Aspergillus, such as A.flavus and A.parasiticus. Aflatoxins reportedly have carcinogenic effects on human, poultry, and livestock, and therefore could be linked to severe human illnesses. Aflatoxin biosynthesis pathway involves different clustered genes, including structural, regular, and unassigned genes. The present study was conducted to detect aflR,aflP, and aflD as three important genes contributing to aflatoxin B1 production cycle in Aspergillus species isolated from the feedstuffs of animal husbandry.Aflatoxins are naturally produced by some species of A. flavus, A. parasiticus, A. nomius, and A. nidulans, isolated from animal feedstuff as a test group. The test group was compared with two standard strains  as aflatoxigenic reference organisms and negative controls  in terms of the presence of aflR, aflP, and aflD genes using polymerase chain reaction (PCR). The determination of the toxigenicity and aflatoxin production of isolated Aspergillus species was accomplished using thin-layer chromatography (TLC) and high-performance liquid chromatography (HPLC).This study was conducted on 25 isolates of Asprgillus species were significantly correlated with TLC and HPLC results. Accordingly, all samples, having positive results for aflatoxin B1 production in TLC and HPLC, were able to show the amplification of three target genes. However, 4 cases out of 6 (66%) non-aflatoxigenic isolates were positive for three or two genes. The results obtained by the amplification of the selected genes by PCR method for the detection of aflatoxigenic aflP, aflD, and aflR) could be considered as a quick and reliable method for the detection of aflatoxigenic Aspergillus. Furthermore, this method could be useful in planning and implementing strategies targeted toward improving the safety of human or animal food. Based on the findings, the molecular detection of aflatoxin biosynthesis genes (i.e.,  The fungal contamination of food or feedstuff is considered as a major problem in humans or animals’ health worldwide. Nearly every food can be contaminated by fungal pathogens . Many ofAflatoxins are the most important mycotoxins reported in many clinical toxicosis. These carcinogens could be accompanied with a wide range of diseases, such as cancers . AccordiAspergillus, such as A. flavus, A. parasiticus, and A. nomius, are known as aflatoxin-producing fungi, which are distributed on a broad spectrum of feeds, such as corn, barley, wheat, and bran . Aflatoxin biosynthesis is a complicated pathway involving at least 18 enzymatic steps to produce these toxins from acetyl coenzyme A. Different investigations have been conducted to study the various genes involving in this process. Accordingly, they have introduced 25 genes, such as some III -11.aflR gene regulates the activity of other structural genes in the aflatoxin biosynthesis pathway. On the other hand, aflD (Nor-1) gene plays an essential role in the early conversion of norsolorinic acid into averantin. The aflP (omt) is involved in the conversion of sterigmatocystin into aflatoxin in the late steps of the aflatoxin pathway  was added to the mixture and subjected to a 30-min heat shock treatment at 65°C for 20 min. The fungal DNA was extracted according to our previously described method . The gen) method. The procedure was followed by centrifugation at 2,000 g for 15 min. The supernatant was then transferred to a fresh microcentrifuge tube, and equal volumes of isopropanol was added. Following centrifugation at 2,000 g for 5 min., the supernatant was removed, and the pellet was resuspended in 100 µl distilled water.The resultant suspension was centrifuged for 5 min at 2,000 g, and the supernatant was transferred to a fresh, labled microfuge tube. The DNA extraction was performed on the supernatant using chloroform: isoamyl alcohol  Fluorescence observation on plateThe ability of all fungal samples for aflatoxin production was detected on coconut agar medium (CAM). To this end, the fungi were cultured on CAM and incubated at 30°C in the dark for 7-10 days. The plates were periodically screened for blue fluorescence under ultraviolet (UV) light (365 nm).b) Qualitative determination of aflatoxin by thin-layer chromatography The assessment of aflatoxin levels in isolates was performed after initial extraction. To this end, the samples were cultured in 100 ml yeast extract-sucrose broth medium  and incubated in the dark for 7 days at 30°C. Afterwards, the culture was finely mixed with NaCl and methanol 55% for 30 min and filtered through Whatman filter paper No. 1. Then, 100 ml chloroform was added to culture flask and centrifuged at 1,500 g for 15 min at 4°C. Subsequently, the lower phase was transferred to a new tube and evaporated at 80°C for the removal of chloroform. For the evaluation of aflatoxin-producing ability of fungal isolates, 20 µl of prepared extract was transferred to silica gel paper by Dispenser Capillary for TLC. After the development of plates by chloroform:acetone (1:9) protocol, the fluorescence intensities of the samples were observed under UV light. c) Quantitative determination of aflatoxin B1 by high-performance liquid chromatography The concentrations of aflatoxin B1 were determined according to a method described by Namjoo [17] using high-performance liquid chromatography (HPLC) with a fluorescent detector . To this end, 20 µl of toxin extract was injected into the HPLC reversed-phase columns C18 column  and washed at a flow rate of 1 ml/min by water: methanol: acetonitrile (60:30:15 v/v/v). The fluorescence was detected at the excitation and emission wavelengths of 365 and 440 nm, respectively. The B1 aflatoxin standards were provided from Sigma . Additionally, the different concentrations of aflatoxin B1 standards  were analyzed by HPLC, according to which a standard curve was prepared. The quantities of aflatoxin B1 in samples were detected by comparing the under the curve area of the chromatogram with the standard curve. The total recovery was obtained as 93.4%.Aspergillus species, including A. flavus (n=17), A. parasiticus (n=5), A. nomius (n=1), and A. nidulans (n=2), were isolated from the feedstuff samples. All of the species were identified by their macroscopic and microscopic features and sequencing of the internal transcribed spacer region. The presence of aflP, aflD, and aflR genes were evaluated by PCR using three sets of primers. In this study, four aflD, aflP, and aflR gene fragments could be seen at 702, 611, and 1458 bp, respectively. A heterogenic pattern was observed in the positive and negative controls. A similar electrophoretic pattern was observed on the PCR products of 20 isolates, which represented the concomitant presence of the three genes. However, other isolates demonstrated different patterns. aflD, aflP, and aflR), which were greatly detected by PCR method in the positive aflatoxigenic samples, were absent in the negative control species.As shown in aflD, aflP, and aflR genes. On the other hand, 4 cases out of 25 samples (16%), which were detected as aflatoxin non-producing Aspergillus, showed a complete set or both of genes. Only 2 (8%) samples, which were negative for aflatoxin production, had negative results in PCR and other conventional methods.The TLC and HPLC methods and the PCR amplification rendered completely similar results regarding the prevalence of target genes and aflatoxin B1 production ability . As seenAspergillus, scientists have opted for new and sensitive methods for the early detection of foodstuff contamination with different aflatoxigenic Aspergillus species . Schmidt showed that environmental factors have a complex influence on the regulation of aflatoxin biosynthesis genes [Houssain oduction . In the is genes .A. flavus and A. parasiticus, which showed negative results in the conventional methods, could express at least one of the aflP, aflD, or aflR genes. In line with the previous studies, our results indicated that the lack of aflatoxin production in some aflatoxigenic species could be due to the deletion and simple mutation (replacement of some bases) of aflR, aflD, and aflP genes or loss of other responsible genes in aflatoxin production pathway. However, some of the physiological conditions could affect aflatoxin biosynthesis [Inconsistent with previous reports , some noynthesis , 21.Aspergillus. The results of this study could be helpful for agricultural development and medical or veterinary organization in aflatoxin regulatory controls.Furthermore, the additional molecular character-rization of these genes or other eventual genes in aflatoxin biosynthesis pathway could be useful for the application of these methods in differentiating between toxinogenic and nontoxinogenic strains of aflP, aflD, and aflR) could be considered as a quick and reliable method for the identification of aflatoxigenic Aspergillus species. Moreover, this method could be useful in planning and implementing the strategies targeted toward improving the safety of human or animal food.As the findings of the present study indicated, the molecular detection of aflatoxin biosynthesis genes (i.e.,


M = 9.13; SD = 1.70), including 50 children who stutter and 50 children who do not stutter. Analyses, which were performed separately for younger and older participants, sought to identify correlations between key variables. Temperament was evaluated through a parent questionnaire, executive functioning was evaluated through children’s responses on a performance test, and anxiety level was assessed through a self-perception scale. On the temperament measure, comparisons between children who stutter and their non-stuttering peers revealed that older children who stutter exhibited significantly higher scores on the Anger/Frustration, Impulsivity, and Sadness subscales, and lower averages on the Attention/Focusing, Perceptual sensitivity, and Soothability/Falling Reactivity subscales. On the executive functioning task, comparisons revealed that the group of younger children who stutter exhibited significantly higher average execution times than their non-stuttering peers. There were no statistically significant differences in anxiety between children who stutter and children who do not stutter, and there were no statistically significant correlations between temperament factors and measures of executive functioning. Children who stutter experienced lower ability to orient attention and greater emotional reactivity compared with their non-stuttering peers. Significant correlations were found between executive functioning and age and among the temperament factors themselves. These results, which support the need for a multidimensional view of stuttering, were interpreted in the context of the Dual Diathesis – Stressor model. Findings indicate that temperament and executive functioning abilities may contribute to the development of stuttering.The purpose of this study was to examine temperament dimensions, executive functioning ability, and anxiety levels in school-age children who stutter and their non-stuttering peers. Participants were 100 Portuguese children aged 7 to 12 years ( Temperament is an overarching term for a collection of traits that are assumed to be biologically determined and related to individual differences in reactivity and self-regulation .Temperament can develop over time  and be iFindings regarding temperament in children who stutter have been inconsistent. Therefore, it is not yet possible to draw firm conclusions about differences in temperament between children who stutter and their non-stuttering peers. Still, there