Changes in the composition and diversity of gut microbiota, which can be altered by autonomic nerve activity, contribute to the development of heart failure (HF). Renal denervation (RDN) can improve cardiac function by reducing sympathetic nerve activity. However, whether the beneficial role of RDN on HF is related to gut microbiota is unknown.  Thirty rats were assigned to a control, HF (with induced transverse aortic constriction (TAC)), RDN (with RDN induced 10 weeks after TAC), Nog (HF rats with Nogo-P4-administered 8 weeks after RDN), and NEP (HF rats with NEP1-40-administered 8 weeks after RDN) group. Then, 16SrRNA amplicon sequencing and analyses of fecal samples were performed. Firmicutes/Bacteroidetes ratio was reduced in the HF group (1.59) compared with the control group (3.21) and was significantly decreased compared to the Nog (7.19), RDN (6.20), and NEP (4.42) groups. At the genus level, the HF group showed decreased abundances of Lactobacillus and Alistipes and increased abundances of Bacteroides and Clostridium compared with the control group. The abundances of Lactobacillus and Alistipes were increased, and those of Bacteroides and Clostridium were decreased in the RDN, Nog, and NEP groups compared to the HF group. However, no differences were observed between the three groups that underwent RDN. The microbial function showed the same tendency.  Beta diversity analyses revealed that compared to the HF group, the RDN, Nog, and NEP groups clustered closer to the control group. The  RDN reversed the abnormal changes in the gut microbiome in HF rats. Inhibition of reinnervation after RDN did not affect intestinal bacteria. Heart failure (HF) is a common, costly, and life-threatening disease . DespiteAltered gut microbiota is associated with several chronic diseases including HF. The severity and prognosis of HF can be influenced by gut bacteria and their products. Some special products of intestinal bacteria such as trimethylamine (TMA)  and butyHowever, gut microbiota and their hosts' nervous systems are in constant communication via neural, endocrine, and immunological mechanisms . TherefoWe hypothesized that RDN could reverse intestinal microflora aberrations observed in HF rats and had a beneficial effect on cardiac function by influencing intestinal bacteria. Therefore, this study aimed to investigate the specific changes in gut microbiome composition and function in HF rats before and after RDN. We also explored the effects of regulating nerve regeneration after RDN on cardiac function and intestinal microbiota by intraperitoneally injecting Nogo-P4, an inhibitor of axonal regeneration , or NEP n = 4), the rats received sham transverse aortic constriction (TAC), sham RDN, and an intraperitoneal injection of 2 ml of 0.9% saline; (2) in the HF group (n = 7), the rats received TAC to induce HF, sham RDN, and an intraperitoneal injection of 2 ml of 0.9% saline; (3) in the RDN group (n = 6), the rats received TAC, RDN 10 weeks after TAC, and an intraperitoneal injection of 2 ml of 0.9% saline; (4) in the Nog group (n = 7), the rats received TAC and RDN 10 weeks after TAC and were intraperitoneally injected with 0.02 mg  Nogo-P4  daily for 2 weeks at 8 weeks after RDN; and (5) in NEP group (n = 6), the rats received TAC and RDN and were intraperitoneally injected with 0.025 mg  NEP 1–40  daily for 2 weeks at 8 weeks after RDN  purchased from Guangdong Medical Laboratory Animal Center were assigned into five groups as follows: (1) in the control group . The protocol was approved by the institutional ethics committee of Guangzhou First People's Hospital.All the rats were housed in a clean environment under a 12-h light-dark cycle with free access to food and water. This investigation conforms to the Heart failure was induced by TAC. The rats were anesthetized with 2% pentobarbital sodium . The suprarenal abdominal aorta was exposed through a midline abdominal incision and isolated from the surrounding tissue. Abdominal aortic constriction was performed using a 4-0 suture tied around the suprarenal aorta and a blunt needle (23G), and then the needle was removed immediately. The rats were treated with penicillin and returned to their home cages after surgery. Sham-operated rats were subjected to the same surgeries except for ligation of the aorta.After anesthetization with 2% pentobarbital sodium , the rats were placed in a supine position, and the left kidney was exposed by a median longitudinal incision. Unilateral left renal denervation was performed by stripping the renal artery and painting it with 10% phenol in absolute alcohol. Right renal denervation was performed in the same way. The muscle and skin layers were separately sutured. The rats were treated with antibiotics after surgery. Sham RDN rats were subjected to the same surgeries except for painting the left and right renal arteries with saline water.In the 16th week after intraperitoneal administration, plasma N-terminal prohormone B-type natriuretic peptide (NT-proBNP) levels were measured using the NT-proBNP ELISA Kit  according to the manufacturer's protocol.μl using sterile water. Moreover, fresh stool samples from the Con group  and Con + RDN group  were also collected.In the 16th week after intraperitoneal administration, after blood collection, rats were sacrificed by pentobarbital sodium overdose (100 mg/kg). The intestines were dissected with sterile scissors, and the contents of the intestines were collected with a sterile device. Fresh stool samples from each group were immediately frozen in a liquid nitrogen tank and then stored at −80°C. The CTAB/SDS method was adopted to extract all of the genomic DNA from the samples, and the genomic DNA sample was diluted to 1 ng/16S rRNA sequencing was performed at the Novogene Bioinformatics Co. Ltd. . The V4 region of 16S rRNA genes was analyzed. The specific primers 515F (5′-GTGCCAGCMGCCGCGGTAA-3′) and 806R (5′-GGACTACHVGGGTWTCTAAT-3′) with the barcodes were applied to amplify 16S rRNA genes. An NEB Next®Ultra™ DNA Library Prep Kit for Illumina  was used to produce sequencing libraries, and index codes were added. The library was sequenced on an Illumina MiSeq platform.http://metastats.cbcb.umd.edu/) [P < 0.05 was considered to indicate a statistically significant result. Nonparametric tests and one-way ANOVA with LSD post hoc tests were used. Statistical analysis was performed using SPSS software (SPSS version 20.0).The same operational taxonomic units (OTUs) consisted of sequences with a similarity of 97%. Alpha diversity was represented by the abundance coverage estimator (ACE) and observed species. Principal component analysis (PCA), principal coordinate analysis (PCoA) based on the unweighted UniFrac distance, and nonmetric multidimensional scaling (NMDS) were performed using R software to describe the beta diversity. To determine the differences in microbial communities between groups, analysis of similarity (ANOSIM), analysis of molecular variance (AMOVA), analysis of distance matrices (ADONIS), and MRPP (multiresponse permutation procedure) were carried out. The difference in individual taxonomy between groups was analyzed by Metastats (md.edu/) . The biomd.edu/) . Gut micmd.edu/) . The expP=0.006). Rats in the RDN group , the Nog group , and the NEP group  had significantly lower plasma NT‐proBNP levels than those in the HF group.As shown in Amplicon sequencing technology was used to sequence the 16S rDNA of the gut flora of rats from 30 samples from 5 groups. An average of 78,210 sequences per sample was obtained. These sequences were clustered into 2,747 OTUs at a 97% similarity threshold.The rarefaction curves gradually tended to be flat with the increased number of sequences. This meant that even if the sequencing depth was expanded, no more bacterial species were detected. The rarefaction curves showed that the data volume of this study was reasonable, and the sequencing depth was sufficient, meeting the requirements of subsequent analysis .P > 0.05 for all comparisons between groups).As shown in Figures Beta diversity was analyzed to estimate the extent of variation between gut bacterial profiles of the five groups. PCA, PCOA, and NMDS analyses revealed that the respective distance between the RDN, Nog, and NEP groups and the control group was shorter than the distance between the HF group and the control group.NMDS statistics showed that the stress was 0.111 (stress <0.2 was used as an acceptable threshold ), indicaFirmicutes and Bacteroidetes were the major bacteria in each group at the phylum level. The abundance of Bacteroidetes was higher in the HF group (34.56%) than in the control group (24.98%), while Firmicute abundance was decreased (59.30% vs. 68.72%). After RDN treatment, this trend reversed. The abundance of Bacteroidetes was decreased in the RDN group (18.78%), the Nogo group (12.11%), and the NEP group (18.04%) compared with the HF group (34.56%). The abundance of Firmicutes was increased in the RDN group (75.21%), the Nog group (80.03%), and the NEP group (68.91%) compared with the HF group (59.30%). As an indicator of dysbiosis [Firmicutes/Bacteroidetes (F/B) ratio of HF rats (1.59) was decreased compared with that of control rats (3.21) and was lower than that of RDN rats (6.20), Nog rats (7.19), and NEP rats (4.42). There was no significant difference between the RDN, Nog, and NEP groups . Synergistetes and Thermotogae was increased in the HF group compared with the control group and then decreased in the RDN, Nog, and NEP groups when compared with the HF group.ysbiosis , the FirLactobacillus and Alistipes, which had potential myocardial protective effects or anti-inflammatory function [Bacteroides and Clostridium, which were harmful to the myocardium [Lactobacillus and Alistipes were increased, and Bacteroides and Clostridium were decreased in the RDN, Nog, and NEP groups compared to the HF group . The RDN group had increased relative abundances of  Figures . The heaDN group .Firmicutes ((0.511 ± 0.145) vs. (0.517 ± 0.120); P=0.940) and Bacteroidetes ((0.324 ± 0.118) vs. (0.273 ± 0.085); P=0.449) were not significantly different between the Con and Con + RDN groups. No difference was observed in the Firmicutes/Bacteroidetes ratio ((1.899 ± 1.280) vs. (1.975 ± 