Aedes mosquitoes. As dengue shares similar clinical symptoms with other infectious diseases, prompt and accurate diagnosis is pivotal to clinicians’ decisions on appropriate management. Conventional diagnostic tests to detect the dengue-specific IgM antibody are limited in their performance and ease of use. To address these issues, we developed and evaluated a biosensor based on screen-printed carbon electrodes (SPCEs) for the detection of dengue-specific immunoglobulin M (IgM) antibodies. Various optimisations were performed in order to increase the sensitivity and specificity of the biosensor. For optimal and proper orientation of the paratope sites of goat anti-human IgM capture antibodies (GAHICA), various antibody techniques, including passive, covalent, protein A, protein G and streptavidin/biotin systems, were tested on the SPCEs. The assay reagents for the biosensor were also optimised prior to its evaluation. Analytical sensitivity evaluation was carried out using pooled sera, while analytical specificity evaluation was conducted on a panel of six non-dengue serum samples. Subsequently, diagnostic sensitivity and specificity evaluation were performed using 144 reference samples. Electrochemical current signals generated from H2O2 catalysed by HRP-labelled anti-dengue detection antibodies were measured using the chronoamperometric technique. With a limit of detection (LOD) of 106 serum dilution, the analytical sensitivity of the developed biosensor was 10 times higher than commercial ELISA. The analytical specificity of this dengue IgM biosensor was 100%. Similarly, the biosensor’s diagnostic performance was 100% for sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV). These findings suggest that the developed biosensor has a great potential to be used to diagnose dengue after seroconversion.Dengue is an arbovirus disease transmitted mainly by  Dengue is among the most important human viral diseases that exert a considerable global health burden. In the past few decades, the global prevalence of dengue has risen significantly. Currently, dengue, which poses risk to approximately 3.6 billion people, is endemic in over 100 tropical and subtropical countries. Annually, 390 million dengue cases are estimated to occur. Dengue patients often experience a variety of clinical manifestations, ranging from mild dengue fever to life-threatening severe dengue . AlthougSerological assays to detect the dengue-specific non-structural 1 (NS1) antigen or immunoglobulin M (IgM) antibodies are among the most common diagnostic methods used for the detection of dengue virus infection ,9. The mElectrochemical biosensors are an emerging technology that could be incorporated into clinical diagnostic kits to enhance diagnosis, since it is highly sensitive, specific, simple, rapid and reliable . CompatiWe previously developed an electrochemical biosensor for the detection of dengue-specific non-structural 1 (NS1) antigen. The biosensor, which was designed based on the principle of direct ELISA and fabricated using SPCEs, exhibited good sensitivity and specificity . HoweverThe SPCEs were bought from Scrint Technology . The SPCEs were based on three carbon electrodes, namely, the working electrode, counter electrode and reference electrode. The working electrode was used for developing an immunoassay, while the two other electrodes surrounded the working electrode to form a complete electrical circuit. The electrochemical characterisation, reproducibility and stability of the SPCEs have been evaluated in our previous study . Bovine Chronoamperometric measurements were performed with an Autolab PGSTAT III potentiostat/galvanostat , which was interfaced to Nova software .Blood samples were obtained from suspected dengue patients visiting the clinic or emergency department at Hospital Universiti Sains Malaysia. The collected samples were tested with the dengue IgM capture ELISA (Panbio) at the Department of Medical Microbiology and Parasitology, Universiti Sains Malaysia (USM). Afterwards, ELISA positive and negative samples were pooled separately and used to develop and optimise the electrochemical biosensor. For diagnostic evaluation, 144 reference samples were provided by the Department of Microbiology, Universiti Malaya (UM) . This reA number of methods were evaluated to attain the best immobilisation strategy of GAHICA on the carbon working electrode (CWE). These strategies were either based on random antibody immobilisation  or oriented antibody immobilisation .For passive adsorption, 20 µL (10 µg/mL) of GAHICA diluted in carbonate buffer (pH = 9.4) was pipetted on CWE. The SPCEs were then incubated overnight at 4 °C. Following washing, the CWE was blocked with 3% BSA for 15 min.O-acylisourea intermediate, which is readily converted by nucleophilic attack from the primary amino group into an amide bond and isourea as a by-product. The amino group with primary reactive amine side chains on the capture antibodies was then linked by adding 20 µL (10 µg/mL) of GAHICA and incubated for 1 h. 20 µL of 1 M of ethanolamine hydrochloride was subsequently pipetted on the SPCEs for 10 min in the dark to remove unbound ester groups. Later, 3% BSA was added on the CWE for 15 min to block non-specific binding.EDC/NHS, a chemical cross-linker, was used to immobilise GAHICA permanently on CWE of SPCEs. Initially, 20 µL (50 mg/mL) of CMD was added on the CWE to introduce the carboxylic group (COOH). Following overnight incubation, unbound CMD was washed away with PBS. Afterwards, the COOH group was activated on the CWE by incubating 20 µL of the cross-linkers (0.4 M of EDC and 0.1 M of NHS) for 10 min at room temperature. The cross-linker reacts with the COOH group and converts it into an active Protein A or G was immobilised on separate CWE by pipetting 20 µL (5 mg/mL) of each protein and incubating for 24 h. Subsequently, 20 μL (10 μg/mL) of GAHICA was incubated on the CWE for 1 h. Following washing, 20 μL of (3%) BSA was added on CWE for 15 min to block non-specific bindings.For a stable immobilization of streptavidin on the CWE, the covalent technique as stated in Following antibody immobilisation as described in Following successful immobilisation of GAHICA on the SPCEs, dengue IgM ELISA positive serum samples were pooled and used as a positive control/test, while pooled negative serum samples were used as a negative control. Pooled serum samples were diluted 1:100 in 0.01 M of PBS and then pipetted on the CWE to allow reaction with GAHICA for 1 h. Following incubation and washing, 20 µL (5 µg/mL) of dengue antigen prepared in PBS was added on the CWE. To complete the assay, 20 µL (5 µg/mL) of HRP-conjugated anti-human IgM detection antibodies was added on the CWE and left for 1 h. Before electrochemical measurement, the electrodes were washed with PBS. The cyclic voltammograms analysis following the immobilisation of GAHICA and other assay reagents showed a decrease in redox peaks, similar to that described in our previous study , and the2O2 by the HRP enzyme were measured by applying a fixed reduction potential of −200 mV to the reference electrode. A cut-off value was established during each experiment to differentiate positive from negative results, and was obtained by calculating the average of three negative samples plus three times the standard deviation (SD).To generate an electrochemical response, 70 µL of TMB substrate was pipetted on the three electrodes present on the SPCEs to immerse all three electrodes. Subsequently, electrochemical signals generated from the catalysis of HFor successful commercialisation, it is imperative that the established biosensor satisfies the criteria of a standard diagnostic test, such as exhibiting high sensitivity and specificity. Considering this fact, analytical and diagnostic evaluation was carried out for the developed biosensor.1–107. These dilutions were later tested on the developed dengue IgM biosensor and a commercially available dengue IgM capture ELISA (Panbio). The biosensor assay was performed as mentioned in To determine the analytical sensitivity of the proposed biosensor, the pooled serum sample containing dengue-specific IgM antibodies was diluted from 10To ensure that the developed dengue IgM biosensor selectively detected dengue IgM antibodies, it was exposed to a panel of different samples containing IgM antibodies specific either for hepatitis B, hepatitis C, chikungunya, leptospirosis, malaria or healthy serum samples. The serum was diluted in 1:100 using PBS buffer.Reference samples  were tesp-value ˂ 0.05 was considered statistically significant. Diagnostic sensitivity, specificity, PPV and NPV were calculated using the online MEDCALC® calculator.Statistical analysis was performed using Statistical Package for the Social Sciences (SPSS) software, version 25. All of the assays were carried out on three independent SPCEs, and the values were presented as mean ± standard error (SE). One-way ANOVA with Tukey’s post hoc test was used for the analysis. A p > 0.05) in the current signals generated from the various immobilisation techniques assessed in this study. However, covalent, protein A and protein G techniques generated slightly lower current signals. Interestingly, compared to these techniques, passive immobilisation produced a higher current response with low background signals. However, the best antibody immobilisation that yielded maximum current signals with minimum background signals (0.31 µA) was observed following the use of the streptavidin/biotin immobilisation system. The successful GAHICA immobilisation using this technique was also evident from FESEM images  of the HRP-labelled anti-dengue detection antibody were incubated on the CWE. Following washing, the electrochemical response was measured. As demonstrated in p < 0.05), although the current signals directly correlated with the concentration of the capture antibody only in the presence of 1.25 to 10 µg/mL of the antibody. The maximum current response (3.54 µA) was generated when 10 µg/mL of the capture antibody was utilised.Secondly, the optimum concentration of GAHICA was determined by testing various concentrations ranging from 1.25 to 40 µg/mL. As shown in p > 0.05) was observed when the non-specific reaction in the assay was