued to grow at an exponential rate through 2080, 73% of PhDs would be URMs (at which point these populations would no longer be underrepresented). However, in the presence of the 0.25% transition rate, the model predicted that in 2080 fewer than 10% of assistant professors would be URMs, no matter the number of positions available . In contIncreasing faculty diversity in academic science departments has been a long-standing challenge and has received renewed attention in recent years . Here, wAlthough the dearth of URM faculty members in medical schools typically has been framed as a "pipeline" problem—i.e. a lack of available URM talent—our analysis shows that the rate of PhD production for scientists from URM backgrounds has increased significantly over the past 33 years, and at a faster rate than that of WR scientists. Despite this progress, there was no statistical linkage between the size of the pool of URM talent, and the number of URM assistant professors hired in basic science departments of medical schools –are insuObtaining an assistant professorship position requires, at a minimum: (i) a position to be available; (ii) a candidate to be interested in and apply for the position; and (iii) the applicant to be favorably evaluated, offered the position and ultimately accept the position. Systematic data on the applications, evaluations, offers and acceptances for assistant professor candidates in any academic discipline are not typically made available , thus we were unable to include this information in the model. However, a recent study has shown that inequality and hierarchy characterize assistant professor hiring across disciplines, and that prestige of doctoral institution plays a major role in who is hired . While 8Beyond institutional pedigree, previous work has shown that interest in assistant professor careers at research-intensive universities such as medical schools declines as training progresses , and theIndeed, prominent scientists from URM backgrounds have written about the unique experiences, challenges, and biases (implicit and explicit) faced while conducting science in these environments . FurtherThe modeling data we presented indicate that given current rates of transition from PhD to assistant professorship among URMs, the percentage of URM assistant professors in basic science departments of U.S. medical schools could remain below 10% in the short- and long-term (i.e. by 2080), even in the context of exponential growth of the URM PhD and postdoctoral pool and the absence of discrimination. Thus, faculty diversity efforts that rely primarily on enhancing rates of PhD graduates (i.e. “filling the pipeline”) can only have their desired impact if they are coupled with efforts to get these candidates on the market and hired. This would require making faculty positions and work environments attractive and supportive to these scientists, ensuring the proper types of support  to allow URM postdocs to effectively progress to independence , and ensWhile the challenge of achieving faculty diversity has been longstanding, with concerted and targeted effort, the numeric realities of assistant professor hiring and turnover mean that higher diversity could be achieved relatively quickly among junior faculty. On average, the pool of assistant professors turns over every six years. The analysis presented here demonstrated that in recent years, assistant professor hiring has been relatively stable at around 1000 positions each year . Thus, to achieve parity with the pool of PhD graduates (estimated to grow to 10% URM in 2016) would require hiring around 100 URM assistant professors annually at medical schools. Put another way, if roughly two-thirds of medical schools hired (and retained) just one faculty member from an URM background annually for the next six years, the system would reach parity with the PhD pool within one tenure cycle. While this would still not reflect the proportion of people from URM backgrounds in the overall population (currently greater than 30%), this would represent a meaningful first step to addressing the longstanding goal of enhancing scientific excellence by increasing faculty diversity.Biomedical PhD attainment data were obtained from the National Science Foundation’s Survey of Earned Doctorates (SED), an annual census of individuals receiving research doctorates from accredited U.S. institutions , as compTo determine trends in representation of faculty in medical school basic science departments, we obtained faculty data from the AAMC Faculty Roster, 1980-2014 1 in year one to n2 in year two, and the number of assistant professors leaving in year one was l1, then the number of assistant professors hired in year two (h2) equaled (n2-n1) + l1. Thus, using real data showing that there were n1=132 assistant professors from URM backgrounds in 1980, and n2=129 in 1981, we assumed that one-sixth of the assistant professors left the rank in year 1980 (l1=22), and thus h2=19. These data are shown in To calculate the aggregate number of assistant professors hired each year, we made two assumptions: (i) the length of time that an individual occupied the position of assistant professor was six years based on traditional academic promotion cycles , and simAvailable evidence indicates that scientists who pursue faculty careers in the biomedical sciences remain in postdoctoral training for five or more years . To estiTo determine the relationships between various constructs, we performed statistical analysis in R (version 3.2.2) . SpecifiWe used System Dynamics (SD) to create an abstract model  that couSD is a modeling framework that emphasizes the role of a system’s structure on its ultimate behavior , and hasOur model extends beyond the standard “pipeline” conceptualization