Early childhood caries is the most common infectious disease in childhood, with a high prevalence in developing countries. The assessment of the variables that influence early childhood caries as well as its pathophysiology leads to improved control of this disease. Cystatin S, as one of the salivary proteins, has an essential role in pellicle formation, tooth re-mineralization, and protection. The present study aims to assess salivary cystatin S levels and demographic data in early childhood caries in comparison with caries-free ones using statistical analysis and machine learning methods.A cross-sectional, case–control study was undertaken on 20 cases of early childhood caries and 20 caries-free children as a control. Unstimulated whole saliva samples were collected by suction. Cystatin S concentrations in samples were determined using human cystatin S ELISA kit. The checklist was collected from participants about demographic characteristics, oral health status, and dietary habits by interviewing parents. Regression and receiver operating characteristic (ROC) curve analysis were done to evaluate the potential role of cystatin S salivary level and demographic using statistical analysis and machine learning.The mean value of salivary cystatin S concentration in the early childhood caries group was 191.55 ± 81.90 (ng/ml) and in the caries-free group was 370.06 ± 128.87 (ng/ml). T-test analysis showed a statistically significant difference between early childhood caries and caries-free groups in salivary cystatin S levels (p = 0.032). Investigation of the area under the curve (AUC) and accuracy of the ROC curve revealed that the logistic regression model based on salivary cystatin S levels and birth weight had the most and acceptable potential for discriminating of early childhood caries from caries-free controls. Furthermore, using salivary cystatin S levels enhanced the capability of machine learning methods to differentiate early childhood caries from caries-free controls.Salivary cystatin S levels in caries-free children were higher than the children with early childhood caries. Results of the present study suggest that considering clinical examination, demographic and socioeconomic factors, along with the salivary cystatin S levels, could be usefull for early diagnosis ofearly childhood caries in high-risk children; furthermore, cystatin S is a protective factor against dental caries.The online version contains supplementary material available at 10.1186/s12903-021-02016-x. Dental caries is one of the most common chronic infectious diseases in children, and it is a major health problem in many countries. Early childhood caries (ECC) is defined as the presence of one or more decayed (non-cavitated or cavitated lesions), missing teeth (because of caries), or filled tooth surfaces in any primary tooth in a child under 72 months of age , 2. The Streptococcus mutans. Although these treatments help control the disease, caries recurrence is still common around or after repair, with a recurrence rate of approximately 40% reported during the first year [Dental caries is a multifactorial disease that results from multiple factors, including immature immune systems, individual characteristics of saliva, cariogenic microorganisms, hyposalivation, enamel hypoplasia, enamel defects, cariogenic diet, night breastfeeding, and oral hygiene care in early childhood . Prematurst year , 9.Saliva is a unique body fluid that is easily accessible and contains complex components with great diagnostic value. Saliva collection and storage are simple, non-invasive, and inexpensive. . The salCystatin S has four sites for phosphorylation that bond with hydroxyapatite and has an important role in dental pellicle formation and calcium and phosphate equilibrium and cause enamel remineralization. It also prevents enamel demineralization by attachment to the enamel surface. Cystatin S protects the oral mucosa by its antimicrobial and antiviral effects , 17.Artificial intelligence (AI) is a computer's ability to perform reasoning processes that generally associate with intelligence in human beings. Machine learning is one of the most common forms of artificial intelligence that consists of a set of instructions for processing and finding patterns in large data sets to enable decision-making without human intervention . A largeConsidering the role of cystatin S in caries prevention, this study aims to compare the salivary level of cystatin S in ECC patients and caries-free (CF) children.This study was approved by the Tehran University of Medical Sciences Ethical Committee  and this study was conducted in accordance with the Declaration of Helsinki . After dA cross-sectional case–control study was undertaken on 20 cases of ECC and 20 CF children as a control group. The participants enrolled in this study were selected from children referred to the dental clinic of Tehran University of Medical Sciences  for routine oral examinations. The oral health status of each participant was determined by three professional dentists. The inclusion criteria were children aged between 48 and 72 months with one or more decayed (non-cavitated or cavitated lesions), missing teeth (because of caries), or filled tooth surfaces in any primary tooth. CF controls were matched regarding age and gender. Children with no clinical signs of early caries or white spots were considered to be free of caries and their Decayed, Missing, and Filled Teeth (dmft) index was zero.After oral examination of participants, the researcher completed the checklist by interviewing parents, which collected information about the demographic characteristics of child and parents, dietary intakes , birth wUnstimulated whole saliva samples by the suction method were collected. Before sampling, the children were in a rest position and did not eat anything for 30 min. Saliva sampling was done between 9:00 am to 11:00 am to avoid circadian variations in the case and control group. Complete protease inhibitor cocktail  was added immediately after the completion of saliva collection. Saliva samples were centrifuged at 10,000 × g for 15 min at 4 °C; the supernatant was obtained and stored in − 80 °C.Cystatin S concentrations were determined using human cystatin enzyme-linked immunosorbent assay (ELISA) kit . The samples were thawed at 25 °C and assayed in accordance with the manufacturer’s instructions. The absorbance of samples at 450 nm was measured using Hyperion ELISA microplate reader. The concentrations of cystatin S were determined by spectrometer software based on standard curves.Statistical analysis was performed with SPSS software  and GraphPad Prism 8.2.1 for Windows . In order to assess the relationship between dental caries and age with cystatin S salivary level, T-test, and Levenes' test were used. Mean value and standard deviation of cystatin S levels were reported. Regression analyses were performed for cystatin S level with the backward stepwise method. The contribution of each variable  was expressed by the p-value (p) and standardized coefficients beta (β). The receiver operating characteristic (ROC) curve analysis was done to evaluate the potential role of cystatin S salivary level and combination of cystatin S salivary level with weight of birth for early diagnosis of ECC. All results are presented as mean ± standard deviation (SD), and p ≤ 0.05 was considered statistically significant.We applied multiple supervised machine learning methods to assess the usefulness of cystatin S in addition to demographic and clinical factors, besides nutrition habits in predicting ECC. Supervised learning models are trained using labeled training data, where the model learns about each type of data. After the training phase is completed, the model is evaluated on the test data to predict the type of unlabeled data. In this paper, several supervised learning models such as feed-forward neural networks, XGBoost, Random Forest, and Support vector machine (SVM) are used to generalize our findings.The first model uses the clinical features, patient characteristics, and nutrition habits as the input features for ECC prediction.The second model, in addition to the features used in the first model, utilizes cystatin S levels as the input feature to predict ECC.For implementing a feed-forward neural network  are depicted in Table In the ECC group, 75% of children did not have regular dental visits, but 85% of children had regular dental visits in the CF group. In the ECC group, 95% of children brush daily while 70% of ECC children brush daily. 65% of CF children had daily dental floss; this value was 15% for ECC group. Just 22.5% of children from both groups used regular mouthwash. 75% of CF children brush twice a day, and this value was 30% for ECC group. 70% of children in the case and control group used fluoride toothpaste, and 12.5% used toothpaste without fluoride. There was no difference in smoking by parents in the case and control groups.The frequency of eating sweet snacks  in the cThe mean value of salivary cystatin S concentration in ECC group was 191.55 ± 81.90 (ng/ml) and in CF group was 370.06 ± 128.87 (ng/ml). T-test analysis indicated a statistically significant difference between ECC and CF group in salivary cystatin S levels (p = 0.032). The cut-off value of cystatin S in saliva for differentiation of ECC cases and CF was calculated based on Youden’s index . ConsideThe mean value of salivary cystatin S levels in CF and ECC groups based on the age of children, birth weight, and birth order are shown in Fig. In order to assess the effect of risk factors with and without ECC on salivary cystatin S levels, backward stepwise regression was performed, and two models were concluded by including variables (criterion: Probability of F-to-remove ≥ 0.100) , father education  and mother education  with salivary cystatin S levels regression modeling of cystatin S level in regression model considering risk factors without ECC. Furthermore, logistic regression was used for modeling and early diagnosis of ECC risk based on the cystatin S and weight of birth  for modeling and early diagnosis of ECC risk based on risk factors.Additional file 2. The receiver operating characteristic (ROC) curve analysis by logistic regression modeling using cystatin S & birth weight for discriminating of ECC from CF controls.