blocked using these different BSA concentrations. Subsequently, 3% BSA was chosen in the following experiment, as it generated the highest current signal.To further reduce background signal, 1%, 2% and 3% BSA were tested in this dengue IgM biosensor assay C. IntereThe sensitivity of the developed IgM biosensor could be further boosted by establishing a suitable concentration of the polyvalent dengue antigen. As shown in 1 to 106 generated current signals above the cut-off value (0.59 µA). Hence, the LOD of the developed biosensor was 106, and a linear relationship with the current signals was within 103 to 106 serum dilutions. However, as shown in 2 dilution, suggesting the ideal dilution for the assay. The electrochemical response was slightly inhibited at low serum dilution (101). This could be due to the matrix effect, where, at lower dilution, other substances present in the serum affect the binding between the target and its respective antibodies, resulting in a lower current signal. Further serum dilution can, however, weaken this matrix effect.Electrochemical responses produced from different dilutions of serum samples are shown in 1 to 105 . In contrast to the dengue IgM biosensor, only serum dilution in the range of 101 to 105  had an OThe electrochemical response generated during analytical specificity evaluation is demonstrated in The electrochemical responses of 96 dengue IgM positive samples were classified according to infection status and days after onset of symptoms . As expeOn the other hand, dengue-specific IgM negative samples were used to determine the diagnostic specificity of the biosensor. The profile of electrochemical responses generated from a total of 48 dengue negative serum samples consisting of both dengue IgM and NS1 negative samples, dengue IgM negative but NS1 positive samples (primary infection) and dengue IgM negative samples (secondary infection) are shown in The developed dengue IgM biosensor had 100% sensitivity, specificity, PPV and NPV . The bio−3 to 1.7 × 10−4 mol/L) toward IgM antibodies [In this study, a highly specific dengue IgM biosensor was constructed and subsequently assessed for its future potential as an alternative diagnostic assay to confirm dengue infection. For the IgM-based biosensor, proper immobilisation of GAHICA on the CWE of SPCEs is a crucial step to ensure that a sensitive test is developed. This is because the sensitivity of the developed biosensor partly depends on the ability of the GAHICA to successfully bind the CWE with proper orientation of the antibodies. Among the techniques tested, covalent, protein A and protein G techniques generated slightly lower current signals. The lower current response observed during covalent based antibody immobilisation may be due to the effect of antibody crosslinking. The rather harsh treatment of cross-linkers and goat anti-human IgM antibodies could affect the biological activity of the antibodies . Similartibodies . Thus, wHigh sensitivity is always a mandatory criterion for good diagnostic kits. This helps to address, particularly, the concern of a low concentration of antigen/antibodies in some clinical specimens. In terms of analytical sensitivity, the biosensor developed in this study surpassed the commercial dengue ELISA assay. In the future, this notable sensitivity can be further enhanced, perhaps by using a highly efficient electrochemical conductor, such as a gold electrode. Wong et al., 2014 and Atias et al., 2009 used an optical transduction approach for detecting dengue IgM antibodies . The appSpecificity is another critical component of a diagnostic assay. Cross-reactivity, a phenomenon that involves the interaction of specific antibodies with more than one antigen/agent, often leads to false positive outcomes in immunoassays, and could affect patient management. Thus, the specificity of an immunoassay typically lies in the quality of the antibodies used for the assay . In thisThe IgM antibody is detectable in only 50% of patients from day 3–4 after the onset of illness, although this detection rate increases to 80% by day five and 99% by day 10 onwards . TherefoNotably, some of the reference samples collected on day five, six, seven and eight after the onset of illness were positive for the NS1 antigen and negative for the dengue IgM antibody. Interestingly, the electrochemical biosensor accurately recognized these samples as dengue IgM antibody negative samples. Theoretically, antibody titre is detectable from day five after the onset of fever. In this case, it is possible that these samples were not stored at the optimal temperature, thus, the structure of IgM antibodies may have been compromised. It is also possible that the samples might contain inhibitors that interfere with the antibody/antigen complex.The developed dengue IgM biosensor demonstrated good analytical sensitivity and specificity, as well as diagnostic sensitivity and specificity. It is therefore a promising tool for the diagnosis of dengue infection after seroconversion. However, the diagnostic evaluation in this study was carried out using a limited number of reference samples. More reference samples, particularly from other closely related flaviviruses, including Japanese encephalitis virus and Zika virus, should be included in the future for a more robust validation of the dengue IgM biosensor.In conclusion, an electrochemical biosensor based on the MAC-ELISA principle was successfully developed on screen printed carbon electrodes for the detection of dengue IgM antibodies. The developed biosensor demonstrated a high specificity as well as a high sensitivity with low LOD compared to commercial ELISA. Furthermore, diagnostic evaluation showed that the biosensor could be used for the detection of dengue IgM antibodies in real clinical serum samples. Therefore, the developed electrochemical biosensor provides a good alternative for rapid, sensitive and specific detection of dengue IgM antibodies in real serum samples. However, to decentralize the assay, the autolab reader utilised could be replaced in the future with a portable electrochemical reader or smartphone. Additionally, re-designing the developed biosensor as a multiplex assay with reduced operation time to diagnose different infections could enhance the usability, efficiency, and cost effectiveness of the biosensor in the future.


In group 1, we applied vitamin C supplementation in the first six weeks of training, while in group 2 during the remaining six weeks of training. In both phases, the health-related training occurred three times per week. Training accompanied by vitamin C supplementation did not affect prooxidative/antioxidative balance but significantly decreased ferritin heavy chain (FTH) and ferritin light chain (FTL) mRNA in leukocytes . We concluded that vitamin C supplementation might have caused a decrease in gene expression of two important antioxidative genes  and had no effect on plasma prooxidative/antioxidative balance.Physical training and antioxidant supplementation may influence iron metabolism through reduced oxidative stress and subsequent lowering of mRNA levels of genes that are easily induced by this stress, including those responsible for iron homeostasis. Fifteen elderly women participated in our 12-week experiment, involving six weeks of training without supplementation and six weeks of training supported by oral supplementation of 1000 mg of vitamin C daily. The participants were divided into two groups ( FTH1 (ferritin heavy chain 1), FTL (ferritin light chain), PCBP1 (poly(rC)-binding protein 1), PCBP2 (poly(rC)-binding protein 2), FOXO3a (forkhead box O3A), or CAT  are easily induced by oxidative stress. Oxidants can directly induce ferritin gene expression by targeting conserved regions of these genes [Oxidative stress can influence iron metabolism and iron-regulatory protein status . Genes ase genes . MoreoveFTH and FTL encode “acute phase” proteins. It is well known that these genes represent the level of the labile iron pool (LIP), and their upregulation or downregulation is associated with free iron levels [All genes investigated in this study are involved in iron homeostasis and are easily induced by stressors. n levels ,6.In the literature PCBP1 and PCBP2 proteins are described as iron chaperones that deliver iron to ferritin ,8. Thus,An augmentation in oxidation accompanies exercise training but also ageing and some diseases. An easy way to increase antioxidant capacity is to supplement antioxidant vitamins such as vitamin C. This vitamin plays a crucial role in preventative therapy against ageing  and diseIt is well documented that supplementation with vitamins C and E during acute exercise did not attenuate oxidative stress in muscle cells . AdditioAccording to Mankowski et al. , antioxiUnfortunately, to this day, there are no published data showing the effects of vitamin C supplementation combined with exercise in terms of adaptation of ferritin mRNA in leukocytes. Furthermore, there are no data which could answer the question of whether introducing supplementation of ascorbic acid during the training period is important in regard to iron metabolism. Moreover, in current data, there are many studies associated with antioxidant supplementation, but usually in healthy and active men or as an adjunct to treatment of cancer and other diseases. Thus, we decided to investigate the influence of 1000 mg vitamin supplementation used in elderly  healthy women.The aim of this study was to evaluate the effects of sessions of six-week endurance training with and without six-week oral vitamin C supplementation (1000 mg daily) on plasma oxidative stress and antioxidant capacity, as well as on genes associated with cellular stress response and iron metabolism. We assumed that an increase in antioxidant capacity, induced by training and vitamin C supplementation, would have resulted in a decrease in mRNA concentration of the tested genes. Moreover, we assumed that there were no differences in mRNA levels of genes associated with iron metabolism regardless of the timing of supplementation during training.The study protocol was completed by 15 women  with a mean age of 69.2 ± 6.5 years and body weight of 72.9 ± 12.7 kg. We excluded from the analysis the participants