of faculty hiring . There aWe expanded upon this standard model in a number of ways See .The number of “faculty aspire” candidates is based upon the number of URM and WR assistant professors hired in the period of 1980-1997 . Without intervention, as the total number of PhD graduates grows, the pools of “URM faculty aspire,” “URM other aspire,” “WR faculty aspire,” and “WR other aspire” are expected grow proportionally. The overall PhD graduate growth rate is represented as a variable termed “baseline PhD graduate growth rate.” This is a piecewise linear function that mirrors the actual growth in the overall number of PhD graduates from 1980- 2013.The model assumes all PhD graduates in the “faculty aspire” stock pursue assistant professorships in research-intensive environments. The remaining graduates pursue other careers and depart the system. Each year, the system attempts to fill all “slots available.” Further, depending on market hiring conditions, 20% of the candidates on the market drop out of the market annually. That is, if the probability of being hired is relatively high (>20%) all candidates remain on the market that year. Otherwise, one-fifth of the available pool drops out of the system. Thus, the “half-life” of a candidate on the market who is not hired is 5 years .Candidates are chosen from the stocks of WR and URM candidates in proportion to their respective representations on the market. For example, if there are 100 slots available, and 25% of the candidates on the market are from URM backgrounds and 75% are from WR backgrounds, then 25 slots will be filled by URMs and 75 slots will be filled by WRs. Although the career development pathways for WR and URM students are separate, the total number of assistant professor slots available links them. If there are not enough candidates to fill all slots, these slots are removed from the system. Specifically, we posit that candidates in a specific group (URM or WR) are hired with likelihood proportional to their representation on the market. That is, the model posits no hiring bias.Beyond the baseline student growth rate, “URM target growth rate”  is a var0”) we used the average number of assistant professors hired from 1980-1997, corresponding to the period before the NIH budget doubling, which drove significant growth of the biomedical enterprise  were then scaled to match empirical trends, resulting in numbers of PhD graduates. The patterns of growth differed between scientists from WR and URM backgrounds . Thus, for scientists from WR backgrounds, we used the difference between the 1980 population of PhD graduates and “WR Faculty Aspire” candidates to calculate the “WR other aspire P0.” For URM scientists, we fit an exponential function to URM student growth data and used the associated coefficient to derive the “URM other aspire P0”.To determine the initial number of faculty aspire candidates for both URM and WR scientists , with a step increase in 1998, when the NIH budget-doubling lead to an era of expansion in the biomedical sciences. Thus, the numbers of slots available from 1980-1997 (n=602.1 slots), and 1998-2013 (n=1064.7 slots) represent the average number of total assistant professors hired during these periods. The final model structure is shown in There are a number of limitations to the analyses presented. Postdoctoral training has become an almost uniform prerequisite to obtaining a faculty position in biomedical research. There are no reliable estimates on the number of postdocs in the US , thus these data were not included in the model . However In the interests of transparency, eLife includes the editorial decision letter and accompanying author responses. A lightly edited version of the letter sent to the authors after peer review is shown, indicating the most substantive concerns; minor comments are not usually included.eLife for consideration as a Feature Article. Your article has been reviewed by two peer reviewers and the eLife Features Editor, and this decision letter has been compiled to help you prepare a revised submission.Thank you for submitting your article "Decoupling of the Minority PhD Talent Pool & Assistant Professor Hiring in Medical School Basic Science Departments" to Summary:This paper attempts to examine issues related to the hiring and retention of PhD underrepresented minorities (URM) in assistant professor positions at academic medical centers. It uses a system dynamics (SD) model to assess expectations of how many PhD URM individuals we should expect to see entering assistant professor positions. While others  have examined issues of representation along the 'pipeline,' this work expands on those efforts by examining specifically issues related to hiring and the flow and stock of assistant professors in academic medicine centers and, specifically, URM hiring. Additionally, the extention to an SD model is a unique analysis for this population and with this data.Essential revisions:1) This might be a discipline issue, but I find it confusing that in the body of the paper and in the figures, the data source is not cited! It is only cited in the back as an appendix of sorts. Data sources should be cited throughout the text and at the bottom of each figure.2) Equation documentation should improve. In your appendix you should use more conventional approaches for model documentation than simple copy-paste of Vensim formula. Also, report all your parameters in a table with proper references (fine if it appears in the Appendix). For model documentation example, see other SD works such as Ghaffarzadegan, Hawley and Desai, 2014.3) Definitions of subgroups need to be more precise. Instead of saying "including[…]" or "(i.e. white)," precise definitions should be clearly articulated within the paper of exactly