0.483); P=0.904) between the two groups. No significant differences were identified between the Con and Con + RDN groups in terms of the abundances of Alistipes ((0.001 ± 0.000) vs. (0.004 ± 0.003); P=0.070), Bacteroides (0.015 (0.001–0.032) vs. 0.036 (0.032–0.056); P=0.222), or Clostridium ((0.012 ± 0.006) vs. (0.072 ± 0.034); P=0.051; As shown in Tax4Fun analysis allowed us to predict functional pathways potentially affected by the changes in bacteria. The Venn diagram showed that the HF group had 12 unique functional pathways, while there was only one in the control group and zero in the RDN, Nog, and NEP groups . No obviLactobacillus and Alistipes and the increases in Bacteroides and Clostridium caused by heart failure. However, no differences were observed between the three groups that underwent RDN. These findings indicated that gut microbiota composition profiles and community structure were altered when heart failure occurred, but these alterations could be reversed by RDN. Reinnervation of renal nerves or inhibition of reinnervation after RDN had no effect on intestinal bacteria.In this work, the beta diversity was altered in fecal samples of HF rats compared with that of the controls, but these alterations were reversed after RDN treatment. RDN increased the F/B ratio, which was decreased in HF rats. RDN reversed the decreases in Consistent with previous studies, our study showed that RDN reduced the plasma concentrations of NT-proBNP in HF rats . There wFirmicutes and Bacteroidetes have potential impacts on cardiac function. Many bacteria belonging to the Firmicutes phylum have butyrate as their primary metabolic end products, which can provide energy to the gut bacteria and the intestinal epithelium, exert local anti-inflammatory effects in the gut wall, and play important roles in maintaining the gut barrier [Firmicutes is beneficial to HF. Bacteroidetes are Gram-negative bacteria that can release lipopolysaccharide (LPS) endotoxin. Elevated Bacteroidetes in the gut of HF rats may cause an increase in LPS, which contributes to the development of left ventricular dysfunction [Bacteroidetes is harmful to HF. It has been demonstrated that a low F/B ratio was associated with a poor prognosis in HF [Firmicutes and reducing the abundance of Bacteroidetes.In this study, RDN increased the ratio of F/B at the phylum level, which was decreased in rats with HF. It has been reported that products of  barrier . Mayerho barrier . Therefofunction . Patientfunction . In thisis in HF . In thisLactobacillus and Alistipes, which have potential intestinal and myocardial protective roles [Bacteroides and Clostridium was increased in the HF group and reduced in the RDN group [Furthermore, our results showed that some anti-inflammatory bacteria such as ve roles , 24, decDN group . TMA proDN group . RDN affAdenosine triphosphate-binding cassette (ABC) transport involves transmembrane proteins localized in many tissues, including the heart and intestine. ABC transport in the heart can exert a protective effect against chemical injury or oxidative stress, and many transporters have roles in controlling the absorption and distribution of endogenous substrates or xenobiotics in the intestine . In our Increased sympathetic activity to the gut could lead to an imbalance of short-chain fatty-acid-producing bacteria and stimulate the growth of a range of bacterial species , 34. TheSeveral limitations should be discussed. First, gut neural activity in rats after RDN was not recorded. The degree of decrease in the intestinal sympathetic nerve activity was not clear. The relationship between intestinal sympathetic nerve activity and gut microbiota remains to be determined, and it is necessary to validate this work. Second, some important bacterial products related to HF, such as TMAO, were not detected. Bacterial products may be more important to HF than bacteria themselves.Lactobacillus and Alistipes, and reduced the abundances of some harmful bacteria such as Bacteroides and Clostridium. However, no differences in the changes in the gut microbiome were observed between RDN rats regardless of whether they were administered an inhibitor of axonal regeneration or its antagonist. This study showed that RDN could reverse the abnormal changes in the gut microbiome in HF. The beneficial effect of RDN on cardiac function may also be mediated by influencing intestinal bacteria. Inhibition of reinnervation after RDN did not affect intestinal bacteria.RDN recovered the altered composition structure of gut microbial communities caused by HF and increased the F/B ratio, which was decreased in HF rats. RDN also increased the abundances of some beneficial bacteria to HF, such as


At multivariate binary logistic regression (including age and sex) nadir CD4 cell count (p = 0.034), presence of central nervous system (CNS) opportunistic infections (p = 0.024) and cerebrospinal fluid (CSF) HIV RNA (p = 0.002) in naïve participants and male sex (p = 0.021), a history of CNS opportunistic infections (p = 0.001) and CSF HIV RNA (p = 0.034) in treated patients were independently associated with BBBi. CSF cells and neopterin were significantly higher in participants with BBBi. BBBi was prevalent in naïve and treated PLWH and it was associated with CSF HIV RNA and neopterin. Systemic control of viral replication seems to be essential for BBB integrity while sex and treatment influence need further studies.Despite the substantial changes resulting from the introduction of combination antiretroviral therapy (cART), the prevalence of HIV-associated neurocognitive disorders (HAND) remains substantial. Blood–brain barrier impairment (BBBi) is a frequent feature in people living with HIV (PLWH) and it may persist despite effective antiretroviral treatment. A cross-sectional study was performed in PLWH who underwent lumbar puncture for clinical reasons or research protocols and several cerebrospinal fluid biomarkers were studied. BBBi was defined as cerebrospinal fluid-to-serum albumin ratio (CSAR) >6.5 (<40 years) or >8 (>40 years). We included 464 participants: 147 cART-naïve and 317 on cART. Male sex was prevalent in both groups (72.1% and 72.2% respectively); median age was 44 (38–52) years in naïve and 49 (43–57) years in treated subjects. BBBi was observed in 35.4% naïve and in 22.7% treated participants; the use of integrase inhibitors was associated with a lower prevalence (18.3 vs. 30.9%,  There are approximately 38 million people living with HIV worldwide , out of Monocyte transit across the BBB is a pivotal process in HIV central nervous system (CNS) infection  and seveA number of neurodegenerative disorders, such as Alzheimer’s disease (AD), are associated with BBBi, microvascular and neurovascular degeneration . MoreoveBBBi has been observed despite cART and it has been associated with neuronal damage biomarkers, such as increased levels of total tau and phosphorylated tau . SeveralThe aim of this study was to describe demographic, clinical and therapeutic characteristics, risk factors, comorbidities, as well as CSF and plasma biomarkers in both naïve and treated PLWH, potentially associated with BBBi.A cross-sectional study was performed involving patients with confirmed HIV infection, who underwent lumbar puncture for clinical reasons or research protocols and who were capable to sign the informed consent. The trial was approved by Ethics Committee of the University of Turin .Demographic data, risk factors, co-infections, psychiatric comorbidities, therapeutic and immunovirological data were recorded. The cerebrospinal fluid-to-serum albumin ratio (CSAR), calculated as CSF albumin (mg/L)/serum albumin (g/L), was used to evaluate BBB integrity.Blood–brain barrier damage definition was derived from age-adjusted Reibergrams  .CSF total tau (t–tau), phosphorylated tau (p–tau), and beta–amyloid1–42 (Abeta1–42) were measured by immunoenzymatic methods  with limits of detection, respectively, of 87, 15, and 87 pg/mL. Neopterin was measured through validated ELISA methods . Reference values were as follows: t–tau < 300 pg/mL (in patients aged 21–50), <450 pg/mL (in patients aged 51–70), and <500 pg/mL in older patients; p–tau < 61 pg/mL; 1–42 beta-amyloid > 500 pg/mL; neopterin < 1.5 ng/mL HIV–RNA was quantified by the Roche Amplicor assay v2.0  with a lower limit of quantification of 20 copies/mL.HAND was diagnosed according to the Frascati criteria ; the neu2 test for categorical ones. A multivariate analysis was performed to select the determinants independently associated with BBBi: we used a binary logistic regression analysis using variables with a p-value <0.05 at bivariate comparisons. Data analysis was performed using SPSS software for Mac .Data were analyzed using nonparametric statistical methods: variables were described with medians , absolute values (proportion) or ranges (minimum–maximum). Then, the associations between these variables with BBBi were assessed using Spearman’s test for continuous numerical variables, Mann–Whitney and Fisher’s exact/ChiFour hundred sixty-four patients were included, of which 147 were cART-naïve (median age of 44 years) and 317 were cART-treated (median age of 49 years); their demographic features, risk factors and comorbidities are shown in Both groups of patients consisted mostly of male subjects (72.1% of naïve and 72.2% of ART-treated subjects). With regard to the co-infections, HCV, past syphilis and toxoplasmosis were prevalent among ART-treated subjects .Clinical and cART-related features of the study participants are shown in 3 versus 49 cell/mm3 of naïve patients), as well as current CD4+ T cell count (366 cell/mm3 in ART-treated subjects versus 57 CD4+/mm3 in naïve). With regard to CSF biomarkers, naïve subjects had higher neopterin , but lower tau  and p–tau levels ; Beta42  and S100Beta  were similar between the two groups.Plasma and CSF characteristics and bivariate comparisons among naïve and treated subjects are shown in BBBi was observed in 35.4% of naïve patients and in 22.7% of ART-treated people; clinical, demographic, and therapeutic variables stratified according to treatment group and presence/absence of BBBi are shown in Given the potentially different mechanisms underlying BBBi in naïve and cART