Integrins are a family of 24 adhesion receptors which are both widely-expressed and important in many pathophysiological cellular processes, from embryonic development to cancer metastasis. Hence, integrin inhibitors are valuable research tools which may have promising therapeutic uses. Here, we focus on the four collagen-binding integrins α1β1, α2β1, α10β1 and α11β1. TC-I-15 is a small molecule inhibitor of α2β1 that inhibits platelet adhesion to collagen and thrombus deposition, and obtustatin is an α1β1-specific disintegrin that inhibits angiogenesis. Both inhibitors were applied in cellular adhesion studies, using synthetic collagen peptide coatings with selective affinity for the different collagen-binding integrins and testing the adhesion of C2C12 cells transfected with each. Obtustatin was found to be specific for α1β1, as described, whereas TC-I-15 is shown to be non-specific, since it inhibits both α1β1 and α11β1 as well as α2β1. TC-I-15 was 100-fold more potent against α2β1 binding to a lower-affinity collagen peptide, suggestive of a competitive mechanism. These results caution against the use of integrin inhibitors in a therapeutic or research setting without testing for cross-reactivity.  •50 < 30 μM on GFOGER.TC-I-15 inhibits the collagen-binding integrin, α2β1, with IC•50 < 1 μM, on low-affinity GLOGEN.Inhibition seems competitive with high potency, IC•TC-I-15 inhibits α1β1 with similar potency, α11β1 weakly, but not α10β1.•The KTS disintegrin, obtustatin, is specific for α1β1.•Both inhibitors act on integrins in situ, not on isolated α-subunit I-domains. In humans, there are 18 α-subunits and 8 β-subunits that combine to form 24 different integrins . IntegriBoth the α and β subunits have a large extracellular N-terminal ‘head’ domain, a transmembrane domain and a small cytoplasmic C-terminal ‘tail’ . By linkThe four collagen-binding integrins, α1β1, α2β1, α10β1 and α11β1 all adhere to the GFOGER motif found primarily in collagens I and II, and to GLOGEN that is unique to collagen III. α2β1 and α11β1 adhere more strongly to GFOGER while α1β1 and α10β1 adhere more strongly to GLOGEN. Triple-helical peptides (THPs) containing these motifs have been synthesised and are used throughout this study . Integri2+ to which acidic residues, such as glutamate in the GFOGER motif, can bind. Conformational changes in the αI-domain are required to allow it to bind its ligand  to block its ligation by E336 and so preventing the downward movement of helix 7. Consequently, the α subunit MIDAS remains concealed behind the C-helix and the integrin is stabilised in the inactive conformation. In platelets, this results in potent inhibition of platelet adhesion to collagen and the inhibition of subsequent thrombosis in animal models  is consl models . TC-I-15l models . E318 isl models . Thus, iKTSLTSHY . Each condition was performed in triplicate, with at least three independent repeats.Immulon 2HB 96-well plates were coated with 100 μl per well of peptides at 10 μg/ml in 0.01 M acetic acid overnight at 4 °C. After 3 × 200 μl/well PBS washes, plates were blocked with 200 μl/well filtered 3% BSA in PBS at RT for 1 h. Plates were washed, and 20,000 cells/well were added at room temperature (RT) for 1 h in serum-free media with 5 mM MgCl2.32 and various concentrations of inhibitor as stated. After 3 × 200 μl/well washes with washing buffer, anti-GST detection antibody  were added for 1 h. Plates were washed 4× with 200 μl per well of washing buffer and bound protein was quantified using the Pierce™ TMB Substrate Kit. The colorimetric reaction was stopped with an equal volume of 1 M H2SO4 and A450 was read as above. Each condition was performed in triplicate and each experiment was repeated at least three times using different preparations of proteins.Immulon 2HB 96-well plates were coated with 100 μl per well of peptides at 10 μg/ml in 0.01 M acetic acid. After 3 × 200 μl/well washes with washing buffer (1 mg/ml BSA in TBS), plates were blocked with 200 μl per well of filtered 3% BSA in TBS for 1 h at RT. αI-domains were added at 10 μg/ml in washing buffer for 1 h at RT with 5 mM MgCl2.410GPC-amide) is used as a negative control. The GPP repeats adopt triple-helical structure but the sequence is inert, with no binding motifs present.Peptides containing the sequences GFOGER or GLOGEN (single amino acid nomenclature where O is hydroxyproline) were synthesised as C-terminal amides, and assembled as triple-helical homotrimers, as described previously . Peptide2.550 > 0.PRISM 8.2.1 or later , was used for all statistical tests. For single concentration studies one-way ANOVA was used with Sidak's multiple comparisons test to compare means for each condition with the appropriate control. Means ± SD are shown in all data sets. Inhibition curves were analysed using nonlinear regression comparing each data set with either a horizontal line model  or three-parameter dose-response curve (inhibition occurs). Three-parameter curves were constrained with lower value <0.1, reflecting inhibition of adhesion to baseline GPP10 values, and IC33.1p < 0.0001) but not the α1 I-domain adhesion to GLOGEN, confirming its specificity for α2β1. This confirms that, whereas 6F1 directly targets the free αI-domain, obtustatin and TC-I-15 are not able to do so, in agreement with the literature.To confirm that these inhibitors have no effect on isolated αI-domains, GST-tagged αI-domains were tested in static adhesion assays