is an increasing literature reporting a propensity for a more reactive and sensitive temperament in children who stutter , and theTemperamental characteristics in preschool children that have been shown to contribute to stuttering include difficulty concentrating on tasks , and lowWhile studies of temperament in preschool children and adults who stutter have revealed notable differences compared to peer groups who do not stutter e.g., , temperaThe role of EF in childhood stuttering has been a subject of increased attention in recent years . EF is aSymptoms similar to those seen in children with attention deficit disorders have been identified in some children who stutter ; howeverCognitive processes described above are closely linked to emotional regulation  and can trait anxiety (related to stable anxious baseline characteristics) and state anxiety . People who stutter often struggle with state anxiety, since anxiety will likely become a secondary effect of living with stuttering condition rather than being a static condition  . AccordiResearch has further identified temperamental characteristics and cognitive abilities as predictors of anxiety . EnvironThe present study was designed to address the literature gap on the research of temperament, EF, and anxiety jointly, comparing school-age children who stutter and non-stuttering peers. The combination of these three aspects can give us further information about the interaction between emotional and cognitive factors. Moreover, the DD-S model, which focuses the interaction between intrinsic and external factors and how they may change over time, highlights the need to concurrently consider factors such as temperament, EF, and anxiety. Taken together, these factors can provide more clues about the onset, development, and possible persistence of stuttering during childhood. A better understanding of such relationships may help clinicians understand how stuttering affects children, and this understanding may contribute to the development of more effective and personalized treatment programs.th Edition (SSI-4)  and 50 age-matched children who do not stutter (“N” Group), ages 7 to 12 years old. The Stuttering Severity Instrument – 4 (SSI-4)  was usedn = 50) and their non-stuttering peers (n = 50) were grouped according to age: younger children  and older children .In order to explore developmental differences, the participants who stutter (th and 6th grades (about 10–12 years old). Depending upon a child’s birth date, however, it is possible to find children in the 7th grade who are 12 years old. Pre-school education in Portugal is intended for children between 3 and 6 years old; from the age of 13, Portuguese children are usually in high school . Children who had previous therapy had received between 3 and 48 months of treatment .When the study was performed, 22% of the children who stutter were in speech therapy, 22% had previous speech therapy, and 28% were waiting for therapy or just initiating speech therapy. The children who were in therapy at the time of data collection had been in treatment between 1 to 96 months   is a parThrough the TMCQ, it is possible to identify reactivity/sensitivity and self-regulation characteristics. For example, the TMCQ scales such as Anger/frustration are connected to reactivity, whereas scales such as Inhibitory control are more related to self-regulation . For exaOf the 17 dimensions of temperament that are part of the instrument, 13 dimensions derive from the well-validated Children’s Behavior Questionnaire CBQ: , which hThe questionnaire was translated to European Portuguese for this study .Children were assessed using the Portuguese version of the Children’s Color Trails Test (CCTT), a neuropsychological paper-and-pencil test of EF . The CCTThe results of both parts of this test consist of: (a) time (in seconds) that the child takes to complete the tasks, (b) the number of times almost failed (the failures), (c) the number of errors, and (d) the number of warnings .CCTT has been increasingly used around the world e.g.,  for the The children also completed the Portuguese version of Multidimensional Anxiety Scale for Children (MASC), which examines the symptoms of anxiety in children and adolescents ages 7 to 19 years. It contains 39 questions, with four-point Likert scale responses . Items otrait anxiety), though it is also influenced by transitory conditions and situations (state anxiety) (The normative data for the MASC show that it is oriented mainly toward inherent characteristics (anxiety) . Decadesanxiety) . The orianxiety) . The Poranxiety) .This study received full approval by the Ethics Committee of the Institute of Health Sciences of Universidade Católica Portuguesa (register number 34/2017). Prior to their participation in this study, parents signed a written informed consent for themselves and their children. Consent also included permission for the researcher to record the child and the right for participants to withdraw from the study at any time was clarified.Children were assessed while parents completed the questionnaires. This was carried out in two sessions of approximately 30 min each.All testing was conducted between December 2017 and May 2018. The SSI, MASC, and CCTT instruments were applied on different days and in a different order, to reduce potential order effects that might bias results.Temperament was assessed using the Portuguese version of the TMCQ, with the 157 original questions, distributed in 17 temperament dimensions . After aFor the EF assessment, the researcher presented and explained to the children how to perform the CCTT1, using the trial test. In both trial test and experimental test, children drew a line between the circles following a numerical order, as fast as they could; however, the CCTT1 trial test was performed with just 8 numbers. For the CCTT2 the procedures were similar, with the difference that children should switched between colors . The researcher recorded 9 scores for each child. These scores corresponded to: the time that the child took to complete the tests for both CCTT1 and CCTT2, as well as the number of warnings, failures, and wrong answers (Number Sequencing and Color Sequencing) .For the anxiety assessment, the MASC questionnaire was presented to each child. Children were asked to read all the questions and to choose the best option for each. Children were informed about the importance of responding to all questions. For 7-years-old children, the MASC questions were read in full by the examiner.After the children completed the questionnaire, the researcher summed the items for each factor, obtaining four final scores, corresponding to: (a) Physical symptoms, (b) Social anxiety, (c) Separation anxiety, and (d) Harm avoidance.n = 50 for each participant group, the central limit theorem suggests that parametric tests (t-test) would still be sufficiently robust to avoid deviations from normality. Two-sample t-tests were used to compare mean scores for the stuttering and non-stuttering groups for the temperament (TMCQ), EF (CCTT), and Anxiety (MASC) measures. These analyses were performed separately for younger and older participants. A multivariate analysis using principal component analysis (PCA) was performed in order to determine which variables were correlated and to summarize children characteristics in an ordination diagram. For the PCA analyses, younger and older children were separetely. This was done because of apparent differences between age groups. The use of PCA provided a dynamic view of the interaction among all of the variables, including age. To account for the large number of variables in the study  only the variables that showed statistical significance in the t-tests were used in the PCA. Data analysis was completed using SPSS .Preliminary analyses were made in order to check the assumptions of homogeneity. Results for some variables were not normally distributed; however, with the p > 0.05) for any of the variables of temperament including: (1) Activity Level, (2) Affiliation, (3) Anger/Frustration, (4) Assertiveness/Dominance, (5) Attention Focusing, (6) Discomfort; (7) Fantasy/Openness, (8) Fear, (9) High Intensity Pleasure, (10) Impulsivity, (11) Inhibitory Control, (12) Low Intensity Pleasure, (13) Perceptual Sensitivity, (14) Sadness, (15) Shyness, (16) Soothability/Falling Reactivity, (17) Activation Control.No statistically significant differences were found between groups of children who stutter and their non-stuttering peers (t(48.75) = 3.144, p = 0.003; CCTT2: t(52.27) = 3.753, p < 0.001), as well as number of failures (CCTT1: t(38.23) = 2.627, p = 0.012), number of warnings (CCTT1: t(52.47) = 2.968, p = 0.005; CCTT2: t(53.71) = 3.757, p < 0.001), number of sequencing errors (CCTT2: t(34.99) = 3.337, p = 0.002), and color sequencing errors (CCTT2: t(49.31) = 2.416, p = 0.020)  .p > 0.05) for any of the variables of anxiety including: (1) Physical symptoms, (2) Social anxiety, (3) Separation anxiety, and (4) Harm avoidance, for each child.No statistically significant differences were found between groups of children who stutter and their non-stuttering peers (t(36) = −3.526, p = 0.001), Perceptual Sensitivity (t(36) = −2.411, p = 0.021), and Soothability/Falling Reactivity (t(36) = −2.932, p = 0.006). Children who stutter scored higher than non-stuttering peers in temperament factors of Anger/Frustration (t(36) = 2.801, p = 0.008), Impulsivity (t(36) = 2.899, p = 0.006), and Sadness (t(36) = 3.683, p = 0.001).Statistically significant differences were found for several temperament factors . Childrep > 0.05) for any of the variables of EF, including: (1) CCTT1 execution time, (2) CCTT1 number of sequencing errors, (3) CCTT1 number of failures, (4) CCTT1 number of warnings, (5) CCTT2 execution time, (6) CCTT2 number of color sequencing errors, (7) CCTT2 number of sequencing errors, (8) CCTT2 number of failures, (9) CCTT2 number of warnings.No statistically significant differences were found between groups of children who stutter and their non-stuttering peers (p > 0.05) for any of the variables of anxiety, including: (1) Physical symptoms, (2) Social anxiety, (3) Separation anxiety, and (4) Harm avoidance.As in the younger group, no statistically significant differences were found between groups of children who stutter and their non-stuttering peers  were plotted on the right side of the first dimension. The first axis accounted for 27.30% of the total variance. The parameters with greater contribution to the second axis (dimension 2 – Temperament dimensions) were Sadness (component loading = 0.78), Anger/Frustration (component loading = 0.75), Soothability/Falling Reactivity (component loading = −0.72), Attention/Focusing (component loading = −0.69), and Impulsivity (component loading = 0.60). Most of the children who stutter were displayed on the upper part of the diagram, as they exhibited higher values of Sadness, Anger/Frustration and Impulsivity, and lower values of Soothability/Falling Reactivity and Attention/Focusing. The bottom part of the diagram shows mainly children who do not stutter, due to lower values of Sadness, Anger/Frustration and Impulsivity, and higher values of Soothability/Falling Reactivity and Attention/Focusing.The second axis accounted for 20.04% of the total variance. The CCTT1 Time, CCTT1 Warnings, CCTT1 failures, CCTT2 Time, CCTT2 Warnings, CCTT2 number of sequencing errors, and CCTT2 color sequencing errors were highly and positively correlated with one another and negatively correlated with