The mathematical analysis of a syntrophic relationship between two microbial species in a chemostat

  • A mathematical model involving a syntrophic relationship between two populations of bacteria in a continuous culture is proposed. A detailed qualitative analysis is carried out as well as the analysis of the local and global stability of the equilibria. We demonstrate, under general assumptions of monotonicity which are relevant from an applied point of view, the asymptotic stability of the positive equilibrium point which corresponds to the coexistence of the two bacteria. A syntrophic relationship in the anaerobic digestion process is proposed as a real candidate for this model.

    Citation: Tewfik Sari, Miled El Hajji, Jérôme Harmand. The mathematical analysis of a syntrophic relationship between two microbial species in a chemostat[J]. Mathematical Biosciences and Engineering, 2012, 9(3): 627-645. doi: 10.3934/mbe.2012.9.627

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  • A mathematical model involving a syntrophic relationship between two populations of bacteria in a continuous culture is proposed. A detailed qualitative analysis is carried out as well as the analysis of the local and global stability of the equilibria. We demonstrate, under general assumptions of monotonicity which are relevant from an applied point of view, the asymptotic stability of the positive equilibrium point which corresponds to the coexistence of the two bacteria. A syntrophic relationship in the anaerobic digestion process is proposed as a real candidate for this model.


    1. Introduction

    Prostate cancer (PCa) is a global health problem that demands considerable attention as the disease is indolent, shows prolonged latency and PCa progression is associated with high morbidity and mortality [1,2]. In Europe and North America, PCa is the most common malignancy in men and is among the leading causes of death from cancer in males [3,4,5]. The American Cancer Society estimates that more than 2.9 million men in the United States live with prostate cancer, and 180, 000 new cases are expected in 2016.

    Due to the high incidence rates, carcinoma of the prostate is one of the most extensively studied malignancies. Despite this intensive international research PCa aetiology remains unclear. However its three hallmarks are well established: (i) the incidence rate of the PCa drastically increases with age, being three orders of magnitude higher for the age group 40-79 years than for those younger than 40 years [6,7]; (ii) about 80% of PCa tumours are formed in the peripheral zone of the prostate gland [8,9]; (iii) there is a positive association between the risk of PCa and consumption of dairy products [2,10,11,12,13,14].

    The above well-established PCa features, when combined, allow us to hypothesize that there is an etiological factor(s) of malignant transformation, which may be located in, or selectively affects, the peripheral zone of the prostate gland. This effect increases with age and acts synergistically with a factor (or factors) linked to milk and dairy productsconsumption. Because milk and dairy products are the main source of Ca, Ca2+ intake for humans [11,12,13,14,15], we believe that dietary Ca could be such an etiological intra-prostatic factor.

    Ca2+ is a key signaling molecule and is involved in a variety of fundamental biological processes from fertilization to programmed cell death. Almost every tissue and bodily liquid has specific functions that are controlled by Ca2+ and its spatio-temporal levels are tightly regulated by an extensive Ca2+-signalling toolkit [16]. In particular, the prostatic gland differs markedly from other organs and soft tissues because of its relatively high Ca content [17,18]. For example, in the normal prostate Ca accumulates to up to seven-fold higher levels than in the liver and whole blood [19,20]. Further, prostatic Ca levels are age dependent, i.e. they increase from puberty to young adulthood [19,20,21,22,23] and then continue to increase until the age of 55-60 years [24,25,26,27,28].

    Some literature reports Ca content in the prostate parenchyma. According to Deering et al. [29], prostatic parenchyma contains three main components: glandular epithelium (E), prostatic fluid contained in the glandular lumina (L), and fibromuscular tissue or stroma (S). In our previous study, we showed that Ca concentration in the prostatic fluid is almost two times higher than in the prostate parenchyma [23] and the prostatic fluid contained in the glandular lumina is the main pool of prostatic Ca in pediatric and nonhyperplastic young adult prostate glands [22,23]. Also, it was found that the relative volume of the prostatic fluid continues to increase for ages above 30, but the correlation between the Ca content in the prostatic parenchyma and the relative volume of the glandular lumina fades away [26,27,28,30,31]. These findings prompted us to investigate the age-related intracellular changes of Caconcentration in the prostate.