where plates had been coated with either GLOGEN (for the α1 I-domain) or GFOGER (for the α2 I-domain) in the presence or absence of the inhibitors obtustatin, 6F1 and TC-I-15. Previous work in this laboratory established that GFOGER is a strong ligand and GLOGEN a moderate ligand for α2β1 whereas GLOGEN is a strong ligand and GFOGER a moderate ligand for α1β1 . The α2β3.250 = 26.8 μM, R2 = 0.9066, P < 0.0001 and for GLOGEN IC50 = 0.4 μM, R2 = 0.9943, P < 0.001), but it also inhibited α1β1 . At higher concentrations, α11β1 was also inhibited . For TC-I-15-mediated inhibition of α10β1, and all the control conditions, the preferred statistical model was a horizontal line, i.e., no inhibition was seen. Secondly, the degree of inhibition was peptide-dependent for α2β1 and α11β1, but not for α1β1. For α2β1, complete inhibition of adhesion was seen at very low concentrations of TC-I-15 for the lower-affinity peptide, GLOGEN, but a much higher concentration of TC-I-15 was needed to achieve the same effect for adhesion to GFOGER. A similar substrate-dependence was seen with α11β1. In contrast, for α1β1 the potency was the same for both peptides tested and the IC50 values are very similar.Next, to test the effects of these inhibitors on the full-length integrin receptors, C2C12 cells that have been stably transfected to express one of the four integrins were used in static adhesion assays. Plates were coated with GFOGER, GLOGEN or GPP10 (as the negative control) and inhibition dose curves for TC-I-15 and Obtustatin were carried out. 3.350 = 0.45 μM, R2 = 0.8920, P < 0.0001) and GLOGEN . The difference between inhibition on the two peptides was not significant. For the other transfected cells , we considered that TC-I-15 might also inhibit other β1 integrins. As a representative example of such receptors, adhesion of full-length recombinant human α3β1 was tested with TC-I-15, using laminin 511 as the substrate . In thes4Currently, TC-I-15 is available commercially as an inhibitor for α2β1. Our results show that TC-I-15 is not specific, but has a broader specificity including α1β1, α2β1 and, at a much higher concentration, α11β1. In contrast, TC-I-15 has, at best, slight effect on the adhesion of α10β1 to GFOGER or GLOGEN peptides. The inhibition is substrate-dependent for α2β1 and α11β1, in that TC-I-15 inhibits adhesion to the lower-affinity GLOGEN at a much lower concentration than applies to GFOGER. The difference in potency of TC-I-15 inhibition of adhesion to these two ligands suggests a competition, where inhibition of adhesion to the higher-affinity GFOGER requires a higher concentration of TC-I-15 than inhibition of binding to GLOGEN. This suggests a reciprocal relationship between GFOGER binding to the upper surface of the αI-domain and TC-I-15 recognition of its inhibitory site on the βI-domain. In contrast, the lower affinity GLOGEN does not require such a high concentration of TC-I-15 to achieve the same effect. Interestingly, this difference in potency is not seen for α1β1, where both peptides are inhibited by similar concentrations of TC-I-15, presumably reflecting the similar affinity of α1β1 for GLOGEN.Crystal structures provide clear insight into the movement of helix 7 and the C-helix in the α2 I-domain upon binding of GFOGER ), and thThe question of selectivity of both TC-I-15 and obtustatin for the different collagen-binding integrins is more difficult to explain. We assume that both inhibitors must interact with both the βI-domain MIDAS and part of the α-subunit at the α–β interface. There is no crystal structure of an intact integrin that contains an αI-domain, and although this interface has been modelled , no authWe show here, through the use of recombinant αI-domains, that obtustatin does not compete directly with collagen at the αI-domain. Instead, obtustatin may interact with α1β1 in a similar way to other disintegrins, by binding to the βI-domain at or close to the α–β interface. The action of obtustatin could be analogous to that of TC-I-15, by stabilising both the inactive conformation of the βI-domain and blocking the reorganisation of helix 7 and the C-helix. Structural work is needed to clarify how the selectivity and potency of the active KTSL motif is achieved.Given that TC-I-15 interacts primarily with the β1 subunit to stabilise the inactive conformation of α1β1 and α2β1, we considered whether TC-I-15 might also inhibit other β1 integrins that lack an αI-domain. The previous report  had showIn conclusion, it is imperative that integrin inhibitors are thoroughly tested for cross-reactivity before any therapeutic or research use. Obtustatin, in these conditions, was a potent and specific inhibitor for α1β1 adhesion to collagen peptides. The data presented here supports the use of obtustatin for the specific inhibition of α1β1 in cell-based assays, in-vivo assays or potential therapeutic settings. However, because TC-I-15 inhibits α1β1, α2β1 and, at high concentration, α11β1, it must be used with caution in cellular environments where more than one of these integrins is present. TC-I-15 would be a useful tool when inhibition of both α1β1 and α2β1 is required, or where only one of these receptors is present. For example, TC-I-15 been proposed as a potential antithrombotic agent and has been used to block α2β1 on the surface of platelets to inhibit collagen-stimulated platelet aggregation . PlateleRWF is Chief Scientific Officer, CambCol Laboratories, Ely, Cambs, UK.