who had less than 90% attendance in training. All participants were volunteer students at the University of the Third Age at the Gdansk University of Physical Education and had never trained professionally before. The volunteers had to meet the following inclusion criteria: age between 60 and 80 years, a medical certificate confirming that there were no contraindications to participation in the research, no participation in other projects, a low level of physical activity, and a properly-balanced diet in terms of energy content and basic nutrients. We excluded from the study women who were under 60 or over 80 years of age; had movement limitations that disrupted training or who had ongoing injuries; had endoprostheses or other conditions that limited the possibility of performing tests (including InBody); had poor health in general, including neoplastic diseases, advanced cardio-respiratory diseases, arrhythmias, history of arterial congestion, hypertension (>160/100 mm Hg), transient ischemic attacks, thyroid malfunction, diabetes, were smokers, had high total cholesterol levels (>300 mg/dL), were on a weight-loss diet, or who were taking anti-inflammatory drugs. None of the women had a disease requiring constant treatment and all avoided supplementation for 3 months before the experiment. Additionally, only those women whose dietary intake of energy, protein, fat, and carbohydrates was within the norms established for a given age group for the Polish population qualified to participate in the project.The women were divided randomly into two groups (simple randomization). Group 1  received oral supplementation with vitamin C (1000 mg daily) for the first six weeks of training while group 2  received cellulose. During the next 6 weeks, the groups received the alternative supplement. The study was double-blinded . Body mass analysis was performed using the InBody 720 composition analysis . The anthropometric characteristics of the two tested groups are summarized in This study was approved by the Bioethics Committee for Clinical Research at the Regional Medical Chamber in Gdansk  and conducted according to the Declaration of Helsinki. All participants gave their written, informed consent prior to participation and were informed about the possibility of withdrawal at any time for any reason.All participants recorded their dietary intake for 5 days—3 working days and 2 holiday days at the beginning of the experiment—before starting the training and vitamin C supplementation. The obtained data were analyzed using the Diet 5.0 software, developed by the Food and Nutrition Institute . Meal sizes were estimated using the photo album of products and dishes . On thisThe training program was implemented using the basic principles of health-related training. The 15 women participated in a 12-week multidisciplinary training program  consisting of water gymnastics, gyrokinesis, stabilization training, and Nordic walking at moderate intensity. Each 6-week training period involved 1080 min of exercise . During each session, participants maintained their heart rate (Polar H1) at less than 130 beats/min.In the first 6 weeks of training, group 1 received 1000 mg of Vitamin C  and group 2 received cellulose in tablets . In the following 6 weeks of the training period, participants received the alternative supplement (vitamin C or placebo). Neither they nor the people carrying out the experiment knew what supplements had been given. The choice of vitamin C dose was due to its easy availability and high frequency of consumption in the Polish population.2 max. was determined directly with the cycloergometer, Ergoline Ergoselect 150p (Jaeger OxyconPro) and a gas analyzer (Jaeger OxyconPro).The VO2 max. are presented in Each participant was tested according to the following procedure: 2 min for registration of resting values followed by 5 min of a warm-up with 30 W load and 60 rpm cadence; then the commencement of the appropriate exercise test with a gradual increase of the load by 10 W in intervals of 1 min. Each participant’s test was interrupted when they were exhausted and unable to continue with a given power and the required term of 60 rpm, or after the occurrence of symptoms indicative of the need to end the trial. The results of the VOThree blood samples (5 mL) were collected from each participant—at baseline and 24 h after the first and second training periods.g at 4 °C for 10 min). The obtained leukocytes were lysed using Fenozol . After 5 min incubation 200 µL of chloroform  was added and the suspension was shaken. The water phase was moved to another Eppendorf tube, and to precipitate RNA, 500 µL of isopropanol  was added. Then samples were centrifuged again . The obtained pellet of RNA was washed two times in 1 mL of 75% ethanol and centrifuged one more time (7500× g at 4 °C). Then, ethanol was removed and the pellet was set aside to dry. Dry RNA was diluted in 20 μL molecular grade water. Purity and quality were evaluated spectrophotometrically . For reverse transcription, 1000 ng of pure RNA (A260/280 ≥ 1.7) was used  on Eppendorf Mastercycler Gradient 5331. The profile of the reaction was in accordance with the manufacturer′s instructions. Obtained cDNA was diluted 10-fold indirectly before the PCR reaction. Each gene’s expression was detected using quantitative real-time PCR . To amplify gene expression the following primers were used:TUBB : forward primer: TCCACGGCCTTGCTCTTGTTT and reverse primer: GACATCAAGGCGCATGTGAAC;For FTH1 (NM_002032): forward primer: TCCTACGTTTACCTGTCCATG and reverse primer: CTGCAGCTTCATCAGTTTCTC;For FTL (NM_000146): forward primer: GTCAATTTGTACCTGCAGGCC and reverse primer: CTCGGCCAATTCGCGGAA;For For PCBP1 (NM_006196): forward primer: AGAGTCATGACCATTCCGTAC and reverse primer: TCCTTGAATCGAGTAGGCATC;For PCBP2 (NM_001128913): forward primer: TCCAGCTCTCCGGTCATCTTT and reverse primer: ACTGAATCCGGTGTTGCCATG;CAT (NM_001752): forward primer: GATGGACATCGCCACATGAAT and reverse primer: AAGATCCCGGATGCCATAGTC;For FOXO3A: forward primer: TTCAAGGATAAGGGCGACAGC and reverse primer: CCCATCAGGGTTGATGATCCA.For RNA was isolated using the procedure of Chomczynski and Sacchi  as descrg at 4 °C for 10 min), and the resultant supernatant was frozen at −80 °C for further analysis. Analysis of vitamin C concentrations was performed in an accredited laboratory in Krakow. Concentrations were measured using high-performance liquid chromatography (HPLC) with UV detection (wavelength: 245 nm). Chromatography was performed on a reverse-phase chromatographic column (RP-18)  with a length of 25 cm, diameter 4.6 mm, and a grain diameter of 5 μm, and the mobile phase pH was 2.7. A 2140 Rap1d Spectral Detector Optical Unit UV detector  and Rheodyne® (Model 7010) injector  were used. The retention time of ascorbic acid was 3 min. [Plasma vitamin C concentrations were determined using the method of Robitaille and Hoffer . In bries 3 min. .g at 4 °C for 10 min), and the obtained plasma was stored immediately at −80 °C for further analysis. To evaluate TOS/TOC a photometric PerOx assay kit was applied , and for TAS/TAC an ImAnOx assay kit  was applied. Prooxidative/antioxidative balance was also calculated. The photometric PerOx test was applied ; for TAS, ImAnOx  was applied.For TOS/TOC and TAS/TAC analysis, venous blood was collected into BD Vacutainer tubes  and centrifuged  tests, as appropriate. To evaluate within-person changes, the paired t-test and ANOVA one-way test were applied. The prooxidative/antioxidative balance was calculated as the prooxidative/antioxidative ratio. The genetic data were collected and relative gene expressions were analyzed in Microsoft Excel 2015. The level of mRNA was calculated using the comparative method of Schmittgen and Livak [2 max. were observed during the experiment, both during the training period supported by supplementation and without supplementation .No significant differences in the mRNA of tested genes were observed during six weeks of the unsupplemented training period . At the Dietary analysis indicated energy shortages in group 2 deviating from standards for the Polish population amounting to 1900 kcal/day. Protein intake accounted for 17% of the caloric value of the diet in both groups and was within the norm of 15–20% of energy. Fat intake differed in both groups from the norm for women with the same body weight and age of 79 g/day. Consumption of carbohydrates in group 1 accounted for 50% of the calorie diet value in group 2 and constituted 47% of the calorific value and was in the norm of 45–65% of energy  Table 3Table 3.Further, the participants achieved the recommended daily intake of vitamin C of around 100 mg per day via consumption of foods like peppers, apples, and oranges. Participants in group 2 had lower consumption of kilocalories per day resulting from a significantly-lower amount of fat in their diet. Both groups had a similar intake of vitamin C per kg of body weight.p = 0.03). Six weeks of training without vitamin C supplementation did not affect the plasma concentration of vitamin C. There were no significant differences between groups in the plasma vitamin C concentrations during the whole experiment . After six weeks of training with supplementation, the vitamin C plasma concentration in both groups increased significantly . Little change in TOS was noted during the experiment, although the mean values after supplementation were slightly higher in both groups  as well as of CAT and FOXO3a, and a slight tendency to increase in PCBP1 and PCBP2 mRNA caused by vitamin C did not occur when the participants trained without supplementation. Moreover, the results suggest that the influence of vitamin C on genes associated with iron metabolism is much more important than the applied training.In our study, we hypothesized that vitamin C would increase antioxidant capacity and simultaneously decrease oxidative stress and that the expression of genes associated with oxidative stress, such as FTH1 and FTL genes. The main function of ferritin is to store iron intracellularly [According to the literature, antioxidants may influence both oxidative stress and iron metabolism . The labllularly , thus itllularly  and is illularly . Moreovellularly . Post-trllularly .FTH and FTL mRNA levels occurs only after the