Objective: The physiological-induced conductive response has been visualised for evaluation in specific muscle compartments under hybrid (hybridEMS) of electrical muscle stimulation (EMS) and voluntary resistance training (VRT) by electrical impedance tomography (EIT).Methods: In the experiments, tendency of conductivity distribution images σ over time was clearly detected for three specific muscle compartments, which are called AM1 compartment composed of biceps brachii muscle, AM2 compartment composed of triceps brachii muscle, and AM3 compartment composed of brachialis muscle, under three training modalities.Results: From the experimental results, the tendency of physiological-induced conductive response are increased in all three training modalities with increasing training time. Correspondingly, the spatial-mean conductivity <σ>AM1,AM2,AM3 increased with the conductance value G and extracellular water ratio β of right arm by bio-impedance analysis (BIA) method. In addition, hybridEMS has the greatest effect on physiological-induced conductive response in AM1, AM2, and AM3. Under hybridEMS, the spatial-mean conductivity increased from <σpre > AM1 = 0.154 to <σ23mins > AM1 = 0.810 in AM1 muscle compartment ; <σpre > AM2 = 0.040 to <σ23mins > AM2 = 0.254 in AM2 muscle compartment ; <σpre > AM3 = 0.078 to <σ23mins > AM3 = 0.497 in AM3 muscle compartment .Conclusion: The paired-samples t-test results of <σ>AM1,AM2,AM3 under all three training modalities suggest hybridEMS has the most efficient elicitation on physiological induced conductive response compared to VRT and EMS. The effect of EMS on deep muscle compartment (AM3) is slower compared to VRT and hybridEMS, with a significant difference after 15 min of training. Previously, several fundamental electrical phenomena were investigated by electrical impedance measurement to characterize the oxidative stress in single skeletal muscle cells , which is performed to detect the physiological response areas of human calf muscles under single-segment EMS in pre-training, post-training, and relaxation   first appeared in the 1980s as a safe, non-invasive, low-cost and real-time detection method that has matured into industrial applications and medical detections. Recently, the EIT is upgraded to frequency-difference EIT (laxation . fdEIT wvic-EMS) . Since thybridEMS training, 2) to clarify the tendency of physiological-induced conductive response in the specific muscle compartments of human upper arm over time under three training modalities, and 3) to quantitatively evaluate the physiological-induced conductive response by three training modalities with conductance value G and extracellular water ratio β by bio-impedance analysis method.Therefore, this study provides three objectives which are 1) to propose electrical impedance tomography (EIT) as a novel method to visualize the specific muscle compartments for hybridEMS). In the VRT procedure, subjects were required to perform bicep curls using 6 kg dumbbell for 3 sets of 12 reps over 5 min under professional guidance. There is a 1-min break between each set. In the EMS procedure, subjects were required to perform continuous EMS stimulation of the biceps on right upper arm for 5 min. The commercial EMS equipment  was employed in this study, which used a constant-controlled current (8 mA) but uses a different voltage value to adapt the training intensity. The stimulation cycle rule was 4 s stimulation with 4 s pause and a stimulation frequency of 20 Hz. After testing the EMS tolerance limit of each experimental subject, level 8 of EMS training intensity was selected from twenty training levels of EMS. Level 8 means that the EMS output has an average voltage of 22.99 V. In the hybridEMS procedure, subjects were required to perform continuous EMS stimulation of the biceps on right upper arm with a training intensity of level 8 continuous stimulation for 5 min. Simultaneously, three sets of VRT procedure were performed on the subjects under professional guidance within 5 min, with a training intensity of 12 reps per set by using a 6 kg dumbbell.pre-training, training, and post-training. In all experimental protocols, subjects were required a sitting position.In this study, eight healthy young men  volunteered for this study. All voluntary subjects gave informed consent. None of the subjects had any history of any musculoskeletal or neurological disorders. σpre in the right upper arm. V of the ten measurements were obtained which is used to reconstruct the conductivity distribution images σ. Secondly, BIA  is able to measure the impedance value Z, the reactance value Xc, and the phase angle value φ, therefore, the conductance value G is obtained by:In the pre-training and post-training parts, firstly, EIT is conducted to reconstruct the conductivity distribution images β = ECW/TBW, where ECW is extracellular water, TBW is total body water. Therefore, conductance value G and extracellular water ratio β are compared with the conductivity distribution changes measured from EIT method.Also, the BIA method is conducted to measure the extracellular water ratio hybridEMS, as shown in In the training part, in order to explore the tendency of physiological-induced conductive response changes by three training modalities. The same subjects were requested to visit the laboratory four times, 2 weeks between each visit. The first visit was to test and decide on the training load to be used for the experiment. The experiment decided to use a 6 kg dumbbell as the training load for resistance training and an output voltage of 22.99 V as the training load for EMS training, after testing the training tolerance limits of each subject. From the second visit, subjects were requested to perform three different training modalities, VRT, EMS, and σ from boundary voltage V use Gaussian-Newton method  descriptive statistics function is used to examine the normal distribution of experimental data from EIT and BIA measurements. α = 0.05, p > 0.05. Therefore, the experimental data from EIT and BIA measurements are considered to obey a normal distribution. The level of significance for paired-samples t-test was set at 0.05.In order to clarify the tendency of physiological-induced conductive response in the specific muscle compartments of upper arm over time under three training modalities, a paired-samples σ of eight subjects’ right upper arm in AM1, AM2, and AM3 under three training modalities obtained by Eq. σ, the conductivity distribution between pre-training and post-training under three training modalities, namely voluntary resistance training (VRT), electrical muscle stimulation (EMS), and hybrid of VRT and EMS (hybridEMS), are clearly detected, which shows the tendency of physiological-induced conductive response are increased in all three training modalities with increasing training time. According to σ, the physiological-induced conductive response of AM1 compartment is significantly affected by all three training modalities. In contrast, the physiological-induced conductive response of AM3 compartment is moderately affected. And the physiological-induced conductive response of AM2 compartment is minimally affected by training.σ5mins, the conductivity distribution of the AM1 compartment is significantly changed between pre- and post-hybridEMS training compared to VRT and EMS, which indicates a faster effect of hybridEMS on the upper arm muscles compared to the other two training modalities. Furthermore, the images σ23mins show that hybridEMS is more effective in stimulating deeper muscle compartment (AM3) than VRT and EMS. The hybridEMS has the greatest effect on physiological-induced conductive response for the same training time.From the images σ>AM1,AM2,AM3 were obtained by a dedicated Python script which analysed the conductivity distribution images σ. t-test results of spatial-mean conductivity <σ>AM1,AM2,AM3 between pre-training and post-training parts under VRT, EMS, and hybridEMS.In order to quantitatively evaluate the physiological-induced conductive response of specific muscle compartments in right upper arm under three training modalities, the spatial-mean conductivity <σpre > AM1 = 0.154 to <σ5mins > AM1 = 0.262, <σ10mins > AM1 = 0.386, <σ15mins > AM1 = 0.565, <σ20mins > AM1 = 0.662, <σ23mins > AM1 = 0.810 in AM1 muscle compartment ; the spatial-mean conductivity increased from <σpre > AM2 = 0.040 to <σ5mins > AM2 = 0.072, <σ10mins > AM2 = 0.128, <σ15mins > AM2 = 0.193, <σ20mins > AM2 = 0.213, <σ23mins > AM2 = 0.254 in AM2 muscle compartment ; the spatial-mean conductivity increased from <σpre > AM3 = 0.078 to <σ5mins > AM3 = 0.119, <σ10mins > AM3 = 0.213, <σ15mins > AM3 = 0.374, <σ20mins > AM3 = 0.394, <σ23mins > AM3 = 0.497 in AM3 muscle compartment .Under VRT, the spatial-mean conductivity increased from <σpre > AM1 = 0.155 to <σ5mins > AM1 = 0.214, <σ10mins > AM1 = 0.285, <σ15mins > AM1 = 0.436, <σ20mins > AM1 = 0.563, <σ23mins > AM1 = 0.782 in AM1 muscle compartment ; the spatial-mean conductivity increased from <σpre > AM2 = 0.052 to <σ5mins > AM2 = 0.076, <σ10mins > AM2 = 0.100, <σ15mins > AM2 = 0.137, <σ20mins > AM2 = 0.177, <σ23mins > AM2 = 0.242 in AM2 muscle compartment ; the spatial-mean conductivity increased from <σpre > AM3 = 0.096 to <σ5mins > AM3 = 0.133 , <σ10mins > AM3 = 0.176 , <σ15mins > AM3 = 0.261 , <σ20mins > AM3 = 0.329 , <σ23mins > AM3 = 0.431  in AM3 muscle compartment.Under EMS, the spatial-mean conductivity increased from <hybridEMS, the spatial-mean conductivity increased from <σpre > AM1 = 0.153 to <σ5mins > AM1 = 0.316, <σ10mins > AM1 = 0.529, <σ15mins > AM1 = 0.691, <σ20mins > AM1 = 0.830, <σ23mins > AM1 = 0.947 in AM1 muscle compartment ; the spatial-mean conductivity increased from <σpre > AM2 = 0.053 to <σ5mins > AM2 = 0.112, <σ10mins > AM2 = 0.181, <σ15mins > AM2 = 0.231, <σ20mins > AM2 = 0.273, <σ23mins > AM2 = 0.359 in AM2 muscle compartment ; the spatial-mean conductivity increased from <σpre > AM3 = 0.109 to <σ5mins > AM3 = 0.188, <σ10mins > AM3 = 0.335, <σ15mins > AM3 = 0.452, <σ20mins > AM3 = 0.478, <σ23mins > AM3 = 0.621 in AM3 muscle compartment . Therefore, the quantitative results also highlight that hybridEMS has the greatest effect on physiological-induced conductive response for the same training time. In addition, EMS has a slower effect on deep muscle compartment (AM3) compared to VRT and hybridEMS, with a significant difference between <σpre > AM3 and <σ15mins > AM3 after 15 min of training.Under t-test results of conductance value G between pre-training and post-training parts under VRT, EMS, and hybridEMS. Under VRT, the conductance value increased from Gpre = 3.09 mS to G5mins = 3.19 mS, G10mins = 3.27 mS, G15mins = 3.33 mS, G20mins = 3.39 mS, G23mins = 3.41 mS . Under EMS, the conductance value increased from Gpre = 3.04 mS to G5mins = 3.06 mS, G10mins = 3.09 mS, G15mins = 3.10 mS, G20mins = 3.11 mS, G23mins = 3.12 mS . Under hybridEMS, the conductance value increased from Gpre = 3.11 mS to G5mins = 3.23 mS, G10mins = 3.32 mS, G15mins = 3.39 mS, G20mins = 3.42 mS, G23mins = 3.45 mS .t-test results of extracellular water ratio β between pre-training and post-training parts under VRT, EMS, and hybridEMS. Under VRT, the conductance value increased from βpre = 37.48% to β5mins = 37.63%, β10mins = 37.76%, β15mins = 37.85%, β20mins = 37.92%, β23mins = 38.07% . Under EMS, the conductance value increased from βpre = 37.47% to β5mins = 37.55%, β10mins = 37.66%, β15mins = 37.70%, β20mins = 37.80%, β23mins = 37.87% . Under hybridEMS, the conductance value increased from βpre = 37.43% to β5mins = 37.66%, β10mins = 37.75%, β15mins = 37.85%, β20mins = 37.95%, β23mins = 38.10% . Therefore, the tendency of <σ>AM1,AM2,AM3 is the same as the tendency of G and β under VRT, EMS and hybridEMS.AM1 compartment composed of biceps brachii muscle and AM3 compartment composed of brachialis muscle. From a previous study, the biceps brachii muscle and brachialis muscle are recognized to be mainly involved in the type II (fast-twitch) muscle fibres (hybridEMS). However, the brachialis muscle located behind the biceps brachii muscle (farther from the EMS electrodes) is not able to elicit a physiological-inducted conductive response by EMS in a short time. According to a recent study, EMS provides undifferentiated stimulation of only the most superficial muscle fibres under the electrodes , which are called e fibres , which aectrodes . TherefoAM2 compartment, which is recognized as the position of the triceps brachii muscle, has a less physiological-induced conductive response compared to AM1 and AM3 compartments under VRT. Similarly, EMS is applied above the biceps, the EMS stimulation current does not induce contraction of the triceps. The physiological-induced conductive response of AM3 compartment after 15 min resulted from the triceps working in concert with the biceps to complete the arm bending movement without loading weight, therefore, the spatial-mean conductivity <σ>AM3 under EMS is less than VRT at the same training time.Secondly, the biceps curl movement consists of two processes, namely the centripetal contraction and the centrifugal contraction . Figure hybridEMS compared to VRT and EMS for specific muscle compartments is discussed. Due to the ability of EMS to activate muscle fibres that would not normally be used in the daily activities  group and people who are not able to perform standard VRT (unVRT) group. In stdVRT group, the spatial-mean conductivity <σ23mins > AM1,AM2,AM3 under three training modalities showed a minor difference in values, as shown in σ23mins > AM1,AM2,AM3 under three training modalities showed a significant difference in values, as shown in hybridEMS takes much shorter time compared to VRT and EMS. hybridEMS is recommended for people who are unable to perform standard voluntary resistance training, because hybridEMS has a better training effectiveness over the same training time.1) Based on the reconstructed images, the conductivity distribution between pre-training and post-trarining parts under three training modalities are clearly detected by EIT, which shows the tendency of physiological-induced conductive response are increased in all three training modalities with increasing training time.σ>AM1,AM2,AM3 increases as the conductance value G and extracellular water ratio β of right arm by bio-impedance analysis (BIA) method increase.2) In the post-training part, the spatial-mean conductivity <t-test results of this investigation demonstrate that hybridEMS has the greatest effect on physiological induced conductive response for the same training time. EMS has a slower effect on deep muscle compartment, AM3 is recognized as brachialis muscle, compared to VRT and hybridEMS, with a significant difference between <σpre > AM3 and <σ15mins > AM3 after 15 min of training.3) The paired samples The present study reveals that the physiological-induced conductive response of specific muscle compartments in human upper arm under three training modalities have been detected by electrical impedance tomography (EIT). The key findings of this study are as follows.


Also, significantly lower blood lactate and glucose (BL & BG) concentrations were found after USRPT (p ≤ 0.001 and p = 0.037). Heart rate (HR) and rate of perceived exertion (RPE) were significantly lower after USRPT than HIIT (p < 0.001 and p = 0.015). According to the results, an USRPT swimming set consisting of 20 × 25 m at a 100 m pace seems to induce more specific responses in kinematic characteristics, biomarkers, HR and RPE compared to a 5 × 50 m HIIT set.The aim of this study was tο examine the acute responses to an Ultra-Short Race Pace Training (USRPT) and a High-Intensity Interval Training (HIIT), both oriented for the event of 100 m freestyle. Eighteen national-level swimmers  aged 13.5 ± 0.1 years, with 8.0 ± 0.5 years of experience participated in the study. All participants completed a USRPT and a HIIT protocol consisting of 2 × 10 × 25 m (USRPT1 & USRPT2) and 5 × 50 m. Significantly higher swimming velocity (SV) were achieved in USRPT compared to HIIT ( Swimming coaches use a variety of high-intensity interval training (HIIT) sets to increase and even evaluate swimmers’ performance. These kinds of set-tests are usually implemented in swimming training systematically. However, their frequent use may also be avoided by coaches to reduce the monotony in swimmers’ psychology  and the USRPT’s conceptualization mainly originated in the research of Astrand et al.  and BeidHIIT is used by coaches as an effective way for swimmers’ improvement ,8,9,10 i2max and work-to-rest ratio of 1:2 to 1:4. In swimming, standardized HIIT sets, in adult and puberty swimmers, is four to ten repetitions of 50 m with maximal intensity and work-to-rest ratio near to 1:4 [−1 after a 4 × 50 m maximal freestyle with a rest ratio of 1:4 [According to the American College of Sports Medicine  the durar to 1:4 ,8,9,16. o of 1:4  and rateo of 1:4 . Therefoo of 1:4 ,12,13,14o of 1:4 ,8,9,16. −1, RPE from 8.0 ± 1.6 to 18.0 ± 1.6 and HR up to 188 ± 9 beats per minute (bpm). Therefore, their conclusion was that USRPT is an anaerobic style of training and can be used by coaches for the improvement of a mostly anaerobic event, such as 100 m. Furthermore, in a case report where USRPT was used for the preparation of a middle-distance swimmer for 11 weeks, it appeared to be successful for performance improvement in the events of 200 and 400 m freestyle [In support of that notion, Cuenca-Fernández et al. , found tAccording to Rushall , the strAlthough USRPT has gained much attention, there is a lack of data about this training method, the potential responses to it, especially in young swimmers, and the claimed superiority compared to HIIT method. Thus, the aim of the present study was to examine the acute training responses of an USRPT set on kinematic characteristics, biomarkers, HR and RPE and compare them with those to a HIIT set, both oriented for the event of 100 m freestyle, in national-level adolescent swimmers. The purpose of comparing the two training methods was to explore new variations of high-intensity training. Based on the literature, our hypothesis was that USRPT would result in lower physiological demands compared to HIIT. Regarding the kinematic analysis, our expectations were that USRPT would be a more efficient training method when compared to HIIT.A total of 18 swimmers, 8 boys and 10 girls, aged 13.5 ± 0.1 years old (Mean ± SD) took part in the study. The swimmers had an average experience of 8.0 ± 0.5 years in the sport and 2 years in the competitive category, while they were trained for 12 h covering close to 30 km per week. Additionally, their best performances in the 100 m front crawl event in a long course pool were rather similar, with an average time of 66.4 ± 2.8 s. The anthropometric characteristics as well as the seasonal best performance in the short course pool at 25, 50 and 100 m front crawl were recorded prior to the study .Inclusion criteria were (a) healthy participants, (b) aged between 13–14 years old, (c) females in the middle period of menstruation (d) 100 m freestyle as one of their main events, (e) daily participation in swimming training, (f) participation in swimming meetings, (g) placed, in at least one swimming event, in the top sixteen of their age group’s national championship and (h) World Aquatics (WA) points > 500. Before the measurements, all the swimmers and their parents were informed about the study’s process and safety. Then, a written consent form was signed by the parents to ensure swimmers’ participation. The study was in accordance with the Declaration of Helsinki and the design was approved by the Research Ethics Committee of the School of Physical Education and Sport Science .The study included two tests, a HIIT and an USRPT one and was conducted in a randomized counterbalanced order on two separate days with 24-h of recovery before and between them. All participants were familiar with HIIT and USRPT sets from their usual workouts. The swimmers were asked to follow the same nutrition plan as well as daily schedule at these two days. Before the tests, the swimmers followed the same warm-up which included a five minute full-body dry land routine of dynamic and explosive exercises. This was followed by a 20 min warm-up with 900 m of swimming that they regularly did in training and included drills, kicking and a short high intensity set (2 × 25 m front crawl with 30 s of rest in between) for priming purposes. At the end of the warm-up procedure the swimmers had ten minutes of rest and continued with the swimming tests. The measurements were conducted in an indoor 25 m pool.The HIIT protocol consisted of 5 × 50 m front crawl ,7,8, at −1), stroke index (SI) (speed × DPS) (m2·s−1) and swimming velocity (SV) (distance/time) (m·s−1) [A digital video camera (SONY HDR-CX450 BLACK) was placed at a high point on one side and in the center of the pool , 20 m fr (m·s−1) . The kinBL and blood glucose (BG) concentrations were measured in capillary blood from a fingertip using portable analyzers . In the HIIT protocol, blood sampling for BL determination was taken before the set and 1 and 3 min after the 5 × 50 m repetitions, whereas BG measurements were measured before and 1 min after the set. In the USRPT protocol, blood sampling for BL