age. Sadness, Anger/Frustration, and Impulsivity were highly and positively correlated with each other; Attention, Soothability/Falling Reactivity and Perceptual Sensitivity were negatively correlated with Anger/Frustration, Impulsivity, and Sadness.This study investigated temperament dimensions, EF skills, and anxiety levels in children who stutter and their non-stuttering peers. The main results are consistent with the hypothesis that some children who stutter may differ in temperament and EF factors when compared to children do not stutter. Specifically, in these group comparisons, children who stutter were found to be more reactive and sensitive than their non-stuttering peers. However, the findings were different across the two age groups that were analyzed. The differences in temperament level were noted in the group of older children only, while differences in EF were noted in the group of younger children only. Furthermore, results did not support the idea that children who stutter exhibit higher rates of anxiety than children who do not stutter, regardless of age group. Correlation analyses highlighted the dynamic nature of stuttering and suggested a link between endogenous abilities and external factors .Results on the temperament scale are consistent with previous studies that have suggested difficulties in children who stutter compared to non-stuttering peers in attention span  and a teYounger children who stutter required longer execution times and had a higher number of warnings and failures, number sequencing errors, and color sequencing errors compared age-matched peers who do not stutter. This suggests that children who stutter in the first years of schooling might have a lower attention span than their peers . They mitrait anxiety measure could have influenced the results. Speech tasks can trigger anxiety, so future research may benefit from using speech tasks rather than questionnaires  and from parent reports of daily observations . MoreoveBecause temperament characteristics can change over time , the difFindings from the current study support the predictions from the DD-S Model , which sBecause endogenous capacities, such as temperament and EF, can change over time, and because exogenous factors, such as demands of the environment, may be different for each person, future research should examine the interactions between temperament and the development of EF both individually and over time. Similar studies that involve the analysis of several variables simultaneously may help to better explain the onset of anxiety in older children or other aspects of how stuttering – and reactions to stuttering – develop over time.In future research, the use of multiple instruments would strengthen both the reliability and validity of these findings. For example, experimental methods that complement self-perception scales might allow the evaluation and analysis of child behavior in different situations. It would also be worthwhile to add inhibitory control and working memory tasks to better understand EF. These are the concepts that are encompassed in EF and have been examined independently in other studies . The DD-Future studies should also employ a more balanced sample collection, with a more tight matching of groups in variables such as sex, age, and other relevant factors. Although this study involved a reasonable sample size, the participants were in different stages of treatment, and it is possible that participants’ treatment histories might have affected the results. Similarly, the presence of some differences in sex ratio and age between sub-groups of children who stutter and children who do not stutter suggest that these preliminary results should be interpreted with caution.Results highlight the potential role of emotional processes, temperament, and EF in the development of stuttering. Examining the cognitive and emotional skills of children who stutter across age groups can add further knowledge about stuttering. Ultimately, such knowledge may lead to refinements in clinical and educational practices. A principal outcome of this study is the finding that endogenous abilities in children who stutter may be different according to their age. Older participants were found to be more prone to difficulties in temperament dimensions, while younger participants exhibited predispositions for difficulties related to EF. This suggests that differences between children who stutter and children who do not stutter may be mediated by age and development. These results are in agreement with a dynamic view of the development of stuttering influenced by internal and external factors.The datasets generated for this study are available on request to the corresponding author.This study received full approval by the Ethics Committee of the Institute of Health Sciences of Universidade Católica Portuguesa (register number 34/2017). Prior to their participation in this study, parents signed a written informed consent for themselves and their children. Consent also included permission for the researcher to record the child and the right for participants to withdraw from the study at any time was clarified.MR collected the sample, conducted the analysis, and wrote and edited the manuscript. JY contributed to the study design, analysis, and writing, editing, and reviewing of the manuscript. JR designed and supervised the study, and contributed to the writing and reviewing of the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Anti-Müllerian hormone (AMH) is a reliable and easily detectable reproductive marker for the fertility competence of many farm animal species. AMH is also a good predictor of superovulation in cattle, sheep, and mares. In this review, we have summarized the recent findings related to AMH and its predictive reliability related to fertility and superovulation in domestic animals, especially in cattle. We focused on: (1) the dynamics of AMH level from infancy to prepubescence as well as during puberty and adulthood; (2) AMH as a predictor of fertility; (3) the association between antral follicle count (AFC) and plasma AMH level; (4) AMH as a predictor of superovulation; and (5) factors affecting AMH levels in domestic animals, especially cattle. Many factors affect the circulatory levels of AMH when considering the plasma, like nutrition, activity of granulosa cells, disease state and endocrine disruptions during fetal life. Briefly, we concluded that AMH concentrations are static within individuals, and collection of a single dose of blood has become more popular in the field of assisted reproductive technologies (ART). It may act as a potential predictor of fertility, superovulation, and ovarian disorders in domestic animals. However, due to the limited research in domestic animals, this potential of AMH remains underutilized. AMH gene has been mapped to chromosome 7 in cattle, mares, and goats; chromosome 5 in sheep; chromosome 9 in buffalo; and chromosome 2 in pig [Anti-Müllerian hormone (AMH) has a long history, but its presence was recognized after the mid-20th century. Alfred Jost was the first to introduce the existence of AMH in 1953. At that time, scientists thought that testicular tissues not only synthesize testosterone, the chemical messenger responsible for the development of male external genitalia, but also produce a chemical that regressed Müllerian ducts in rabbit fetuses , cattle 2 in pig ,13. Rece2 in pig . Hence, The superfamily TGF-β has over 30 ligands, including bone morphogenetic proteins (BMPs), which are the largest subfamily, as well as growth and differentiation factors (GDFs) ,16. PrevIn mammals, five different type II receptors have already been identified, with AMHRII specifically involved in AMH signaling ,20 whileAMH production starts as early as the initial selection of ovarian follicular waves . AMH expr = 0.89, p < 0.001) with low vs. high AFC [p < 0.01) [In the bovine estrus cycle, the growth of follicles occurs under the influence of FSH at an interval of 7–10 days . The grohigh AFC . The bashigh AFC  and beefhigh AFC  heifers,high AFC  and lacthigh AFC . The con < 0.01) , while t < 0.01)  and caus < 0.01) . The ova < 0.01) . In conc < 0.01) ,50,54,55r = 0.97) with the average of the AMH level determined from measurements at multiple time points at different days of multiple estrus cycles [r = 0.65; p < 0.01) with a superstimulated response (number of corpus luteum at the time of flushing) and total collected embryos  and progesterone  [Emerging knowledge depicts that AMH level slightly varies during the estrus cycle of cattle. The measurement of the AMH level in young adult beef heifers at a single time point was found to be highly positively associated  . The abor = 0.90) with the disparity in AFC and the histologically determined total number of morphologically healthy follicles  and oocytes in the ovaries of young adult cattle [r = 0.92) with an average peak AFC during two or three waves of an estrous cycle [AMH was highly positively correlated  was positively associated with AMH in heifers. In the division of the above-discussed study, further analysis revealed that Q1 cows (low AMH group) had a short lactation period (180 days) as compared to Q2 and Q3 cows. The percentage of cows in Q1, Q2, Q3, and Q4 were respectively 24%, 37%, 43%, and 32% after culling in the herd. This result indicates that the probability of culling was high in Q1 group as compared to the other three groups . These findings lead to the conclusion that a single test of circulating AMH concentration in young heifers can predict herd longevity .It has been shown that the quantity of AMH varies slightly during the same days of two estrus cycles in the same cattle ,59. In dBos indicus , both AMH and AFC were used as markers for superstimulation, but the response of superovulation was negatively correlated with the number of follicles and ova in cattle ovaries ,83,84,85s  fos  have a potential impact on the physiology, offspring, and reproduction of animals . In sheeOvarian diseases can lead to altered ovarian function, contributing to the follicular persistence and endocrine/paracrine changes found in domestic animals. AMH emerged as a potential biomarker for several ovarian tumors in cows ,102,103,Naturally, gestation and lactation traits are interlinked by hypothesis. Cows were selected as having a chronic mammary gland infection (increased somatic cell count (SCC)) , and dauIn superstimulation treatment, cattle with low AFC show a poor response . To testRecently, AMH has become a hot topic for researchers due to its ability to make predictions regarding the ovarian reserve pool. Due to its static nature, the collection of a single dose of blood has become more popular in the field of ART. In contrast to AFC, the strong genomic and pedigree-based heritability of AMH strengthens the case for its use as a reproductive biomarker of fertility. The peripheral AMH level has become representative of the ovarian reserve pool and is currently a promising marker for fertility and a diagnostic marker for ovarian disorders in domestic animals. The relationship with reproductive performance parameters—i.e., breed, age, longevity, fertility, and ovarian reserves (for heifers)—needs further confirmation within large herds. The impact of management factors (disease and nutrition), hormones, and lower response of AFC to cattle and goat granulosa cells opens a new pathway for future research. In many domestic farm animal species, the association of AMH to fertility superovulation and disease remains unexplored.