The ocean moderates the world’s climate through absorption of heat and carbon, but how much carbon the ocean will continue to absorb remains unknown. The North Atlantic Ocean west (Baffin Bay/Labrador Sea) and east (Fram Strait/Greenland Sea) of Greenland features the most intense absorption of anthropogenic carbon globally; the biological carbon pump (BCP) contributes substantially. As Arctic sea-ice melts, the BCP changes, impacting global climate and other critical ocean attributes (e.g. biodiversity). Full understanding requires year-round observations across a range of ice conditions. Here we present such observations: autonomously collected Eulerian continuous 24-month time-series in Fram Strait. We show that, compared to ice-unaffected conditions, sea-ice derived meltwater stratification slows the BCP by 4 months, a shift from an export to a retention system, with measurable impacts on benthic communities. This has implications for ecosystem dynamics in the future warmer Arctic where the seasonal ice zone is expected to expand. The North Atlantic biological pump has the most intense absorption of C globally, but how this will fare in light of climate changes  is poorly understood. Here the authors present a 24-month continuous time series of physical, chemical, and biological observations in the Fram Strait. For example, in a MLD of 20 m, a bloom can start 4–6 weeks earlier than in a MLD of 100 m4. Large interannual differences in the timing of blooms may be challenging for higher trophic levels due to temporal and spatial mismatches with key prey, and could therefore impact trophic interactions considerably5. Also, different pelagic bloom scenarios can result in different proportions of sinking algal aggregates, fecal pellets, and marine snow, and the sea-ice cover plays an important role in such scenarios in the Arctic7. Consequently, the structure, sinking rate, biogeochemical composition, and nutritional quality of particles reaching the benthic community may change with Arctic warming and sea-ice retreat8.Phytoplankton require light to flourish. Stratification keeps algal cells in surface layers. In the Arctic Ocean, this is often controlled by sea ice melt and brine release. The extent of stratification, often simplified as mixed layer depth (MLD), impacts the timing of biological production in nutrient-rich open waters9. Subsurface waters, however, are richer in nutrients10 and upwelling of these nutrients at the ice edge may support patchy phytoplankton blooms, which can account for half of the regional production within a season11. When the ice recedes during spring/summer, ice-edge blooms may form in the warm water in the Nordic and Barents Seas12 and move with the receding ice. In the Greenland Sea, three successive phases of phytoplankton growth were identified: first under ice, then at the ice edge, and finally in the open water with a subsurface chlorophyll a maximum3. North of the Greenland Sea in Fram Strait, primary production can change by 0.3 g C m−2 day−1 between years, with higher values occurring in years when more sea ice is exported southwards from the Arctic Ocean14.Stratification affects both light availability and nutrient supply as essential factors for phytoplankton growth. Typically, the open ocean regions of the Arctic are characterized by a well-stratified surface layer with rather low nutrient concentrations, and limited replenishment, leading to fast depletion upon the onset of the productive season15. The North Atlantic-Arctic gateways are sites of intense climate-induced changes affecting food-webs and carbon export17. Thus, moving from the concept of a single spring bloom to a nuanced and mechanistic understanding of Arctic productivity including the role of sea ice is essential for our understanding of the biological carbon pump (BCP) at high latitudes.The understanding of the ocean’s role in the global carbon balance and in response to climate change is an urgent scientific task18 provides continuous in-situ data that can help bridge key gaps in ecosystem research with regard to temporal dynamics. Two mooring clusters, equipped throughout the water column with a comprehensive suite of physical and biogeochemical sensors as well as autonomous sampling systems, are located in central (mooring cluster “HG-IV”) and eastern (mooring cluster “F4”) Fram Strait 20 and subducts below the colder and fresher Polar Water (PW) exiting the Central Arctic Ocean. This subduction stirs and mixes AW and PW on small horizontal scales21. The southward flowing PW carries sea ice from the Transpolar Drift and forms the East Greenland Current  Ocean Observing System in Fram StraitHere we investigate the effect of varying sea ice export from the Arctic Ocean on local biogeochemical processes and the biological carbon pump. We hypothesize that high ice-export results in strong meltwater stratification leading to the formation of a thin productive layer near the surface. By contrast, low sea ice export results in a classical (deeper) mixed layer which features a bloom of pelagic diatoms that is rapidly exported to the seafloor. Building on work that was partially able to achieve this, we tested the hypothesis that sea ice export is a key regulating factor not only for the biological carbon pump but also for the plankton community composition and retention efficiency.24. As a result, there are substantial interannual differences in ice export through Fram Strait. Overall, Arctic warming has increased Transpolar Drift velocity25, which in turn has led to an intensified sea ice area export out of Fram Strait in winter , but temporally variable haline  stratification at mooring HG-IV as estimated from our time series observations between 30 m  and 55 m : Strong salinity stratification due to meltwater  and relatively weak stratification with a significant mixed layer .The mooring measurements in our high-resolution time series must be understood within this changing oceanographic context, particularly in the vertical dimension. As we demonstrate below 31. The chlorophyll increase coincided with shading by the increased turbidity from growing phytoplankton reducing PAR levels at 30 m to values equivalent to those at the end of the preceding Polar night  suggests this depth is at or below the base of the productive mixed layer. We therefore estimate that the ML is on the order of 50 m. Integrating nitrate (~12 μmol l−1) over this depth indicates the standing stock available at the onset of the productive season is 0.6 mol m−2 of nitrate   early in the season as measured in multiple depths  was dominated by pelagic diatoms (ra) Fig. . Associara) Fig. . It appeths Fig. . Chloropoor Fig. . In addioor Fig. .−2 of carbon  of the year 2017 was fundamentally different from the bloom phenology during the ML regime in 2018. The reduction of PAR at 30 m depth started later (mid May) and lasted only for about half a month Fig. , but wasa Fig.  and incra Fig. .