    There are direct and indirect ways to investigate the prostatic intracellular Ca. The direct way includes measurement of Ca concentration in cells using imaging techniques. One of the oldest relevant imaging techniques is the X-ray microanalysis of freeze-dried cryosections [32]. Recently, the X-ray fluorescence (XRF) analysis of tissue Ca using a scanning beam of synchrotron radiation has been used for this purpose [33]. Although the synchrotron offers an extraordinary beam intensity and resolution, the sample preparation method, which can introduce uncertainties, remains a disadvantage of the method. The technique requires cutting the tissue into thin sections and fixing the tissue samples using certain chemicals. During these procedures, some prostatic fluid is lost, and also Ca redistribution in prostate tissue takes place [34,35]. Thus, at best, the results of such studies can only give qualitative data and in the worst case give an erroneous Ca distribution.

    In this study, an indirect but quantitative way of intracellular Ca estimation in the prostate gland was used. The primary purpose was to obtain data about the age-related changes in the morphometrics and Ca concentration in the peripheral zone of the non-hyperplastic prostate gland of healthy males. The second aim was to collect and assess published relevant reports on Ca concentration in the prostatic fluids, and the third aim was to evaluate the changes in the Ca concentration in the intracellular space of the prostate with age.


    2. Materials and Methods

    To clarify the age-dependent histological and Ca concentration changes in peripheral zones of nonhyperplastic prostate glands, a quantitative morphometric and two analytical methods of Ca determination were used. The prostates were obtained from autopsies of 99 subjects (European-Caucasian) aged 0-87 years who died mainly from sudden infant death syndrome, acute pulmonary etiologies (infants), pneumonia (children), and trauma (adults). All subjects were divided into the seven groups listed in Table 1, dependent on their age. The available clinical data were reviewed for each subject. None of the subjects had a history of an intersex condition, endocrine disorder, neoplasm or other chronic disease that could affect the normal development of the prostate. None of the subjects was receiving medications known to affect prostate morphology, function or Ca content. All samples of the p eripheral zone were divided by an anterior-posterior cross-section into two portions. One portion was reviewed by a histopathologist, while the other was used for the Ca concentration determination. Prostate glands containing any focus of benign prostatic hyperplasia, carcinoma, intraepithelial neoplasia, and slices with sample preparation artifacts were excluded from the study.

    Table 1. Mean (M±SEM) values of Ca concentration (mg/dm3, wet mass basis) in prostate glands of seven age groups obtained by two analytical methods.
    Group NoAge (years)nNAA-SLRICPAESTwo methods combined
    RangeMean
    Group 10–133.329275 ± 34234 ± 29254 ± 31
    Group 214–2018.25322 ± 53284 ± 50320 ± 75
    Group 321–3026.416361 ± 45401 ± 51397 ± 52
    Group 431–4035.812457 ± 48457 ± 47457 ± 48
    Group 541–5045.416442 ± 47433 ± 47439 ± 47
    Group 651–6055.611743 ± 188763 ± 183753 ± 185
    Group 761–8768.810397 ± 34416 ± 46412 ± 46
    All groups 0–8731.099405 ± 22395 ± 32404 ± 31
    M: arithmetic mean, SEM: standard error of mean, NAA-SLR-instrumental neutron activation analysis with high resolution spectrometry of short-lived radionuclides, ICPAES-inductively coupled plasma atomic emission spectrometry.
     | Show Table
    DownLoad: CSV

    Morphometric evaluations were then performed quantitatively using a stereological method [36]. The mean volume fractions of the stroma (S), glandular epithelium (E), and glandular lumina(L) in prostate tissue were determined for each prostate specimen. Details of the stereological method and procedures used here were presented in our earlier publications concerning quantitative morphometric studies of the human prostate gland [22,23,27,28,30,31].

    The samples intended for the Ca determination were weighed, freeze-dried and homogenized. Ca concentrations were estimated using instrumental neutron activation analysis with high resolution spectrometry of short-lived radionuclides (INAA-SLR) and inductively coupled plasma atomic emission spectrometry (ICP-AES). There was a good agreement between the Ca levels determined by the two methods, and means of the two results from every sample were used in the study (Table 1). Details of the analytical methods and procedures used and appropriate details of relevant nuclear reactions, radionuclides, gamma-energies, wavelength, isotopes, spectrometers, spectrometer parameters and operating conditions have been presented in our earlier publications concerning the chemical elemental content of the human prostate gland [17,18]. For quality control of the results appropriate certified reference materials (CRM) including IAEA H-4 (animal muscle) were used [17,18,22,23,27,28,37].