This interrupted time series analysis and cross-sectional study examines changes in alprazolam prescribing patterns after a national policy change that reduced alprazolam subsidies in Australia. Was implementation of changes to public subsidy of alprazolam associated with changes in alprazolam prescribing, dispensing, or poisonings?In this interrupted time series analysis and cross-sectional study, after the February 2017 implementation of the policy intervention, subsidized dispensings decreased by 51.2% but prescribing approvals increased by 17.5%. Despite the policy reducing pack size, dispensing of more than 50 tablets also increased overall and among people receiving new alprazolam prescriptions.This study found a reduction in subsidized alprazolam use after the policy change, but prescribing contrary to best-practice recommendations was common, with a likely shift to the private market. Benzodiazepines have been a common target for policy interventions to curtail inappropriate use, with mixed results. To reduce alprazolam misuse, in February 2017, Australia delisted the 2-mg tablet strength from public subsidy, eliminated refills, and reduced the pack size from 50 tablets to 10 tablets.To describe changes in alprazolam dispensing, prescribing, and poisonings associated with the implementation of a new policy to reduce inappropriate prescription of alprazolam in Australia.This interrupted time series analysis and cross-sectional study included data from a 10% sample of Australian people who received publicly subsidized dispensing claims and prescribing approvals for alprazolam from January 1, 2015, to December 31, 2018, and all calls to a poison information service involving alprazolam from February 1, 2015, to October 31, 2018. Autoregressive error models were used to quantify changes over time and compare patterns of use before and after the intervention. Data analyses were conducted from November 2018 to May 2019.Implementation of the policy change on February 1, 2017.Monthly trends in alprazolam prescribing approvals and dispensings, quarterly trends in telephone calls involving alprazolam to a poison information service, and patterns of prescribing and dispensing before and after the intervention.From 2015 to 2018, there were 71 481 alprazolam dispensings to 6772 people. After the intervention, overall dispensing decreased by 51.2%  and prescribing approvals increased by 17.5% . Overall, the proportion of dispensing of packs of 51 to 100 tablets increased from 5776 of 24 282 dispensings (23.8%) to 4888 of 10 676 dispensings (45.8%)  and dispensing of packs of more than 100 tablets increased from 1029 of 24 282 dispensings (4.2%) to 1774 of 10 676 dispensings (16.6%) . Among people receiving their first alprazolam prescription, initiation with packs of 10 tablets or fewer increased from 16 of 1127 people (1.4%) before the intervention to 139 of 589 people (23.6%) after the intervention . Alprazolam treatment initiation with packs of more than 50 tablets also increased from 63 of 1127 people (5.6%) before the intervention to 144 of 589 people (24.4%) after the intervention . During 1 year before the intervention, patients received a median (interquartile range [IQR]) total of 250 (50-600) tablets and median (IQR) total combined tablet strength of 188 (50-550) mg. During 1 year after the intervention, people were dispensed less alprazolam, with a median (IQR) total of 200 (50-500) tablets and median (IQR) total combined tablet strength of 120 (30-360) mg. There was little change in poisoning calls involving alprazolam.This study found that after the policy intervention, subsidized alprazolam use decreased, but the increase in prescribing approvals placed additional burden on prescribers. Even after the intervention, most people who were dispensed alprazolam were still receiving treatment contrary to best-practice recommendations. Furthermore, the poison information center data suggested that people were still being dispensed the 2-mg tablet strength, presumably as nonsubsidized  prescriptions. While policy interventions are often associated with a reduction in overall benzodiazepine use, these shifts in prescribing behavior often occur across the entire treated population and, in many cases, among people for whom use is considered appropriate.12 In recent years, there has been a renewed interest in benzodiazepine harms due to their use in combination with opioids, which greatly increases the risk of fatal overdose.15Benzodiazepines have been a frequent target for policy interventions owing to long-standing evidence about overprescribing and misuse.16 but with no demonstrable additional therapeutic benefit.17 It is also misused frequently by people who inject drugs19 and commonly present in drug overdose.22 Concerns have been raised about inappropriately large pack sizes and tablet strengths, and in February 2017, in an attempt to reduce the inappropriate use of alprazolam, the Australian Pharmaceutical Benefits Scheme (PBS) delisted the 2-mg tablet strength from public subsidy, reduced the pack size from 50 tablets to 10 tablets, and eliminated refills.23 Therefore, we used an interrupted time series analysis and cross-sectional study to determine whether these changes to the public subsidy of alprazolam were associated with in changes in (1) overall prescribing and dispensing, (2) patterns of prescribing and person-level use, or (3) poisoning calls to a poison information center (PIC) involving alprazolam.Alprazolam, a short-acting benzodiazepine, is subsidized in Australia for treatment of panic disorder when other treatments have failed or are inappropriate. It is significantly more toxic than other benzodiazepinesSTROBE) reporting guideline.This study was approved by the New South Wales Population and Health Services Research Ethics Committee and the Sydney Children’s Hospital Network Human Research Ethics Committee. The requirement for informed consent was waived because the data were deidentified. Access to the PBS data was granted by the Australian Department of Human Services External Request Evaluation Committee. This study used the Strengthening the Reporting of Observational Studies in Epidemiology  or less.24 On February 1, 2017, multiple changes were made to the authority-required PBS listing of alprazolam. First, the 2-mg tablet strength was delisted from subsidy, but it could still be dispensed through private  prescriptions. Second, the number of refills was reduced from 2 to 0, with no possibility of an increase; thus, people were required to visit a prescriber for each pack dispensed. Third, the pack size was reduced from 50 tablets to 10 tablets, but prescribers could request approval for larger amounts if deemed clinically necessary.23 Prescriptions written prior to February 1, 2017, could still be dispensed after this date if they were still valid.In Australia, alprazolam is only PBS subsidized for panic disorder when other treatments have failed or are inappropriate.We used dispensing records from the PBS for a 10% random sample of Australian residents who had ever been dispensed alprazolam; this is a standard data set provided by the Australian Department of Human Services for analytical use and is selected based on the last digit of each individual’s randomly assigned unique identifier. This data set captures original and repeated dispensings for PBS-listed medications. Private dispensings are not captured. Prescribing approvals  for all alprazolam PBS-subsidized prescriptions are recorded in a separate database by date of approval , regardless of whether they were subsequently dispensed. To protect privacy, all dates for both data sets are randomly offset by −14 or +14 days; the direction of the offset is the same for all records for each individual. We used data from February 1, 2013, to December 31, 2018.25We also used data from telephone calls involving alprazolam exposure to a PIC from February 1, 2015, to October 31, 2018, to identify changes in poisonings associated with alprazolam. Australian PICs provide advice to health care professionals and members of the public 24 hours per day, 7 days per week. We used data from Australia’s largest PIC, New South Wales PIC, which takes approximately 50% of the nation’s 205 000 poisoning telephone calls per year. This includes calls from the states of New South Wales and Tasmania and the Australian Capital Territory, with after-hours calls taken from all of Australia 7 days per 2 weeks as part of the national roster.26 A new dispensing of alprazolam without a dispensing in the previous 730 days was considered initiation of a new treatment episode.To identify changes in patterns of prescribing as well as person-level use of alprazolam during 1 year, we identified all people who had been dispensed alprazolam between August 1, 2017, and July 31, 2018, as the postintervention cohort. We excluded the first 6 months after the intervention to ensure that all dispensed alprazolam had been prescribed after the intervention date, as people could still refill prescriptions written prior to the intervention up to 6 months after the date of prescribing. As the comparison group, we identified all people dispensed alprazolam between November 1, 2015, and October 31, 2016, as the preintervention cohort. We excluded the 3 months leading up to the intervention because prescriber behavior may have changed in anticipation of the intervention, as we observed with the rescheduling of alprazolam in 2014.Prior to February 1, 2017, alprazolam was available in the following tablet strengths: 0.25 mg, 0.5 mg, 1 mg, and 2 mg. After February 1, 2017, the 2-mg tablet was no longer subsidized. Alprazolam is relatively inexpensive, and it was still possible to obtain the 2-mg tablet strength alprazolam on the private market. During the study, among people receiving additional government benefits, such as those 65 years or older or with low incomes, the cost of alprazolam was lower if accessed via the PBS. However, for people who were not receiving government benefits, the out-of-pocket costs for a PBS-subsidized prescription or a private prescription were comparable.To ensure that any observed changes were associated with the subsidy changes and not other interventions or nonspecific changes to dispensing and prescribing practices, we examined dispensing and prescribing for several control medications. As controls for changes