−1  diatoms 39. Since the water sampler was moored below the productive layer, we cannot quantify relative species abundance in the productive layer  was dominated by oms Fig. . Phaeocyyer Fig. . Calanusted Fig. , suggestted Fig. , i.e., 246. Emiliania huxleyi accounted for <1% of sequences at 30 m (not shown), and pteropod aragonite typically dissolves before reaching 2000 m depth, suggesting that these factors did not significantly contribute to vertical flux. Melosira arctica, which when white in color is aged and nutrient poor47, contributed to the white material as seen under the microscope from the lander trap. However, irrespective of what exactly constituted the pale material, its lack of color suggests that labile photosynthetic pigments had been degraded, and the material itself was of highly degraded nature and thus low nutritional quality. This interpretation is supported by the fact that this export event did not elicit a comparable benthic response  in less than a month by meltwater effects. Later in the season, the shipboard observations showed stratification to within 5 m of the surface (the mixed layer may have been even thinner than 5 m) with a likely meltwater contribution of up to 1/6 by volume. Temperature-driven stratification can typically not achieve such density differences and can therefore be more easily broken down intermittently by wind induced mixing49. The observed surface forcing by winds in 2017–2018 differed somewhat, but had no effect on the evolution of the mixed layer  and shorter, more intense pulses of export carrying significant quantities of algal detritus to the seafloor, which supported higher megafauna densities. An additional mechanism that likely contributed to retaining the organic matter in the surface ocean in the MW regime is that sinking rates of aggregates are slowed by strong density gradients50. For the same density gradient, this effect is much stronger in a salinity stratified case because of the relatively slower diffusion of salt into aggregates51. Our data suggest that it depends on the ice export through Fram Strait whether the hydrographic conditions in the Fram Strait marginal ice zone region follow the MW regime or the ML regime. The exact timing of the onset of the bloom in turn is determined by when the local heat flux turns positive such that deep winter mixing stops and stratification sets in52. According to ERA-Interim, this happened around May 8th with a standard deviation of 8 days between 2010 and 2018.We identified two types of surface stratification regimes that resulted in different bloom dynamics as summarized in Fig. Our conclusions are based on a temporally highly resolved continuous dataset, which together engender confidence in our description of the ecosystem phenology  and its drivers. Typical ship-based surveys often miss key transition moments in the system, such as the onset of the spring bloom or the summer/fall bloom in polar regions. Furthermore, the duration over which processes take place can be more fully assessed by autonomous observations that include in-situ estimates of rates and stoichiometries.53, but this does not hold more generally, in open waters where no ice is available to be melted or over the duration of the productive season40. The MW regime we have investigated here is characterized by the meltwater left behind by sea ice that has melted rather than by processes associated with ongoing sea ice melt, i.e., sea ice may no longer be present as it has either fully melted or has been advected out of the area, but the MW regime persists as long as the euphotic zone remains (strongly) salinity stratified.Between early March and late August , more than twice as much particulate organic carbon (POC) reached the seafloor in the ML regime than in the MW regime Table . We note56 and the nature of the physical setting has a measurable impact on pelagic-benthic coupling.Our data implies that the meltwater-stratified conditions  favored the longer-term growth constrained within thin layers over multiple months, while the ice unaffected situation  favored a short intense bloom that sank while still rich in chlorophyll, providing fresh labile organic carbon to the benthic ecosystem. In other words, the MW regime might be considered a retention system while the ML regime is more similar to an export system57. In those scenarios, salinity stratification is reduced as sea ice may be increasingly absent, even in winter; alternatively, the sea ice and its associated meltwater could be advected out of the area such that the system is no longer directly impacted by ice. Conversely, the MW regime (2017) appears to be representative of blooms in low (but non-zero) ice concentration regions of the parts of the central Arctic Ocean that are covered by sea ice in winter. The sea ice melts prior to complete consumption of the nutrients in the productive layer in spring and produces very strong salinity stratification that cannot be overcome by wind mixing (except possibly for major storms that are not common in the area in summer).The differences in bloom progression between the two years of observation point to large effects of ice advection  on the local salinity stratification, ultimately impacting the ecosystem as a whole. We note that the bloom progression in the ML regime (2018) may be representative of future scenarios in the eastern Arctic Ocean subject to projected Atlantification2 larger in spring/summer 2017 than its typical extent  or decrease (like the ML regime) of the meltwater stratification.Climate change will substantially reduce the area covered by sea ice in summer, but in many parts of the Arctic the winter sea ice extent will probably be reduced much less. The seasonal ice zone, in which ice melts in spring and provides strong salinity stratification, could therefore actually become larger over time, increasing the spatial extent of the region experiencing dynamics similar to the MW regime described here. Furthermore, as ice becomes more mobile in the central Arctic, ice area export will likely increase further. However, the observed thinning of sea ice20. This AW then remains isolated from the atmosphere for a long time and partially crosses Denmark Strait to contribute to the formation of North Atlantic Deep Water59. Owing to their much larger salinity relative to the surface waters of the MW regime, the surface waters of the ML regime likely participate in this part of the physical carbon pump. This contribution to carbon sequestration needs to be considered in addition to the vertical carbon removal from the atmosphere through the biological carbon pump discussed above.Part of the Atlantic Water present near the surface in eastern Fram Strait subducts below Polar Water in the recirculation in central Fram StraitMelosira arctica) likely are rare in the region60 and therefore may only subsidize part of the annual benthic production. While the productivity of larger benthic organisms likely depends primarily on the integrated flux from pelagic blooms throughout the growth season, the quality of less degraded fast-sinking ice algal detritus may also play a role as has been shown in shallow Arctic areas61. The benthic community could benefit from an increased frequency of ML regimes, as long as diatoms are winners of the system, and provide intense, nutrient-rich pelagic export events62. Where diatoms are replaced by other phytoplankton groups which are not rapidly sinking, the higher productivity may not result in more export flux.We note that sudden massive algal falls 65 and downloaded from https://seaice.uni-bremen.de/sea-ice-concentration-amsr-eamsr2/66. At each grid point the sum of days during all April/May/June of 2013–2018 when the sea ice concentration at the grid point was >20% was divided by the total number of days with data in those months to obtain the percentage of days with ice concentration >20%  were downloaded from 70 data at the surface on a 0.25° latitude by 0.25° longitude grid at 12 hourly resolution was downloaded from https://apps.ecmwf.int/datasets/data/interim-full-daily/levtype=sfc/. Incoming shortwave radiation (ssr) and outgoing longwave radiation (str), sensible heat flux (sshf), and latent heat flux (slhf) were extracted and averaged to daily values.ERA-Interim reanalysis71. FESOM is a sea ice-ocean model that solves the hydrostatic primitive equations for the ocean and comprises a finite element sea ice component. It uses triangular surface meshes for spatial discretization, allowing for a refined mesh in regions of interest, while keeping a coarser mesh elsewhere. In the model configuration used here, a mesh resolution of nominally 1° was applied in the global oceans. The mesh was refined to 25 km north of 40°N, and to 4.5 km in the Nordic Seas and Arctic Ocean. In the wider Fram Strait (20°W-20°E/76°N-82°30′N), the mesh was further refined to 1 km. In this region, the simulation can be considered as eddy-resolving, as the local internal Rossby radius of deformation is about 2–6 km73. In the vertical, the model used 47 z-levels with a resolution of 10 