determination was done before exercise, 1 min after USRPT1 and 1 and 3 min after USRTP2, while the BG measurement was done before exercise, 1 min after USRPT1 and 1 min after USRPT2 .The swimmers, during the measurements, were wearing a HR sensor  on their dominant arm. The sensor monitored their HR immediately before and after the 5 × 50 m sets in the HIIT protocol, as well as immediately before and after USRPT1 and USRPT2 in the USRPT protocol.RPE was measured via the revised category-ratio scale (0 to 10) before and after HIIT protocol and before USRPT protocol, after USRPT1 and after . The whoA priori sample size (n) calculation was completed with G*Power 3.1.9.7  on Windows . Determiη2) was estimated  [r analysis between the variables. The statistical analysis was performed with the software SPSS, Version 25.0 . The level of significance was set at α = 0.05.All values are shown as mean with standard deviation (±). Descriptive statistics and a test of normality (Shapiro–Wilk) for all the variables were used. Additionally, the measurements were checked for homogeneity and sphericity via Box’s M test of equality of covariance and Mauchly’s test, respectively. When sphericity was not met, Greenhouse Geisser was used to analyze the results. A three-way ANOVA (protocol × gender × measurement) with repeated measures, checking for possible within or between subjects’ effects, was utilized for data analyzation. Possible statistically significant differences were analyzed via Syntax, making pairwise comparisons between groups with Bonferroni’s post hoc test. The effect size (ES) with partial Eta square ( ≥ 0.14) . Also, cp > 0.05). Thus, parametric analyses were followed for all examined variables. Also, the data of the swimmers’ kinematic characteristics , biomarkers , HR, and RPE showed homogeneity (p > 0.05), according to Box’s test of equality of covariance test metrices.According to the Shapiro–Wilk test, the data were normally distributed (p < 0.05). Specifically, the swimmers had a lower DPS during USRPT1 and USRPT2 than during the HIIT set, with a large effect size (DPS(USRPT1), DPS(USRPT2) vs. DPS(HIIT): 1.41 ± 0.81, 1.46 ± 0.23 vs. 1.63 ± 0.37 m, p = 0.007 and p < 0.001 respectively, η2 = 0.20). On the other hand, no statistically significant difference was found between genders (p < 0.05).Statistically significant differences were found between USRPT and HIIT protocols . Specifically, the swimmers had a lower SI during USRPT1 and USRPT2 than during the HIIT set, with a large effect size (SI(USRPT1), SI(USRPT2) vs. SI(HIIT): 1.82 ± 0.70, 1.78 ± 0.71 vs. 2.26 ± 0.82 m2·s−1, p < 0.001 in both cases, η2 = 0.60). Moreover, a statistically significant difference between genders was found only in USRPT1, with a large effect size .Statistically significant differences were found between the USRPT and HIIT protocols and between genders (p < 0.05). Specifically, the swimmers had a faster SV during USRPT1 and USRPT2 than during the HIIT set, with a large effect size (SV(USRPT1), SV(USRPT2) vs. SV(HIIT): 1.61 ± 0.20, 1.60 ± 0.20 vs. 1.56 ± 0.20 m s−1, p < 0.001, η2 = 0.70). A statistically significant difference between genders was found only in the USRPT set, which had a large effect size   .p < 0.05). Specifically, the swimmers’ maximal BL concentration was higher at USRPT2 than USRPT1 (BL(USRPT1) vs. BL(USRPT2): 8.7 ± 0.8 vs. 10.0 ± 0.9 mmol L−1, p = 0.007). Also, in both USRPT sets, the swimmers had lower maximal BL concentration than in the HIIT set, with a large effect size (BL(USRPT1) & BL(USRPT2) vs. BL(HIIT): 8.7 ± 0.8 and 10.0 ± 0.9 vs. 12.9 ± 0.4 mmol L−1, p < 0.001 and p = 0.001, respectively, η2 = 0.90) (p < 0.05).Statistically significant differences were found between USRPT measurements and between USRPT and HIIT protocols ( = 0.90) . On the p < 0.05). Specifically, the swimmers’ BG concentration was higher in USRPT2 than in USRPT1 (BG(USRPT1) vs. BG(USRPT2): 6.0 ± 0.9 vs. 6.4 ± 1.4 mmol L−1, p = 0.038). Also, the swimmers had lower BG concentrations in USRPT1 than in the HIIT set, with a large effect size (G(USRPT1) vs. G(HIIT): 6.0 ± 0.9 vs. 6.4 ± 0.9 mmol L−1, p = 0.037, η2 = 0.40) (p < 0.05).Statistically significant differences were found between USRPT measurements and between USRPT and HIIT protocols ( = 0.40) . On the p < 0.05). Specifically, the swimmers had higher HR in USRPT2 than USRPT1 (HR(USRPT1) vs. HR(USRPT2): 173 ± 1 vs. 180 ± 0 bpm, p < 0.001). Also, the swimmers’ HR in USRPT1 and USRPT2 was lower than in HIIT, with a large effect size (HR(USRPT1), HR(USRPT2) vs. HR(HIIT): 173 ± 1, 180 ± 0 vs. 196 ± 1 bpm, p < 0.001, η2 = 0.90). Moreover, a statistically significant difference between genders was found only in USRPT2 set, with a small effect size : 181 ± 1 vs. 179 ± 1 bpm, p = 0.004, η2 = 0.02)  .p < 0.05). Specifically, the swimmers’ RPE was higher in USRPT2 than in USRPT1 (RPE(USRPT1) vs. RPE(USRPT2): 7 ± 0 vs. 8 ± 0, p < 0.001). Also, the swimmers’ RPE was lower in USRPT1 than in HIIT, with a large effect size (RPE(USRPT1) vs. RPE(HIIT): 7 ± 0 vs. 8 ± 0, p = 0.015, η2 = 0.30) (p > 0.05).Statistically significant differences were found between USRPT measurements and USRPT and HIIT protocols ( = 0.30) . On the r2 = 0.816, p < 0.001 and r2 = 0.829, p < 0.001). Also, BG in the HIIT protocol was correlated with BG in USRPT1 and USRPT2 .Statistically significant correlations were observed between USRPT and HIIT protocols in SR and BG. Specifically, SR in HIIT protocol showed a statistically significant correlation with SR in USRPT1 and USRPT2 . Having a lower DPS in USRPT protocol, one would expect SR to be higher than in HIIT. However, SR is a parameter which is mainly determined by neural activation [Regarding SR, there was no statistically significant difference between protocols while a high correlation was found (tivation . However−1) with our participants. Therefore, it could be hypothesized, that in swimming protocols which are oriented to a specific event distance, in this instance 100 m, swimmers show similar SR. In that sense, the absence of a difference in SR between USRPT and HIIT protocol was a rather relevant result.In addition, in the study from Wądrzyk et al. , it was SI is also an important determinant of front crawl swimming performance, especially in young and high-level swimmers ,30. AccoThe total volume of the sets (500 vs. 250 m) and of each repetition (25 vs. 50 m), most likely affected the SI. Notably, Sánchez and Arellano  suggesteAccording to anecdotal reports, some of the swimmers’ benefits who follow the USRPT method are relevant to the events’ swimming paces and the specific kinematic patterns . HoweverBoth USRPT and HIIT protocols induced increases in BL and BG concentration. These results are similar to the ones of Terzi et al. , William−1, implying an important contribution of anaerobic metabolism to energy demands while BG also increased, except for during the first half of the set (10 × 25 m), possibly indicating a metabolically stressful stimulus to the swimmers.According to Rushall , Cuenca-However, the maximal mean BL in USRPT was lower compared to the values found by Williamson et al. . It is bAdditionally, Cuenca-Fernández et al. , who comAnother reason that the HIIT protocol induced higher BL than USRPT is most likely that the more high-intensity work (mostly relied on the glycolytic system) before rest (where aerobic metabolism dominates) that had to be done in each repetition, as the average bout duration was 32.3 s for HIIT and 17.0 s for USRPT. This difference possibly indicates a greater glycolytic stimulus in HIIT than in USRPT, a result that Cuenca-Fernández et al.  found toBased on the present findings regarding biomarkers, the use of either USRPT or HIIT by coaches must be chosen according to the training period, the swimmers’ age and the distance of the event. Specifically, for maximal BL and stronger anaerobic stimulus in adolescent swimmers, who work for the event of 100 m, HIIT may be a better solution than USRPT. On the other hand, USRPT can be utilized when more moderate BL is required with higher SV.HR was lower in USRPT compared to HIIT. Moreover, HR was higher in USRPT2 than USRPT1, whereas RPE was also higher in USRPT2 than USRPT1. Therefore, the results, also considering the BL and BG results, enhance the notion that the USRPT protocol was most likely less physiologically demanding than HIIT . In addiWilliamson et al. , also moHigher HR was found in males compared to females, but only after USRPT2. The literature regards that, at rest and in submaximal exercise intensity, females, because of the lower cardiac output, show higher HR than males . While iRegarding RPE, the difference between USRPT1 and HIIT displays the higher internal load of HIIT compared to USRPT when total volume of the set is equal. On the contrary, RPE did not differ between USRPT2 and HIIT, showing that USRPT needed a double total volume of set  to reach the same RPE as HIIT. This pertains to Rushall’s  guidelinAccording to the results of the present study, an USRPT protocol, which consisted of 20 × 25 m on 100 m pace, can be identified as a novel approach to HIIT, inducing similar responses regarding only SR and different responses regarding DPS, SI, SV, BL, BG, HR and RPE compared to a more classic HIIT protocol which consisted of 5 × 50 m sets at maximal intensity. Coaches should be aware of the possible effects of the voluminous use of USRPT. This contrasts with Rushall’s guidelines; however, the aforementioned similar or different responses could suggest two viewpoints, one regarding the markers prioritized by coaches for the interpretation of the USRPT and HIIT effects and one regarding which markers are eventually more appropriate for the monitoring of the possible differences between these two protocols. For example, regarding the first viewpoint, coaches could choose a training protocol according to the responses of the kinematic parameters or the fluctuation of biomarkers. Regarding the second viewpoint, sport scientists could pick specific parameters for the differentiation of the responses of the two adjacent protocols.According to the present findings, the acute utilization of USRPT demonstrates differences in kinematics, such as higher SV, lower DPS and SI, in biomarkers, such as lower BL and BG concentration and lower HR and RPE. To conclude, USRPT can be used by swimming coaches as a training stimulus to improve 100 m performance. However, since this suggestion is based on acute responses, it is recommended for future studies to confirm whether or not the USRPT’s possible beneficial effects on swimming performance through the evaluation of its long-term implementation.