how subgroups are defined.4) One of the weaknesses of an SD model is that you are not able to account for individual agents' behavior, like in agent-based models. Lots of changes in the external environment  have the potential to influence an individual agent's actions in ways that are not necessarily linear and not accounted for in the model the authors present.5) While the authors acknowledge the issue of postdocs in the supporting documentation, they do not even mention postdocs in the main paper. The reality is that hardly anyone transitions directly from PhD receipt to an assistant professor position, and the postdoc experience is extremely diverse. What if the differences the authors are seeing here are not a result of stalled entrance into the assistant professor position, but rather stalled entrance into a postdoc that will make the individual attractive for an assistant professor position. This dilemma and absence in their model must, at a minimum, be discussed in the body of the paper. Ideally, the authors would be able to incorporate some assumptions about the postdoc phase into their model.6) The authors have no data on who is applying for assistant professor positions (as they acknowledge in the third paragraph of the Discussion). Therefore, there is no way to really claim, as they do, that if institutions increased their efforts to hire more URM, this would increase diversity in the assistant professor pool.7) In the main model there is no drop-out from the pool of people in the market . I see that in your sensitivity analysis you report that you have conducted an analysis of effect of drop-out from the pool of people in the market. Very good, but I would argue that this should be in the main model. You simulate the model until 2080, and by then the whole population has retired and many have died! So, simply replace the results of your sensitivity analysis as the main analysis. I understand that this might not affect the results, but it is a better modeling practice.8) The simulation period of 55 years in future is simply too long. And the assumption that 73% of PhD graduates will be URM feels unrealistic unless you provide evidence . I suggest the authors to simulate for the next 1-2 decades; there are many things that can happen until 2080 which your model cannot predict and are out of the boundary of your analysis.9) One may argue that the reason "URM Faculty Aspire P0" is much smaller than the "WR Faculty Aspire P0" is that you are assuming that hiring in faculty positions is proportional to population of the pools. URM might be weaker in the market or be discriminated. From a modeling standpoint, your model has two degrees of freedom, if you assume there is no "weight" toward hiring WR relative to URM, you end up with much higher "WR Faculty Aspire P0" anyway. I think the best way, but difficult, is to provide some references for this argument (that there is less faculty aspiration among URM). The easier way is to clarify that you are aware of this assumption and discuss its implications in your policy recommendation. You may need to modify your language throughout the paper too. […]Essential revisions:1) This might be a discipline issue, but I find it confusing that in the body of the paper and in the figures, the data source is not cited! It is only cited in the back as an appendix of sorts. Data sources should be cited throughout the text and at the bottom of each figure.We have added the following sentence to the main text and to 2) Equation documentation should improve. In your appendix you should use more conventional approaches for model documentation than simple copy-paste of Vensim formula. Also, report all your parameters in a table with proper references (fine if it appears in the Appendix). For model documentation example, see other SD works such as Ghaffarzadegan, Hawley and Desai, 2014.We have updated equation documentation consistent with the notation used by Ghaffarzadegan et al. (2014). This is now in appendix 1.3) Definitions of subgroups need to be more precise. Instead of saying "including[…]" or "(i.e. white)," precise definitions should be clearly articulated within the paper of exactly how subgroups are defined.We have endeavored to clarify these terms. The Introduction now reads:“Scientists from certain underrepresented minority (URM) racial/ethnic backgrounds – specifically, African American/Black, Hispanic/Latin@, American Indian, and Alaska Native – receive 6% of NIH research project grants  despite having higher representation in the relevant labor market , and constituting 32% of the US population .[…] This work focuses on three possible reasons for the low number of scientists from URM backgrounds in the professoriate relative to their peers from well-represented (WR) backgrounds  that are amenable to intervention by the scientific community”The Methods now read:“To calculate the number of PhD graduates from URM backgrounds, we added together the number of U.S. citizen and permanent resident PhD graduates who identified as one of the following: “Black/African-American (non-Hispanic/Latino),” “Hispanic/Latino,” or “American Indian or Alaska Native” . PhD graduates from all non-URM backgrounds  were called “well represented” (WR).”http://grants.nih.gov/grants/guide/notice-files/NOT-OD-15-053.html), and conventions in the biomedical training and diversity literature:We used definitions of “underrepresented minority” and “well-represented” groups consistent with the NIH definitions  One of the weaknesses of an SD model is that you are not able to account for individual agents' behavior, like in agent-based models. Lots of changes in the external environment  have the potential to influence an individual agent's actions in ways that are not necessarily linear