m in the upper 100 m, and coarser resolution with depth (with a resolution of ~100 m at 800 m depth). For bottom topography, the RTopo-2 data set was used74. The model simulation covers the period 2010–2018 and has daily model output. It was forced with atmospheric reanalysis data from Era-Interim70, and was initialized with model fields from the simulation described in ref. 75. River runoff (except for Greenland) was taken from the JRA-55 data set76, and Greenland ice-sheet runoff was taken from ref. 77. Tides were not taken into account in this simulation. Here we studied the model data of 2016 to 2018 in Fram Strait for comparison with our observations.In this study, we used model data from the Finite-Element Sea ice-Ocean Model (FESOM) version 1.478 1-dimensional mixed layer model simulates the response of the ocean to surface fluxes. It ignores horizontal gradients and horizontal advection. This allows to judge whether certain surface flux conditions can on their own explain observed conditions. We ran the PWP model (as implemented for Matlab by http://www.po.gso.uri.edu/rafos/research/pwp/) with four different scenarios  of RRS James Clark Ross. The data were processed according to standard routine79. Additionally, we use underway CTD data from an OceanScience underway CTD collected during PS107 in 2017 (10.1594/PANGAEA.886146) and processed according to ref. 21.Shipboard CTD casts of a standard dual sensor Seabird 911+ CTD-rosette were occupied in spatial and temporal vicinity to the moored observations Tab.  on three80.The mooring data discussed in this paper is from two mooring clusters in the central and eastern Fram Strait (named “HG-IV” at ~79°N 4°20’E and “F4” at ~79°N 7°E) where moorings were located as close to each other as possible  in order to enable more measurements than could be fit physically onto a single mooring. Tab. 82. In order to make as few assumptions as possible, we used the following approach: we could have determined the conversion factors from the instance when the ship was there with the CTD-rosette, but these conversion factors might not be appropriate for the majority of the time series. Hence, simply using the manufacturers’ calibrations, as we do here, introduces fewer uncertainties. Where we have different estimates of the same parameter, we present them together and demonstrate that they agree qualitatively and also mostly quantitatively  change over the seasons, depths, and regionsAt some locations, the target variables were not measured the whole time or the measurements failed, hence we present what is available. The vertical location of the instruments Fig.  and S1c 83; the processed data is also available at ref. 80.The physical sensors  were pre-cruise manufacturer calibrated and processed similar to ref. σ) between the uppermost (~30 m) temperature/salinity recorder and the underlying temperature/salinity recorders is calculated. The 0.5th percentile of each Δσ time series is added to the Δσ time series for the different deployments. This fixes slight offsets in the temperature and/or conductivity calibrations which result in too negative or too positive density differences. The minimum estimate of the mixed layer depth at hourly resolution is then determined as the depth of the deepest instrument where Δσ < 0.05 kg m−3. If Δσ > 0.05 kg m−3 for all depths at a time step, then the minimum mixed layer depth can only be determined as 0 for that time step. Daily values of the MLD were defined as the depth at which three hourly realizations of MLD were shallower within a 24 h time span and at which the remaining 21 MLD realizations were deeper. This biases the daily MLD estimate towards situations where phytoplankton is kept in the surface ocean rather than also being mixed down for some amount of time.Since there are no autonomous vertically profiling measurements available, we can only determine the minimum value of the mixed layer depth. At each hourly time step, the potential density difference  and salinity (N2S) are estimated as T/ΔS are the temperature/salinity differences and α/β are the thermal expansion/haline contraction coefficients estimated from the average temperature/salinity at the two measurement depths.Based on the temperature and salinity time series observed at ~30 m and ~55 m, we estimate the buoyancy frequency as http://www.cmar.csiro.au/datacentre/ext_docs/seawater.htm) minus the measured oxygen concentration.Oxygen concentration from the microcats was calculated using the pre-cruise manufacturer calibrations. AOU was calculated as the atmospherically equilibrated oxygen concentration  was calculated from the sunrise equation as implemented for Matlab by −1.32 μmol m−2 s−1. Hourly values are linearly averaged to daily values  to phytoplankton being moved around in the clear water mixed layer of depth MLD was calculated as the depth averaged vertical integral of the clear water extinguished PAR at the surface (PARsurf from the shortwave radiation of ERA-Interim): The WetLabs Eco PAR measured PAR for 5 (in 2016–2017) or 10 (in 2017–2018) individual measurements 1 s apart from each other before it slept for 1 h before repeating the measurement cycle. These 5 or 10 individual measurements are averaged linearly to obtain hourly values at ~30 m depth Fig.  blue. Vaues Fig.  black. Tues Fig.  yellow. zdz Fig.  red.a concentration (in μg l−1) follows a manufacturer determined conversion determined for a mono-culture of phytoplankton , which typically overestimates the chlorophyll concentration. Hence, we applied the community-established calibration bias of 2 for the WetLabs ECO-series fluorometer to these in situ fluorometric chlorophyll values81. This conversion factor may be different in ocean waters of Fram Strait, but it still gives reasonable agreement with independent estimates.The WetLabs ECO Triplet measures fluorescence at a “chlorophyll wavelength” and at a “CDOM wavelength” as well as optical scattering at 700 nm. The conversion from fluorescence to chlorophyll −1 sr−1 are indicative of strong optical backscattering not due to small particles in the water column, but rather to larger potentially aggregated particles. The times of strong backscattering are marked individually  were then measured, with the output being monitored live (expected to be within ±2 μmol l−1 of each concentration). A measuring time of 20 s yields stable results and was thus applied during the deployments with an interval of 6 h. Upon recovery, SUNA data were processed using the SeaBird UCI software package version 1.2.1. Here, temperature and salinity data were used to remove the spectrum of bromide and compensate for temperature dependent absorption using an algorithm developed by ref. 86. This step yields the spectrum of nitrate only, at a precision of ±0.3 μmol l−1. The sensor is characterized by a drift of 0.3 μmol l−1 per hour lamp time. Given the deployment settings, a total operational time of about 8 h was accumulated. Therefore, a linear drift correction of 2.4 μmol l−1 (365 days)−1 was applied. Up to this point, however, accuracy remains at 2 μmol l−1 as per manufacturer specifications. Therefore, an offset correction is then applied based on the in situ concentrations observed at the beginning of the deployment as well as with the RAS (see below) where available, with outliers excluded.Prior to deployment , the reference spectrum of the sensors were updated as per manufacturer specifications. We first let the sensors cool down for 24 h at 0 °C in a temperature controlled laboratory. Next, the reference spectrum update was achieved by measuring Milli-Q water . To verify if this update was successful, solutions with three different nitrate concentrations  approximately every other week. Samples within the RAS were collected in sterile plastic bags and fixed with 700 μl of 50% mercuric chloride solution. Upon recovery, two samples from a given sampling date were combined to yield a volume of 1 l, required for bacterial and phytoplankton genetic analyses (see below), and