receiving participants, we stratified analysis on predictors and biomarkers according to treatment status.p = 0.034), higher CSF HIV RNA  and with the presence of CNS opportunistic infections . In treated participants BBBi was associated with male sex , higher CSF HIV RNA , a history of CNS opportunistic infections  and with non INSTI based regimens .In naïve participants we observed that BBBi was associated with younger age  in INSTI–receivers.Of note, demographic, clinical and immunovirological features were not statistically different among INSTI and other-ARV recipients with the exception of a longer time since first positive HIV serology  and EBV DNA  .Besides higher CSF HIV RNA, we observed significantly higher levels of CSF neopterin in participants with BBBi .p = 0.034, for 100 cells/uL increase aOR 1.401, 95% CI 1.026–1.912), presence of CNS opportunistic infections  and CSF HIV RNA  in naïve participants.At multivariate binary logistic regression (including age and sex) we identified nadir CD4 cell count , a history of CNS opportunistic infections  and CSF HIV RNA  were independently associated with BBBi.Aside from the aforementioned factors, we included the use of INSTI in the multivariate model for cART-treated participants: male sex , whose rate of infection is higher in men than in women in all Mediterranean countries . FurtherIt is worth noting that a major problem of the literature is the clear inequality of female representation in the study populations. Women constitute 51% of HIV-positive subjects worldwide and sex differences in HIV infection have been highlighted in several studies conducted both before and after the introduction of cART . NeverthIn this study cART therapy resulted as an independent protective factor of BBBi. Interestingly, the effect of antiretroviral therapy on BBB has not been clearly demonstrated in literature despite similar analytical methods. Indeed, in their study, Abdulle and colleagues did not find a significant correlation between cART treatment and the reduction of BBB permeability . FurtherOur univariate analysis shows a lower prevalence of BBB alteration among participants treated with integrase inhibitors (INSTI), compared with patients treated with other classes of antiviral drugs (protease inhibitors or non–nucleoside reverse transcriptase inhibitors). Integrase inhibitors  are commonly used as first-line cART regimen, in association with other classes of antivirals, such as two nucleoside reverse transcriptase inhibitors . MoreoveThe association found between BBBi and CSF viral load, both among ART-naïve and treated patients, confirms the evidence observing an increase in CSF HIV–RNA among patients affected by neurological symptoms which were associated with BBBi : a direcIn our analysis, EBV and CMV infections were more common among ART-naïve patients. The incidence of CMV infection has significantly decreased with cART introduction , despiteEBV infects more than 90% of the worldwide population and it is associated with several cancers in PLWH, including Hodgkin lymphomas, non-Hodgkin lymphomas and Burkitt lymphomas . Dehee aFinally, the mechanism that underlies BBB impairment and HAND is not totally clear. HAND could be a direct consequence of the BBB breakdown by different mechanisms, such as an increased permeability, that allow an increasing entry of virus to CNS , or a hiBBB impairment is a common finding in PLWH affected by neurological or neurocognitive disorders either with or without suppressive cART. Indeed, BBB plays a critical role in CNS physiology and in neurological disorders, such as neurodegenerative disorders.We observed higher levels of HIV RNA and neopterin in the CSF of study participants with BBBi, highlighting the significant role of inflammation in the pathogenesis of BBBi. Aside from virological control, female sex was found to be protective: further studies are needed to confirm this finding and to understand thelong–term consequences of an impaired BBB in PLWH.


This research would make a worthwhile contribution to HCV management.This study aims to develop a new self-report tool (HCV-AD) measuring adherence factors, intentional or unintentional, during Hepatitis C Virus (HCV) treatment with direct-acting antivirals (DAA) aiming to achieve high efficacy, otherwise resulting in drug resistance and treatment failure. Two phases were conducted: in the first phase, items were generated based on an extensive literature review, and, in the second phase, a prospective cohort study was conducted using HCV patients from Gastroenterology Department from University County Hospital of Craiova, Romania (n = 222), to evaluate the validity and reliability of the questionnaire. A number of 19 items were generated following a systematic review and through expert opinion. The internal consistency reliability was evaluated using Cronbach’s alpha. The construct validity was assessed using correlations with two other instruments: visual analog scale (VAS) and medication possession ratio (MPR). The final questionnaire (HCV-AD10) was derived through exploratory factor analysis, with 82% of total variance explained. This instrument appeared as a reliable and valid measure for medication adherence, with Cronbach’s alpha (0.867) and significant high positive correlations between adherence scores calculated with HCV-AD10 and VAS (ρ = 0.61,  Direct-acting antivirals (DAA) have resulted in path breaking development of hepatitis C virus (HCV) management . HCV wasHCV management with DAA lacks in measurements studies, with only a few evidence-based methods included so far. Medication adherence is known to be influenced by negative perceptions about medication, poor knowledge, high costs or fear of possible side effects . While tDespite the high success of therapy, DAA agents still require valid tools to assess their adherence in clinical practice. The threshold of 80% has been used to characterize a good adherence since 1976 , but a nThe aim of our study is to develop a reliable and valid adherence self-report tool, easy to administer on a large scale, while attending to the main limitations of currently used tools in DAA adherence of HCV patients.Within a prospective study on HCV patients, we developed a new tool for assessing self-reported adherence, by starting with item generation and content validity, followed by a preliminary questionnaire development, and concludes with a rigorous scientific evaluation, succeeding by implementing the following steps: pilot testing, data collection (sampling and survey administration), item reduction analysis and evaluation ,22. DataThe items of the questionnaire used for DAA adherence assessment in HCV patients  were proposed based on a prior literature review of self-reported adherence, followed by a careful analysis of the content validity by two experts (B.S.U. and A.T-S.). We included many items to better capture all the factors influencing medication adherence. The questions were arranged and reworded in order to eliminate ambiguity, and technical jargon. A pilot testing of the proposed instrument was conducted in the next step in the target population (a sample of 30 HCV patients).The Kaiser–Meyer–Olkin (KMO) criterion was applied for testing the appropriate sample size. The determinant and Bartlett’s test of sphericity were used to establish the stability of the factors. Reliability and validity were evaluated. Factors were extracted and optimized through Exploratory Factor Analysis (EFA). Kaiser’s criterion and Cattell’s scree plot were used, a factor with more than one eigenvalue was retained after the elbow indicated the cut-off point for factor extraction. Internal consistency was assessed through Cronbach’s alpha (α) coefficient. Construct validity was demonstrated by correlation matrices of associations between HCV-AD score and two other instruments measuring adherence: VAS and MPR. The VAS recorded the respondent’s self-related adherence where the endpoints are labelled “100% adherent” and “0% adherent”, being a quantitative measure of medication adherence as judged by the individual respondents. We used individual patient data reported by community pharmacies at the Health Insurance House, following the legal requirements on personal data protection, to calculate the medication adherence with MPR formula:Patients with detectable RNA-HCV at baseline, regardless of the value, were considered eligible. We did not exclude patients which followed previous treatment with interferon, which either did not respond to treatment or were or stopped the treatment due to side effects. We excluded individuals with HIV- coinfection, or recently diagnosed with malignancies.A total of 236 were enrolled across the University County Hospital of Craiova, Romania, from March 2020 to April 2021, as in p < 0.01) were considered suitable for factor analysis [p-value less than 0.05 was considered statistically significant.Continuous variables were expressed as means (standard deviation), and categorical variables as frequencies (percentage). Data management and analysis, and exploratory factor analysis (EFA) were done using GraphPad Prism 9.1.0 . Prior to the extraction of the factors, Kaiser–Meyer-Olkin (KMO) Measure of Sampling Adequacy and Bartlett’s Test of Sphericity were determined. A KMO index of 0.5 and significant Bartlett’s test of sphericity ; the negatively stated items were reverse coded.The range for completing the survey was between 5 and 10 min.A sample of 222 HCV patients completed all survey items, including 25% were male. More details about the sample characteristics can be seen in The initial questionnaire proposed 19 items  with fivp < 0.001) confirmed that the item scores were suitable for factor analysis.An EFA was used to reduce the items to a more parsimonious set for measuring DAA adherence for HCV patients. Two questions were deleted (Q2 and Q7) because their variance was null. The sample size measure through KMO (0.834) and Bartlett’s test of sphericity  had α = 0.888 and we included them in the final questionnaire. Factor 2  had α = 0.681 and after Q16 and Q18 were deleted, α = 0.732. Factor 3  had α = 0.720 and after Q12 was deleted, α = 0.864. Factor 4  had α = 0.786 and after Q11 was deleted, α = 0.831. Factor 