training period supported by vitamin C supplementation.Some published studies showed a decrease in plasma iron and ferritin after 12 and 32 weeks of Nordic-walking training ,27. The FTH, FTL, FOXO3a, PCBP1, PCBP2, or CAT mRNA levels in human leukocytes. Our results showed that independent of the length of the training period, a significant decrease in FTH mRNA was observed after vitamin C supplementation. A decrease in FTL mRNA may indicate or lower oxidative stress within cells in subjects after vitamin C supplementation. Genes encoding iron chaperones (PCBP1 and PCBP2) did not change their expression significantly. This may suggest that intracellular free iron level has not changed. Furthermore, FOXO3a and CAT have apoptosis-regulation properties [FOXO3a and CAT mRNA. Although there were no statistically-significant differences, we observed a similar tendency of changes in CAT mRNA levels after vitamin C supplementation compared to FTH and FTL. In summary, the effect of vitamin C supplementation on leukocytes supports the decrease in intracellular oxidative stress  and should be considered positive in regard to human health.To our knowledge, there are no published studies investigating the effects of training supported by vitamin C supplementation on operties ,29. Receoperties ,31, thusFTH mRNA levels before the unsupplemented period. This difference could be associated with the fact, that group 1 had foregone vitamin C supplementation for six weeks before going through the unsupplemented period. Moreover, this effect could still be observed at the end of the experiment (after another six weeks). It is possible that the use of antioxidant supplementation has a long-term effect. However, the duration of the supplementation effect requires further research.Interestingly, a significant difference between groups was observed in 3+ or Cu2+, vitamin C could promote a generation of the reactive oxygen species i.e., OH, O2−, H2O2, and ferryl ion [Plasma vitamin C concentrations of the participants of our study were in the middle and (after the supplementation) upper range of normal. According to Pearson et al. , women hrryl ion . In the rryl ion . Hydrogerryl ion ,36. Furtrryl ion  suggesterryl ion .Vitamin C is not the only antioxidant that can manifest antioxidant and prooxidant properties. There are some studies in which both effects were observed, not only in humans but also in other species ,40. AccoGheorghe et al.  postulat2 max but no difference in metabolic indicators in muscle cells between the supplemented and unsupplemented group. In our study, there was no significant change in VO2 max, but changes in body composition were associated with the length of training.Our study was conducted on healthy elderly women. Ageing is accompanied by an increase in oxidative stress. However, the interpretation of changes in oxidative stress and its influence on ageing is difficult because increased ROS production is associated with healthy ageing as well as ageing caused by inflammation. In the literature, the results related to oxidative stress and ageing obtained by various authors are inconclusive. Some authors postulated an oxidative damage theory of mammalian ageing  and indiThus, in our opinion Vitamin C in a dose of 1000 mg/day did not bring the expected effect in a reduction in oxidative stress and its influence on this parameter was neutral. Despite the influence that vitamin C has on oxidative status, changes in ferritins mRNA levels were observed during the supplementation period, however in group 1 these lasted until the end of training. This could indicate a positive effect of vitamin C supplementation in terms of adaptation to training, but further research is needed to confirm this theory.FTH and FTL mRNA levels in elderly women. We concluded that vitamin C supplementation had a greater effect on gene expression (and could indirectly indicate lower oxidative stress within the cells), compared with its influence on plasma prooxidative/antioxidative balance. The influence on ferritin mRNA levels could indicate a positive effect of supplementation on adaptation to training in elderly women. Additionally, this effect can be observed during the following six weeks of training. Further, the use of supplementation later in the training period caused major changes in body mass, muscle mass, and FTL mRNA, but there were no significant differences between the groups. In our opinion, in the absence of plasma vitamin C levels indicative of deficiency, the need for its supplementation is questionable.Our findings indicated that six weeks of training supported by daily supplementation of 1000 mg of vitamin C did not influence prooxidative/antioxidative balance but did cause a significant decrease in Our study has some limitations. We investigated the changes caused by training supported by vitamin C supplementation in healthy, elderly women, and thus our findings cannot be extrapolated with confidence to the women of different ages or males. Moreover, only one dose (1000 mg per day) of vitamin C was used. The effects of supplementation may be dose-dependent.


The aim of this study was to compare the effects of HRG80®, WG, and placebo on the electrical activity in the brain of elderly human subjects during relaxation and mental challenges. Methods: Changes in the electroencephalogram (EEG) frequency ranges of 17 different brain regions were measured after single and repeated administration of HRG80®, WG, and placebo across a four-week randomized, double-blind, placebo-controlled three-armed cross-over trial. Results: Both red and white ginseng preparations had a strong impact on brain activity, with different effects on various brain regions depending on the mental load during relaxation and cognitive tasks associated with memory, attention, and mental performance. Both ginseng preparations exhibited significant effects on spectral powers compared to placebo, reflecting an activating action. The spectral changes in the quantitative EEG induced by HRG80® indicated an improvement in mood as well as calming effects, evidenced by the modulation of β2 waves, representing changes in GABA-ergic neurotransmission. HRG80® attenuated δ/θ powers during relaxation, suggesting the potential improvement of pathologically enhanced spectral power in aging. Conclusion: The results of this study suggest that both hydroponically cultivated red and wild growing white ginseng have similar beneficial effects on the cognitive functions of elderly subjects, as reflected by electric brain activity, but their modes of action on the brain are different.Background: Recently, the superior efficacy of hydroponically cultivated red ginseng preparation HRG80 Panax ginseng Meyer) have been traditionally used in China, Korea, and Japan for thousands of years “to promote vitality and healthy aging, to enhance cognitive function, mental activity, general weakness, and enhance longevity” with long-term intake. It has been used primarily as a tonic to stimulate weak bodies and to maintain homeostasis, which is a contemporary term associated with adaptive stress syndrome, adaptability and adaptogen concepts [Ginseng Radix and Rhizoma  preparations in preventing stress-induced symptoms associated with the daily work situation of healthy subjects was reported [® was more effective compared to that with the WG and placebo regarding attention, memory, and perceived stress scores after single and repeated administrations for 5 and 12 days [® was also more active than WG in inducing excitatory neurotransmission of rat hippocampal slice preparations in an ex vivo model of long-term potentiation (LTP), reflecting time and spatial dependent memory [®) on electrical activity of the brain of elderly human subjects in normal (relaxing) condition and during mental challenges (cognitive tasks), after repeated administration of test articles for four weeks.Recently, the efficacy of white ginseng (WG) and hydroponically cultivated red ginseng . Overall, 31 participants were assessed for eligibility; all met the inclusion criteria. Thirty patients were recruited in the study, of which all patients completed treatment and were included in the final analysis, Baseline demographic and efficacy outcome measures are shown in The primary efficacy outcomes were the responses of electric brain activity measured as spectral power in 17 different brain regions within six specially defined frequency ranges  during relaxation as well as during the following psychometric tests of cognitive performance: concentration test for attention (d2 test), memory test (ME test), and calculation performance test (CPT).®, and placebo for four weeks.The primary efficacy endpoint was achieved by comparison of the changes in neuronal electrical activity of the brain from baseline to the end of the treatment with WG, HRG80Electric brain activity was recorded under several different conditions. The first recording was always in a relaxed state with open eyes. After this, three different mental challenges were presented during quantitative EEG recordings . ® in comparison to placebo with respect to the frontotemporal brain areas under the eyes open recording condition and during the performance of the d2 test on the first day. The electric maps constructed after the intake of the placebo or one of the two ginseng preparations showed somewhat stronger differences for HRG80Under recording conditions, the CPT and memory test after ingestion of either of the ginseng preparations induced similar patterns of change; however, they were only slightly different from that of placebo. The details are provided in 2) for each electrode position (brain area) and each frequency range (δ–β2). The absolute power values from the baseline recording with respect to all recording conditions were then set to 100%. Drug-induced changes were documented as a pre-post intake comparison of the changes in percentage of these baseline values for every recording condition. When comparing the median values at the baseline (time 0) before all treatments, no major differences were detected. Thus, the starting values of the outcome measures were comparable. Drug-induced changes were documented as a comparison of the pre-post intake values as a percentage of the baseline