    Using the Microsoft Office Excel software, the summary of statistics, arithmetic mean, standard deviation, standard error of mean, minimum and maximum values, median, percentiles with 0.025 and 0.975 levels was calculated for Ca concentrations in the peripheral zone of nonhyperplastic prostate glands of males in the age range 0-87 years (seven age groups). The difference in the results between mean values of Ca concentration (mg/dm3, wet mass basis) in prostate glands of the seven age groups was evaluated by Student’s t-test. For the construction of the “Age dependence of intracellular Ca concentration in the peripheral zones of the prostate” diagram the Microsoft Office Excel software was also used.


    3. Results

    Table 2 presents basic statistical parameters (arithmetic mean, standard deviation, standard error of mean, minimal and maximal values, median, and percentiles with 0.025 and 0.975 levels) of the Ca concentrations (mg/dm3, wet mass basis) and the histologic components (fraction of dm3, wet tissue) in the peripheral zone of nonhyperplastic prostate glands of males in the age range 0-13 years (group 1), 14-20 years (group 2), 21-30 years (group 3), and 31-40 years (group 4), 41-50 years (group 5), 51-60 years (group 6), and 61-87 years (group 7). In our previous publications, significant age-dependent changes of Ca content were found, and a good agreement was shown between our results and the medians of means for those age groups reported in the literature [22,23,27,28]. From results in the Tables 2 and 3 we can conclude that Ca concentration in the prostate parenchyma begins to increase after the age of puberty and by the age of 55 it is nearly 2.4 times higher than in the prostate glands of the 18-year-old males. Virtually the same trend can be seen for the relative volume of prostatic fluid, which equals to the relative volume of the glandular lumina.

    Table 2. Certain statistical characteristics of the Ca concentration (mg/dm3, wet mass basis) and the histologic components (percent volumes) in the nonhyperplastic prostate gland of males aged 0-87 years.
    Age group No. (Age range) Mean, yearsParameterMSDSEMMinMaxMedianP0.025P0.975
    Group 1Ca2541523173.767120578.9598
    (0–13 years)Stroma75.313.02.644.491.380.449.790.5
    3.3Epithelium20.48.41.79.741.317.010.138.2
    Lumen4.54.70.90.3015.82.90.3615.8
    Group 2Ca32013075183441336191436
    (14–20 years)Stroma48.06.73.040.154.649.640.354.5
    18.2Epithelium38.93.71.634.943.938.835.043.6
    Lumen13.04.92.29.321.110.59.420.4
    Group 3Ca39718652214764331219763
    (21–30 years)Stroma46.012.13.226.770.945.728.069.6
    26.4Epithelium38.49.62.625.455.938.525.955.0
    Lumen15.65.51.53.724.116.04.523.1
    Group 4Ca45715148239692470251673
    (31–40 years)Stroma51.27.82.537.761.653.238.261.0
    35.8Epithelium32.05.21.625.941.431.425.941.0
    Lumen16.83.41.110.320.916.411.220.9
    Group 5Ca43915547245725373248690
    (41–50 years)Stroma45.08.62.533.957.443.334.057.2
    45.4Epithelium32.35.51.625.338.931.225.338.8
    Lumen22.77.02.010.329.824.710.429.6
    Group 6Ca75355618529120775752961859
    (51–60 years)Stroma52.811.53.839.772.649.839.870.7
    55.6Epithelium26.77.32.414.637.527.315.236.3
    Lumen20.59.33.19.734.319.49.734.0
    Group 7Ca41213046261656420265627
    (61–87 years)Stroma60.88.53.251.676.760.351.875.1
    68.8Epithelium25.65.92.214.631.927.315.631.6
    Lumen13.64.01.58.720.513.18.919.9
    All groupsCa4042723173.7207734693.7960
    (0–87 years)Stroma57.616.41.826.791.353.933.989.2
    31.0Epithelium28.910.01.19.755.928.812.546.7
    Lumen13.68.71.00.3034.314.20.5129.8
    M: arithmetic mean, SD: standard deviation, SEM: standard error of mean, Min: minimum value, Max: maximum value, Med.: median, P0.025: percentile with 0.025 level, P0.975: percentile with 0.975 level.
     | Show Table
    DownLoad: CSV
    Table 3. Ratio of mean values (M) and the difference between mean values of Ca concentration in prostate glands of seven age groups (Student’s t-test).
    Ratio Mi/Mi (where I = 1–7)M1M2M3M4M5M6M7
    M1/Mi1.000.790.64*0.55**0.58**0.34*0.61*
    M2/Mi1.261.000.810.700.730.430.78
    M3/Mi1.57*1.241.000.870.900.530.96
    M4/Mi1.81**1.431.151.001.040.611.11
    M5/Mi1.74**1.371.110.961.000.581.07
    M6/Mi2.98*2.351.901.651.721.001.83
    M7/Mi1.63*1.291.040.900.940.551.00
    Mi: arithmetic mean values of Ca mass fractions in the i-age group, *p≤ 0.05, **p≤ 0.01, statistically significant difference.
     | Show Table
    DownLoad: CSV