5 contained only two items . The other items were not included in factors.The analysis yielded three factors that accounted for 70% of the total variance with Factor 1 explaining 31.55% of the variance whereas Factor 2 explaining 24.8%, as seen in As in The adherence score after applying the 10-items HCV-AD will be calculated as the sum of all scored items minus 10 and divided by 0.40:In the total sample, the Cronbach’s alpha coefficient for the total HCV-AD10 was 0.867 and item-total correlations ranged from 0.17 to 0.79. None of the 10 final items could be deleted without a decrease in Cronbach’s alpha. The McDonald’s omega value (ω = 0.877) confirmed that the HCV-AD10 is high.To investigate whether HCV-AD10 captures medication adherence, we examined the correlations (Spearman’s ρ) between the obtained scores and VAS and MRP scores. Descriptive statistics of adherence scores are presented in HCV-AD19, the initial questionnaire with 19 items; HCV-AD10, the final questionnaire with 10 items; VAS, visual analog scale; MPR, medication possession ratio.p < 0.001) or with HCV-AD10 and MPR , as shown in Spearman’s correlation analysis demonstrated significant positive correlations between adherence scores calculated with HCV-AD10 (SCORE10) and VAS  being very well applicable to stable behaviour .Because all patients had SVR of 100% we could not establish a threshold for DAA adherence. However, we are convinced that by having this instrument, future studies must be conducted to assess how small the adherence level can be, as not to achieve high virological response and sustained virological response.This instrument might be a helpful tool in the WHO’s objective of HCV eradication as it may cover some patients who may be non-adherent to therapy, exploring its predictors and finding strategies to promote DAA adherence.Our developed HCV-AD10 is a validated and reliable instrument for evaluating adherence among HCV patients using the DAAs in Romania. It is simple to use and suitable to assess the patient-specific, illness-specific, or medication-related factors which are barriers to HCV eradication.


Saccharomyces cerevisiae. The relative importance of the strain-specific metabolic capabilities for the production of volatile organic compounds (VOCs) remains unclear. We investigated which amino acids contribute to VOC production and whether amino acid-VOC relations are conserved among yeast strains. Amino acid consumption and production of VOCs during grape juice fermentation was investigated using four commercial wine yeast strains: Elixir, Opale, R2, and Uvaferm. Principal component analysis of the VOC data demonstrated that Uvaferm correlated with ethyl acetate and ethyl hexanoate production, R2 negatively correlated with the acetate esters, and Opale positively correlated with fusel alcohols. Biomass formation was similar for all strains, pointing to metabolic differences in the utilization of nutrients to form VOCs. Partial least-squares linear regression showed that total aroma production is a function of nitrogen utilization (R2 = 0.87). We found that glycine, tyrosine, leucine, and lysine utilization were positively correlated with fusel alcohols and acetate esters. Mechanistic modeling of the yeast metabolic network via parsimonious flux balance analysis and flux enrichment analysis revealed enzymes with crucial roles, such as transaminases and decarboxylases. Our work provides insights in VOC production in wine yeasts.Genetic background and environmental conditions affect the production of sensory impact compounds by IMPORTANCESaccharomyces cerevisiae is widely used in grape juice fermentation to produce wines. Along with the genetic background, the nitrogen in the environment in which S. cerevisiae grows impacts its regulation of metabolism. Also, commercial S. cerevisiae strains exhibit immense diversity in their formation of aromas, and a desirable aroma bouquet is an essential characteristic for wines. Since nitrogen affects aroma formation in wines, it is essential to know the extent of this connection and how it leads to strain-dependent aroma profiles in wines. We evaluated the differences in the production of key aroma compounds among four commercial wine strains. Moreover, we analyzed the role of nitrogen utilization on the formation of various aroma compounds. This work illustrates the unique aroma-producing differences among industrial yeast strains and suggests more intricate, nitrogen-associated routes influencing those aroma-producing differences. It has been widely recognized that yeast cell growth and overall wine fermentation performance are regulated by initial nitrogen levels within the grape must. Consequently, nitrogen limitation can induce sluggish or stuck fermentations –4. Ammon–7–S. cerevisiae that amino acids are directly involved in the formation of higher alcohols, esters, and fatty acids, and that these volatile organic compounds subsequently influence aroma attributes of wines  and fusel alcohol concentrations , 13–16. 13–of wines , 17. Nonof wines –20. Althf wines –, 21, 22.f wines –, 23. Mort aromas –26. ThusS. cerevisiae strains that are selected for winemaking differ immensely in their aroma production profiles  regression. Moreover, since mechanistic understanding of the relation between amino acid consumption and VOCs production is currently lacking  production capabilities across strains growing in the same enological medium. All fermentations were conducted under atmospheric conditions at a temperature of 20°C and were performed until completion (t = 404 h). Throughout the fermentation, cell biomass  and degrees Brix (°Bx) levels were monitored at 11 time points. Biomass growth, sugar utilization, and ethanol formation curves are shown (Fermentations were carried out for each of the re shown .P = 0.974). All cultures were fermented to completion  (P < 0.05). In contrast, concentrations of the other six major metabolites (P > 0.05).All strains reached maximum biomass at approximately 120 h. Furthermore, all strains did not significantly differ in biomass concentrations  . More spl sugar) . These vl sugar) . For alll sugar) . Acetic l sugar) . Succinil sugar) . Final cl sugar) . One-wayabolites  did not P < 0.05). However, these and most variations in amino acid concentrations were observed at 20 and 28 h. As noticed , and Thr (Uvaferm only) occurs, with 95% of their concentrations being drastically depleted by 28 h. Group II contains the subsequently preferred compounds, where 95% of the compound was consumed by 44 elapsed hours. These group II compounds are Arg, Gln, Ile, Leu, Phe, Ser, Thr, His, Asp, and Val. Group III consists of compounds such as Ala, Trp, and Tyr, which all show steady consumption until 95% of their concentrations were utilized by 72 h. A remaining group, group IV, was taken up after some initial delay (not consumed within the first 20 h) and did not have 95% utilization until after 96 h. This sole amino acid was Gly.Many amino acids were mainly consumed during the exponential cell growth stage of fermentation. Only some small amounts of Ala, Asn, Gly, and Met remained in the medium after 100 h, though all were utilized shortly after that. The consumption data reveal preferences of yeast for particular amino acids during utilization over the exponential growth phase. The consumption of the nitrogenous compounds can be separated into four groups based on the time at which 95% utilization occurs from the compound. Group I consists of the earliest-consumed compounds, where strain-dependent consumption of NHP < 0.05). At 168 h of fermentation, the VOC concentrations among the strains were significantly different for eight VOCs, while two were the same. These compounds that did not differ significantly at the end of fermentation were 2-methyl-1-propanol and 2-methyl-1-propyl acetate.To study the relationship between amino acid consumption and VOC formation during grape juice fermentation, 10 VOCs (aromas) were measured using headspace solid-phase microextraction gas chromatography mass spectrometry (HS SPME GC-MS) from various compound classes pertaining to different aroma properties throughout the fermentation process . The comAll VOCs begin to form early in the fermentation process. Some compounds, such as 3-methyl 1-butanol and methionol, were even generated before 20 h, though nearly all VOC formation characteristically corresponds with yeast growth. Moreover, the maximum production rate of fusel alcohols and acetate esters occurred from 28 h to 96 h. Fusel alcohols were produced at the highest concentrations, with isoamyl alcohol, isobutanol, and 1-propanol showing the most rapid production earliest during fermentation. The acetate ester production rate began to decline for all of the strains after 96 h and became relatively stagnant after 168 h. Profiles for ethyl esters were similar to those observed for acetate esters. However, initial ethyl ester formation proceeded at a lower rate than acetate esters, and the maximum concentrations were much less than acetate esters. Overall, most VOCs showed stagnated production after 96 h, which indicates growth-dependent behavior. Some VOCs, in particular 2-methyl-1-propyl acetate, showed a decrease in concentration toward the end of fermentation, most likely due to volatilization. All final VOCs concentrations were found within the typical range found in wines  of the VOCs was performed. From the PCA, 76.26% of the variance was explained by the first two principal components (PC) (PC1 = 51.25% and PC2 = 24.98%). As depicted, separation of the samples was achieved according to the yeast strains . PC1 sep acetate .S. cerevisiae culture. Therefore, enhancing growth of yeast cultures leads to the overall increase of production of VOCs and VOC precursors. Second, it is known that specific amino acids are utilized and degraded which contribute to the synthesis, via the Ehrlich pathway, of fusel alcohols and subsequently to the production of acetate esters. However, other pathways related to lysine and glycine degradation, which have been shown to play a role in VOC formation in other types of fermentations, may be essential to enological fermentations as well. To evaluate this hypothesis and understand the causes of