values for each condition , and memory test. Under the recording conditions of the d2 test, WG changed spectral power only at the electrode positions C® in all three tests, although there were some similarities, e.g., only three of the 17 brain regions were significantly affected  during the d2 test compared to the placebo. On the contrary, all the δ, θ, α1, α2, β1, and β2 spectral powers were significantly decreased in 12 of the 17 brain regions during the CTP, and the δ, θ, α2, β1, and β2 spectral powers were significantly decreased in 14 of the 17 brain regions during the memory test compared to the placebo. The details are provided in A quite different response was observed in the CPT, where an increase in δ power was recorded in the frontal F3 lobe with decreases in θ power in the frontal F8 and α2 power in the temporal T5 location. Similarly, decreases in θ power in Cz and F8 as well as δ power in the Cz brain region were recorded during performance of the memory test. The EEG fingerprint response to WG treatment was different from that of HRG80® and memoLoges® appear more toward the front, whereas HRG80® and White Panax ginseng capsules appear toward the back. The details are shown in All 102 parameters from the EEG recordings (17 electrode positions × 6 frequency ranges) during the eyes open condition were fed into the linear discriminant analysis containing data from several preparations earlier tested with identical methodology . The res®, WG, or placebo preparations at a daily dose of two capsules per day for four weeks. One participant dropped out during the screening, and there were no study dropouts. Thirty elderly subjects were administered HRG80®, WG, and placebo capsules in phases A, B, and C of the study; for details, see In total, four adverse events (AEs) were observed in three patients during the treatment with HRG80Overall, the treatment was well tolerated: all EEG measurements were within the normal range, and physical examinations did not reveal any deviation from normality. No organic disease emerged during the study; for details, see ® decreased the α1 and α2 spectral powers in six locations compared to the placebo, while WG decreased the α power in only one location and the β1 spectral power in two locations, In the relaxation state, repeated administration of HRG80Alpha1 spectral power is known to be associated with serotonin (5HT)-mediated neurotransmission. Thus, an increase in α1 power is positively correlated with relaxation and deep satisfaction , whereas a decrease signalizes a higher activated state; meanwhile, α2 power is mainly associated with dopaminergic (DA)-mediated neurotransmission. A decrease in α2 is positively correlated with a stimulating effect, such as that induced by amphetamine, having an influence on mood and motivation that is possibly related to the pleasure–reward pathway. Attenuation of these waves must be interpreted as a potential positive action on mood. β1 power is associated with the modulation of glutamatergic (Glu) = mediated neurotransmission. A decrease in β1 power signalizes an activating effect .Since the electric activity of the frontal brain seems to be especially important for mental performance, analyzing this activity during treatment with drugs is essential. Even though both of the ginseng preparations seemed to generally act in a similar way during relaxation based on the results of the discriminant analysis, some differences were detected under the different challenging recording conditions and with respect to brain locations.® and WG was observed during relaxation. Whereas HRG80® reduced the spectral power in three frontal brain regions, WG did not affect any of the frontal locations under this recording condition -mediated neurotransmission; the activation of δ power in the presence of mental challenges is positively correlated with an improvement in learning, memory, and concentration, while the θ spectral power is mainly associated with the activation of norepinephrine (NE)-mediated neurotransmission related to attention. The β2 spectral power is mainly associated with the activation of GABA-mediated neurotransmission, which inhibits excessive excitation and is positively correlated with sedation and calmness: Strong sedative molecules such as diazepam induce large increases of β2 power. Therefore, ginseng seems to lead to more activation.These data are in accordance with the results of a recent study, where the beneficial effects of HRG80subjects . These dsubjects  since gi®  in only one electrode position (C3) during the d2 test for attention, where it was significantly less effective in comparison to HRG80e et al. ). Duringe et al. ), where In summary, both ginseng preparations acted in a similar and statistically significant manner in terms of the effects on electric brain activity of older subjects in comparison with placebo. However, some differences were also observed between red and white ginseng with respect to the involved brain regions, especially for the frontal lobe.® Final V1 from 3 July 2019). This study was conducted in accordance with the current version of the Declaration of Helsinki . The trial was conducted in agreement with the International Conference on Harmonization (ICH) guidelines on Good Clinical Practice (GCP). This trial was registered at ClinicalTrials.gov (accessed on 23 February 2021) , Effects of Korean Red Ginseng Extract on Electrical Brain Activity in Elderly Subjects—Full Text View—ClinicalTrials.gov (accessed on 23 February 2021); last assessed on 26 February 2021). All participants gave written informed consent to participate in this study.This clinical trial was performed at the contract research organization (CRO) NeuroCode AG  with governing approval of an ethical committee at Landesärztekammer Hessen, Germany  and a placebo in elderly subjects. The effects of both ginseng preparations and placebo capsules, taken for four weeks, were studied  containing 209 mg of hydroponically cultivated P. ginseng Meyer dry root powder (HRG80®) corresponding to 31.7 mg of total ginsenosides Rg1, Re, Rf, Rh1, Rg2, Rb1, Rc, Rb2, Rd, Rg6, Rh4, Rg3, PPT, Rk1, C(K), Rh2, Rh3, and PPD, including 25.9 mg of rare ginsenosides Rh1, Rg2, Rg6, Rh4, Rg3, PPT, Rk1, C(K), Rh2, Rh3, and PPD; 209 mg of inactive excipient rice flour.The dietary supplement used in this trial was a 418 mg HRG80Details of phytochemical analysis including HPLC profile are shown in our recent publication .P. ginseng Meyer dry root powder (WG) corresponding to 9.8 mg of total ginsenosides Rg1, Re, Rf, Rh1, Rg2, Rb1, Rc, Rb2, Rd, Rg6, Rh4, Rg3, PPT, Rk1, C(K), Rh2, Rh3, and PPD, including 3.06 mg of rare ginsenosides Rh1, Rg2, Rg6, Rh4, Rg3, PPT, Rk1, C(K), Rh2, Rh3, and PPD, calculated as ginsenoside Rb1 .The second dietary supplement used in this trial was a generic 418 mg WG capsule containing 382 mg of wild growing white The visually identical placebo capsules each contained 418 mg of rice flour. The label included the drug name, study code, and storage conditions. Reference samples were retained and stored at Botalys SA.®, or placebo capsules. They were instructed to take two capsules in the morning with water for four weeks. After a four-week washout period, all participants started to undergo further test preparation for the next four-week period.The participants received a package containing either WG, HRG80Study preparations were randomly labeled by a qualified pharmacist (QP) and the random sequence of treatment codes was retained at the manufacturing site until the study was completed. Randomization, blinding, and allocation concealment were performed as previously reported , ensurinThe time administration of investigational products was under the investigator’s control, assuring 100% compliance. It was calculated by counting the remaining capsules for each subject from the first to the last day of the study and verified by the study monitor at the end of the study. Unused capsules (two capsules in each package) were returned to the sponsor.During the visits, the patient was isolated in a quiet, darkened room, sitting relaxed in a comfortable chair. EEG data were recorded twice: at baseline before drug administration  and 120 min after drug administration . These tOn visit 1, the participants were checked for eligibility and informed about the details of the study, including restrictions—do not consume more than one cup of coffee a day (in the morning) during the study and do not take medicines or dietary supplements that may have potential effects on their cognitive functions. They signed written informed consent and passed a routine medical examination to be eligible for inclusion in the trial.On day A , the parOn the first day of phase B day C in , the parOn the first day of phase C day E in , the par®, MEWICON CATEEM-Tec GmbH, D94089 Neureichenau, Germany) using an electro-cap. For a detailed description of the procedure, please refer to reference [The primary efficacy outcome measures were responses of electrical brain activity as spectral power in the 17 different brain regions within six specifically defined frequency ranges  during the cognitive performance tests: d2 test, ME test, and CPT with financial rewards. EEG data were recorded bipolarly from 17 surface electrodes according to the International 10–20 system, with differences in Cz as the physical reference electrode to provide a common average reference , θ (4.75–6.75 Hz), α1 (7.00–9.50 Hz), α2 (9.75–12.50 Hz), β1 (12.75–18.50 Hz), and β2 (18.75–35.00 Hz) [The signals of all 99 electrode positions  were subject to fast Fourier transformation (FFT) based on 4 s sweeps of data epochs (Hanning window). The data were analyzed from 1.25 to 35 Hz using CATEEM5.00 Hz) . Frequen5.00 Hz) ,25.Safety outcome measures—the occurrence and severity of AEs—were recorded from the date of randomization until the end of the trial. All AEs observed by a subject or investigators were recorded during the trial in detail, e.g., description of the event, onset (date and time), resolution (date and time), maximum intensity, action taken, outcome, and causality.Thirty patients were enrolled per treatment phase. The sample size was not determined during this pilot study. It was estimated based on the results of our previous studies carried out under a similar experimental design.Statistical analysis was done as previously reported . Electri® capsules are reported as percentage changes. WG and HRG80® capsules versus the placebo were compared by evaluating the baseline recording of the last day in comparison to the recording 2 h after the intake. A nonparametric sign test was used for the comparison between the effects of the placebo, WG, and HRG80®. The p-values are provided for the statistics of the exploratory study.Data from the first recording (baseline) were set as 100% and electrophysiological changes produced by the placebo or the WG and HRG80Linear discriminant analysis according to Fischer was used for comparison with other drugs of herbal preparations, as previously reported .