and not accounted for in the model the authors present.https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3737001/), and Ghaffarzadegan and colleagues (examining the impact of different strategies on systems level postdoc diversity: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4215734/). In order to further clarify this point, we have added the additional reference by Larson and Diaz throughout the paper to refer readers to other examples of how SD modeling can be used to address the types of questions posed here.In general, each modeling methodology has its strengths and weaknesses. System Dynamics (SD) models excel at capturing stocks, flows, nonlinear causal loops, and overall aggregate trends. The nature of our data is that they are aggregated and continuous. Thus, for the questions we aimed to address, specifically assessing the impact at an aggregate level of different intervention strategies on flows of PhDs from URM and WR backgrounds into faculty positions, SD modeling techniques are both adequate and preferred. This approach is standard in this domain; see, e.g., Larson and Diaz  is better suited to modeling behavior at the level of the individual. In line with the reviewer’s comments, Bonabeau (2002) notes that ABMs excel when “Individual behavior is nonlinear and can be characterized by thresholds, if-then rules, or nonlinear coupling. Individual behavior exhibits memory, path-dependence, and hysteresis, non-markovian behavior, or temporal correlations, including learning and adaptation. Agent interactions are heterogeneous and can generate network effects.” In the event that we are able to gather data validating the extent to which these heterogeneities lead to systematic sources of error in our results, we hope to use ABM in future work.5) While the authors acknowledge the issue of postdocs in the supporting documentation, they do not even mention postdocs in the main paper. The reality is that hardly anyone transitions directly from PhD receipt to an assistant professor position, and the postdoc experience is extremely diverse. What if the differences the authors are seeing here are not a result of stalled entrance into the assistant professor position, but rather stalled entrance into a postdoc that will make the individual attractive for an assistant professor position. This dilemma and absence in their model must, at a minimum, be discussed in the body of the paper. Ideally, the authors would be able to incorporate some assumptions about the postdoc phase into their model.We thank the referee for pointing out our need for greater clarity, and have modified the main text to more clearly discuss the issue of postdocs. Specifically, we have:Clarified that “candidates on the market” refers primarily to postdocs pursuing faculty positions in medical school basic science departments;Highlighted the fact using the model that includes market drop out , the average half-life for “candidates on the market” who are not hired is five years, and that this consistent with the average length of time for postdoctoral study for candidates pursuing faculty positions in research-intensive environments ;Added a brief discussion of focusing on postdoctoral transitions into the Discussion section.We too recognize the importance of postdoctoral training in career development of biomedical PhDs . As has been noted by elsewhere  data quality about postdocs in the United States remains very poor—estimates about their numbers range from 30,000 – 100,000. Thus, we did not feel there was adequate and rigorous data to include postdocs in the model.https://www.nsf.gov/statistics/2015/nsf15311/tables/pdf/tab8-3-updated-2016-06.pdf; “Location and type of postgraduate activity for U.S. citizen and permanent resident S&E doctorate recipients with definite postgraduate plans, by ethnicity and race: 2014”) indicate that rates of postdoctoral transition are largely consistent across URM and WR status.With respect to question of stalled entrance into postdoc positions by URMs, available data from the NSF  + 0.433*(35.7% African American postdoc rate) + 0.033 (33.3% American Indian/Alaska Native postdoc rate)).Among WR groups, from 2004-2014, Whites were 55.6% of WR PhD graduates, Asians were 9.6% of WR graduates and “Other” ethnicities are 34.8% of WR PhD graduates. Using the NSF rates of postdoctoral study, we see that 42.6% of WR PhD graduates have definitive plans to progress to postdoctoral study (42.6% WR postdoc transition rate = 0.556*(41.7% White postdoc transition rate) + 0.096*(33.9% Asian postdoc transition rate) + 0.348*(44.7% Other” postdoc transition rate). We have added the following sentence to the manuscript when describing the model:“Candidates on the market are composed primarily of the subset of postdoctoral scientists pursuing faculty careers in medical school basic science departments, and current evidence suggests that the rates of transition to postdoctoral training are comparable between URM and WR PhD graduates ”.6) The authors have no data on who is applying for assistant professor positions (as they acknowledge in the third paragraph of the Discussion). Therefore, there is no way to really claim, as they do, that if institutions increased their efforts to hire more URM, this would increase diversity in the assistant professor pool.We agree with the reviewer that systematic data regarding the demographics of faculty applicants would be ideal. However, these data are not available, which we acknowledge in the manuscript, “systematic data are not available on the demographics of faculty applicants.” However, it is established in the higher education and faculty development literature that increasing diversity in the applicant pool is a proven strategy to increase diversity in the