strain-dependent variation, the ammonia and amino acid utilization for all four yeast strains were measured and correlated with biomass formation and VOC production for 11 different aroma compounds during the exponential growth phase , and total VOC concentration were the response variables that comprised the Y-block in 16 different PLS regressions. The response variables contained concentration measurements corresponding to the same time points as the predictor variables. From the initial duration of the fermentation until 96 h, the ammonia and amino acid utilization data were input as the predictor variables used to develop the X-block in each of the 16 PLS regressions. Subsequently, the PLS regression analysis determined which variables in both the Y-block and the X-block contributed most to the variation in the data. Lastly, the PLS regression analysis indicated how the variables were correlated and then lumped the variables into a new latent variable (LV). Our summarized results show that nitrogen utilization is strongly correlated with biomass formation and production of each of the aroma compounds, except methionol, for which only moderate correlation was found  linear regression was employed to correlate the contributions of ammonia and individual amino acid utilization to the production of biomass and VOCs by the yeast strains during fermentation. Statistical determination of the nitrogenous variables that contribute most to the variation in the fermentation kinetic data regarding VOCs was performed using interval-partial least squared (iPLS) regression analysis. iPLS was done using the ammonia and amino acid utilization of all four as found . The reaR2 = 0.96, which signified a robust linear relationship between the measured biomass dry cell concentration versus the predicted biomass dry cell concentration according to the nutrient utilization of these yeast strains . Cross-validation (CV) was performed in order to prevent the model from overfitting the data  and to evaluate how the model would operate using a new set of data. CV correlation coefficients (Q2) were generated to illustrate the predictive strength of the model .PLS regression was first conducted to determine how nitrogen utilization contributed to yeast growth (biomass formation) during the exponential growth phase in the fermentation. he model . The rooR2 value for each model for VOCs achieved an R2 value greater than 0.77, indicating nitrogen utilization was correlated with the production of each VOC. The only aroma compound that the PLS regression analysis showed to have a more modest correlation with nitrogen utilization was methionol. Partial least-squares regression modeling yielded eight LVs and generated a coefficient of determination (R2) of 0.61. The model cross-validation results indicate a Q2 of 0.5 and RMSEC and RMSECV values of 0.64 mg/liter and 0.73 mg/liter of methionol, respectively. Overall, these data point to a modest correlation between the methionol concentration and nitrogen utilization during fermentation. As a result, it is suggested that not only nitrogen utilization determines the production of methionol during fermentation and that there may be other processes that play a role in methionol production, such as sulfur utilization.A separate series of PLS regression analyses were performed subsequently for each of the VOCs, as well as classes of compounds, to investigate a correlation between the production of VOCs during the fermentations and nitrogen utilization of the yeast strains. Each of the models captured at least 99.5% of the variation in the nitrogen utilization data and at least 77% of the variation in the aroma concentration data were captured by each of the models except methionol . In addiOne of the core goals of this work was to improve understanding of the impacts of nitrogen utilization on VOC profile differences among four commercial wine yeast strains. By applying PLS to the data sets mentioned above, information about how specific nitrogen utilization variables correlate with each of the 16 response variable sets was obtained. This facilitated understanding of which nitrogenous compounds are responsible for aroma production and might offer clues about metabolic variations among the strains. The PLS models were able to explain the biomass formation and the production of each of the aroma compounds, excluding methionol, which was moderately predicted. Regression vector plots were created to assess the statistical weights of the original nitrogen predictor variables on the PLS models. In other words, regression vector plots were used to determine the degree to which the 18 original nitrogen variables were positively or negatively correlated with the response variable. These regression vector plots for PLS models predicting individual aroma compounds and classes of aroma compounds are provided in the supplemental material , while a summary is provided in The regression vector plots for all the yeast strains illustrate the degree to which the 18 original nitrogen predictor variables are correlated with the response variables (VOC and biomass concentrations) . Furthermore, it is worth noting that the magnitude of the correlation coefficients for each nitrogen predictor variable was different across the PLS regression models . The model for biomass growth indicated that asparagine, serine, glycine, lysine, isoleucine, and tryptophan were all positively correlated with biomass concentration, whereas, histidine, threonine, and valine are negatively correlated with biomass concentration . AmmoniaA summary of the results from all the regression vector plots highlights correlative behavior of the nitrogen variables for predicting individual VOC production . The regTo test which metabolic pathways are crucial in VOC production, we applied parsimonious flux balance analysis (pFBA) and flux enrichment analysis (FEA) with fermentation data used as constraints. The pFBA analysis revealed many essential genes/reactions for nutrient uptake and turnover, including amino acids, and VOC production . After eP < 1 E−10). This result could indicate substantial influence coming from lipid metabolism and sulfur metabolism. Despite potential influence from other parts of metabolism on VOC formation, our statistical and metabolic modeling results firmly indicated that amino acid utilization routes such as leucine, glycine, lysine, and tyrosine induce VOC production  by chance, we employed flux enrichment analysis (FEA) to identify statistically significantly enriched subsystems with essential reactions . FEA higoduction . We alsooduction . InteresS. cerevisiae strains with diverse aroma bouquet-producing potential and growth characteristics under identical experimental conditions to analyze the nitrogenous compounds that correlated with yeast cell growth and aroma production. In agreement with previous studies  on the one hand, and methionol concentration with nitrogen utilization (R2 = 0.61) on the other hand, it appears likely that nitrogen utilization is not the only significant factor influencing methionol production. The relatively low correlation for methionol formation could be due to the absence of causal relationships between the metabolic pathways of methionol biosynthesis and nitrogen metabolism. Methionol biosynthesis is also intricately linked to the sulfate reduction pathway and, thus, the relationship of sulfur uptake during fermentation . The strains were stored at −80°C in a 25% (vol/vol) glycerol solution according to the method of Amberg et al. , Lalvin R2 (R2), Lalvin ICV Opale , and Vitilevure Elixir Yseo (Elixir), used in this study are Lallemand  commercial yeast strains. Uvaferm and R2 are g et al. . The str600 of ∼0.1 (∼15 ml) was added to 400 ml of MMM medium. The pH of the MMM medium was 3.25 and the fermentation temperature was maintained at 20°C. Cultures were stagnantly cultivated at 20°C for 17 days. Initial cell concentration (OD600) and °Bx measurements were performed at the beginning of fermentation and subsequently 10 more times over the course of the fermentation until °Bx fell below one or remained constant between two consecutive measurements. °Bx measurements were performed with a refractometer and OD600 measurements were performed with a spectrophotometer. Samples (10 ml) were taken at regular intervals and transferred to a 15-ml Greiner tube, sealed, and frozen at −20°C until analysis. Experiments were performed as biological triplicates.MMM synthetic grape juice medium , with a 1:1 mixture of glucose (110 g/liter) and fructose (110 g/liter), 123 mg/liter of YAN, and 11 mg/liter of ammonium, was prepared according to the method of Giudici and Kunkee . MMM med600 measurements using a calibration curve for each yeast strain. Total cell dry weights were determined in triplicates.The total cell dry weight (biomass) of the samples was determined by taking a sample directly from the culture medium and passing through dried and preweighed membrane filters with a pore size of 0.2 μm  by a vacuum filtration unit, as described by van Mastrigt and coworkers . Total bg for 10 min at 4°C), and the supernatant was stored at −20°C until analysis. Supernatants were deproteinated by adding 0.25 ml Carrez A (0.1 M potassium ferrocyanide trihydrate) and 0.25 ml Carrez B (0.2 M zinc sulfate heptahydrate) to a 0.5-ml sample followed by centrifugation for 10 min at 13,000 × g. Glucose, fructose, lactate, acetate, malate, citrate, ethanol, 1-propanol, and 1,2-propanediol were quantified by high-performance liquid chromatography (HPLC) on an Ultimate 3000  equipped with an Aminex HPX-87H column (300 × 7.8 mm) with precolumn (Bio-Rad), as described by van Mastrigt and coworkers  for quantification and UV measurements at 220, 250, and 280 nm for identification. All analysis was performed in duplicate.After taking a sample from the Erlenmeyer flask, cells were immediately removed by centrifugation  for 10 min. at 4°C. Amino acids were derivatized using the AccQ-Tag Ultra Derivatization kit (Waters), for which 20 μl of the deproteinated sample solution supernatant or standard amino acids mixture was mixed with 60 μl of a modified AccQ-Tag Ultra Borate buffer . Next, 20 μl of an AccQ-Tag reagent previously dissolved in 2.0 