Escherichia coli, Staphylococcus aureus) and sterile (mitochondria) agents. When compared to body temperature (37°C), NETs formation increased at 40°C; interestingly, the response was stunted at 35°C and 42°C. While CD16+ CD49d+ PMNs represent a small proportion of the neutrophil population, they formed ~45-85% of NETs irrespective of temperature. Temperature increased formyl peptide receptor 1 (FPR1) expression to a differential extent in CD16+ CD49d- vs. CD49d+ PMNSs, suggesting further complexity to neutrophil function in hypo/hyperthermic conditions. The capacity of NETs to induce Toll-like receptor 9 (TLR9)-mediated NF-κB activation was found to be temperature independent. Interestingly, NET degradation was enhanced at higher temperatures, which corresponded with greater plasma DNase activity in response to temperature increase. Collectively, our observations indicate that NETs formation and clearance are enhanced at 40°C whilst temperatures of 35°C and 42°C attenuate this response. Targeting PMN-driven immunity may represent new venues for intervention in pathological inflammation.Fever and hypothermia represent two opposite strategies for fighting systemic inflammation. Fever results in immune activation; hypothermia is associated with energy conservation. Systemic Inflammatory Response Syndrome (SIRS) remains a significant cause of mortality worldwide. SIRS can lead to a broad spectrum of clinical symptoms but importantly, patients can develop fever or hypothermia. During infection, polymorphonuclear cells (PMNs) such as neutrophils prevent pathogen dissemination through the formation of neutrophil extracellular traps (NETs) that ensnare and kill bacteria. However, when dysregulated, NETs also promote host tissue damage. Herein, we tested the hypothesis that temperature modulates NETs homeostasis in response to infection and inflammation. NETs formation was studied in response to infectious ( One of e.g., sepsis , calprotectin, cathelicidin, and other defensins to trap and kill bacteria, important defensive mechanisms in homeostasis and in disease; , sepsis –15. In vocytosis , 17. Wheocytosis –20. The ocytosis . There iPseudomonas aeruginosa-induced NETs formation (Staphylococcus aureus (S. aureus), gram-negative Escherichia coli (E. coli) and sterile (mitochondria) stimuli at varying temperatures representative of hypothermia, hyperthermia and extreme hyperthermia. The impact of temperature on the phenotype of PMNs and NETs stability, an important aspect of their clearance was also investigated. Our study offers new insights into NET homeostasis in response to temperature; features that may offer new targets for improved therapeutic interventions.To date, there is limited information on the reactivity of PMNs in fever and hypothermia. Only one study has previously reported the impact of fever-range hyperthermia on ormation . We exte22.1® blood collection set into 10 ml BD Vacutainer® Heparin Tubes . Whole blood was used for PMNs isolation and ex vivo NETs formation assay or centrifuged at 1600g for the collection of plasma. Human PMNs were isolated by 1-Step Polymorphs . The procedure was done according to the manufacturer protocol with adaptations published elsewhere . Blood was collected by venous puncture using BD Vacutainerlsewhere . Finally2.2E. coli CFT073 (ATCC 700928) and S. aureus subspecies aureus Rosenbach (NCTC 8530) were inoculated from frozen stocks into LB Broth  and incubated overnight in aerobic conditions at 37°C. Next, bacteria were centrifuged at 5000g for 5 minutes and resuspended in sterile PBS . Bacterial quantification was determined by optical density (O.D.) at 600 nm using a spectrophotometer , where O.D. 1 equaled 8 x 108/ml of colony forming units (CFU) for E. coli CFT073 and 7.8 x 108/ml for S. aureus. We also verified that an increase or decrease in temperature in the range of 35-42°C did not affect the growth of bacteria (2.3ex-vivo studies (EK 218/2020)  . Mitocho9/ml mitochondria from 100 mg of placental tissue.Mitochondria purity and quantity were assessed by qPCR using primers designed to amplify part of the D-loop hypervariable region of mitochondrial DNA  and part of the human globin gene to quantify nuclear DNA . qPCR was performed on the QTower3  using the Advanced Universal SYBR Green Supermix . We routinely isolated ~1 x 102.47/ml isolated PMNs were plated in a 10 cm tissue culture dish  in phenol-red free Gibco™ RPMI 1640 Medium  supplemented with 10% (v/v) FBS . PMNs were then exposed to an established NETs inducer 1 µM phorbol-12-myristate-13-acetate (PMA)  for 3 hours in the 35-42°C temperature range. After the incubation, supernatant was gently aspirated and discarded and NETs that remained attached to the dish were harvested by repeated washing with 10 ml of ice-cold PBS . Suspension containing NETs was then first centrifuged at 400g for 10 minutes at 4°C to pellet debris (dead cells) and NETs-rich supernatant was then centrifuged again at 20000g for 10 minutes at 4°C to pellet NETs. NETs-rich pellet was finally resuspended in several aliquots with 100 µl PBS and stored at -80°C until required. NETs induction by PMA was independently verified by fluorescence microscopy  coated coverslips in phenol-red free Gibco™ RPMI 1640 Medium  supplemented with 10% FBS . Control PMNs were left unstimulated, whilst remaining were treated with E. coli (multiplicity of infection (MOI) 20), S. aureus, (MOI 20), mitochondria (MOI 20) or 100 nM PMA for 3 hours at 37°C and 5% CO2. Post-incubation, cells were fixed and stained, with all steps performed at RT in the dark. Fixation and permeabilization was done by the addition of 2% paraformaldehyde for 10 minutes, followed by 0.05% Triton-X100  for 15 minutes. Next, 1 hour incubation in the blocking buffer consisting of 5% FBS in PBS  was conducted. For citrullinated histone H3 staining, fixed cells were incubated for 2 hours with 0.5 µg/100 µl of primary anti-Histone H3 (citrulline R17) antibody  followed by 1 hour of a 0.5 µg/100 µl of secondary PE Donkey anti-rabbit IgG  antibody . Coverslips were then gently washed with PBS and stained for DNA with 200 nM SYTOX™ Green Nucleic Acid Stain  for 15 minutes. Following staining, coverslips were mounted with Fluorescent Mounting Medium  and images were collected with an Axiolab 5 fluorescence microscope  using Filter Sets 43 and 44 .1x102.750 ng/ml of NETs were stained with 200 nM SYTOX™ Green Nucleic Acid Stain  and incubated in either plasma of a corresponding donor or PBS  in a thermal gradient ranging from 35-42°C using a real-time PCR machine QTower3 . Fluorescence signal was read on a FAM channel at 10 minutes intervals over a period of 6 hours. Effect of exogenously administered DNase I was analyzed by adding RNase-Free DNase I  to a final concentration 2.5 KU/ml. Quantity of undegraded NETs was expressed in % and calculated from the fluorescence signal of a sample normalized to the signal of NETs in PBS.2.84/ml PMNs were incubated in 100 µl of complete RPMI medium supplemented with 200 nM SYTOX™ Green Nucleic Acid Stain  in the presence of E. coli, S. aureus, mitochondria  or 100 nM PMA. 0. PMNs were lysed with 0.05% Triton X-100  for quantification of maximum signal. All samples were assayed utilizing real time PCR machine QTower3  for 3 hours at a temperature gradient ranging from 35-42°C. DNA fluorescence was detected on a FAM channel every 10 minutes. Quantity of PMNs releasing DNA was expressed in % of the maximum signal of the sample treated by 0.05% Triton X-100 . For the analysis of DNA release onset, an automatic threshold was used.5 x 102.9E. coli, S. aureus or mitochondria set to O.D. 1 (600 nm) for 3 hours at 35-42°C. Post-treatment, erythrocytes were lysed using ice-cold isotonic ammonium chloride buffer , and leukocytes were centrifuged at 400g for 10 minutes at 4°C, and the pellet was resuspended in FACS buffer (PBS with 1% of FBS). All samples were then stained for 15 minutes at RT in the dark. All antibodies and dyes except primary anti-Histone H3 (citrulline R17) antibody were purchased from Biolegend, San Diego, CA, USA.100 µl of whole blood was treated with 100 nM PMA or 10 µl of either Analysis of NETs by flow cytometry was conducted as published with gating verified accordingly , 28. StaDe Novo Software, Pasadena, CA, USA) purchased from Biolegend, San Diego, CA, USA.To assess PMNs phenotype, antibody mix used for the detection of NETs was combined with 0.05 µg/sample of anti-human CD16 APC (360706) and either the mix containing 0.04 µg/sample of anti-human antibody CD49d PE/Cyanine 7 (304314) and 0.2 µg/sample PerCP/Cyanine5.5 anti-human formyl peptide receptor 1 (FPR1) (391608) or with 0.025 µg/sample of PE/Cyanine7 Annexin V (640950) to quantify apoptosis. Stained samples were transferred on ice and immediately assayed on a DxFlex flow cytometer , where data were collected on the appropriate channels. Dynamic gains were set upon previous testing to 100. Samples were analyzed by FCSExpress 6.0 software . Bacteria were labelled with 1 µM (E. coli) or 0.5 µM (S. aureus) BacLight™ Red Bacterial Stain  whilst the mitochondria preparation was exposed to 100 nM MitoView™ Green . Staining was performed in the dark at 37°C for 30 minutes (E. coli) or for 15 minutes (S. aureus & mitochondria). All preparations were then washed at 5000g for 5 minutes.Firstly, all agents were labelled; for this purpose, 100 µl of whole blood was treated with 10 µl of appropriate stimuli for 30 minutes at 35-42°C. Post-treatment, all cells were washed and subsequently centrifuged to wash away non-ingested bacteria or mitochondria that are not internalized in cells. Erythrocytes were then lysed and stained for 15 minutes at RT in the dark for flow cytometric analysis.De Novo Software, Pasadena, CA, USA) purchased from Biolegend, San Diego, CA, USA.To assess PMN phenotype, samples were stained with the mix of 0.05 µg/sample of anti-human CD16 APC (360706), 0.1 µg/sample of APC anti-mouse/human CD11b (101212) and 1 µM DRAQ7™ (424001). Stained samples were transferred on ice (to inhibit phagocytosis) and immediately assayed on a DxFlex flow cytometer , where data were collected in the appropriate channels. Dynamic gains were set to 100. Samples were analyzed by FCSExpress 6.0 software .For the quantification of plasma nuclease activity, a customized short PE-labelled DNA oligonucleotide probe was used, as reported previously . The DNa2.12E. coli, S. aureus or mitochondria set to O.D. 1 (600 nm) or 100nM PMA for 3 hours at 35°C-42°C. Post-stimulation, the sample was centrifuged at 1600g at 4°C and plasma collected. The concentrations of cytokines  were determined using the LEGENDplex™ Human Inflammation Panel (13-plex) in V-bottom plates  and measured on a DxFlex cytometer  according to the manufacturer’s instructions.1 ml of whole blood was treated with 100 µl 2.132. 