a 50-ml aliquot destined for the measurement of dissolved inorganic nutrients. Aliquots for nutrient analysis were collected in PE bottles, which were then stored frozen (−20 °C) until analysis on land. Analyses for inorganic nutrients were carried out using a QuAAtro Seal Analytical segmented continuous flow autoanalyser following standard colorimetric techniques. The accuracy of the analysis was evaluated through the measurement of KANSO LTD Japan Certified Reference Materials and corrections were applied accordingly. Finally, we evaluated pressure, temperature, and salinity data from the CTD (SBE37-SMP-ODO) attached to the RAS to determine whether the two samples taken one hour apart on a given date drew water from the same depth and with consistent properties.2 sensors measure and yield pCO2 in μatm. For the pH sensor, raw absorption data were converted to pH  in combination with temperature and salinity (SBE37-SMP-ODO) using the quality control tool (QC_pH) supplied by the manufacturer.The calibration of SAMI pH and SAMI CO2 sensors was carried out by the manufacturer, approximately 2 months prior to deployment. The calibration certificates specify accuracy and precision of ±0.003/±0.001 pH units and ±3/<1 μatm, respectively. pCO2 data, values from the HG-IV mooring in 2017–2018 were deemed to be biased high by approximately 130 μatm (with a step jump at the turn-around of the moorings), therefore a constant value of this magnitude was subtracted from that record. The pH sensors ran out of battery towards the end of the deployments, resulting in interrupted records. At HG-IV, some erratic data before the sensors stopped recording were excluded for the first deployment after 16-Feb-2017 and for the second deployment after 02-Aug-2018. At F4 in 2017–2018 pH values below 8 were excluded.Upon assessment of pCO2 is reached. In turn, DIC is calculated from pCO2 and alkalinity87 as well as measured temperature, measured salinity, phosphate concentration (0.5 μmol l−1), and silicate concentration (5 μmol l−1). Alkalinity is taken from the relationship Alk = 736 + 45.2 * S in ref. 88.Carbon takeup is estimated from the change in dissolved inorganic carbon (DIC) between the beginning of the bloom and the time when the minimum pCO89 which we briefly summarize here: the same water samples as for the inorganic nutrients (see above) were used, in which mercuric chloride resulted in fixation of microbes for long-term preservation90. After recovery, the ~1 l per sampling event was immediately filtered through 0.22 µm Sterivex filter cartridges . Filters were immediately frozen at −20 °C until DNA extraction in the home laboratory.The methodology followed−1. Bacterial 16 S and eukaryotic 18 S rRNA gene fragments were amplified using primers 515F–926 R91 and 528iF–964iR92, respectively, according to the 16 S Metagenomic Sequencing Library Preparation protocol . Amplicon gene libraries were sequenced using Illumina MiSeq instruments at CeBiTec  or AWI (eukaryotes). After primer removal using cutadapt93 reads were classified into amplicon sequence variants (ASVs) using DADA294.DNA was extracted using the DNeasy PowerWater kit  according to the manufacturer’s instructions and quantified using a Quantus fluorometer . Obtained DNA quantities ranged between 0.01 and 11 ng (µl)89. Bacterial and eukaryotic reads were taxonomically classified using the Silva v138 and PR2 v4.12 databases, respectively.After singleton removal, we obtained a mean of 60,000 bacterial and 119,000 eukaryotic reads per sample that sufficiently covered community composition95, they were converted to MVBS. We used beam-averaged data because the four beams together gave a better signal-to-noise ratio than individual beams. First, the noise level of all four ADCP beams was determined from the minimum values of RSSI  counts obtained in the remotest depth cell, when the sea surface was outside the ADCP range. Sound velocity c and sound absorption coefficient a were considered variable with depth and time and calculated according to the UNESCO formulas from an interpolation in time of 2 CTD profiles collected at the beginning and the end of the deployment. The mean at each depth for the 20 single pings comprising an hourly burst was calculated.RDI Workhorse Longranger ADCPs were deployed, using a four-beam, convex configuration with a beam angle of 20° and frequencies of 76.8 kHz. The number of bins was set to 70 with a bin length of 8 m. The sampling interval was set to 20 pings per ensemble with a ping rate of about 20 pings every 60 min. The instruments were moored at a nominal depth of ~400 m in upward-looking mode and measured horizontal and vertical currents and acoustic backscatter intensity. Instrument heading, pitch and roll and temperature data were also collected. The echo intensities were given in an automatic gain control count scale of 0 to 255. FollowingAn ASL Acoustic Zooplankton Fish Profiler (AZFP) was moored at F5  with the transducer faces pointing upward in ~150 m depth and operated at four different frequencies . The sampling interval was set to 30 s with a pulse duration of 0.5 ms (38 kHz) and 0.17 ms (125 and 200 kHz), respectively. Pitch and roll were measured with each ping. Data from the 455 kHz transducer were omitted from this analysis. AZFP data were post-processed and integrated with Echoview software version 11.0.239 . Background noise was removed through time-varied thresholds for each transducer, and after removing noise and unwanted signals originating from e.g., other mooring devices that temporally became visible as backscatter in the echograms, the MVBS was integrated and exported for 24-hr bins.96.For both ADCP and AZFP data the 50–100 m vertical average was calculated and for the AZFP also the 15–100 m and 30–100 m vertical averages. The median for each mooring deployment of the daily mean values of the vertical MVBS means was calculated. This median was subtracted from the MVBS to obtain the normalized MVBS, which corrects for possible hardware differences between the different deploymentsNote that no AZFPs existed at moorings HG-IV and F4 and the ADCPs did not return data shallower than 50 m. Therefore, we use the comparison in Fig. 2 collection area and the opening duration. We assume that this sediment volume flux is approximately proportional to total particulate matter  flux and use it only to infer qualitative differences and the timing of events.Sediment traps were located 200 m and 1200 m below the sea surface at mooring HG-IV and at 200 m at mooring F4. The collector cup opening times ranged from 9 to 59 days depending on the season (lower resolution in winter). The cups had an interior diameter of 4 cm and the height of the sedimented layer on the bottom was measured from photos of the cups. From these the sediment volume was calculated and it was normalized by the 0.5 m2 collection area and the cup opening duration. As the sediment trap was deployed 2.5 m above the bottom, it also collected resuspended material in addition to settling material.Aliquots of the sedimented material collected at 2.5 m above the seafloor in sediment traps on the bottom lander at HG-IV were sieved through 500-µm mesh size to remove larger zooplankton swimmers or benthic organisms, then filtered on pre-combusted Whatman GF/F glass fiber filters, acidified with 0.1 N HCl, and dried at 60 °C. POC concentrations were determined with a CaloErba CN-analyzer. These were then normalized by the split factor as well as to the 0.25 m97 was deployed at HG-IV for one year and moved 15 m along the seafloor every 7 days. Upon arriving at the new location, it measured oxygen concentration profiles through the top 15 cm of the sediment. From the shape of the oxygen profile, the benthic oxygen consumption, i.e., the oxygen flux from the water column into the sediment was calculated. Assuming a Respiratory Quotient of 1.0  oxygen consumption rates were converted to POC fluxes reaching the benthos.Benthic carbon mineralization was estimated from sediment oxygen consumption rates. The benthic crawler called TRAMPERAn underwater camera  fitted to a benthic lander at HG-IV took 5-second video sequences twice a day for the 2017–2018 deployment year. Frame grabs were extracted and divided into 100 boxes referring to equal sized areas of the seafloor. At each time, the number of boxes covered by bare seafloor, by accumulating small white material, and green material was calculated. The white material, though very fine in size, accumulated over a larger area of seafloor than the much more massive green material identified as algal detritus. This is presumably related to hydrodynamics associated with the microtopography of the seafloor.Lycodes frigidus) and visible epibenthic megafauna including shrimps (Bythocaris spp), isopods , holothurians , and gastropods (Mohnia spp.) observed in each frame grab were counted. Additionally, at the very bottom edge of the screen, a purple sea anemone and branches of the sponge Cladorhiza gelida were present, but not included in the data.All eelpout fish (Supplementary InformationPeer Review FileDescription of Additional Supplementary FilesSupplementary Data 1