ml AccQ-Tag Ultra reagent diluent was added and vortexed for 10 s. Then, the sample solution was capped and warmed at 55°C in a heatblock for 10 min. Amino acids and ammonium were quantified by ultraperformance liquid chromatography (UPLC) on an Ultimate 3000  equipped with an AccQ-Tag Ultra BEH C18 column   with a BEH C18 guard column  . The column temperature was set at 55°C, and the mobile phase flow rate was maintained at 0.7 ml/min. Eluent A was 5% AccQ-Tag Ultra concentrate solvent A and Eluent B was 100% AccQ-Tag Ultra solvent B. The separation gradient was 0 to 0.04 min 99.9% A; 5.24 min 90.9% A; 7.24 min 78.8% A; 8.54 min 57.8% A; 8.55 to 10.14 min 10% A; and 10.23 to 17 min 99.9% A. One microliter of sample was injected for analysis. Compounds were detected by UV measurement at 260 nm.An aliquot of 40 μl of 5-fold-diluted samples was mixed with 50 μl of 0.1 M HCl solution containing 250 μM norvaline as the internal standard. Then, 10 μl of chilled 30% sulfosalicylic acid (SSA) was added, and the solution was mixed and centrifuged  according to the manufacturer’s procedures. The ammonia levels were verified to exhaust after 28 h of fermentation. This method was also used to correct quantification of ammonium detected from the UPLC. Norvaline was used as an internal standard (IS) for the UPLC amino acid analysis. All analysis was performed with a single replicate.m/z 33 to 250 in full scan mode with 3.0030 scans/second. VOC profiles were analyzed with Chromeleon 7.3 software. The ICIS algorithm was used for peak integration and the NIST main library was used for identification by matching mass spectral profiles with the profiles in NIST. One quantifying peak  was used per compound for quantification, while one or two confirming peaks were used for confirmation.To determine the volatile organic compounds (VOCs), 2 ml of sample was transferred to a 5-ml gas chromatography (GC) vial. Samples were stored frozen (−20°C) until analysis by headspace solid-phase microextraction gas chromatography mass spectrometry (HS SPME GC-MS) . SamplesThe 11 aroma-associated compounds studied were propan-1-ol, 3-methylbutan-1-ol (isoamylol), 2-methylpropan-1-ol (isobutanol), 2-phenylethan-1-ol, methionol, ethyl ethanoate (ethyl acetate), ethyl butanoate, ethyl hexanoate, 3-methylbutyl acetate (isoamyl acetate), 2-methylpropyl ethanoate (isobutyl acetate), and 2-phenylethyl acetate . All of The yeast strain-specific impact on the kinetics of amino acid consumption and aroma compound formation for the 11 volatile aromas was determined by plotting the compound concentrations throughout the fermentation. Furthermore, several performance metrics were accessed from the dynamic consumption and production profiles, such as the final concentration of volatile aroma compounds and utilization of nitrogenous compounds. In this study, nitrogen (ammonia/amino acids) utilization was determined as the difference in the ammonia/amino acid concentration from beginning to sample time point of interest throughout the fermentation . The finP < 0.05) was performed in R (version 3.6.2) using the statistics package applying post hoc Tukey’s honest significant difference (HSD) test (significance level of P < 0.05), as well as in SPSS .One-way analysis of variance (ANOVA)  regression was employed to determine a relationship between biomass and VOC production data (Y-Block) and nitrogen (ammonia and amino acid) utilization data (X-Block). The utilization was calculated as the difference in concentration at the beginning of the fermentation to concentration at the sampled time point. These two data blocks were imported into MATLAB  for PLS regression analysis and interval-PLS (iPLS) variable selection using the PLS Toolbox . Parameters for iPLS were selected according to the method of Wise et al.  and AndeR2), cross-validated correlation coefficient (Q2), root mean squared error of correlation (RSMEC), and RMSECV. The impact of selected nutrient utilization variables on the PLS model was assessed using scores, loadings, and regression vector plots. Overall, the PLS model was used to determine the nutrient utilization (ammonia and amino acids) which contribute to the biomass formation and VOCs production during fermentation.Subsequently, once iPLS was completed, the selected variables were added to PLS Toolbox for structured equation modeling. The approach used was adapted based on an approach by Henderson et al.  using thS. cerevisiae, Yeast 8.4.2   of ast-GEM) . To adeqast-GEM) , constraz et al. , 71  database convention  to evaluate which reactions and pathways are essential under the given system conditions and eliminate blocked reactions . It uses a bilevel optimization in which the growth rate (biomass) is optimized using FBA, followed by the minimization of total flux through all gene-associated reactions at the maximum growth rate calculated. The underlying assumption is that, under growth pressure, there is a selection for strains that can reach the highest growth yield while using the minimum amount of enzyme. Then, genes/reactions are classified into six categories based on Lewis et al. , i.e.,  using the Cobra Toolbox 3.0 . For insAll data generated or analyzed during this study are included in this published article and its supplemental material.


We assessed differences in plasma levels of metabolic health and inflammation biomarkers during mid-childhood and early adolescence between children born by cesarean section vs. vaginal delivery.N = 942) enrolled during pregnancy in obstetric practices and child follow-up started at birth. Risk biomarkers were assessed in blood samples collected at the mild-childhood (median = 7 years) and early adolescence (median = 13 years) in-person visits.Mother–child pairs (Two hundred and six children (22%) were born by cesarean section. There were no significant differences in biomarker levels between children born by cesarean and children born vaginally in mid-childhood. However, adolescents born by cesarean section had significantly lower adiponectin [% difference ) = −11.3  µg/mL] compared to vaginal delivery. We also found some suggestion of higher insulin resistance [insulin levels % difference (95% CI) = 11.5  µU/mL and HOMA-IR (homeostatic model assessment of insulin resistance) % difference (95% CI) = 9.1  U] in adolescents born by cesarean section compared to those born vaginally.We found suggestive evidence that adolescents born by cesarean section show differences in certain metabolic health biomarkers relative to adolescents born by vaginal delivery. Further studies are needed to reevaluate these associations since the clinical significance of these differences is unclear.Multiple studies show that children born by cesarean section are at higher risk of obesity compared to those born vaginally.It is unclear yet to what extent this elevated risk may extend to a more adverse profile of biomarkers of metabolic health and inflammation.Adolescents born by cesarean section show small differences in adiponectin and insulin relative to adolescents born by vaginal delivery.Adolescents born by cesarean section may be at higher risk to a more adverse profile of biomarkers of metabolic health and inflammation, but the clinical significance of these differences is uncertain. We have previously reported that, compared to children born via vaginal delivery, children born by cesarean delivery have a higher body mass index (BMI)-z through childhood and early adolescence.25 In a different population, we also found a 15% : 6, 26) higher risk of obesity from late childhood through early adulthood.18 The association between birth by cesarean delivery and offspring obesity, and the increasing evidence that this risk may persist through adult life, raise the possibility that the adverse long-term offspring health effects of a cesarean section may extend to obesity-related chronic diseases.26 However, it is unclear whether there is a link between mode of delivery and systemic markers related to obesity and chronic disease, and published literature on the relationship between mode of birth and biochemical markers of chronic disease risk in the offspring remains scarce.29 To address this knowledge gap, we used data from Project Viva to assess differences in plasma levels of metabolic health and inflammation biomarkers during mid-childhood and early adolescence among children born by cesarean section compared to those born by vaginal delivery. We hypothesize that children born by cesarean section will show a more adverse profile of metabolic health and inflammation biomarkers compared to those born vaginally.Cesarean deliveries are the most common inpatient surgical procedure in the United States,30 and all mothers provided written informed consent and children provided verbal assent at follow-up visits. Study population, enrollment, and follow-up procedures have been previously described in detail.30 Briefly, we recruited women attending their initial prenatal visit before 22 weeks gestational age at Atrius Harvard Vanguard Medical Associates, a multispecialty group practice. Eligibility criteria included fluency in English and singleton pregnancy. Most mothers gave birth at BWH or BIDMC. A trained research assistant conducted in-person study visits with the mother at the end of the first and second trimesters of pregnancy, and with both mother and child after delivery, during mid-childhood (median age 7 years) and early adolescence (median age 13 years). We collected data from multiple sources, including interviews/surveys, medical records, examinations, and biospecimens. Of the 2128 live singleton infants, 2098 had data on the mode of delivery  or early adolescence (N = 709). Rates of cesarean birth (22 vs. 25%) as well as participant characteristics, including maternal age, prepregnancy BMI, race/ethnicity, education, smoking, paternal BMI, and child sex, were similar between included and excluded participants , and Beth Israel Deaconess Medical Center (BIDMC) approved study protocols,21 We defined planned cesarean sections as those for which participants did not undergo a trial of labor .We obtained information about the mode of delivery from electronic hospital records. For each participant who had a cesarean section