®, where superior efficacy of hydroponically cultivated red ginseng compared to wild growing ginseng on the cognitive functions of healthy subjects was demonstrated . However, no direct evidence on the brain activity of HRG80® was available.Despite numerous studies conducted during the last few decades, ginseng is not yet recognized in Europe and the US as a medicinal product with well-established use. That is mainly due to the inconsistency of the results of clinical studies, where ginseng preparations were not identical, and therefore reproducible efficacy from one study to another has not been achieved. Reproducible efficacy and quality of wild ginseng cannot be achieved because its environmental conditions are not regulated. Standardized methods of cultivation and processing are required to assure reproducible quality and efficacy. The efficacy of cultivated preparations must be validated in clinical studies on humans, where the effects of cultivated ginseng  on the central nervous system are compared with the effects of wild ginseng. To the best of our knowledge, the only publication on this topic is the publication of the results of our recent of study of red ginseng preparation HRG80Red ginseng has an effect on the CNS in humansRed ginseng has an effect on the CNS in elderly subjects with mild cognitive impairmentsCultivated in standard conditions, red ginseng has an effect on the CNS of elderly subjects with mild cognitive impairmentsHydroponically cultivated in standard conditions, red ginseng has an effect on the CNS in elderly subjects with mild cognitive impairmentsThe overall effects of white and red ginseng on the electrical activity of the brain are different, suggesting different pharmacological activity of the red and white ginseng preparationsA treatment duration of 4 weeks seems to be sufficient to uncover the action of ginseng on the activity of the human brainIn this study, we, for the first time, demonstrate that:No side effects were observed, suggesting also longer treatment periods without unwanted actions.CONSORT 2010 Checklist is available in


Urinary retention (UR) is a common urinary system disease can be caused by urinary tract obstruction with numerous reasons, however, the role of urine microbes in these disorders is still poorly understood. The aim of this study was to identify the urine microbial features of two common types of obstructive UR, caused by urinary stones or urinary tract tumors, with comparison to healthy controls.Urine samples were collected from a cohort of 32 individuals with stone UR, 25 subjects with tumor UR and 25 healthy controls. The urine microbiome of all samples was analyzed using high-throughput 16S rRNA  gene sequencing.Pseudomonas, Acinetobacter and Sphingomonas were enriched, while Lactobacillus, Streptococcus, Gardnerella, Prevotella and Atopobium were decreased in both UR groups in comparison with healthy controls, exhibited an approximate urine microbial community and functional characteristics of two types of obstructive UR. Furthermore, disease classifiers were constructed using specific enriched genera in UR, which can distinguish stone UR or tumor UR patients from healthy controls with an accuracy of 92.29% and 97.96%, respectively.We observed dramatically increased urine microbial richness and diversity in both obstructive UR groups compared to healthy controls. Despite different origins of UR, bacteria such as We presented comprehensive microbial landscapes of two common types of obstructive urinary retention and demonstrated that urine microbial features of these patients are significantly different from that of healthy people. The urine microbial signatures would shed light on the pathogenesis of these types of urinary retention and might be used as potential classification tools in the future. Urinary retention (UR) is a series of complex diseases defined as the inability to completely empty the bladder due to various causes –3. UR afEscherichia coli followed by some gram-positive cocci and other Enterobacteriaceae  function of the “vegan” R package, with the maximum number of permutations = 999. For comparison of all continuous variables, community diversity and richness, significantly different OTU abundance and significantly different taxon abundance at phylum and genus levels were selected using the Wilcoxon rank sum test method as previously described , 32. The(stone UR), 25 patients with UR due to the urinary tract tumors (tumor UR), and 25 healthy controls. These negative controls were not sequenced, as the agarose gel electrophoresis showed that no electrophoretic band of microbial DNA, which indicates that there was no artifact and contaminant in the environment. A total of 727 MB of 300 bp paired-end reads were generated after sequenced on the MiSeq platform, and the average number of reads per sample was 36,072 ± 3376 reads . Likewise, the Simpson index of stone UR and tumor UR was significantly higher than that of controls . The Chao1 index and Ace index, which measure the richness of the community, showed that the richness of microbiome in two UR groups was significantly higher than that in controls . In addition, a Venn diagram . In addition, differences between each of the two groups were further evaluated based on unweighted and weighted UniFrac distances and Bray–Curtis dissimilarity ; Gluconacetobacter and Sphingobacterium ; Pseudomonas and Comamonas ; and so on. Likewise, positive correlations were also found in genera that were enriched in control subjects. More interestingly, the bacteria enriched in urine of the two obstructive UR patients were negatively correlated with those enriched in controls ; Sphingobacterium and Lactobacillus ; Elizabethkingia and Atopobium ; and so on. We further explored the association of the urine microbiome with clinical manifestations  level and the genera that were enriched in obstructive UR patients, such as Pseudomonas, Stenotrophomonas, Sphingomonas, and so on.Evaluation of the connections among these different genera was performed by a Spearman correlation test. Significant positive correlations were found in genera enriched obstructive UR, such as for Mycobacterium, Agrobacterium, Ralstonia, Delftia, Acinetobacter, Methylobacterium and Sphingomonas. Here, we further validated our previous finding that stone UR and tumor UR have approximate urine microbial background although they result from different obstruction causes. The POD value was significantly increased in stone UR group versus control group, and a similar trend was also found in tumor UR group .To explore the potential diagnostic value of the urine microbiome in stone UR and tumor UR, we constructed a random forest classifier to discriminate urinary retention samples from control samples. We only selected the microorganisms that were significantly enriched in stone UR and tumor UR to construct the classification models. Finally, 30 and 34 genera signatures were selected for further analysis for stone UR and tumor UR, respectively. The cross-validation error curve distribution was obtained from five trials of five-fold cross-validation. Both 8 biomarkers were selected as the optimal marker set to distinguish stone UR or tumor UR from the control group , which was consistent with these clinical data , which was consistent with the result based on COG categories . We found that both obstructive UR groups were significantly different from control group, while the functional structure between stone UR and tumor UR was similar  The microflora composition abundance of each sample at the phylum level (A) and genus level (D).  Composition of the urine microbiota at the phylum level (B) and genus level (E) among three groups. (C) The 5 different phylum profiles of average relative abundance across three groups tested by the Wilcoxon rank sum test. The dark green star indicates q < 0.01, light green star indicates q<0.05, very light green star indicates p < 0.05, and gray star indicates q ≥ 0.05. (F) PCoA analysis based on genus level of for two types UR and healthy controls.Additional file 5: Figure S2. LEfSe analyses of the urine microbiomes of stone UR and tumor UR patients compared to those of controls. (A) The LDA bar graphs show differential abundance between stone UR and controls. (B) The LDA bar graphs show differential abundance between tumor UR and controls.Additional file 6: Figure S3. A random forest model was established to distinguish stone UR from tumor UR based on microbial genus.  8, 8 and 1 genus were selected as the optimal marker set for the three ‘randomForest’ model respectively . (D) The average AUC value after 100 ROC measurements to distinguish two types of UR. (E) The MDA of this marker between stone UR and tumor UR. (F) The probability of tumor UR value between two types of obstructive UR.Additional file 7: Table S4. The relative abundance of level 3 KEGG pathway profiles predicted by PICRUSt.Additional file 8: Table S5. The relative abundance of level 2 COG functions predicted by PICRUSt.Additional file 9: Figure S4. Microbial function profiles of these UR patients and the control subjects. (A) PCOA analysis for the relative abundance of level 2 COG categories of all participants. (B) A total of 18 COG functions were significantly different among three groups. (C) Heatmap of Spearman’s correlation of the 44 significantly different genera and 18 significantly different pathways among three groups. The genera or pathways that were enriched in controls are shown in blue.