in dispensing, we included dispensing of other subsidized benzodiazepines . Benzodiazepines other than alprazolam generally do not require prior approval to prescribe; thus, as a control for prescribing approvals we included approvals for all medications  that required an approval for the duration of the study.27 including other benzodiazepines , antidepressants (N06A), antipsychotics , and gabapentinoids . We also examined dispensing of opioids (N02A), as their use in combination with benzodiazepines is generally not recommended and increases the risk of mortality in overdose.13Among the preintervention and postintervention cohorts, we also identified the dispensing of other medications for mental health disorders within the year using World Health Organization Anatomical Therapeutic Chemical classification codes,For each calendar month, we summed the number of dispensings and prescribing authority approvals for alprazolam and the control medications. As our data had no negative values, we log transformed our data to estimate relative (percentage) changes rather than absolute changes. We used an interrupted time series analysis to assess the change in each of these measures using a linear regression model with autoregressive errors, which includes previous (lagged) values of the outcome as predictors in the model to adjust for serial correlation of residuals. The number of dispensings and prescribing approvals for each medication was modeled separately, and the autoregressive order  for each model was chosen to maximize model fit  and to eliminate autocorrelation of residuals, as determined by the Durbin-Watson test and the autocorrelation function plot. To control for seasonality, we included monthly dummy variables. We considered both sudden, sustained changes , and changes in slope . We excluded the 6 months following the intervention, which we considered as a transitional period when people could still obtain refills for prescriptions written prior to February 1, 2017.Among our preintervention and postintervention alprazolam-treated cohorts, we also examined changes in the prescribing patterns by calculating the proportion of all dispensings by number of tablets  and total combined strength of all tablets . We did this both overall and among new treatment episodes only. Owing to a relatively smaller cohort of new treatment episodes, we used the categories 10 or fewer, 11 to 50, and more than 50 for both tablets and total combined strength of all tablets. Categories were chosen to reflect the most common pack sizes. Because these proportions were relatively stable (no trend) through time  and R version 3.5.1 . From January 1, 2015, to December 31, 2018, there were 71 481 alprazolam dispensings to 6772 people. After the intervention, the total number of alprazolam dispensings decreased by 51.2%  from August 1, 2017, to December 31, 2018, but there was a 17.5%  increase in prescribing approvals, as after the intervention, every pack dispensed required an approval . We obseIn the preintervention cohort, there were 24 282 dispensings among 4212 people, of which 6874 dispensings (28.3%) were for the 2-mg tablet strength. In the postintervention cohort, there were 10 676 dispensings to 2419 people. In the preintervention cohort, 17 435 dispensings (71.8%) were for 11 to 50 tablets, followed by 5776 of 24 282 dispensings (23.8%) for 51 to 100 tablets A. Only 4Among people receiving alprazolam treatment for the first time  before the intervention, nearly all initial dispensings were for 11 to 50 tablets (1048 dispensings [93.0%]), reflecting the standard pack size of 50 tablets B. After In the preintervention period, 4212 people were dispensed alprazolam, compared with 2419 people in the postintervention period, a 42.6% reduction. People who were dispensed alprazolam before the intervention received a median (interquartile range [IQR]) of 4 (1-9) dispensings, a median (IQR) total of 250 (50-600) tablets, and a median (IQR) total combined tablet strength of 188 (50-550) mg during 1 year; after the intervention, people received a median (IQR) of 3 (1-7) dispensings, a median (IQR) total of 200 (50-500) tablets, and a median (IQR) total combined tablet strength of 120 (30-360) mg.Despite this reduction, 318 people (13.2%) received 10 or more dispensings, 583 people (24.1%) received more than 500 tablets, and 430 people (17.8%) received a total combined tablet strength of more than 500 mg during the year after the intervention . DispensFrom February 1, 2015, to October 31, 2018, there were 1096 calls to New South Wales PIC involving alprazolam; 938 calls (85.6%) were for intentional misuse , 130 calls (11.9%) were for unintentional misuse , and 28 calls (39.1%) could not be classified. Of 606 calls (55.3%) in which the total dose ingested was recorded, the median (IQR) dose before the intervention was 9 (3-25) mg; after the intervention, the median (IQR) dose was 10 (3-36) mg.There was a median (IQR) of 72 (64-84) calls per quarter before the intervention and 74 (64-84) calls per quarter after the intervention. The number of calls was stable before the intervention  . We obseOur study found a substantial 51.2% decrease in overall PBS dispensing of alprazolam after the introduction of the new prescribing restrictions; this was accompanied by an 17.5% increase in the number of approvals for new prescriptions. While we did observe a reduction in PBS-subsidized alprazolam use, which was the main target of the intervention, we estimate that after the intervention, there were approximately 2000 additional prescriptions per month at the population level, each requiring a visit to a prescriber plus an authority approval. Thus, it is unclear whether the observed reduction in dispensing will result in cost savings for the government given the increase in approvals to prescribe, and its impact on health outcomes is uncertain.28 Even among people initiating new treatment courses, we observed an increase in dispensing of pack sizes of more than 50 tablets, putting people at a greater risk of transition to long-term use and dependence.Notwithstanding the reduction in dispensings, among individuals who were still being dispensed alprazolam after the intervention, prescribers appeared to compensate for the elimination of 2-mg tablets and refills by prescribing increased quantities, despite the introduction of a new smaller pack size. Reducing the pack size, while well intended, was not sufficient to reduce quantities dispensed. Since all prescribers had to request approval to prescribe alprazolam, requesting approval for increased amounts required little extra effort, as it could be done at the same time. Thus, a substantial proportion of people were still receiving amounts well above the recommended dosages and durations of therapy.29 When refills for low-dose quetiapine were eliminated in Australia to prevent prescribing outside its approved indications, subsidized dispensing decreased overall, but there was little impact on inappropriate use.5 Despite the reduction in subsidized alprazolam use, we cannot be certain to what extent prescribing decreased overall, as we did not have data on nonsubsidized  prescriptions. Given alprazolam’s low cost, a shift to the private market would not be surprising, as there is little price difference between private or PBS-subsidized prescriptions for many people. Likewise, in Ontario, Canada, after high-strength opioids were delisted from the public formulary, 1 in 3 people accessed them via private insurance or by paying for the medication out of pocket.6Similar approaches have been used to restrict access to other commonly misused medications, such as opioids and quetiapine, with equally mixed results. In the United States, when prescription refills were no longer available for hydrocodone after its rescheduling, the amounts dispensed at the initiation of postsurgery treatment increased.30 suggested that most people who misuse benzodiazepines were prescribed them by a health care practitioner for the treatment of real symptoms, making prescribers an appropriate target for intervention. However, many prescribers are skeptical about certain policy interventions, such as requirements for authorities, to promote prescribing according to best-practice recommendations and safe use of medications.31 Moreover, discontinuing long-term benzodiazepine use can be difficult33; thus, increasing restrictions on subsidized benzodiazepine prescribing on its own may have minimal effect on problematic long-term use, particularly in the context of a thriving private market. Imprecise interventions, such as withdrawing reimbursement, often have unintended consequences and are rarely sufficient on their own to promote safer use of medications.8A 2013 study by Nielsen et al34 and this has likely increased in recent years. While some people may have switched to smaller PBS-listed tablet strengths after the intervention, there was no change in the proportion of calls to the PIC involving the 2-mg tablet strength. While these results suggest that the 2-mg tablet strength is still available in the community, calls to a PIC are a crude measure, only capture a subset of poisonings, and should be interpreted with caution. Further work will be needed to determine the true effect of the intervention on health outcomes.Our study had some limitations. First, we had no information about indication for treatment or other clinical information for people who were dispensed alprazolam; thus, we could not assess appropriateness of prescribing. We also did not have information about the dispensing of alprazolam on the private market; in 2015, approximately one-quarter of alprazolam was prescribed privately,While this study found that the intervention was associated with a decrease in dispensing of PBS-subsidized alprazolam, there was an increase in prescribing approvals, potentially placing an increased burden on the health care system without clear benefits in reducing inappropriate use. Most people dispensed alprazolam were still receiving treatment outside the restrictions and best-practice recommendations, particularly with increased pack sizes to work around the reductions in refills per prescription. Further, the PIC data suggest that the intervention was associated with minimal changes to dispensing of the 2-mg tablet strength, as prescribing appears to have shifted to the private market.