1 x 105 cells/well were stimulated with 100 pg/ml of NETs for 20 hours. ODN 2006  was used as a positive control. ODN 2006 (5’-TCGTCGTTTTGTCGTTTTGTCGTT-3’) is a type B CpG oligonucleotide with a phosphorothioate backbone that contains unmethylated CpG dinucleotides and is a potent activator of TLR9. Cell culture supernatants were harvested and analyzed for NF-κB reporter activity according to the instructions provided. Absorbance was measured using a Synergy H4 Hybrid Reader . Raw data can be found in the supplement (Human Toll-like receptor 9 (TLR9)-expressing HEK-Dual™ hTLR9 (NF/IL8) reporter cells  were selected with antibiotics according to manufacturer’s instructions and cultured in DMEM , supplemented with heat inactivated 10% (v/v) FBS  at 37°C in 5% CO2.14Statistical analysis was performed using GraphPad Prism v8.00 for Windows . TLR9 activation by NETs was analyzed by the Kruskal-Wallis test. Pearson’s correlation coefficient was calculated for the correlation between MPO-DNA complexes and DNA concentration, as well as plasma nuclease activity and temperature. All other results were evaluated using two-factor ANOVA followed by Dunnett’s multiplecomparisons test. Data are presented as a mean and standard deviation (SD). P values < 0.05 were considered statistically significant.33.1E. coli, CFT073) and gram-positive  bacteria and mitochondria  and sterile (mitochondria) stimuli, induce the formation of NETs in isolated PMNs. NETs were identified by the presence of histone H3 citrullination and morphology of the released extracellular DNA. NETs formation was greatest in response to PMA, followed by E. coli, mitochondria and S. aureus , S. aureus (MOI 80) or mitochondria (MOI 80) at temperatures ranging from 35.3-42.2°C . DNA release was quantified at 10 minutes intervals for 3 hours, 100 nM PMA stimulation served as a positive control. PMN DNA is released during cell death, including the formation of NETs. As PMNs employ multiple antimicrobial defense mechanisms each with varying kinetics, it was important to note that NETs formation exhibits slow kinetics (1 to 2 hours). Next, we wanted to elucidate how temperature may affect the kinetics of NETs formation. Although non-specific for a type of cell death, this allowed for the selection of temperatures that will be further investigated in the analysis of NETs formation. We observed no statistically significant effect of temperature on DNA release in the control, unstimulated PMNs, interestingly, percentage of cells releasing DNA concurrently increased in response to all stimuli, showing a maximal response at 40°C, whilst the response at 42.2°C remained impaired  and 26% for PMA (p < 0.001). At 42°C, we have observed a 9-11% decrease for E. coli, S. aureus and mitochondria  and 25% for PMA (p<0.001) . Conversely, decreased DNA release was observed for all of the treated groups at both 35°C and 42°C when compared to 37°C. At 35°C, DNA release in comparison to normothermia was decreased by 9-14% for E. coli induced DNA release at ~58 minutes, mitochondria at ~65 minutes and S. aureus at ~79 minutes. PMA induced DNA release the fastest, with the onset being at ~31 minutes. When compared to 37°C, 40°C promoted onset by 18-24 minutes for E. coli, S. aureus and mitochondria and ~5 minutes for PMA, but none of the differences were statistically significant. At 35°C, DNA release when compared to 37°C was delayed by 59-79 minutes for E. coli, S. aureus and mitochondria  and by ~45 minutes for PMA (p < 0.05). Finally, incubation at 42°C delayed DNA release in comparison to 37°C by 42-73 minutes for E. coli, S. aureus and mitochondria  and ~42 minutes for PMA (p < 0.05)  were recorded in the debris or in the lymphocyte/monocyte population. We found minimal change in cellular granularity in PMNs treated with either bacteria or mitochondria, following a modified protocol from a previous publication .E. coli and PMA induced more NETs  when compared to S. aureus or mitochondria . Incubation at 40°C further increased NETs formation by 12.3-18.1% when compared to 37°C . For CD16+ PMNs incubated at 35°C, relative NETs formation when compared to 37°C decreased by 2.4-4.7% for S. aureus, mitochondria and PMA. Interestingly, E. coli caused ~11% reduction, the most significant impairment amongst the agents tested (p < 0.05). Of note, impairment of NETs formation at 42°C was greater in magnitude (10.7-18%) and importantly reached statistical significance for all stimuli  . At 40°C, CD16+ CD49d- PMNs responded with ~11-14% higher NETs formation to E. coli than to S. aureus or mitochondria (p < 0.01 for both). Similarly, response to PMA was higher by 14-17% than to S. aureus and mitochondria (p < 0.001 for both) . Compared to 37°C, incubation at 42°C resulted in a 3-times decrease in the relative expression of FPR1 on control CD16+ CD49d- PMNs, but the difference was not statistically significant. FPR1 expression was not altered in CD16+ CD49d+ PMNs . When the effect of temperature within each treatment was studied, we observed a 1.8-3-times decrease in expression of FPR1 at 42°C vs. 37°C in all CD16+ CD49d- PMNs . Additionally, when compared to 37°C, increasing the temperature to 40°C resulted in a 1.3-times decrease in FPR1 expression for CD16+ CD49d- PMNs treated with E. coli (p < 0.05)  and treatment with S. aureus resulted in a 1.8-times increase at 42°C (p < 0.01) when compared to respective controls. Mitochondria induced FPR1 expression 2.4-3.3 fold at 40°C and 42°C (p < 0.001 for both) when compared to their respective controls. We have then further examined the effect of temperature on FPR1 expression within each treatment and found when compared to 37°C, mitochondria induced a 1.9-2.4-times increase in FPR1 expression at 40°C and 42°C (p < 0.001 for both) and S. aureus 1.5-times increase at 42°C (p < 0.01)  and phagocytosis of S. aureus increased from 42% at 37°C to 60-63% at 40°C and 42°C (p < 0.05 for both) , with a declining trend observed with an increase in temperature. At 42°C, CD11b expression was increased 3.8-times, however, the difference was not significant and when compared to the induction at 37°C, was relatively decreased 2.2-times (p < 0.01)  (E. coli and S. aureus (p < 0.01 for both), but not mitochondria. At 40°C, S. aureus was the only stimulus that induced a further 1.7-2.9 increase in concentration of IL-6 and TNF-α when compared to 37°C (p < 0.01 for both). The concentration of the anti-inflammatory cytokine IL-10 was increased 20-times in response to all stimuli at 37°C  . No change in IL-10 concentration was observed at 35°C or 42°C in response to any of the stimuli. The concentration of IL-8 increased 3.3-5.1-times in response to both E. coli and S. aureus at 35°C and 37°C, but not at higher temperatures   (S. aureus induced the production of IL-17A at 40°C 5.4-times (p < 0.05), albeit the difference is not clinically relevant and treatment with mitochondria resulted in an 8.6-times increase in MCP-1 at 37°C (p < 0.001) , interestingly, no significant difference between the various NETs preparations was recorded  and while we detected a decreasing trend in large NETs content induced by both stimuli at 40°C, the difference was not statistically significant. In the case of S. aureus-induced NETs, no effect of temperature was seen. Finally, NETs induced by mitochondria at 37°C had 14.5% of large fragments when compared to 5.5% at 40°C (p < 0.05), while no difference was observed between NETs formed at 35°C and 37°C  (p < 0.001)  and sterile (mitochondria) stimuli including PMA followed a similar bell-shaped pattern, with low DNA release at 35°C, progressive increase between 35-40°C and again minimal release at higher temperature. Interestingly, this was inversely related to the onset of NETs formation. These alterations in DNA release kinetics may thus contribute to the differences in PMN death observed at different temperatures, as delayed reaction to stimuli most likely results in smaller overall DNA release and vice versa.Firstly, we found that DNA release in response to infectious  that mediates neutrophil adhesion to endothelium and is in physiological conditions expressed on less than 10% of all neutrophils is present on one-third of neutrophils in patients with sepsis . Herein,E. coli and this change was prominent at all temperatures up to 42°C. E. coli contains LPS, which is like the prototypical FPR1 ligand fMLF (N-formyl-Met-Leu-Phe) a poor inducer of NETs formation by itself, but it is intriguing that these molecules can in combination induce extensive production of ROS and activate NADPH oxidase, an enzyme critical for NETs induction  and sterile stimuli based on PMN phenotype. What is the implication of this observation needs to be further determined, possibly by blocking FPR1 with specific antagonists or antibodies. It can however be hypothesized that in case of sterile injury, targeting CD16+ CD49d+ PMNs with high expression of FPR1 may prove to be a viable strategy to reduce unnecessary NETs formation.PMA itself does not require a receptor, but both bacteria and mitochondria are recognized through FPR1 which detects formyl peptides, present either on their surface or released during septic shock , 39, 40.nduction . InteresE. coli and S. aureus  and gram-positive bacteria (S. aureus), some have shown its increase . The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.JJ: Data curation, Formal Analysis, Investigation, Methodology, Writing – original draft. EB: Formal Analysis, Investigation, Methodology, Writing – original draft. KK: Formal Analysis, Investigation, Methodology, Writing – original draft. BK: Formal Analysis, Investigation, Methodology, Writing – original draft. LH: Formal Analysis, Investigation, Methodology, Writing – original draft. PC: Conceptualization, Methodology, Resources, Supervision, Writing – review & editing. MB-E: Supervision, Writing – review & editing. MP: Conceptualization, Formal Analysis, Funding acquisition, Methodology, Project administration, Resources, Supervision, Writing – original draft.