    There are several publications on the Ca concentration in prostatic fluid [38,39,40,41,42,43]. The median of the means of these concentrations agrees well with the finding by Kavanagh et al. [41]. The Ca concentration in prostatic fluid is strongly correlated to Zn [41] and because Zn concentration in the prostatic fluids is independent of age [44,45,46,47], age-independence of the Ca level might be implied. Thus, two relevant prostatic fluid characteristics have been taken from the literature and used in our subsequent calculations: (i) the mean Ca concentration in prostatic fluid equals 802 mg/dm3 (802 mg/L) and (ii) Ca concentration does not vary with age. Using the Ca concentration in the prostatic

    fluid and values of relative prostatic fluid volume (L) (Table 2) we can calculate the Ca content of the prostatic fluid in 1 dm3 of the wet prostatic tissue(CaL) for different age groups, as

    CaL (mg)=802 (mg/dm3) L (dm3),

    where L is the relative volume of the prostatic glandular lumina. If the prostate’s peripheral zone is divided into two compartments comprising (a) fluid (L) and (b) solid tissue, or stromal (S) and epithelial (E) cells taken together, (S+E), then for these the relative volumes of (a) and (b) we can calculate Ca content of the prostatic cells in 1 dm3 of wet peripheral zone prostatic tissue (CaS+E) for different age groups, as

    CaS+E (mg)=CaT (mg) − CaL (mg),

    where CaT is the Ca content of 1 dm3 of wet prostatic parenchyma, because T the relative volume of the prostatic tissue equals 1 and T=S + E + L. Table 4 presents results of these calculations.

    Table 4. Mean values of Ca contents in all prostatic cells of peripheral zones, contained in 1 dm3 of wet prostatic tissue for the different age groups.
    Group NoMean ageCaTLES+ECaLCaS+E
    yearsmgdm3dm3dm3mgmg
    Group 13.32540.0450.2030.95536.1217,9
    Group 218.23200.1310.3890.869105214,9
    Group 326.43970.1560.3840.844125271,9
    Group 435.84570.1680.3200.832135322,3
    Group 545.44390.2270.3230.773182256,9
    Group 655.67530.2050.2670.795164588,6
    Group 768.84120.1360.2560.864109302,9
    CaT: Ca content in 1 dm3 of wet prostatic tissue,
    L: volume fraction of lumen (prostatic fluid) in 1 dm3 of wet prostatic tissue,
    S: volume fraction of stroma (stromal cells) in 1 dm3 of wet prostatic tissue,
    E: volume fraction of epithelium (epithelium cells) in 1 dm3 of wet prostatic tissue,
    (S+E): volume fraction both of stromal and epithelium cells taken together in 1 dm3 of wet prostatic tissue,
    CaL: Ca of prostatic fluid in 1 dm3 of wet prostatic tissue,
    CaS+E: Ca of all prostatic cells in 1 dm3 of wet prostatic tissue
     | Show Table
    DownLoad: CSV

    Before the next step of the calculation it is necessary to accept two alternative boundary conditions: Case 1 -Ca is uniformly distributed in all cells of the prostate (stromal and epithelial cells), or Case 2 -Ca is present only in the epithelial cells. Using the data in Table 4 for Case 1 we can calculate the intracellular Ca concentration for different age groups as

    CaAll cells (mg/dm3)=CaS+E (mg)/[(S+E) (dm3)],

    and for Case 2 as

    CaEpithelial cells mg/dm3=CaS+E (mg)/[E (dm3)].