recorded on electronic birth logs, we reviewed the operative report to confirm cesarean section and to abstract the primary indication for operative delivery and the timing of cesarean section in relation to onset of labor. Using this information, we divided cesarean deliveries into unplanned cesarean sections preceded by labor and planned cesarean sections not preceded by labor. We defined an unplanned cesarean section as a delivery in which the operative report described a failed induction of labor, prolonged latent phase, prolonged active phase, arrest of dilation, “failure to progress,” arrest of descent in the second stage or failed operative vaginal delivery, “non-reassuring fetal heart rate tracing,” non-reassuring testing prompting immediate cesarean delivery, cord prolapse, or abruption.31 To calculate the metabolic risk z-score in mid-childhood, we used the sex-specific internal z-scores averaging measures of waist circumference, triglycerides, inverted HDL-C, HOMA-IR, and systolic blood pressure. We calculated the metabolic risk z-score in early adolescence using age- and sex-specific external reference data.34Blood samples were collected by phlebotomists and stored within 24 h in liquid nitrogen freezers. We quantified an inflammatory marker  in plasma samples at the Clinical and Epidemiological Research Lab at Boston Children’s Hospital. The concentration of CRP was determined using an immunoturbidimetric assay on the Roche Cobas 6000 system . This high-sensitivity assay has a limit of detection of 0.03 mg/L. The mean intra-assay at concentrations of 0.91, 1.60, and 18.40 mg/L are 3.8%, 3.3%, and 1.9%, respectively. IL-6 was measured by an ultra-sensitive ELISA (enzyme-linked immunosorbent assay) assay from R&D Systems . The assay has a sensitivity of 0.094 pg/mL, and the mean intra-assay at concentrations of 0.49, 2.78 and 5.65 pg/mL are 9.6%, 7.2%, and 6.5%, respectively. Adiponectin was measured by an ELISA method from R&D Systems . The assay has a sensitivity of 0.25 ng/mL and the mean intra-assay at concentrations of 20.5, 74.4, and 157 ng/mL are 6.8%, 5.8%, and 6.9%, respectively. Leptin was measured by an ultra-sensitive ELISA assay, an enzymatically amplified “two-step” sandwich-type immunoassay . The assay has a sensitivity of 7.8 pg/mL. The mean intra-assay at concentrations of 65.7, 146, and 581 pg/mL are 5.4%, 4.2%, and 3.5%, respectively. The determination of triglycerides and HDL-C concentrations was simultaneously performed on the Roche Cobas 6000 System using reagents and calibrators from Roche Diagnostics . Triglycerides at concentrations of 84.0 and 201.8 mg/dL were determined in the laboratory with a reproducibility of 1.8% (SD = 1.6 mg/dL) and 1.7% (SD = 3.5 mg/dL), respectively. We measured plasma glucose enzymatically and insulin using an electrochemiluminescence immunoassay (both Roche Diagnostics). We calculated insulin resistance in overnight blood samples using the homeostasis model (homeostatic model assessment of insulin resistance (HOMA-IR) = (insulin (µU/mL) × glucose (mmol/L)/22.5).2 for both mothers and fathers. Also, we calculated gestational weight gain (GWG) by subtracting prepregnancy weight from the last prenatal weight. We obtained birth weight (BW) and delivery date from hospital medical records. We calculated gestational age (GA) at birth using the date of the last menstrual period. If the estimate of GA by second-trimester ultrasound assessment differed from the calculated GA by >10 days, we used the ultrasound dating. We determined sex-specific BW-for-GA z-scores using US reference data.35 We calculated a pubertal development score using a 5-item written pubertal development scale36 completed by the parents at the early adolescent visit. Items included on the boys’ pubertal development scale were voice deepening, body hair growth, facial hair growth, acne, and a growth spurt. Items included on the girls’ pubertal development scale were breast development, body hair growth, acne, growth spurt, and menarche. Response options and scores for each pubertal development scale item except menarche were: 1 point for “not yet started,” 2 points for “barely started,” 3 points for “definitely started,” and 4 points for “seems complete.” We coded menarche as 4 points if menarche was present and 1 point if not present. To assign a summary pubertal development score to each participant, we calculated the average score across all items.We collected sociodemographic and medical data through in-person interviews at enrollment, mid-childhood, and early adolescence visits, as well as yearly self-administered questionnaires, and hospital, and ambulatory medical records. Mothers reported their age, race/ethnicity, education, parity, prepregnancy weight and height, and paternal weight and height, and we calculated BMI as kg/mn (percentage). We initially defined the mode of delivery as a two-category variable: cesarean section and vaginal delivery. We then used data on timing and type of labor in relation to delivery and on planning of cesarean section and conducted separate analyses defining mode as a three-category  variable. Plasma metabolic health and inflammation biomarker levels were natural log-transformed to approximate normality. We used multivariable linear regression models to estimate the association between mode of delivery and plasma metabolic health and inflammation biomarker levels in mid-childhood and early adolescence while adjusting for confounders. Confounders included covariates associated with both mode of delivery and plasma metabolic health and inflammation biomarker levels that were not in the causal pathway between both. Final models were adjusted for child age and sex at sample collection, maternal prepregnancy BMI, age, education, race/ethnicity, pregnancy smoking, GWG, BW/GA z-scores, and paternal BMI. We used stabilized inverse probability weights to account for censoring.37 To evaluate the robustness of the findings, we conducted a series of sensitivity analyses restricted to the first child per family (N = 923), excluding children whose mother experienced gestational diabetes or preeclampsia (N = 874), excluding macrosomic children (N = 773), excluding preterm births (N = 888), and simultaneously excluding children in these three groups (N = 671). We also conducted a sensitivity analysis restricted to fasting samples for insulin (N = 601), glucose (N = 610), and HOMA-IR (N = 587) outcomes in early adolescence. Results were reported as % difference (95% CI) . All analyses were performed with SAS . We chose not to employ classic multiple comparison correction techniques , as these would be too conservative, given the correlated nature of the outcomes themselves.38Participants’ characteristics as well as plasma metabolic health and inflammation biomarkers for the overall study population, as well as by mode of delivery, were presented using mean ± standard deviation (SD) or 2  age was 31.9 (5.5) years and prepregnancy BMI was 25.1 (5.4) kg/mz-score in mid-childhood, were similar in children born by cesarean section compared to those born vaginally . There were no differences in other measured biomarkers as well as the metabolic risk z-score both in early adolescence between children born by cesarean section compared to vaginally  = −11.3 −18.1, −4.0) µg/mL] compared to vaginal delivery. We also found a suggestion of higher insulin resistance reflected in associations with higher insulin levels (% difference (95% CI) = 11.5  µU/mL) and higher HOMA-IR (% difference (95% CI) = 9.10  U), neither of which was statistically significant. The associations of cesarean section with adiponectin and insulin levels in early adolescence were similar for planned and unplanned cesarean sections , birth by cesarean section was related to higher BMI, total cholesterol, low-density lipoprotein cholesterol, apolipoprotein B, and leptin levels.29 To our knowledge, this is the first study investigating the association between mode of delivery and systemic metabolic health and inflammation biomarkers in mid-childhood and early adolescence. Given the large differences in terms of socioeconomic factors, prevalence of childhood obesity, differences in age at outcome assessment, and frequency of birth by cesarean section across the three studies where this question has been addressed, it is critical that the relationship between mode of delivery and biomarkers of chronic disease risk is evaluated in additional prospective studies.Epidemiological studies,45 Infants delivered via cesarean are less likely to be colonized with Bacteroides spp., and overall have lower community diversity.49 In adults, the ratio of Firmicutes to Bacteroidetes and gut microbial composition overall are related to obesity, weight, and body composition,52 and, importantly for our findings, insulin resistance.53 Although it is unknown whether differences in gut microbiota by mode of delivery observed in infants persist later in childhood or adolescence, such persistence could explain the observed relations. It is also important to consider why an association was observed in early adolescence but not earlier in childhood and only with adiponectin and insulin, but not with other markers of insulin resistance such as glucose or HOMA-IR. It is well documented that puberty is accompanied by a physiologic increase in insulin resistance that is, transient, characterized by a compensatory increase in insulin but no hyperglycemia, and independent of fat mass.54 This physiologic increase in insulin resistance would be expected to increase the variability between subjects in markers of insulin resistance in early adolescence relative to earlier in childhood resulting in greater power to identify differences. This increased variability can be observed in our data, particularly for insulin levels. Therefore, it is a possibility that a downstream consequence of cesarean section is an amplification of the physiologic insulin resistance of puberty. As our findings were of borderline statistical significance, despite robustness in direction and magnitude in sensitivity analysis, and since we did not account for multiple testing, a chance finding should be also considered as an equally plausible explanation for the observed