professoriate .These data are not likely to become available for many reasons, including confidentiality and legal restrictions (two examples of university HR policies regarding privacy are presented below):http://hr.unc.edu/policies-procedures-systems/spa-employee-policies/personnel-information/personnel-records-and-confidentiality-of-personnel-information/https://hr.uoregon.edu/records/classified-employee-records-and-datahttp://www.nature.com/news/insider-s-view-of-faculty-search-kicks-off-discussion-online-1.19165). Therefore, we feel that it is appropriate to highlight the need to increase applications from URM scientists as a means of enhancing diversity. We have endeavored to clarify this logic in the manuscript and have added the additional references by Moody and Smith .Furthermore, Gibbs et al. 2014 demonstrated that URMs have lower interest in faculty positions at research-intensive universities  in comparison to their WR colleagues. In addition to the authors’ personal experiences , the lack of diversity in a recent applicant pool was emphasized and substantiated by a search committee chair at Harvard: 7) In the main model there is no drop-out from the pool of people in the market . I see that in your sensitivity analysis you report that you have conducted an analysis of effect of drop-out from the pool of people in the market. Very good, but I would argue that this should be in the main model. You simulate the model until 2080, and by then the whole population has retired and many have died! So, simply replace the results of your sensitivity analysis as the main analysis. I understand that this might not affect the results, but it is a better modeling practice.We have replaced the current model to incorporate market drop out and have updated the figures, figure legends, and text appropriately.8) The simulation period of 55 years in future is simply too long. And the assumption that 73% of PhD graduates will be URM feels unrealistic unless you provide evidence . I suggest the authors to simulate for the next 1-2 decades; there are many things that can happen until 2080 which your model cannot predict and are out of the boundary of your analysis.Per the reviewer’s suggestion, we have included a model run ending in 2030.We have kept a longer model run in (through 2080) to illuminate for readers how given a “best case scenario” of a limitless URM talent pool and no discrimination, the current structure would not achieve increased faculty diversity unless there is also an increased transition rate. We have acknowledged in the text that there are many things that are likely to change that would impact long-term predictive capability of the model .9) One may argue that the reason "URM Faculty Aspire P0" is much smaller than the "WR Faculty Aspire P0" is that you are assuming that hiring in faculty positions is proportional to population of the pools. URM might be weaker in the market or be discriminated. From a modeling standpoint, your model has two degrees of freedom, if you assume there is no "weight" toward hiring WR relative to URM, you end up with much higher "WR Faculty Aspire P0" anyway. I think the best way, but difficult, is to provide some references for this argument (that there is less faculty aspiration among URM). The easier way is to clarify that you are aware of this assumption and discuss its implications in your policy recommendation. You may need to modify your language throughout the paper too.Two previous papers by the lead author provide evidence of lower interest in faculty careers at major research universities among scientists from URM backgrounds:Gibbs et al., “Biomedical Science PhD Career Interest Patterns by Race/Ethnicity and Gender,” PLOS ONE 2014 demonstrated that at PhD completion, the URM men and URM women have lower interest than their WR counterparts in faculty positions at research-intensive universities, even when controlling for career pathway interest at PhD entry, first-author publication rate, faculty support, research self-efficacy, and graduate training experiences.Gibbs et al., “Career Development of American Biomedical Postdocs,” CBE Life Sciences Education 2015, showed that in a cross section of American postdocs, URM women had the lowest interest in faculty positions at research-intensive universities of all groups, even when accounting for career pathway interest at PhD entry, first-author publication rate, faculty support, research self-efficacy, and graduate training experiences.Therefore, there is evidence that apart from level of preparation, URMs have lower level of interest in faculty positions at research-intensive universities. We have highlighted these references more clearly in the manuscript .The P0 values were based on imputed hiring trends for scientists from URM and WR backgrounds from 1980-1997. That is, we assumed what happened historically with URM and WR faculty hiring would carry forward as the system grew. We have clarified this in the text.We do make the conservative assumption of no discrimination. We do recognize that discrimination can remain a problem in academic hiring. However, we did not include this in the model because we were unaware of high quality, systemic evidence that could be used to quantify its impact. We have noted in the revised manuscript (subsection “Intervention Strategies to Increasing Assistant Professor Diversity”) that discrimination will further attenuate efforts to enhance faculty diversity. The goal of the model was to highlight to readers that even in the absence of discrimination, increasing faculty diversity will remain a challenge unless there is greater attention to enhancing post PhD  transitions onto the market and their subsequent hiring. We thank the reviewer for helping us to clarify this point.