    Figure 1 depicts the age-dependence of the intracellular Ca concentration for the Cases 1 and 2. In Case 1, the level of the intracellular Ca concentration increases very slowly in the age range from newborns to 45 years. In the age range from 18 to 45 years, it remains virtually constant and equals about 320 mg/dm3. A marked increase in the intracellular Ca level begins after the age 45 years and reaches its maximum at about 55. This maximum equals 740 mg/dm3 and is 2.3-fold higher than in the prostate glands of males aged 18 to 45 years.

    Figure 1. Age dependence of intracellular Ca concentration (mg/dm3, wet mass basis) in the peripheral zones of the prostate: Case 1. (■) age dependence of intracellular Ca concentration in the prostate, presuming there is uniform distribution of Ca in both stromal and epithelial cells, Case 2. (♦) age dependence of intracellular Ca concentration in epithelial cells, presuming there is an accumulation of Ca only in the epithelial cells, and the trend curve.

    In Case 2, the intracellular Ca level decreases in the age range from newborns to 18 years old and then slowly increases in males aged 18 to 45 years. Next, a marked increase of the intracellular Ca level begins after 45 years and reaches a maximum at about ten years later. Our data show that 55 years old males have intracellular Ca level in their epithelial cells of about 2200 mg/dm3, which is

    four times higher than in the prostate glands of 18-year-old men. Because both the prostate epithelial cells and cells of the stromal component need Ca for their normal function the real changes in the prostatic intracellular Caconcentrations at different ages lie somewhere between Case 1 and Case 2. Either way, an excessive accumulation of Ca in prostatic cells begins after 45 culminating in the two-to-four fold increase in the intracellular Ca levels by the age of 55 years.


    4. Discussion

    As was shown by us [17,19,20] the use of IAEA H-4 (animal muscle) as a certified reference material for the analysis of samples of prostate tissue can be seen as acceptable. Good agreement of the Ca content analyzed by INAA-SLR (238±59 mg/kg, Mean±SD) with the certified data of IAEA H-4 (163-213 mg/kg, 95% confidence interval) indicated an acceptable accuracy of the results obtained in the study of Ca content in the prostate presented in Tables 1-4.

    This study augments our current understanding of prostate gland physiology. Firstly, this study shows that the intracellular Ca concentration in the 18 to 45 year olds remains almost constant at a relatively high level. In these men, the average intracellular Cain the prostate glands does not increase beyond 760 mg/dm3. Such a high level of Ca in the prostate cells is four-to-five times higher than mean values for Ca in other organs of the human body including skeletal muscle (70-150 mg/dm3), liver (50-130 mg/dm3), lung (80-200 mg/dm3), and kidney (100-190 mg/dm3) [48]. Since the function of the prostate gland in the age range between 18 to 45 years is presumably normal, we must conclude that a specific accumulation of Ca by the epithelial cells of the prostate gland is a normal physiological event.

    Secondly, our workdemonstrates that after the age of 45 the intracellular Calevel in the prostate glands keeps increasing and reaches 740-2200 mg/dm3, which is at least an order of magnitude higher than Ca concentrations in most other tissues. Our results are in line with the results of by Tvedt et al. [32], who demonstrated high cytosolic Ca concentrations in the human prostatic cells (700 mmol/kg dry mass basis or approximately 5600 mg/dm3 wet mass basis) and an age-related increase of intranuclear Ca.

    According to the well-established hypothesis of Costello and Franklin, the main functions of the prostate secretory epithelial cells are production, accumulation, and secretion of a large amount of citrate [49]. In the prostate, intracellular citrate level could reach 1800 mmol/kg [50] and high intracellular Ca level along with other major electrolytes and Zn may be needed for the ionic equilibrium in the cytosol and extracellular prostatic fluid. On the other hand, Ca2+ is one of the most ubiquitous and critical secondary messengers and is involved in a plethora of cellular processes [51,52]. The role of Ca2+ is well established in the majority of cell signaling pathways involved in carcinogenesis such as cellular motility, proliferation, and apoptosis [52,53,54,55,56].

    In particular, intracellular transmission of the Ca2+ signal occurs via Ca2+ sensor proteins such as regucalcin (RGN), calmodulin (CaM) and related members of the Ca2+ binding protein family. The Ca2+/CaM complex regulates over 120 proteins, including transcription factors, channels, pumps, kinases and phosphatases [57]. A rise in intracellular calcium promotes the Ca2+/CaM complex, which targets the CaM dependent kinase that mediate nutrient responses and regulates cell growth and energy balance. Recent work of Dubois et al. [58] demonstrated that through the differential expression of specific ORAI Ca2+ channels prostate cancer cells promote the store-independent Ca2+ influx across the plasma membrane, which results in enhanced proliferation and apoptotic resistance.