L-Azetidine-2-carboxylic acid (AZE) is a non-protein amino acid that shares structural similarities with its proteogenic L-proline amino acid counterpart. For this reason, AZE can be misincorporated in place of L-proline, contributing to AZE toxicity. In previous work, we have shown that AZE induces both polarization and apoptosis in BV2 microglial cells. However, it is still unknown if these detrimental effects involve endoplasmic reticulum (ER) stress and whether L-proline co-administration prevents AZE-induced damage to microglia. Here, we investigated the gene expression of ER stress markers in BV2 microglial cells treated with AZE alone (1000 µM), or co-treated with L-proline (50 µM), for 6 or 24 h. AZE reduced cell viability, nitric oxide (NO) secretion and caused a robust activation of the unfolded protein response (UPR) genes . These results were confirmed by immunofluorescence in BV2 and primary microglial cultures. AZE also altered the expression of microglial M1 phenotypic markers . These effects were almost completely prevented upon L-proline co-administration. Finally, triple/quadrupole mass spectrometry demonstrated a robust increase in AZE-bound proteins after AZE treatment, which was reduced by 84% upon L-proline co-supplementation. This study identified ER stress as a pathogenic mechanism for AZE-induced microglial activation and death, which is reversed by co-administration of L-proline. In addition to the 20 canonical amino acids found in nature, there are several non-protein amino acids (NPAAs) that do not contribute to protein synthesis. These NPAAs are highly abundant in plants and are well known for their role in deterring predators via a biological phenomenon called allelopathy, as well as acting as reservoirs for nitrogen storage ,2. L-AzeAZE was firstly identified by Rubenstein in 2006 . Upon itL-Proline residues constitute nearly 6% of the human proteome . Prolinep < 0.01 at 6 h and **** p < 0.0001 at 24 h vs. control, respectively). Co-administration of L-proline at a concentration 20× lower than AZE (50 µM) was sufficient to fully prevent cell viability at both experimental time points . Whilst L-proline co-administration was unable to prevent AZE-driven IL6 induction at 1 h (p > 0.05), it remarkably diminished IL6 mRNAs at 6 h (*** p < 0.001 vs. AZE) and at 24 h ; however, gene expression was significantly up-regulated at 6 h  corroborating our previous data -2,5-diphenyltetrazolium bromide (MTT) solution was added in each well. Following incubation for 6 and 24 h at 37 °C, the medium was removed, and 100 μL of solubilization solution was added. Formazan formed by the cleavage of the yellow tetrazolium salt MTT was measured spectrophotometrically by absorbance change at 550–600 nm using a microplate reader.To assess cell viability, we used the cell proliferation kit I (MTT)  following the procedures described in previous work . Cells w4 cells per well in a 96-well plate and incubated at 37 °C with 5% CO2 until cells reached 80% confluence. Cells were treated for 6 and 24 h with control media, 1000 µM AZE or 50 µM L-proline. The supernatant was collected and placed into a new 96-well plate. A total of 100 µL of freshly prepared Griess reagent was then added to each well and incubated at room temperature for 15 min on a slow oscillation protected from light. Absorbance was measured at 540 nm using the TECAN Infinite M1000-PRO ELISA reader . Optical density values from each group were recorded and reported as a percentage of control.To assess nitrous oxide levels, cells were seeded at 2 × 10Total RNA was extracted using 1 mL TRI reagent  and 0.2 mL chloroform and precipitated with 0.5 mL 2-propanol (Sigma-Aldrich). Pellets were washed twice with 75% ethanol and air-dried. RNA concentrations and purity were calculated using NanoDrop™ 2000 , where RNA was considered free from DNA contamination or phenols if A260/280 > 1.9 and A260/230 > 2.1, respectively . ProteinA total of 1 µg of total RNA was loaded in each cDNA synthesis reaction. cDNA synthesis was conducted using the T1000 thermal cycler  in a final volume of 20 µL. Each reaction contained 1 μg of RNA diluted in a volume of 11 µL, to which we added 9 µL of cDNA synthesis mix (Tetro cDNA synthesis kit) . Samples were incubated at 45 °C for 40 min, followed by 85 °C for 5 min. Finally, cDNA samples were stored at −20 °C until use.® 96-Well PCR Plates and loaded into a CFX96 Touch™ Real-Time PCR Detection System . Instrument settings were as follows: (1) 95 °C for 2 min, (2) 60 °C for 10 s, (3) 72 °C for 10 s, (4) plate read, and (5) repeat step 2 to 4 for 45 cycles. For the melting curve analyses, settings were (1) 65 °C for 35 s, (2) plate read, and (3) repeat step 1–2 for 60 cycles). To examine changes in expression, we analyzed the mean fold change values of each sample, calculated using the ΔCt method. PCR product specificity was evaluated by introducing a negative control in each experiment and by melting curve analysis, with each gene showing a single peak.Real-time qPCR analyses were carried out as previously reported ,53 with 3 cells/cm2. The next day, cells were fixed with pre-filtered 4% paraformaldehyde (PFA: 4% in PBS pH 7.4) . Coverslips were then washed three times with ice-cold PBS and permeabilized for 10 min in sterile PBS containing 0.25% Triton X-100  for 10 min, followed by 3 × washes in PBS for 5 min. Non-specific binding of antibodies was attained by incubating coverslips with 1% BSA in PBST for 30 min. BV2 cells were then incubated in a humidified chamber overnight at 4 °C using a rabbit anti-PERK primary antibody ; diluted 1/250 in PBST and 1% BSA), whereas primary microglia was incubated with the mouse anti-IBA1 antibody  and the rabbit anti-phospho-IRE1α(Ser724) . The next day, primary antibodies were removed with 3 × washes in PBS for 5 min. BV2 cells were then incubated with a goat anti-mouse AlexaFluor 594-conjugated secondary antibody  in 1% BSA in PBST for 2 h at room temperature with gentle oscillation. Primary microglia were incubated with a mixture of two secondary antibodies: goat anti-mouse AlexaFluor 594-conjugated and goat anti-rabbit AlexaFluor 488-conjugated secondary antibodies . Secondary antibodies were then removed by washing cells three times with PBS for 5 min. Counterstaining of nuclei was performed by applying VECTASHIELD® Antifade Mounting Medium with DAPI . Negative controls, in which the primary antibody was omitted, were included to ensure target specificity, and showed no signal (not shown). BV2 stained coverslips were then imaged using a Nikon Eclipse TS2 inverted microscope (magnification 20×), whereas primary microglia were imaged on Leica Stellaris 8 confocal fluorescence microscope (Leica Microsystems) equipped with a 63.5× oil-immersion objective.BV2 microglial cells were seeded on poly-L-lysine coated  coverslips  at a density of 80,000 cells and allowed to adhere overnight. For primary microglial cells, cell density was 4.5 × 10g × 12 min. Supernatant containing proteins were then quantified using the bicinchoninic acid assay  according to manufacturer’s protocol and measured using the TECAN infinite M1000-PRO ELISA reader at 562 nm. Thereafter, proteins were precipitated by adding trichloroacetic acid (TCA) to a final concentration of 10%. Samples were then left overnight at 4 °C and centrifuged at 10,000× g × 10 min at 4 °C to recover precipitated proteins. The protein pellet was then washed three times with cold 10% (w/v) TCA, and transferred to a glass vial for hydrolysis under vacuum overnight at 110 °C in 6 M hydrogen chloride (HCl). The hydrolyzed pellet was reconstituted with 200 µL of 20 mM HCl and filtered through a 0.2 μm filter. Samples were then kept at −80 °C until analysis. Chromatographic separation was performed using a Shimadzu Nexera X2 UHPLC, using a Shimadzu 8060 triple quadrupole mass spectrometer (TQMS) for detection. Separation was carried out on a Waters BEH Amide column , using a flow rate of 0.8 mL/min with a column oven temperature of 30 °C. Solvent A consisted of 80 mM ammonium formate in ultrapure water plus 0.6% formic acid (FA), solvent B consisted of acetonitrile (ACN) plus 0.6% FA. AZE was eluted using the following stepped gradient of solvent B: 0.00 min 90%, 3.50 min 90%, 5.50 min 80%, 9.25 min 80%, 9.30 min 70%, 11.20 min 70%, 11.20 min 90% and 14.00 min 90%. The injection volume was 5 μL. The TQMS was run with an ESI source in positive mode with the following source parameters: 0.1 kV interface voltage, 400 °C interface temperature, 225 °C desolation line (DL) temperature and 400 °C heat block, 3 L/min nebulizing gas flow, 17 L/min heating gas flow, and 3 L/min drying gas flow. Nitrogen was used for drying, heating and nebulizing gas, while argon was used for the collision gas. The MRM transitions for AZE ([M + H+ ACN] +) are 143.00 m/z → 102.10 m/z (CE: −8.0), 143.00 m/z → 56.10 m/z (CE: −23.2).Untreated, AZE-, L-proline or AZE + L-proline treated BV2 microglia (for 24 h) were harvested, lysed in 50 μL ice-cold RIPA buffer and extracted by probe sonication  for 30 s at 50% power for three times, with 1 min interval on ice in between. Protein lysates were then cleared by centrifugation at 10,000× p-values less than 0.05 were considered statistically significant.Statistical analyses were performed using GraphPad Prism software v9.3 . After checking for normal distribution of data, time course analyses were computed using repeated measures ANOVAs followed by Tukey post hoc tests. Image data was analyzed by a one-way ANOVA and Tukey post hoc tests. TQMS analyses were analyzed using non-parametric testing (Mann–Whitney U test). In conclusion, this study provides critical mechanistic insights into the toxicity of AZE in cultured microglia. UPR activation in response to ER stress seems to be the major contributor to microglial polarization and death, and L-proline co-supplementation is sufficient to prevent such damaging effects. Altogether, this understudied environmental toxicant emerges as a novel potential risk factor for neuroinflammation. Although further in vivo preclinical and/or human studies are needed to substantiate our discoveries, our findings warrant additional monitoring of this toxic amino acid. Similarly, our in vitro data suggest that L-proline supplementation may prove to be an effective and simple-to-implement strategy to prevent AZE toxicity in the CNS.