relations. Clearly, new studies are necessary not only to corroborate or refute our findings but also to examine the underlying biological mechanisms underpinning these relations.Some biological mechanisms have been proposed to explain the relation of cesarean section with childhood obesity that may also apply to the observed relations with adiponectin and insulin we observed in this study. Of note, multiple groups have reported differences in intestinal microbiota composition between infants delivered via cesarean vs. vaginally.r = 0.99). Importantly, we did not assay glucose immediately, but instead used stored, frozen samples, which likely resulted in greater variability and this non-differential error would tend to bias results to the null. Also, generalizability is limited because there is a high proportion of white study participants who also had a relatively high level of education and income. In addition, it is important to consider the possibility that what we interpreted as a signal suggesting for increased insulin resistance in early adolescence among individuals born by cesarean section could also be a chance finding resulting from multiple testing. Finally, pubertal development information was collected by the parents using a questionnaire; thus, it is subject to measurement error. However, the questionnaire has been previously validated36 and the score has been strongly correlated with physician breast Tanner staging in girls55 and pubic hair staging in boys.56 Furthermore, the calculated pubertal score has been associated with BMI among children in Project Viva.57This study includes important strengths. First, we used a well-characterized prospective cohort with a large and detailed collection of covariates to reduce the possibility of residual confounding in the reported associations. Second, our study included objective measures of metabolic health and inflammation biomarkers obtained by highly trained staff using standardized protocols. Third, we used sophisticated statistical methods such as stabilized inverse probability weights to account for selection bias due to loss to follow-up, although similar cesarean section rates, plasma biomarker levels, and maternal-child characteristics were observed between included and excluded participants. Some limitations included self-reported maternal prepregnancy weight to calculate maternal BMI, which can cause measurement error; however, a correlation between self-reported and clinic prepregnancy weight in a subset of Project Viva participants was high (In summary, we found that adolescents born by cesarean section have lower levels of adiponectin and higher levels of insulin, suggesting increased insulin resistance, relative to adolescents born by vaginal delivery. While these findings are intriguing, given the scarcity of data on this topic and its great potential public health impact, it is imperative that this question is addressed in independent studies to confirm or refute these findings, ideally in populations where additional details regarding the specific circumstances leading to the decision to perform a cesarean section can be examined.Supplementary Information


Cactodera milleri cysts were discovered from soil samples collected from a Chenopodium quinoa field, located in Mosca, Alamosa county, Colorado, USA. Approximately 200 lemon shaped cysts and several hundred juveniles were recovered from the affected quinoa plants. The same species was also identified from several counties in Minnesota from samples submitted over the years by the Minnesota Department of Agriculture as part of the Animal and Plant Health Inspection Service (APHIS) efforts to survey states for the presence of Pale Potato Cyst Nematode. The cysts and juveniles (J2) were recovered from soil samples through sieving and Baermann funnel extraction. The nematode species was identified by both morphological and molecular means as Cactodera milleri . To our knowledge this represents the first report of Cactodera milleri from Colorado and Minnesota.In 2019,  Cactodera  currently includes 16 species  in Michigan. Chenopodium quinoa Willd. was among the species that were tested and identified as a host for C. milleri . In 2008, it was first identified in Wadena county and later from Kittson county, in 2011, 2015, and 2016.The Pale Potato Cyst Nematode National Survey program, which is an USDA program meant to keep under control the distribution of the Pale Cyst Nematode, is conducted nationwide by the States Department of Agriculture offices. The Minnesota Department of Agriculture is submitting regularly cysts samples to MNGDBL for identification purposes as part of the PCN program. Currently, Cysts, white females, second-stage juveniles (J2), and eggs were obtained from Colorado (CO) and Minnesota (MN). Juveniles for morphological observations were separated from soil by sieving and Baermann funnel extraction or were live recovered from cysts from fresh roots and kept in water in watch glasses. Juveniles were fixed in 3% formaldehyde and processed to glycerin by the formalin glycerin method . FemalesCactodera milleri.Living nematode juveniles (J2) recovered from the cysts were examined morphologically and molecularly for species identification. Observations of morphological characters critical for identification were: cyst shape, color and nature of fenestration, cyst wall pattern, J2 stylet length, shape of stylet knobs, and shape and length of tail and hyaline tail terminus  thus indRepresentative J2 from two CO isolates and three MN isolates were used for molecular confirmation of the species, using two ribosomal genes , one nuclear gene , and one mitochondrial gene . Markers were amplified with the following primer sets: TW81 and AB28 for ITS rDNA; D2A and D3B for 28S rDNA; U288 and L1110 for Hsp90; and primers JB3 and JB4.5 for COI . DNA extNew sequences were submitted to GenBank under the following accession numbers: ITS from CO  and MN (MK619682-MK619693); Hsp90 from MN (MK105547-MK105550) and CO ; COI from CO (MT328830-MT328835); and 28S from MN , and CO .http://www.phylo.org; Punctodera chalcoensis (AY090885) set as the outgroup. Markov chains were sampled at intervals of 500 generations and burn-in of 5,000. A 50% majority rule consensus tree was generated with posterior probabilities (PP), expressed as a percent, calculated for each clade (Betulodera betulae (KF214751) as outgroup. Hsp90 genomic alignments were analyzed under the model GTR + I + G implemented in MrBayes as described above, with Helicotylenchus digonicus (MK580830) set as the outgroup. COI mtDNA DNA alignments were analyzed in CIPRES under the model GTR + I + G implemented in MrBayes as described above, with Rhizonemella sp. (MF425746) as the outgroup. Alternative trees for each marker were made using the maximum likelihood tree-building algorithm IQ-tree . For ITS, the best-fitting model of nucleotide substitution, General Time Reversible with Gamma distributed rates with Invariant sites (GTR + I + G), was estimated using jModelTest based on the Akaike information criterion. Phylogenetic relationships were estimated by Bayesian inference (BI) on the CIPRES Science Gateway (ch clade . 28S rDN IQ-tree  or the Rn = 15) included length of body , stylet well developed  with concave basal knobs (slight to deeply concave), tail , and hyaline tail terminus . The lateral field had four distinct lines. Shapes of the tail, tail terminus, and stylet knobs were also consistent with C. milleri. The cysts (n = 10) were lemon shaped, abullate, circumfenestrate, dark brown in color and had a straight to wavy line type of cyst wall cuticular pattern in the middle  vs 417 μm (291-581 μm), cysts light to dark brown vs light brown to almost black in color, and J2 stylet length being shorter 22 μm (21-23 μm) vs longer stylet length 25 μm (24-27 μm). In addition, C. solani is the only species in the genus known to parasitize tomato.Measurements of second-stage juveniles from Colorado  which contained 8 bp and 7 bp deletions (at different locations) in addition to single base polymorphisms throughout the sequence. Intraspecific variation among all available ITS sequences from C. milleri ranged from 0.2 to 3.5%. The next closest species was C. solani, which had lower intraspecies variation of 0 to 2 bp (0-0.1%). Cactodera milleri differed from C. solani at 7 to 24 bp. In phylogenetic trees, C. milleri formed a strongly supported clade distinct from C. solani from Mexico  and the m Mexico , consistcription .C. milleri  were identical to an isolate obtained in 2011 and 2 bp different from MN isolates. In the MB tree , differing at 8 to 10 bp , primarily in introns, except for one clone from MN (MK105547) that contained a 56 bp shorter intron than the other sequences. Based upon Hsp90 sequence alignment, C. milleri formed a strongly supported clade that was distinct from C. weissi, C. cacti, and other cyst nematodes . In the tree based upon COI alignments, these two species formed separate clades with moderate support. Relatively few COI sequences are available in GenBank, so contribution of additional sequences representing Cactodera species will undoubtedly contribute to an improved understanding of the genus (COI sequences from 2011 and 2019 CO isolates were identical to each other and varied from he genus .Cactodera milleri. The closest species morphologically and molecularly is C. solani, but was distinguishable based upon direct comparison of ITS rDNA and COI. To our knowledge this is the first report of the Cactodera milleri in Colorado as well as in Minnesota. Together, these data contribute to a growing picture of the phylogenetic relationships within the Heteroderidae, with Hsp90 and COI complementing widely used ribosomal markers for identification of species within the genus Cactodera. The amplified region of Hsp90 contains a relatively high degree of polymorphism, particularly within the introns, providing a rich source of intraspecific variation upon which to separate species. Coding regions or translated protein sequences also contain information that may prove beneficial for phylogenetic analysis of circumfenestrate nematodes (Based upon this collective morphological and molecular data, we identify this isolate as ematodes , 2020.