SOX2 and three of its target genes  were also decreased after treatment with quetiapine. This can, at least in part, explain the mechanisms by which these drugs decrease neurogenesis at a transcriptional level in vitro. These results were supported by the finding of increased metabolite markers of mature neurons following treatment with most of the drugs tested, suggesting increased proportions of mature relative to immature neurons consistent with reduced neurogenesis.Although neurogenesis is affected in several psychiatric diseases, the effects and mechanisms of action of psychoactive drugs on neurogenesis remain unknown and/or controversial. This study aims to evaluate the effects of psychoactive drugs on the expression of genes involved in neurogenesis. Neuronal-like cells (NT2-N) were treated with amisulpride (10 µM), aripiprazole (0.1 µM), clozapine (10 µM), lamotrigine (50 µM), lithium (2.5 mM), quetiapine (50 µM), risperidone (0.1 µM), or valproate (0.5 mM) for 24 h. Genome wide mRNA expression was quantified and analysed using gene set enrichment analysis, with the neurogenesis gene set retrieved from the Gene Ontology database and the Mammalian Adult Neurogenesis Gene Ontology (MANGO) database. Transcription factors that are more likely to regulate these genes were investigated to better understand the biological processes driving neurogenesis. Targeted metabolomics were performed using gas chromatography-mass spectrometry. Six of the eight drugs decreased the expression of genes involved in neurogenesis in both databases. This suggests that acute treatment with these psychoactive drugs negatively regulates the expression of genes involved in neurogenesis in vitro.  Neurogenesis is the development of new neurons from neural stem/precursor cells (NSCs). In the adult human brain, the NSCs reside primarily in two regions: The subgranular zone in the dentate gyrus of the hippocampus, and the subventricular zone of the lateral ventricles .The NSCs are a diverse population of cells with the capacity to self-renew and differentiate into neurons in response to stimuli in order to maintain central nervous system homeostasis. Local stimuli from the niche where these cells are found, as well as extrinsic factors such as neurotransmitters, growth factors, cytokines, and adhesion molecules, can positively or negatively affect the NSCs’ state and differentiation potential, thereby modulating neurogenesis in the adult brain . For exaThis form of circuit plasticity may be altered in different diseases and targeted with pharmacological therapies . CognitiWhile the effects of antidepressants acting through serotonergic receptors is widely investigated and thus better understood, the effects and mechanisms of action of other psychoactive drugs in neurogenesis remain unknown and/or controversial, with studies in mice showing positive effects on neurogenesis. Chronic treatment with atypical antipsychotics  increased neurogenesis in the hippocampus of adult mice . In contThe changes that occur in the NSCs in response to environmental cues such as stress, psychiatric disorders, and aging, together with the evidence of NSCs responsiveness to drugs used in treating psychiatric disorders, supports the idea of neurogenesis being a potential therapeutic target for these diseases. Therefore, this study aims to evaluate the effects of common psychoactive drugs, used in the treatment of affective disorders (bipolar disorder and schizophrenia), on the expression of genes involved in neurogenesis in a human neuronal model in cell culture.The effects of the eight individual psychoactive drugs on the expression level of genes in the GO database classified as involved in neurogenesis were investigated. The effects were quantified and expressed as the enrichment score (ES) and the normalised ES (NES) of all genes following gene set enrichment analysis (GSEA). The results are summarised in p values (p < 0.05). Risperidone was the only drug that led to an increase in the expression of genes involved in neurogenesis.As shown in Having established that the drug treatments generally decreased the expression of genes involved in neurogenesis based on the GO database, we further identified the number of genes that were differentially expressed after the drug treatments.n = 0 and n = 1, respectively) whilst quetiapine appeared to regulate the most (n = 586). Interestingly, a number of differentially expressed genes were commonly regulated by more than 2 and up to 5 of the drugs.As illustrated in The GO database contains 1818 genes that are annotated as being involved in neurogenesis. However, it is likely that a number of these genes are only peripherally involved, many of which are not supported by empirical evidence, and may have more important roles in other biological processes. Therefore, we sought to identify an alternative ontological database that was more specific for genes that play key roles in neurogenesis. The MANGO database classifies approximately 250 genes as involved in neurogenesis and provides experimental evidence to accurately define the role of each gene. Effects of the drugs on MANGO neurogenesis genes are shown in The results showed that 6 of the 8 drugs significantly down-regulated the expression of genes involved in neurogenesis as classified in MANGO . Among the various drugs, quetiapine (median logFC = −0.053), clozapine (−0.028), and lithium (−0.023) showed the strongest effects. Overall, these findings are consistent with the previous results generated using the GO database.2 test was performed. The result showed no statistically significant differences between the drugs of interest (p = 0.87). As depicted in To compare the effects on the expression levels of genes involved in the various processes of neurogenesis across 6 of the 8 drugs , a χTo visualise the number of unique genes transcriptionally regulated by the different drug treatments, both individually and collectively, n = 0), whilst quetiapine appeared to regulate the most (n = 143). Some genes were shown to be transcriptionally regulated in the same direction by up to 4 drugs. We looked closely at the neurogenesis genes that were differentially regulated by 3 or more of the drugs, as these may represent key targets for future drug development. Similar to the findings reported from using the GO database, risperidone and lamotrigine individually regulated the least number of genes (SOX2 (Sry-related HMG box 2), a transcription factor previously implicated in neural development and neurogenesis. As shown in p = 1.75 × 10−8, FDR q = 2.76 × 10−7), clozapine , and valproate , and tended to be decreased by amisulpride  and aripiprazole . To validate these effects, RT-qPCR was performed, and the results were compared to the next generation sequencing data. As shown in SOX2 gene expression. This confirms the next generation sequencing results for these two drugs.Among the genes regulated by multiple drugs was SOX2 gene expression on neurogenesis genes, we first verified the impact of SOX2 on the MANGO neurogenesis genes using the TRRUST database. To achieve this, the list of MANGO neurogenesis genes was submitted to and analysed using the TRRUST database, which generated a list of transcription factors that could affect the expression of the genes submitted for query. Fisher’s exact test was then performed based on the contingency table of gene counts. The results obtained for SOX2 revealed a p value of 0.00059, and an FDR q-value of 0.00096, indicating that SOX2 was likely a major regulator of these neurogenesis genes.To further investigate the effects of reducing As SOX2 is a transcription factor, we then investigated whether the expression of down-stream target genes of SOX2 were affected by the psychotropic agents. We focused on data obtained from the quetiapine, clozapine, and valproate treatment arms as they showed the strongest evidence of negatively regulating SOX2 gene expression compared to the other drugs.DKK1), Bone morphogenetic protein 4 (BMP4), and Cyclin D1 (CCND1). Among the list of genes submitted for query in TRRUST, 3 target genes were identified as most strongly associated with SOX2: Dickkopf WNT signalling pathway inhibitor 1 , l-glutamic acid , Gamma-Aminobutyric acid  and l-glutamine . The exceptions were amisulpride and l-lactic acid , quetiapine and glutathione , and lithium and GABA .The six drugs with effects on genes involved in neurogenesis were tested for their effects on the levels of metabolites suggested to either have a role in neurogenesis, or as markers of neuronal maturity . GeneralThe generation of functional neurons from progenitor cells, neurogenesis, is a continuing process in the hippocampus throughout life, from embryonic development until adulthood . AlteredThe literature around the effects of atypical antipsychotics in neurogenesis is controversial. In rodent models, chronic administration of aripiprazole, quetiapine, and clozapine significantly increased neurogenesis, cell proliferation, and survival ,15,16,17In humans, some studies of antipsychotic treatment were associated with grey matter loss as shown in imaging studies in patients with schizophrenia, but studies have yielded inconsistent results as explored in a meta-analysis by Fusar-Poli . Wang etBcl2 and Bcl-XL, and also decreases the expression of pro-apoptotic genes Bax, Bad, and caspases in rat hippocampal neurons [Antipsychotics are also prescribed for patients with bipolar disorder, together with mood stabilisers and antidepressants. These drugs have also been associated with structural brain differences in these