    In various types of tissues including breast and prostate, Ca2+ homeostasis is maintained by the Ca-binding protein regucalcin (RGN). RGN is conserved in vertebrates and regulates intracellular Ca2+ homeostasis through the modulation of the activity of Ca2+ channels, Ca2+-ATPase in the membrane of the mitochondria and endoplasmic reticulum [59] and (Ca2+-Mg2+)-ATPase in the plasma membrane [60]. The expression of RGN is controlled by intracellular Ca2+ and regulatory transcription factors, and was identified as a target gene for sex steroid hormones in the prostate glands [61]. RGN is down-regulated in prostate cancer tissues and Maia et al. have demonstrated, that RGN immunoreactivity is correlated with the grade of adenocarcinoma cellular differentiation [62]. Notably, in rat brain neurons, the RGN inhibitory effect on Ca2+-ATPase is weakened with aging. Therefore by analogy to the brain tissue age-related or malignant transformation related down-regulation of RGN in the background of increasing intracellular and extracellular Ca concentrations may play a relevant role in cancer initiation and progression in the prostate [63].

    Further, Ca2+ channels in the plasma membrane of neurons are critical for the basal activity of the ubiquitous transcription factor that controls cell proliferation and survival NF-κB [56]. Galheigo et al. have recently shown that in chemically induced mice NF-κB stimulated prostate carcinogenesis, which provides another link between proliferation and Ca influx [64]. In addition, Ca2+ signalling is critical for regulating cell migration and invasion and a number of Ca permeable channels have been implicated in the enhanced migration of cancer cells [65].

    Another aspect of the prostate cancer biology where intracellular Ca overload is may be involved, but has not yet been fully explored, is the cellular energy metabolism. For example, Panov and Orynbaeva have suggested that due to the 20-30 mV higher electrical membrane potential in prostate cancer cell lines, mitochondrial metabolism of the metastatic prostate cancer cells is predominantly based on utilization of glutamate and glutamine, potentially resulting in cachexia [66].

    Overall, excessive intracellular, intranuclear, and extracellular Ca concentrations make the peripheral zone of the prostate prone to tumorigenesis. A continuously increasing intracellular Ca level could disturb the fine-tuned Ca2+ homeostasis and together with the aging effects could trigger a cascade of events resulting in tumor initiation and progression. Almost certainly, a Ca rich diet would contribute to Ca accumulation in the prostate and may support abnormal tissue growth. But the molecular mechanisms of the accumulation are yet to be discovered.

    This study has several limitations. Firstly, analytical techniques employed in this study measure bulk Ca and do not differentiate between Ca ions and elemental Ca. Secondly, the methods we used do not provide information on the spatial distribution of Ca in the cell. Nonetheless, our data are crucial for the understanding of Ca homeostasis in the prostate gland and highlight the need for more studies addressing the unique Ca rich intracellular and extracellular environment in the prostatic gland.


    5. Conclusion

    At rest, the cytosolic concentration of Ca2+ in eukaryotic cells is maintained in nanomolar ranges. In contrast, the prostate gland accumulates and secretes large amounts of Ca and must have evolved mechanisms to control this ubiquitous messenger. Age-dependent increase in the Ca level in the peripheral zone of the prostate and particularly the accumulation of this element in the prostatic intracellular space at age over 45 years were found in this study. This increase may override these protection mechanisms and promote malignancy in this part of the prostate, which is common in aging men and was shown to have a positive association with a Ca rich diet.


    Conflict of interest

    The authors declare no conflict of interest.