Burkholderia genus to be the most abundant among bacteria. The chamber-associated growth conditions further increased their abundances relative to the soils. Ascomycota was the most abundant fungal phylum in the chambers relative to the soils, with Penicillium as the most dominant genus. Metagenomics-based taxonomic findings completely mirrored the taxonomic composition of the retrieved isolates such that the U-resistant bacteria and fungi mainly belonged to Burkholderia and Penicillium species, thus confirming that the chambers facilitated proliferation and subsequent isolation of specific microbiota with environmentally relevant functions. Furthermore, shotgun metagenomic analysis also revealed that the gene classes for carbohydrate metabolism, virulence, and respiration predominated with functions related to stress response, membrane transport, and metabolism of aromatic compounds were also identified, albeit at lower levels. Of major note was the successful isolation of a potentially novel Penicillium species using the MT approach, as evidenced by whole genome sequence analysis and comparative genomic analysis, thus enhancing our overall understanding on the uranium cycling microbiota within the tested uraniferous soils.Despite the recent advancements in culturomics, isolation of the majority of environmental microbiota performing critical ecosystem services, such as bioremediation of contaminants, remains elusive. Towards this end, we conducted a metagenomics-guided comparative assessment of soil microbial diversity and functions present in uraniferous soils relative to those that grew in diffusion chambers (DC) or microbial traps (MT), followed by isolation of uranium (U) resistant microbiota. Shotgun metagenomic analysis performed on the soils used to establish the DC/MT chambers revealed Proteobacterial phyla and  A myriad of ecosystem services are performed by soil microbiota, including biogeochemical cycling of nutrients, degradation of contaminants and as symbionts, and enhancing both animal and plant health . HoweverE. coli and Deinococcus radiodurans; both isolates grew in the presence of up to 20 mM uranium [Penicillium genomes are beginning to provide critical insights into the genomic and metabolic diversity of this soil-borne genus [Furthermore, with the application of 16S ribosomal gene sequencing-based metagenomics or shotgun metagenomic approaches, environmental niches can now be probed to obtain a precise and sensitive understanding of the native microbial diversity along with the plethora of ecosystem services they provide, such as detoxification of environmental contaminants in their native habitats. As examples, metagenomics provided a deeper understanding in soils contaminated with heavy metals and radionuclides ,15,16. I uranium . Further uranium ,20 but tne genus ,22. ThusHowever, in tandem with the above stated omics based analyses, sensitive and precise techniques are also needed to isolate specific microorganisms, identified by molecular surveys, so that the microbially-mediated functional traits can be better studied and understood for appropriate downstream applications, such as bioremediation. Towards this end, Bollmann et al.  conducteHowever, such studies have generally focused on the isolation of bacterial communities, with soil fungi continuing to be largely ignored. Note that a growing body of literature now shows that fungi often outcompete bacteria at high concentrations of environmental contaminants, specifically U  and otheCaulobacter crescentus [Microbacterium oleivorans A9 was grown in the presence or absence of uranyl nitrate [Burkholderia spp. and Arthrobacter spp. Both these bacterial genera have been demonstrated to serve as bioindicators of environmental contamination as well as agents of U bioremediation [Burkholderia spp. and Arthrobacter spp. is beginning to unravel the molecular basis for resistance against uranium, including a suite of substrate binding proteins, permeases, transport proteins/regulators, efflux pumps, metal resistance proteins , stress proteins, cytochromes, and drug resistance gene determinants, likely working in concert to potentially detoxify uranium toxicity within the SRS impacted ecosystem [Burkholderia spp. and Arthrobacter spp. have a strong metabolic basis for colonization and survival in radionuclide and metal contaminated habitats.Among the more well-known molecular mechanisms that underpin bacterial and fungal response(s) to uranium, included are the overexpression of a phytase enzyme and an ABC transporter in escentus . Another nitrate . To furt nitrate ,34. A 16ediation ,36. Furtcosystem ,34,37. TOther than the above stated works on the responses of axenic microorganisms to heavy metals and uranium, only a handful studies are available on the impacts of U stress at the metagenomic levels, especially the shotgun metagenomic response(s) in context with community-wide functional potential ,38,39,40Streptomyces, Streptacidiphilus, Catellatospora, Lentzea, and Catenulispora were amenable to isolation [Our study site, the SRS, is located near Aiken, South Carolina, where large quantities of U were released to the environment from decades of nuclear materials production and refinement for nuclear weapons production activities . Successsolation . Therefosolation  and micrsolation , using uPenicillium species MT2, a draft genome sequence was obtained, which led to a detailed comparative genomics study, thus providing a unique peek into strain MT2′s arsenal of metal-resistance traits. Overall, such DC/MT based studies will be useful for the isolation of native, and potentially novel, soil microbiota that have developed resistance against uranium and, potentially, other environmental contaminants, so that a holistic understanding on metal-microbe interactions and mechanisms that underpin microbially-mediated U detoxification processes are obtained for better stewardship of historically contaminated systems, such as the SRS.The efficacy of the DC/MT technique was successfully demonstrated for (1) identification of the predominant bacterial and fungal communities present in the tested soils and (2) isolation of the predominant bacterial and fungal strains, including a potentially novel species of Penicillia. Overall, this provides a proof-of-concept for the successful application of both the DC and MT techniques to garner a better understanding of structural-functional relationships of environmental microbiota in uraniferous soils. To further gain a detailed understanding on the nature of the newly isolated Triplicate surficial soil samples were collected from an abandoned farm pond, the Steeds Pond, that served as a natural settling basin along the Tims Branch stream corridor on the SRS, located near Aiken, South Carolina. A total U concentration of 4.2 mM was observed in the soil samples used in this study for the establishment of DC/MT chambers , which i−3 dilution. One ml of this diluted sample was mixed with 9 ml of sterile molten agar at 45 °C to give a final concentration of 10−4. This was followed by fixing of a 0.03 µm pore size polycarbonate membrane  glued to the tray (using silicone glue) in such a way that 9 holes on the tray would fall exactly towards the center of the membrane. Instead of working on a single DC/MT chamber, we used a plate with several even sized holes 0.8 mm in height and 0.7 mm in diameter; 9 of such holes were used as multiple chambers, representing DC or MT, to increase throughput microbial cultivation. Approximately 435 µl of the 10−4 diluted soil sample in agar was added to each well to fill it completely. After the agar solidified, a second membrane (0.03 µm pore size for DC and 0.2 µm pore size for MT) was glued on top to seal the chamber. Note that the MT approach is used for the isolation of uncultivable actinomycetes, many of which are well-known for their biodegradative and metabolic potential. The premise of this approach is that the 0.03 µm pore-size membrane permits the diffusion of nutrients into the chamber and facilitates the growth of environmental microbiota within the agar by mimicking in situ growth conditions. The DC (any side) and MT  were then placed on the same U contaminated soil (approximately 5 mm thick) and incubated at 28 °C for 20 days. The DC plates were flipped every 2 days and the soil underneath was mixed to remove the buildup of anaerobic conditions. The MT plates were not flipped but the soil underneath was mixed every two days to prevent the buildup of anaerobic conditions. After 20 days of incubation, chambers were opened and the gel-embedded biomass inside the DC and MT were collected and homogenized by passaging through a 22 gauge needle syringe, twice. This was called generation 1 (Gen1), part of which was used for DNA isolation as well as inoculation of the second-generation chambers , which were further incubated for 20 days. Bacteria and fungi from the Gen1 and Gen2 chambers were isolated on Luria Broth (LB) media supplemented with uranium, as well as soil extract media, to retrieve those isolates that are not able to grow with the high nutrients contained in the LB media. The soil extract media was prepared by modifying the method used by Bollman et al. [To establish the diffusion chamber, a 1 g soil sample (a mixture of the 3 replicated samples) was mixed with 9 ml of sterile normal saline and serially diluted to 10Genomic DNA was isolated from soils and DC/MT plugs using the DNeasy PowerLyzer Kit, according to the manufacturer’s instructions . Quantity and quality of the isolated genomic DNA was evaluated by using a micro-volume spectrophotometer  and further processed for shotgun metagenomics. Briefly, sequence libraries were prepared using the Illumina Nextera XT kit, according to manufacturer’s instructions . Sequencing was performed on an Illumina NextSeq500 instrument employing a mid-output kit with 2 × 150 paired-end sequencing. For taxonomic profiling, raw reads were mapped to the NCBI non-redundant protein database using DIAMOND . Taxonomp-value cut off of 0.05.MicrobiomeAnalyst pipeline  was run DNA isolation from the DC and MT gels and from the bacterial and fungal strains isolated from this study was performed using DNeasy PowerLyzer Microbial Kit . Bacterial and fungal strains were identified based on the 16S and 18S rDNA sequencing analysis, respectively. PCR was performed with 27F-1492R universal bacterial primers  at an in600 of ~0.3. The OD was measured every 4 hours for 3 days at 28 °C with constant shaking. All the assays were performed in triplicate. Growth efficiencies of the isolated fungal strains on U were determined by growing the strains on potato dextrose (PD) agar in the presence of different concentrations of U (0–15 mM). Two-day old fungal cultures from PD broth were inoculated in the center of PD agar plates. The resulting diameter of the fungal colony was measured every 24 hours at 28 °C as a measure of resistance to U.Growth efficiencies of the isolated bacterial strains on U were determined as follows. Briefly, LB media was mixed with uranyl nitrate to yield different concentrations of U, ranging from 0 to 5 mM. The isolated strains grown overnight in LB media were then added to obtain an OD3 (v/v). These samples were analyzed using