patients, but data is still inconclusive and difficult to parse from illness effects. In bipolar disorder, total grey matter volume was reduced in individuals treated with atypical antipsychotics . The ENI neurons . This efOverall, drugs analysed in our study appear to increase neurogenesis in rodent models, which is in contrast to the findings from human imaging studies, where the drugs appear to decrease grey matter volume, suggestive of reduced neurogenesis, although it is unclear in some designs whether this relates to illness effects or other lifestyle or medical confounders. Our data is at transcriptional levels. The increases in grey matter demonstrated in imaging studies probably occurred because of neurotrophic effects and could explain the differences in results. To the best of our knowledge, there is no study with a similar approach to ours.SOX2. SOX2 is a transcription factor and a marker of the nervous system from the beginning of development in many species, and acts to co-ordinate widespread transcriptional regulation of genes involved in neurogenesis. SOX2 mutations in humans cause defects in the brain, particularly in the hippocampus, involving cognition, movement control, and vision [CCND1, BMP4, and DKK1. CCND1 promotes neurogenesis in vivo, a role that is not linked to its cell cycle function [DKK1 in adult brains [BMP4, CCDN1, and DKK1 by quetiapine could represent a molecular mechanism for the reduction in expression of neurogenesis genes observed in this study after treatment with quetiapine.We further investigated possible mechanisms by which these drugs decrease genes involved in neurogenesis in vitro, identifying a candidate target molecule in d vision . As idenfunction . Both infunction . DKK1 ist brains . The dowThe drugs appeared to cause a general increase in a number of metabolites in NT2-N cells that have previously been suggested to be related to the process of neurogenesis. While it may appear that this suggests a positive effect on neurogenesis, the increased levels of these particular sets of metabolites are related to the presence of more mature neurons, with active neuritogenesis, and not the generation of new immature neurons.For example, decreased levels of NAA is used as a marker of neuronal integrity and is reportedly decreased after whole-brain radiation in rodents, associated with changes in neurotransmission and loss of neuronal viability . The patGABA is another example, with four of the drugs increasing the levels of this metabolite in NT2-N cells. GABA agonists reportedly regulate synaptic integration by increasing the numbers and extension of neurites and promoting the survival of existing neurons ,41.SOX2 and its targets genes BMP4, CCDN1, and DKK1. It also showed the alterations in the levels of metabolites involved in neuronal health, particularly NAA and GABA.In summary, the present study demonstrated that psychoactive drugs decrease the expression of genes involved in neurogenesis in neuronal cell culture after 24 h treatment, partially through inhibition of This study has some limitations that need to be acknowledged. Only one dose of each drug was tested. In addition, we explored acute effects of these drugs, and there is a possibility of a different effect during chronic administration. Our study did not evaluate the effects of these drugs in models of any particular disease state, therefore the nature of the pathophysiologic process of specific diseases might interfere in the effect of these drugs in patients.−5 M RA  for 28 days, with media refreshed every 2–3 days. For experiments, cells (2 × 105 cells/well) were seeded onto 24-well plates coated with 10 μg/mL poly-d-lysine (Sigma-Aldrich) and 10 μg/mL laminin (Sigma-Aldrich). To enrich for a culture of differentiated neuronal cells, mitotic inhibitors  were added to the media every 2–3 days for a total of 7 days. The expression of the neuronal markers NeuroD, Tau, and GluR were evaluated using polymerase chain reaction and agarose gel electrophoresis (data not shown). This was used to validate the generation of differentiated cells with a neuron-like phenotype.NTera2/cloneD1 (NT2) is a pluripotent cell line used as a model of human neurons due to its ability to differentiate into post-mitotic neurons (NT2-N) following retinoic acid (RA) treatment ,43. NT2 n = 4–6 per group). All drugs were purchased from Sigma-Aldrich . Vehicle control cells were treated with an equal volume of Milli-Q water for lithium or valproate controls, 0.1% dimethyl sulfoxide (DMSO) for amisulpride, aripiprazole, clozapine, and risperidone, and 0.2% DMSO for lamotrigine or quetiapine controls. The drugs that were chosen are commonly used in psychiatry and are considered to be mechanistically different. Doses were selected based on previous dose response studies performed in our lab.NT2-N cells were treated with amisulpride (10 µM), aripiprazole (0.1 µM), clozapine (10 µM), lamotrigine (50 µM), lithium (2.5 mM), quetiapine (50 µM), risperidone (0.1 µM), or valproate (0.5 mM) for 24 h . The quality of the extracted RNA was evaluated using an Agilent 2100 Bioanalyzer . The RNA quantity was determined using a NanoDrop 1000 .Following the 24-h drug treatment, cells were harvested using Trizol and total RNA was extracted using RNeasyRNAseq libraries were prepared for all samples from 1 µg total RNA using a TruSeq RNA Sample Preparation Kit  as per the manufacturer’s instructions. Samples were run on an Illumina HiSeq platform  to quantify genome wide mRNA expression.https://github.com/m-richardson/RNASeq_pipe). In summary, this involves: Raw read quality filtering and adapter trimming  with Trimmomatic v35 [n samples, where n is the number of samples in the smallest group for comparison).The raw data were obtained in fastq format and processed using the Deakin Genomics Centre RNA-Seq alignment and expression quantification pipeline  across the 8 drugs [GSEA was deployed using the R package fgsea from Bioconductor ,50, with 8 drugs ,54.t-tests for normally distributed data and Mann–Whitney U tests for data not normally distributed. The 95% confidence interval for the median was obtained by bootstrapping 1000 samples using R [2 test of homogeneity was used to test if the proportions for subprocesses of neurogenesis  were homogenous across different drugs. Aiming to unravel the biological processes driving neurogenesis, we further investigated transcription factors that are more likely to regulate MANGO neurogenesis genes using the prediction tool of key transcription factors from TRRUST—a manually curated database for transcriptional regulatory networks [For the purpose of focusing on genes with well-established evidence of involvement in the neurogenesis process, the MANGO database was utilised to identify genes regulated by the drugs of interest. MANGO version 3.2 contains 397 genes curated and classified according to their effects and associated subprocesses in adult neurogenesis . Differe using R . χ2 testnetworks .® mini kits (Qiagen) and reverse-transcribed to produce cDNA using Maxima H Minus first strand cDNA synthesis kit (Thermo Fisher Scientific) following the manufacturer’s instructions. RT-qPCR was used to measure the expression of specific genes as listed on ® ssDNA Assay Kit (Life Technologies) was used to quantify the cDNA concentration in each sample as per the manufacturer’s instructions. Gene expression data was quantified using the ΔΔCt method normalised to the derived cDNA concentration of each sample. Kolmogorov–Smirnov test was used to check data sets for normality of distribution. Levene’s Test was used to determine whether or not equal variances could be assumed between groups. Drug treatment groups were compared against their respective controls using independent sample t-tests for normally distributed data and Mann–Whitney U tests for data not normally distributed. Statistical analysis was performed using Statistical Package for the Social Sciences version 22 (SPSS) software. Differences were considered statistically significant when p ≤ 0.05.Following the 24-h treatment, cells were harvested, and RNA was extracted using RNeasyv/v), containing the internal standards, U-13C-sorbitol (4 µM) and 13C5, 15N-valine (4 µM). Cells were scraped and incubated on ice for 10 min. Samples were then centrifuged  to pellet precipitated proteins, and the supernatants were transferred to fresh 1.5 mL tubes. Briefly, 200 µL of the aqueous extract was dried for analysis in vacuo. An aliquot of each extracted sample was also taken and pooled to create a pooled biological quality control (PBQC) sample. This pooled sample was split into equivalent loadings as for the biological samples and also dried for analysis. These PBQC samples were run at regular intervals throughout the sample sequence. Gas chromatography–mass spectrometry (GC-MS) analysis was performed following methoximation and trimethylsilylation using a Shimadzu GC/MS-TQ8050NX system and analysed in multiple reaction monitoring (MRM) mode using the Shimadzu Smart Metabolites Database containing 521 MRM metabolite targets. Subsequent data analysis was performed in a targeted manner using Shimadzu LabSolutions Insight software (version 3.6). Briefly, target ion areas for polar metabolites contained within the Shimadzu Smart Metabolites database were integrated and output as a data matrix for downstream data analysis. Each detected metabolite was visually inspected and manually integrated if required. This resulted in a highly curated matrix representing the detected metabolites in each sample.Cells were treated as described on