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    9. Miled El Hajji, How can inter-specific interferences explain coexistence or confirm the competitive exclusion principle in a chemostat?, 2018, 11, 1793-5245, 1850111, 10.1142/S1793524518501115
    10. Tewfik Sari, Jérôme Harmand, A model of a syntrophic relationship between two microbial species in a chemostat including maintenance, 2016, 275, 00255564, 1, 10.1016/j.mbs.2016.02.008
    11. T. Sari, M.J. Wade, Generalised approach to modelling a three-tiered microbial food-web, 2017, 291, 00255564, 21, 10.1016/j.mbs.2017.07.005
    12. Sarra Nouaoura, Radhouane Fekih-Salem, Nahla Abdellatif, Tewfik Sari, Mathematical analysis of a three-tiered food-web in the chemostat, 2020, 0, 1553-524X, 0, 10.3934/dcdsb.2020369
    13. Sarra Nouaoura, Nahla Abdellatif, Radhouane Fekih-Salem, Tewfik Sari, Mathematical Analysis of a Three-Tiered Model of Anaerobic Digestion, 2021, 81, 0036-1399, 1264, 10.1137/20M1353897
    14. Sarra Nouaoura, Radhouane Fekih-Salem, Nahla Abdellatif, Tewfik Sari, Operating diagrams for a three-tiered microbial food web in the chemostat, 2022, 85, 0303-6812, 10.1007/s00285-022-01812-5
    15. Radhouane Fekih-Salem, Yessmine Daoud, Nahla Abdellatif, Tewfik Sari, A Mathematical Model of Anaerobic Digestion with Syntrophic Relationship, Substrate Inhibition, and Distinct Removal Rates, 2021, 20, 1536-0040, 1621, 10.1137/20M1376480
    16. Amer Hassan Albargi, Miled El Hajji, Mathematical analysis of a two-tiered microbial food-web model for the anaerobic digestion process, 2023, 20, 1551-0018, 6591, 10.3934/mbe.2023283
    17. Hajji ME, How the competitive exclusion principle can be validated using optical density measurements collected on artificially reconstituted soil ecosystems, 2019, 001, 10.17352/ojeb.000009
    18. Tewfik Sari, Best Operating Conditions for Biogas Production in Some Simple Anaerobic Digestion Models, 2022, 10, 2227-9717, 258, 10.3390/pr10020258
    19. Abdulrahman Ali Alsolami, Miled El Hajji, Mathematical Analysis of a Bacterial Competition in a Continuous Reactor in the Presence of a Virus, 2023, 11, 2227-7390, 883, 10.3390/math11040883
    20. Tewfik Sari, Boumediene Benyahia, The operating diagram for a two-step anaerobic digestion model, 2021, 105, 0924-090X, 2711, 10.1007/s11071-021-06722-7
    21. Carlos Martínez, Eugenio Cinquemani, Hidde de Jong, Jean-Luc Gouzé, Optimal protein production by a synthetic microbial consortium: coexistence, distribution of labor, and syntrophy, 2023, 87, 0303-6812, 10.1007/s00285-023-01935-3
    22. Amer Hassan Albargi, Miled El Hajji, Bacterial Competition in the Presence of a Virus in a Chemostat, 2023, 11, 2227-7390, 3530, 10.3390/math11163530
    23. Miled El Hajji, Mathematical modeling for anaerobic digestion under the influence of leachate recirculation, 2023, 8, 2473-6988, 30287, 10.3934/math.20231547
    24. Juan Carlos Arceo, Olivier Bernard, Jean-Luc Gouze, 2022, Bacteria Mutualism in a Chemostat: Analysis and Optimization with Interval Detector, 978-1-6654-6761-2, 3225, 10.1109/CDC51059.2022.9992750
    25. M. Guo, W. Shen, M. Zhou, Y. Song, J. Liu, W. Xiong, Y. Gao, Safety and efficacy of carbamazepine in the treatment of trigeminal neuralgia: A metanalysis in biomedicine, 2024, 21, 1551-0018, 5335, 10.3934/mbe.2024235
    26. Tewfik Sari, Commensalism and syntrophy in the chemostat: a unifying graphical approach, 2024, 9, 2473-6988, 18625, 10.3934/math.2024907
    27. Nabil Ben Ali, Nahla Abdellatif, Stability and bifurcations in a model of chemostat with two inter‐connected inhibitions and a negative feedback loop, 2024, 0170-4214, 10.1002/mma.10349
    28. Lin Wang, Linlin Bu, Jianhua Wu, Dynamics of a diffusive model in the anaerobic digestion process, 2025, 142, 10075704, 108523, 10.1016/j.cnsns.2024.108523
    29. Nabil Ben Ali, Nahla Abdellatif, Stability of density-dependent model with indirect feedback and biomass inhibition, 2025, 1431-7613, 10.1007/s12064-025-00440-z
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