an ICP-OES  for the presence of soluble U.Uranium reduction by the isolated strains was evaluated in soil microcosms. In a 250 ml Erlenmeyer flask, 10 g SRS uraniferous soil was added to liquid growth media (LB for bacteria and Potato Dextrose Broth (PDB) for fungi) to make a total volume of 100 ml and autoclaved. Uranium was added to the flasks, as uranyl nitrate, to reach a final concentration of 1 mM or 2 mM U. All microcosms were set up in duplicates. The bacterial strains grown overnight in LB media were used as bacterial inoculum, the fungal strains grown for 3 days were used as fungal inoculum. A total of 1ml of each inoculum was added to the respective microcosm and incubated at 30 °C at 100 rpm for 96 hrs. Samples to determine U concentration were withdrawn every 24 hrs. Each sample was centrifuged at 7000 rpm for 10 min and supernatant was collected and acidified to 2% HNOPenicillium oxalicum strain (KB644408.1) for training. A circular genomic map of strain MT2 was generated using the CGView Comparison Tool pipeline or the embedded tool in the EDGAR pipeline [Genomic DNA from strain MT2 was extracted using a MoBio PowerLyzer kit , prepared for sequencing with Illumina Nextera XT library preparation protocol , and sequenced using a NextSeq500 instrument. De novo assembly was performed using the Spades assembler  and comppipeline .st + 2nd + 3rd. There was a total of 9777 positions in the final dataset.Based on the presence of coding sequences for genes Tsr1, Cct8, RPB1, and RPB2A within the genome sequence of strain MT2, a phylogenetic tree was constructed. Sequences were aligned using the Muscle algorithm in the MEGA X package , realignPenicillium janthinellum strain NCIM1366, as previously described [Further evolutionary relatedness of strain MT2 was inferred by using EDGAR , which aescribed . This ANescribed .Burkholderia sp. DC2 (MH595922), Burkholderia sp. DC3 (MH595923), Penicillium sp. DC1 (MH595924), Penicillium sp. MT1 (MH595925), and Penicillium sp. MT2 (MK300050), respectively.The 16S rDNA sequences of strains isolated in this study are deposited in NCBI GenBank, as shown in parentheses, as follows: The metagenomic sequences obtained from this study are available from NCBI’s Sequence Read Archive/European Nucleotide Archive, accession number SUB4896106 under BioProject PRJNA509237 .Penicillium sp. strain MT2 reported in this study has been deposited at DDBJ/ENA/GenBank and is available using accession number PZKB00000000 [The Whole Genome Shotgun sequence of 00000000 .Shotgun metagenomics was performed to evaluate the soil microbiome colonizing the DC and MT chamber niche relative to the soils used for these experiments. The total sequence read counts obtained from all the soil samples used in this study are shown in Proteobacteria accounted for almost half of the diversity, followed by Actinobacteria, Acidobacteria, and Firmicutes. Similar results have been observed in a U contaminated soil in southern China, which also revealed Proteobacteria and Actinobacteria predominated as a function of U contamination [Proteobacteria and Acidobacteria, with the members of genus Geobacteraceae dominating the overall bacterial population [Geobacteria genus are both well known to be metabolically, ecologically, and environmentally diverse and, hence, outcompete other phyla in a variety of soil conditions, including contamination with U. Of further interest was the observation that Proteobacterial communities significantly proliferated in the growth conditions presented by both DC and MT  and relative abundance of 0.2%, respectively. The core microbiome abundance further increased significantly in the subsequent transfers, such that ectively B. HoweveRS soils ,37. In fRS soils ,66. Simicrobiota ,68,69. Mbilities ,73,74,75bilities . TherefoFurthermore, dendrogram analysis revealed that the soil microbiome community was distinctly different between soils and the DC/MT generations , suggestMethanosarcina, Nitrososphaera, Methanocaldococcus and Methanocella  [Methanosarcina spp. play critical roles within the SRS U-contaminated soils, especially under anaerobic conditions. Previous studies of acetate-stimulated U bioremediation have largely focused on the Geobacter spp. because no other microorganism capable of coupling oxidation of acetate with U(VI) reduction has been demonstrated thus far. We are tempted to speculate that, in the SRS soil habitat, Burkholderia spp. are active in the surficial aerobic soil niches and, once the redox potential becomes anoxic, the U bioremediation is catalyzed by Methanosarcina spp., which will be the subject of our future research. Furthermore, dendrogram analysis showed that the soil archaeal community was distinctly different relative to the DC/MT generations   in the Rerations , suggestPenicillium, Aspergillus, Talaromyces, and Fusarium, were the most predominant. It is interesting to note that the relative abundance of Penicillium spp. increased considerably in both DC and MT, relative to the soils. Penicillium spp. reached a relative abundance of 40%–48% in the 2nd MT generation. Similar response was shown by Aspergillus spp., whose relative concentration significantly increased in both the DC and MT plugs. From these results it can be concluded that the DC and MT gels are selective for Penicillium and Aspergillus spp. It is noteworthy that similar to Burkholderia spp., which was one of the most abundant bacterial genera in the soils and also enhanced in the culture conditions presented by the DC and MT plugs, the fungal Penicillium genus was also facilitated to thrive by the in situ DC/MT culture conditions. Thus, it appears that those communities having the ability to resist and even bioremediate U were preferentially selected by the DC/MT technique. This observation is supported by the isolation and screening of both Burkholderia and Penicillium groups of soil microbiota in the presence of uranium, as shown later in this study.When fungal community structure was evaluated, the Ascomycota phylum was present as much as 75% of the total relative abundance in the tested soils, which increased to almost a 100% within the DC/MT plugs A. The phWe also investigated whether bacterial, archaeal, and fungal community shifts also reflected in functional shifts that were being performed in both the soil habitat and the DC/MT growth conditions, respectively. As shown in Additionally, of major interest was the identification of phosphate metabolism gene functions across the SRS soils used in this study B. HoweveIt was noteworthy that at subsystem level 3, several gene classes known to facilitate the bioremediation of contaminants were also identified, including the oxidative stress-related proteins of the YgfZ family, the YgfZ-Fe-S family, and phosphate metabolism C. It hasWhen heatmaps were plotted to tease out the gene functions that potentially shifted between the soils and DC/MT samples, it became apparent that a cohort of functions were unique to the soils , such asArthrobacter spp. and Burkholderia spp., which have shown to resist high concentrations of U [Using conventional enrichment cultures, our laboratory has previously isolated ons of U ,34. To aons of U .Burkholderia spp. and Penicillium spp., respectively. Phylogenetic trees of the isolated Burkholderia spp. are shown in Penicillium spp. are shown in Burkholderia to be the predominant species in U contaminated sediments. Further, Penicillium spp. has also been shown to resist a variety of heavy metals, including U, especially at high concentrations [The isolated strains were identified by 16S/18S gene sequencing as trations . This coBurkholderia spp., DC2, and DC3 grew well up to 2 mM U . On further increase in the concentration of U to 2.5 mM, both the strains failed to grow . It was also observed that Penicillium spp. MT1 and MT2 were more resistant to U than Penicillium spp. DC1, as it grew at a much faster rate at higher U concentrations of up to 10 mM, indicating that these strains are robust in context with U resistance and/or bioremediation.The fungal strains were grown in PD agar, amended with variable concentrations of U (0–15 mM), for 4 days and the diameter of the fungal colonies was measured every 24 hours C–E. It wPenicillium sp. DC1, MT1, and MT2 were able to deplete 94%, 89%, and 91% of soluble U, respectively. Burkholderia sp. DC2 and DC3 depleted 54% and 96% U, respectively  was calculated, the probability of strain MT2 being the same species as P. janthinellum strain NCIM1366 was estimated to be merely 6.05% (via logistic regression). Note that a DDH > 70% (via logistic regression) would be inferred as the two genomes belonging to the same species. When syntenic association of MT2 with P. janthinellum was evaluated, an extremely low similarity was seen  value of 91.45% between strain MT2 and bove 95% . This iswas seen , furtherOf further interest was EDGAR pipeline-based comparative genomics with the above stated genomes of Penicillia, which identified 1904 genes  that were unique to MT2, relative to the four closest relatives, as shown in Burkholderia spp. and Penicillium spp. were the isolated bacterial and fungal strains regardless of being treated as DC or MT, respectively. Of major mention is the isolation of a potentially new species of Penicillia using the microbial trap approach, as supported by comparative genomic analysis. The metagenomics data was in line with the culture-based findings such that the top 3 bacterial genera are taxonomically affiliated with Burkholderia, Rhodanobacter, and Bradyrhizobium in the soils. This increased to as much as 60%–80% under the conditions of DC and MT. Similarly, the top 3 fungal genera were identified as Penicillium, Aspergillus, and Talaromyces, but Penicillium colonized more favorably under the DC and MT conditions. A relative abundance of genes, coding for different functions, were also identified, which mainly belonged to carbohydrate metabolism, virulence, respiration, and, at a finer scale (subsystem level 3), the gene families for DNA replication, flagellum, and YgfZ family were the major ones, but not much change was observed between soils and the DC/MT conditions. With this study, we provide the proof-of-concept for utilizing the diffusion chamber and microbial trapping techniques for obtaining a broader understanding on the bacterial, archaeal and fungal communities that persists in a U contaminated soil habitat, as well as isolation of the key microbial players for further “omics”-based downstream analysis.In summation, the ability of bacterial strains to survive in uraniferous ecosystems has been well demonstrated for anaerobic ecosystems, but the potential of aerobic microorganisms to biomineralize uranium has been largely ignored and, hence, remains understudied. Overall, this study reports on an innovative metagenomics-guided isolation of aerobic bacteria and fungi that resist high concentrations of U. Notably, we first compared the microbial diversity using shotgun-based metagenomics in soil samples collected from the SRS and the microbiota colonizing within the DC and MT gel plugs across 2 different incubation times . Simultaneously, we isolated U resistant bacteria and fungi directly from soils as well as the Gen1 and Gen2 agar plugs.