Penicilliumparvum 4-14 to enzymatically saccharify CBAX and reveal the fungal carbohydrate-active enzyme (CAZyme) repertoire by genome sequencing and secretome analysis.Corn bran is a major agro-industrial byproduct from corn starch processing. It contains abundant arabinoxylan that can be converted into value-added chemicals via biotechnology. Corn bran arabinoxylan (CBAX) is one of the most recalcitrant xylans for enzymatic degradation due to its particular heterogeneous nature. The present study aimed to investigate the capability of the filamentous fungus P.parvum based on the fungal genomic sequence (25.8 Mb). Proteomic analysis indicated that the expression of CAZymes in P.parvum varied between CBAX1 and CBR, and the fungus produced complete cellulases, numerous hemicellulases, as well as high levels of glycosidases under the culture conditions.CBAX1 and CBAX2 with different branching degrees, together with corn bran residue (CBR) were generated from corn bran after alkaline hydrogen peroxide (AHP) pretreatment and graded ethanol precipitation. The protein blends E_CBAX1, E_CBAX2, and E_CBR were produced by the fungus grown on CBAX1, CBAX2, or CBR, respectively. Under the optimal conditions, E_CBAX1 released more than 80% xylose and arabinose from CBAX1 and CBAX2. Almost complete saccharification of the arabinoxylans was achieved by combining E_CBAX1 and a commercial enzyme cocktail Cellic®CTec3. Approximately 89% glucose, 64% xylose, and 64% arabinose were liberated from CBR by E_CBR. The combination of E_CBR with Cellic®CTec3 enhanced the saccharification of CBR, with conversion ratios of 97% for glucose, 81% for xylose, and 76% for arabinose. A total of 376 CAZymes including plentiful lignocellulolytic enzymes were predicted in P.parvum at the genomic and proteomic levels, and elaborated on the promising potential of fungal lignocellulolytic enzymes upon saccharification of corn bran biomass after AHP pretreatment.This investigation disclosed the CAZyme repertoire of The online version contains supplementary material available at 10.1186/s13068-023-02319-x. Zeamays L.) is one of the four crops with the highest production and the largest cultivated area worldwide [https://www.statista.com). Corn bran is the outermost layer of the corn kernel and a plentiful byproduct of the corn flour industry, accounting for 6–9% of the corn grain weight [Corn  units decorated with diverse side chains involving α-l-arabinofuranosyl (Araf) residues at O-3 and/or O-2 positions, 4-O-methyl-α-d-glucuronic acid (m-GlcA) at O-2 position, and phenolic or acetyl groups on Araf or Xylp residues  in CBAX ranges from 0.46 to 0.74, depending on the material source (genotype) and extraction method [p residues to attack the main chain [l-galactopyranosyl--β-d-Xylp--5-O-trans-feruloyl-l-Araf (FAXG) structure  [l-arabinofuranosidase , α-glucuronidase (GH67 and 115), and acetylxylan esterase (CE1 and 16) [Complete saccharification of heteroxylans requires the synergistic action of multiple enzymes, which are divided into main-chain degrading enzymes and side-chain degrading (debranching) enzymes . The mai and 43) . The deb and 16) . Other e and 16) , 19. In  and 16) –22. Cons and 16) , 23, seeTrichoderma and Aspergillus species. For example, Trichodermareesei (synonym: Hypocreajecorina) has been developed as the most famous producer of cellulases [Aspergillusniger is used industrially to produce hemicellulases [Penicillium and Talaromyces are promising sources of hemicellulases [Penicillium species exhibited different characteristics from those of Trichoderma and Aspergillus [From an industrial point of view, filamentous fungi are the most popular enzymatic arsenals for the deconstruction of plant biomass because of their strong ability to produce extracellular enzymes . Commercllulases , and Aspllulases . Recent llulases . Particuergillus , 28.Penicilliumparvum (synonym: Eupenicilliumparvum) 4-14 is a valuable decomposer of corn bran [The soil fungus orn bran , and somorn bran –33. The f substitution of CBAX2 was higher than that of CBAX1 and CBR, which was confirmed by the A/X ratios in Table As shown in Table P.parvum 4-14 was grown normally in modified Mandels’ medium, with CBAX1, CBAX2, or CBR as the sole carbon source. After 8 days of fungal growth, the protein concentrations in the supernatants of CBAX1, CBAX2, and CBR media were 0.57 mg/mL, 0.61 mg/mL and 1.12 mg/mL, respectively (Table Sodium dodecyl sulphate-polyacrylamide gel electrophoresis (SDS-PAGE) analysis showed that E_CBAX1 and E_CBAX2 had similar band compositions, which were distinctly different from that of E_CBR  in E_CBR were 4.9- or 4.6-fold and 3.4- or 4.6-fold of those in E_CBAX1 or E_CBAX2, respectively . The enzyme blend released the maximum level (10.8 mg/mL or 11.9 mg/mL) of reducing sugars from CBAX1 or CBAX2 at pH 4.0. Changing the pH value to 3.5, 3.0, or 4.5 resulted in a slight reduction (less than 10%) of the reducing sugars released by enzyme hydrolysis. At a higher pH value of 5.0 or 5.5, the amount of reducing sugar released by E_CBAX1 was reduced by 16–19%  was lower than that on CBAX2 (A/X 0.7), particularly when a low enzyme dosage was used  or 145.4 mg/g 33.5%) xylose, 88.8 mg/g (39.4%) or 142.3 mg/g (46.9%) arabinose, and 99.9 mg/g (84.0%) or 22.4 mg/g (71.7%) glucose were released from CBAX1 or CBAX2 after 2 h of enzymatic hydrolysis, respectively cellulase cocktail Cellic®CTec3 (CTec3) showed a low capability on saccharification of CBAX1 and CBAX2 Fig. a, b. TheHydrolysis of CBR with 10% solid loading was performed using CTec3, E_CBAX1, or E_CBR at 0.2%, 0.4%, and 0.6% dosages, respectively. Among them, CTec3 exhibited the highest saccharification efficiency on the cellulose of CBR, and the lowest conversion ratio on the hemicellulose fraction of the substrate. The amounts of released glucose from the substrate by the low, medium, and high dosages of CTec3 were 451.7 mg/g (79.3%), 527.7 mg/g (92.7%), and 555.3 mg/g (97.5%), respectively , T.reesei (33.9 M), A.niger (33.9 M), and A.oryzae (36.5 M) , 90.15% (8021), 24.12% (2146), 93.19% (8291), 67.22% (5981), 37.72% (3356), 6.90% (614), and 4.23% (376) genes exhibited similarity  to the annotated proteins in the Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Cluster of Orthologous Groups (COG), Non-Redundant (NR), Pfam, Swiss-Prot, Transporter Classification Database (TCDB), and CAZymes databases, respectively. Additionally, 146 cytochrome P450 proteins (genes), 484 secreted proteins (genes), and 35 secondary metabolism clusters (involving 475 genes)  and T.reesei (387) and less than that of A.niger (475) or A.oryzae (518)  and higher than that of T.reesei (68)  possesses more hemicellulolytic enzymes. At least eight α-L-arabinofuranosidases were predicted in the genome of P.parvum, and only three were found in T.reesei. Three α-xylosidases (GH31) and two feruloyl esterases (CE1) were identified in P.parvum, and the two types of enzymes were deficient in T.reesei. Meanwhile, T.reesei had CE15 glucuronooyl esterase, GH74 xyloglucan-specific endo-β-d-1,4-glucanase, and GH115 α-glucuronidase/α-(4-O-methyl)-glucuronidase enzymes, which were not found in P.parvum , 14 carbohydrate esterases CEs, 7 families), 3 polysaccharide lyases , 44 auxiliary activities , 94 glycosyltransferases , and 28 carbohydrate-binding modules   and liquid chromatography–tandem mass spectrometry (LC–MS/MS) analysis, a total of 329 proteins were identified in the secretomes (E_CBAX1 and E_CBR) of l-arabinofuranosidase, were produced by the fungus under the experimental conditions. Two GH3 β-1,4-xylosidases (PP02076 and PP05440) accounted for 20.3% and 9.7% of the total protein abundance in E_CBAX1 and E_CBR, respectively. The total abundances of the two GH3 β-glucosidases (PP00508 and PP07999) were 8.4% for E_CBAX1 and 9.2% for E_CBR. In addition, α-galactosidase (mainly protein PP04893) and α-l-arabinofuranosidase accounted for 4.2% and 4.1% of the total protein abundance of E_CBAX1, respectively , followed by hemicellulose-degrading enzymes (24.7%) and other CAZymes (24.3%), and the least were non-CAZy proteins (14.0%) , existed in the group , followed by CBAX1 (0.55), and insoluble arabinoxylan had the lowest A/X value in CBR (0.49). This is in agreement with the viewpoint that the distribution of Araf substitutions on xylan backbone is not random, and xylan subfractions with varied branching degrees form in plant cell walls [This study aimed to evaluate the saccharification capability of ing acid , alkali ing acid , autohyding acid , and AHPing acid  have beeondition , 39, andondition , 39. In ondition . A largeondition , 40. CBRll walls , 42. Thell walls . The brall walls , 43, whiP.parvum was grown in a chemically defined medium using CBAX1, CBAX2, or CBR as the sole carbon source. Under the induction of CBAX1 or CBAX2, the fungus produced protein blends (E_CBAX1 and E_CBAX2) with similar yields, enzymatic activities, and protein band compositions . Complete monosaccharification of CBAX depends on the synergistic actions of multiple enzymes [Among these protein blends, E_CBAX1 had the highest saccharification efficiency on the extractable arabinoxylans, with the following optimal reaction conditions: pH of 4.0, temperature of 55 °C, and reaction time of 72 h. CBAX, one of the most complex plant xylans with a high branching degree and various substitutions, exhibited remarkable resistance to enzymatic hydrolysis by pure endo-xylanase as well as some commercial enzyme cocktails in previous reports , 46. Her enzymes . We specP.parvum was investigated by genome sequencing as well as secretome analysis. According to the genome (25.8 Mb) annotation, the fungus possesses abundant CAZymes (376) responsible for the decomposition, biosynthesis, or modification of glycoconjugates, oligosaccharides, and polysaccharides [P.parvum are comparable with many famous lignocellulose-degrading fungi  [The CAZyme repertoire of charides . The numCAZymes 36 responsecumbens , T.rees.reesei , and A.A.niger . As expeenome 25. Mb annotA.niger , two GH6PP08284) , 31, a CPP08284) , and an PP08284) .P.parvum grown on CBAX1 or CBR, respectively , endo-β-1,4-glucanase , cellobiohydrolase (GH6 and 7), and LPMO (AA9). High levels of hemicellulolytic enzymes (24.7% of the secretome) were simultaneously produced by the fungus in the presence of the complex substrate  or 37% (118) of the proteins were identified as CAZymes in the secretome of ly Table . Eighteeoxalicum  and couloxalicum . The comase Fig. . Among crolase GH and 7, arolase GH and 7, ad-xylose, and l-arabinose), which are natural inducers of cellulase and/or hemicellulase genes in different filamentous fungi [P.parvum. Meanwhile, a variety of inducers from CBR (cellulose and arabinoxylan) led to high expression of cellulase as well as hemicellulase genes in the fungus. Of note, the production level of endo-β-1,4-xylanases  in the fungus under the induction of CBR was higher than that of CBAX1  was made up of the four enzymes , one α-1,2-glucuronidase (GH67), two feruloyl esterases (CE1), and two acetyl xylan esterases (CE5 or 16) (Table f and m-GlcA) from xylan [l-galactopyranosyl moieties in the FAXG structure. Additionally, the functional complementarity of P.parvum secretomes and the enzyme cocktail CTec3 (designed based on T.reesei lignocellulolytic enzymes) was observed in the saccharification experiments, indicating that one or several components of the latter played an important role in the decomposition of CBAX. For example, T.reesei instead of P.parvum can synthesise GH115 α-glucuronidase , two β-1,4-xylosidase (GH3), five α-om xylan , 18. In P.parvum 4-14  were prepared by culturing the fungus on different fractions  of AHP-pretreated corn bran. Under the optimal conditions, the fungal secretome E_CBAX1 effectively released monosaccharides  from CBAX1 and CBAX2, with