Papillomaviridae, Anelloviridae, Genomoviridae, and Herpesviridae. Papillomavirus reads were more abundant in women with premalignant cervical lesions, which were also strongly associated with multiple (≥3) high-risk HPV infection. Anellovirus read abundance was negatively correlated with host CD4+ T-cell counts. The bacteriome revealed the presence of CST III and CST IV, and women with ≥1% frequency of genomovirus or herpesvirus reads displayed an increased risk of carrying CST IV. By characterizing the composition of the cervical circular DNA viruses and the bacteriome of HIV/HPV co-infected women, we identified putative interactions between these two microorganism communities and their associations with patients’ clinical characteristics, notably immunodeficiency status.The human cervical microbiome is complex, and its role in health and disease has just begun to be elucidated. In this study, 57 cervical swab samples from 19 HIV/HPV co-infected women were analyzed for both virome and bacteriome composition. Virome analysis focused on circular DNA viruses through rolling circle amplification followed by next-generation sequencing (NGS). Data were assigned to virus families and genera, and HPV types were identified. NGS data of bacterial 16S from a subset of 24 samples were assigned to operational taxonomic units and classified according to vaginal microbiome community state types (CSTs). Four viral families were found:  Papillomaviridae is the most prevalent eukaryotic viral family [The human microbiome consists of a collection of microorganisms such as viruses, bacteria, and fungi that symbiotically colonize the human body. This microbiome shows different profiles in each anatomical site of the body ,2,3. In l family ,7; its ol family ,5,7,8. Al family ,10,11,12l family ,14. Amonl family ,15,16, el family ,23,24,25Lactobacillus species , while CST IV shows higher bacterial diversity and a high proportion of anaerobic bacteria such as Prevotella, Dialister, Atopobium, Gardnerella, Megasphaera, and Sneathia [+ CCR5+ cell recruitment to the mucosal vaginal region, increasing the risk of HIV acquisition [Lactobacillus sp. dominant CSTs  show a negative association with HIV and HPV infections [Despite the recognized complexity of viral species in women’s cervical region, little is known about its association with bacterial communities in that anatomical site. There are five well-established distinct bacterial community state types (CSTs I–V) in the cervicovaginal region, classified according to their bacterial frequency profiles . CSTs I,Sneathia ,27. InteSneathia ,29,30. Wuisition ,29. Moreuisition ,32,33,34fections ,36. LessResearch in the microbiome dramatically improved with the advent of novel sequencing methodologies. Together, these studies have exposed the complexity of the cervical virome and bacteriome in heath and disease. This is especially important in HIV-positive individuals, since HIV/AIDS has been related with enteric and blood microbiome alterations ,38. In tCervical samples from 19 HIV/HPV co-infected women with multiple HPV infection were selected from a group of 140 HIV-positive women followed up between 2009–2011 through the “Program for HIV-infected Pregnant Women” in Rio de Janeiro, Brazil. These samples were assessed for HPV infection by PCR and Sanger sequencing and for risk factors for HPV infection and persistence in previous studies ,40. PatiCervical sample processing was performed as previously described . Total De-value < 0.001 were compared to an in-house protein database with non-viral sequences derived from GenBank’s non-redundant database. Finally, the e-values were compared, and sequences that showed the lowest e-value when compared to virus protein sequences were classified into a virus family according to the most similar sequence in the database.Reads obtained were sorted for each sample based on the dual barcodes used. Bacterial and human host reads were removed by mapping these sequences to the bacterial genomes present in the RefSeq database and the human reference genome hg19 using Bowtie 2 . DuplicaRetroviridae were HERVs, we also excluded this family from further analysis to avoid the biased underrepresentation of this virus family. We have used the normalized number of reads to each virus family in our analyses. The number of reads assigned to each virus family from the remaining viruses was normalized by calculating the log10 of 1 plus the number of reads assigned to each viral family divided by the total number of reads multiplied by one million ). We have also normalized the number of reads assigned to each virus family divided by the sequences submitted to BLASTX . Finally, the proportion of reads of each virus family was also used, calculated by dividing the number of reads assigned to each virus family by the total number of sequences submitted to BLASTX.To avoid false-positive results, virus families with less than 50 reads were excluded from further analyses. During the removal of host reads, human endogenous retroviruses (HERV) were also discarded, since they represent greater than 8% of the human genome . As mostVirome reads from each sample were mapped to genomes of different HPV types with BWA . Reads tR environment and was applied to define clusters according to the abundance and taxa diversity of each sample. The clusters found were assigned to vaginal microbiome CSTs, as defined in previous studies [The bacteriome analyses were performed for the postpartum samples (timepoints B and C) from 12 out of the 19 women of this study, because their bacterial 16S gene had already been sequenced in a previous study . Briefly studies ,50.Genomoviridae were submitted to an assembly with reference using Geneious® v.9.1 . The reference used for each sample was the sequence from the database that showed the best similarity score to the reads in BLASTX searches. The consensus sequences were extracted and aligned using ClustalW2 [Samples with reads from lustalW2 . PhylogelustalW2  with thelustalW2 .Genomoviridae were analyzed for the presence of fungal DNA using semi-nested PCR with ITS1/ITS4 primers in the first round and ITS86/ITS4 in the second round under previously described conditions [® v.9.1 (Biomatters). The consensus sequences were extracted and submitted to BLASTN to identify the fungi present in the samples.Since the only genomovirus with known tropism infects fungi , four cenditions , except + T-cell counts. The Mann–Whitney U test was used to compare the difference of read distribution or normalized number of reads for all virus families between samples with distinct cytological results. The odds ratio (OR) and 95% confidence interval values were estimated for the association of cytological lesions with multiple infections by high-risk HPV types. Similarly, the comparison of the frequency of reads or normalized number of reads of each virus family to CSTs was determined with the Mann–Whitney test. The association and risk analysis of CSTs with the presence of HPV16 was performed with the relative risk (RR) statistics. The RR was also used to analyze the association of frequency below 1% of Anelloviridae, Genomoviridae, or Herpesviridae with CSTs. All statistical analyses were performed with SPSS , and graphical representations were generated with GraphPad Prism  or with Microsoft Excel .The frequency of reads or the normalized number of reads of each virus family was used to calculate the Spearman’s correlation coefficient with the HIV viral load and CD4The consensus sequences obtained in this study were deposited in Genbank under the accession numbers MK513442 and MK513443. Sequencing reads were submitted to the Sequence Read Archive (SRA) under the project numbers PRJNA418043 and PRJNA392046.+ T-cell counts were 327/mm3, and the HIV-1 viral load was 8227 copies/mL at moment of the study’s enrollment (timepoint A). At the first, second, and third collection timepoints, nine, 14, and 10 women presented low-grade or high-grade squamous intraepithelial lesions (LSIL or HSIL), respectively. During the complete follow-up, 16 women presented LSIL or HSIL at least in one timepoint studied , Genomoviridae (2%), and Herpesviridae (0.06%). Papillomavirus reads were found in all but two of the 57 samples (44A and 44B), and reads from Genomoviridae were found in a high proportion in three samples (p < 0.001) in women that presented any type of intraepithelial lesion (LSIL or HSIL) compared to women with normal or atypical squamous cells of undetermined significance (ASCUS) cytology  , as well as the percentage of anellovirus reads . The association between HIV viral load and anellovirus reads was not significant in any read normalization calculated .The average number of reads obtained per sample after trimming out the low-quality reads was 4,193,239 . Overall, four viral families presented more than 50 reads in the samples. The most representative was  samples . The norcytology A. A corr = 0.03) B. The noGemykibivirus genus (Human-associated gemykibivirus 1 species includes viruses isolated from human blood (acc.# LK931485) [Human-associated gemykibivirus 2 species, which includes strains isolated from human cerebrospinal fluid , from human feces (acc.# KP133078 and acc.# 1330799) and from sewage (acc.# KP133080) [Reads from two samples (30A and 87B) assembled one complete genomovirus genome each. Both genomes had the three characteristic open reading frames  and the nonamer of the stem-loop structure A,B. A phus genus C. The geK931485) , plasma K931485)  and sewaK931485) . The GmkP133080) .Sclerotinia sclerotiorum hypovirulence-associated DNA virus 1 (SsHADV-1) that infects the plant pathogenic fungus Sclerotinia sclerotiorum [Genomoviridae family, we evaluated the presence of fungi DNA in a subset of cervicovaginal samples. Samples 30A, 31A, 44A, and 87B, presenting Genomoviridae reads, and samples 4A, 48A, 58A, 67A, 101B, and 118A, with no evidence of Genomoviridae reads , were analyzed by PCR. Candida sp. was identified in three samples , and Sarocladium sp. was identified in one sample (87B). Therefore, fungal DNA was identified in three  of four samples with Genomoviridae reads and in one of the controls.The only genomovirus with a confirmed host is the rotiorum . ConsideAlphapapillomavirus genus. Patients showed different HPV type proportion patterns among them, and there was also intrapatient HPV type variation over time  samples . An avern = 2; HPV84, n = 1; HPV86, n = 3; HPV102, n = 2).When different timepoints of the same patient are compared for HPV type persistence, HPV33 was found in all three follow-up samples of the two women positive for this virus type . HPV16 wn = 4; 103C, n = 12), most of their reads (>96%) are assigned to only one (103C) or two (32C) HPV types  and CST IV (high proportion of anaerobic bacteria). They were present in 32% and 68% of the samples, respectively , but no significant differences were found . These results may be due to the limitations of the methodology used, since RCA will amplify circular DNA, and consequently will fail to detect HPV copies integrated into the host DNA, which may be the case for those samples. Despite our limitations, we could observe a high inter-patient variability regarding the frequency and diversity of different HPV types. Concomitant infection with more than one HPV type was associated with an increased risk of cervical lesions in several studies ,82,83,84Lactobacillus sp. . CST IV exhibits higher species diversity and a high proportion of multiple anaerobic bacteria, including Gardenerella, Prevotella, Atopobium, Sneathia, Aerococcus, and Megasphaera [Anelloviridae, Herpesviridae, and Genomoviridae) found in this study, which had not been previously analyzed. We observed a higher frequency of samples with read abundance ≥1% of Genomoviridae and Herpesviridae in CST IV, showing an increased risk of 54% and 47%, respectively. Additionally, CST IV samples also displayed a higher proportion of HPV non-16 viruses. The mechanisms involved in the establishment of such viral infections and how the bacteriome modulates or is modulated by them remains to be elucidated. However, our data strongly point out to a scenario in which a more immunodeficient status, which is commonly associated with CST IV, also allows the establishment of viral infections that are less frequently detected in immunocompetent hosts. This is the case of genomoviruses , herpesviruses, and HPV non-16 types, as seen herein.The bacteriome has been recently described as a critical factor that could affect the increase or decrease of viral infections . The femasphaera ,50. In tasphaera ,90. HoweDespite the small number of patients followed herein, this study was able to describe the composition, dynamics, and the putative interaction of the cervical circular DNA virome and the bacteriome in a highly susceptible group of HIV-positive pregnant women. However, additional studies are necessary to clarify the role and the mechanisms of the microbiome homeostasis and its association with the host health and disease, including the development of cervical lesions and cancer.