a conversion ratio greater than 80%. Almost complete saccharification of the substrates was achieved by combining E_CBAX1 and the enzyme cocktail CTec3. The fungal secretome E_CBR effectively released glucose (89.3%), xylose (64.2%), and arabinose (64.1%) from CBR. The combination of E_CBR and CTec3 enhanced saccharification of the solid substrate, and the conversion ratios of glucose, xylose, and arabinose were up to 97.3%, 81.4%, and 76.1%, respectively. Genomic analysis indicated that the fungus possesses 376 putative CAZymes, including plentiful lignocellulolytic enzymes. Proteomic analysis confirmed that complete cellulases and a variety of hemicellulases with differential expression profiles were produced by the fungus grown on CBAX1 or CBR. High levels of glycosidases  were secreted by the fungus under the growth conditions. The fungal lignocellulolytic enzymes exhibited promising potential for the monosaccharification of AHP-pretreated corn bran.The secretomes of P.parvum 4-14 (CCTCC M2015404) was maintained on potato dextrose agar (PDA) slants at 4 °C in our lab [2PO4, 1.4 g/L (NH4)2SO4, 0.3 g/L urea, 0.3 g/L MgSO4·7H2O, 0.3 g/L CaCl2, 0.3 g/L yeast extract, and 1 mL salt solution , with pH 5.0. The artificial substrates p-nitrophenyl-β-d-glucopyranoside (pNPGlu), p-nitrophenyl-β-d-xylopyranoside (pNPXyl), and p-nitrophenyl-α-d-galactopyranoside  were ordered from Macklin Biochemical Co., Ltd. , and p-nitrophenyl-α-l-arabinofuranoside (pNPAraf) was purchased from Megazyme Co., Ltd. . PASC was prepared according to a previous method [ our lab . The (he our lab  with mins method . Corn br2O2 solution with pH 11.5 (adjusted with solid NaOH) at 40 °C for 24 h. After solid–liquid separation by vacuum filtration with a microporous membrane (0.45 μm), arabinoxylans in the soluble fraction were subjected to graded precipitation by adding ethanol to the final concentrations of 50% and 75%. The arabinoxylans obtained by precipitation with low and high ethanol concentrations were named CBAX1 and CBAX2, respectively. The solid fraction (CBR) was washed three times with distilled water and dried to constant weight in an oven with 60 °C.Corn bran was treated with amylase and papain to remove starch and protein, as described previously . ArabinoThe structural carbohydrate and lignin contents in the raw material, extracted arabinoxylans, and solid residue were determined using the two-step acid hydrolysis method . The monP.parvum 4-14 was grown on a PDA plate at 28 °C for 1 week. To prepare seed culture, a fungal block was aseptically transferred into a 250-mL Erlenmeyer flask containing 50 mL of Mandels’ medium with glucose as the carbon source and incubated on a rotary shaker set at 200 rpm and 28 °C for 120 h. Two millilitres of the fungal seed culture were transferred into a 250-mL flask containing 50 mL of 2 × Mandels’ medium with CBAX1, CBAX2, or CBR as the carbon source. Fermentation was carried out on a rotary shaker set at 28 °C and 200 rpm for 192 h. All fermentation experiments were performed in triplicate. The fermentation broth was sampled periodically and centrifuged at 12,000×g for 10 min. The total protein in the supernatant was quantified using a BCA assay kit .g for 10 min, and re-dissolved in 4 mL phosphate buffered saline . After the same centrifugation, inorganic salts, monosaccharides, and oligosaccharides in the supernatant were removed by dialysis (3 kDa cutoff) against 500 mL phosphate buffer  for 24 h (the buffer was changed every 8 h). Protein samples were quantified using a BCA assay kit and analysed using SDS-PAGE.After fermentation, the supernatant was separated from the fungal mycelium and insoluble substances by vacuum filtration. Mycelial biomass was measured after drying to constant weight at 70 °C. To concentrate the protein solution, the crude extract was subjected to salting-out and dialysis treatments. Briefly, 24 g of ammonium sulphate powder was slowly mixed with 40 mL of the crude extract with continuous stirring, resulting in a salt concentration of 60%. Proteins in the salt solution were precipitated overnight at 4 °C, separated from the liquid fraction by centrifugation at 10,000×l-arabinofuranosidase, β-xylosidase, or α-galactosidase were carried out using pNPGlu, pNPAraf, pNPXyl, or pNPGal as substrates, respectively. The reaction system contained 50 μL sodium acetate buffer , 5 μL substrate (20 mM), 10 μL enzyme (50 ng/μL), and 35 μL dH2O. The mixture was incubated at 50 °C for 10 min, and the reaction was quenched by adding 400 μL of 0.2 M NaCO3 solution. The released p-nitrophenol was quantified by measuring the absorbance at OD405nm and calculating the concentration using a standard curve. One unit (U) of enzyme activity was defined as the amount of enzyme liberating one μmol of glucose, xylose, or p-nitrophenyl from the corresponding substrate per minute under the assay conditions.The activities of crude xylanase, endoglucanase (CMCase), and cellulase were determined using beechwood xylan , carboxymethyl cellulose (CMC-Na) , and PASC as substrates, respectively. The reaction system consisted of 500 μL sodium acetate  buffer, 50 μL (about 1 μg) enzyme sample, and 450 μL substrate solution . After reaction at 50 °C for 10 min, the reducing sugar released from the corresponding substrate was quantified by the 3,5-dinitrosalicylic acid (DNS) method  using a Enzyme hydrolysis of soluble arabinoxylans (CBAX1 and CBAX2) was performed in 2-mL centrifuge tubes. Two hundred microlitres reaction system contained 0.1 M sodium acetate buffer (pH 5.0), 4 mg substrate, and 25–200 μg protein sample. The mixture was incubated at 50 °C and 1000 rpm in a Thermomixer for 48 h (or the set time), and then treated at 99 °C for 10 min to stop the reaction. Different reaction conditions involving pH, temperature, reaction time, enzyme dosage, and metal ion supplementation were designed in the enzymatic hydrolysis experiments. The amounts of total reducing sugars released from the substrates were determined by DNS method. The monosaccharides  in the hydrolysates were quantified by high-performance liquid chromatography (HPLC)  equipped with a Bio-Rad Aminex HPX-87 H column and a refractive index detector, as reported previously .2O to 1 mL. The hydrolysis reaction was carried out at 50 °C in a Thermomixer for 72 h. The monosaccharides liberated from the substrates were quantified by HPLC analysis. All hydrolysate measurements were performed at least in triplicate, and mean values are presented. Conversion ratios (%) of glucose, xylose, or arabinose on the substrate were calculated as follows:CBR was hydrolysed by the fungal CAZymes alone or in combination with the enzyme cocktail CTec3. In a 2-mL centrifuge tube, 100 mg substrate was mixed with 0.75 mL sodium acetate buffer , 200–600 μg crude enzymes, 20 μL tetracycline hydrochloride solution (4 mg/mL) as an antimicrobial reagent, and dHP.parvum 4-14 was grown on a PDA plate at 37 °C for 7 days, and fungal ascospores were collected using a previously described method [d method . Single-d method . Whole-gd method . The lond method . Genome d method .E-value less than 1e−5, minimal alignment length percentage larger than 40%) against the following databases: GO, KEGG, COG, NR, TCDB, Pfam, cytochrome P450, and Swiss-Prot. The CAZyme-encoding genes in the genome were analysed by searching the fungal proteins against the CAZymes database using dbCAN HMMdb v10.0 (https://bcb.unl.edu/dbCAN2/blast.php) [https://services.healthtech.dtu.dk) and antiSMASH 4.02 [Gene annotation of the fungal genome was carried out using a whole-genome BLAST search (ast.php) . Meanwhiast.php)  in combiASH 4.02 , respectP.parvum 4-14 after FASP digestion, as described previously [g for 15 min. The filter was washed with 100 µL of UA buffer twice and then 100 µL of 25 mM NH4HCO3 solution twice. The protein samples were digested with 4 μg of trypsin  in 40 μL 100 mM NH4HCO3 at 37 °C for 18 h. The digested peptides were collected from the filter by centrifugation at 14,000×g for 15 min. The peptide solution was desalted with a C18 Cartridge , freeze-dried, re-dissolved in 40 μL formic acid (0.1%) solution, and quantified by measuring the absorbance at OD280nm.Label-free quantitative (LFQ) proteomics identification was employed to analyse the secreted proteins of eviously , 74. FifLC–MS/MS analysis was employed to identify the peptide products. The peptides were separated using an EASY-nLC 1200 UHPLC system  equipped with a reverse phase trap column  and a C18-reversed phase analytical column . The columns were balanced with 95% A buffer (0.1% formic acid) and eluted with a linear gradient of B buffer (0.1% formic acid and 84% acetonitrile) at a flow rate of 300 nL/min, which included 0–35% B buffer for 0–50 min, 35–100% B buffer for 50–55 min, and 100% B buffer for 55–60 min. The separated peptides were analysed using a Q-Exactive Mass spectrometer .m/z) was performed in the positive ion mode at a resolution of 70,000 at 200 m/z, automatic gain control target of 3 × 106, and maximum injection time of 50 ms. The data (m/z) of peptides and peptide fragments were acquired as follows: 20 fragment files were collected after a full scan, higher-energy collision dissociation (HCD) fragmentation, 2 m/z of isolation window, 17,500 resolutions at 200 m/z of HCD spectra, 30 eV of normalised collision energy, 60.0 s of dynamic exclusion, and 0.1% of the underfill ratio. To identify and quantify proteins, the raw file was searched against the protein database of P.parvum 4-14 using MaxQuant software (v1.5.3.17) (www.maxquant.org/), with a false discovery rate ≤ 0.01. Three biological replicates were carried out, and the proteins with at least two unique peptides detected were selected for quantification and differential expression studies. Protein abundance was calculated on the basis of the normalised spectral protein intensity (LFQ intensity).MS analysis for 90 min with a survey scan (300–1800 mass-to-charge ratios, Additional file 1: Figure S1. Structural model of corn bran arabinoxylan.Additional file 2: Figure S2. Saccharification of CBAX1and CBAX2by different enzyme blends of P.parvum 4-14. Figure S3. Effect of metal ions on saccharification of CBAX1and CBAX2by E_CBAX1.Additional file 3: Table S1. Monosaccharide liberation from CBAX by the enzyme blend E_CBAX1 of P.parvum at different reaction times. Table S2. Saccharification of CBAX by the enzyme blend E_CBAX1 of P.parvum at different dosages. Table S3. Saccharification of corn bran arabinoxylan 1by the enzyme blend E_CBAX1 of P.parvum and/orcellulase cocktail CTec3. Table S4. Saccharification of corn bran arabinoxylan 2by the enzyme blend E_ CBAX1 of P.parvum and/orcellulase cocktail CTec3. Table S5. Saccharification of CBR by two enzyme blends from P.parvum orcellulase cocktail CTec3 at different dosages. Table S6. Saccharification of CBR by the enzyme blend E_CBR of P.parvum and/orcellulase cocktail CTec3.Additional file 4: Table S7. List of Illumina and single molecule real-timesequencing data of P.parvum 4-14. Table S8. General genome properties of P.parvum and other lignocellulose-degrading fungi. Table S9. The predicted secondary metabolism gene clusters in P.parvum 4-14.Additional file 5: Sequences of predicted proteins in P.parvum.Additional file 6: Table S10. The predicted CAZymes in P.parvum genome.Additional file 7: Table S11. Comparison of the number of putative CAZyme-encoding genes in the genomes of five fungal species.Additional file 8: Table S12. Comparison of the number ofcellulose-degrading enzymes among the three fungal species.Additional file 9: Table S13. Summary of the identified proteins in the secretomes of P.parvum 4-14 grown on corn bran arabinoxylan1 or corn bran residue.Additional file 10:Figure S4. Comparison of the numbers of main lignocellulolytic genesin the genome and the secretomes of P.parvum.