The purpose of this research is to detect the antibacterial properties of lactic acid bacteria (LAB) against pathogenic bacteria.Lactobacillus spp. Testing of the antibacterial activity of LAB was conducted using filtrate and nonfiltrate forms. The lactic acid bacterial isolates were confirmed to be identified through Gram staining, cell shape, catalase testing, and motility testing.Isolation and determination of Bacillus cereus were included in the very strong category. The results of the analysis of the LAB inhibitory zone using filtrate and nonfiltrate forms and the agar well method against Staphylococcus aureus bacteria were classified into the very strong category. The results of the LAB inhibitory zone analysis using filtrate and nonfiltrate forms with the well method against Escherichia coli bacteria are included in the very strong category, whereas the results from the LAB inhibitory zone analysis using the filtrate and nonfiltrate forms with the agar diffusion method (disks) are included in the strong category.The results of the analysis of the LAB inhibition zone using filtrate and nonfiltrate forms against the bacteria B. cereus, S. aureus, and E. coli.Based on the results, LAB isolated from Sumba mare’s milk displayed antibacterial activity in the strong and very strong categories against pathogenic bacteria such as  Lactic acid bacteria (LAB) have characteristics of Gram-positive bacteria, are nonsporulating, and are tolerant of anaerobes. LAB are fermentative bacteria that produce antimicrobial compounds such as lactic acid ,2. LAB aSeveral applied studies have been carried out to determine the function of various LAB properties, including antibacterial activity with a broad spectrum ,8–10. ThBased on its habitat, LAB can isolate natural ingredients such as plants and fruits , wine 11, and mi, S. aureus,and E. coli.This research was conducted from August to September 2018 at the Animal Disease and Veterinary Public Health, Faculty of Veterinary Medicine, Universitas Nusa Cendana. The stages of this study include extracting isolates of LAB from Sumba mare’s milk and identifying the antimicrobial activity of LAB extracted from the mare’s milk against pathogenic bacteria B. cereus, S. aureus, and E. coli, antibiotics, oil immersion, filter paper, cotton wool, masks, gloves, and label paper.The research materials used were LAB isolated from Sumba mare’s milk, De Man, Rogosa, and Sharpe (MRS) agar, MRS broth, Mueller Hinton agar media, sulfide indole motility media, aquades, violet crystal solution, iodine solution, 96% alcohol, safranin, physiological NaCl, 70% alcohol, hydrogen peroxide, chloramphenicol antibiotic disks, blank disks, McFarland standards, bacterial cultures of B. aureusThe main focus of this study was to measure the inhibitory diameter of LAB on the growth of bacteria that cause important pathogens . Isolation and determination of Lactobacillus spp. were carried out in accordance with LVS ISO 15214: 1998 guidelines using MRS media . Media preparation procedures are guided by the LVS CEN ISO/TS 111331:2009 guide. Similarly, the sample dilution technique is carried out according to ISO 6887-5:2010 using a salt–peptone solution. The diameter of the inhibition zone was measured after incubation of LAB for 72 h at 37°C on MRS agar media ,23. ConfAccording to Pro-Lab Diagnostics, the detection of antimicrobial activity against pathogenic bacteria was conducted. A volume of 1 ml of active LAB suspension of Sumba mare’s milk from MRS broth was taken using a micropipette and then poured into a test tube. The test tube containing LAB was centrifuged at 3,000 rpm for 30 min to separate the liquid from the filtrate. Next, the separated solution was filtered using a 0.45-µm millipore membrane. The testing of the effectiveness of the filtrate of LAB against pathogenic bacteria was based on several research studies ,22. The The bacteria cultures were observed at 48 h, with the following inhibitory zone results; 29.63 mm in pathogenic bacteria B. cereus, 32.03 mm in pathogenic bacteria S. aureus, and 31.23 mm in pathogenic bacteria E. coli. Inhibitory zones for antibiotics that formed within 48 h were included in the sensitive category. This is consistent with accepted standards for the diameter of a bacterial inhibitory zone, which state that chloramphenicol is resistant if the diameter of the bacterial growth inhibition produced is smaller than 20 mm, or sensitive if the resulting inhibitory diameter is greater than 21 mm ,28.The results of the antibacterial activity test for LAB bacteria against B. cereus using filtrate form and the agar diffusion method were observed at 48 h, with an average inhibition zone of 20.5 mm, while nonfiltrate forms did not form inhibitory zones. Furthermore, the testing of the antibacterial activity of LAB in filtrate form was carried out using wells that were observed at 48 h with an average inhibition zone of 24.7 mm, while the nonfiltrate form had an inhibition zone of 20.4 mm. The results of the inhibition zone associated with LAB using filtrate and nonfiltrate forms against the bacteria B. cereus are included in the very strong category .The antibacterial activity of LAB against S. aureus bacteria in the filtrate form using the agar diffusion method (disks) was observed at 48 h with an average inhibition zone of 24.9 mm, whereas the nonfiltrate test using agar diffusion (disks) had an average inhibition zone of 13.76 mm. The testing of the antibacterial activity of LAB in the filtrate form was carried out using a well and was observed at 48 h with an average inhibition zone of 31.10 mm, while the nonfiltrate had an average inhibition zone of 21.85 mm. Given these results, the LAB inhibitory zone for filtrate and nonfiltrate forms with the agar well method against S. aureus bacteria is included in the very strong category, whereas the nonfiltrate LAB inhibitory zone using the agar diffusion method (disks) is included in the strong category.The results of the antibacterial activity of LAB against E. coli suspension using the agar diffusion method (disks) were observed at 48 h with an average inhibition zone of 13.3 mm, while nonfiltrate was 11.65 mm. Testing the antibacterial activity of LAB in Sumba mare’s milk isolates using well agar was observed at 48 h with an average inhibition zone of 22.3 mm, while nonfiltrate was 22.1 mm. Based on the LAB inhibitory zone results obtained by the filtrate and nonfiltrate forms, using the well method against E. coli bacteria is included in the very strong category, whereas the LAB inhibitory zone obtained by the filtrate and nonfiltrate forms using agar diffusion method (disks) is included in the strong category.in vitro against pathogenic bacteria . After iThe results from this research show that the inhibition zone associated with LAB using filtrate and nonfiltrate forms against B. cereus, S. aureus, and E. coli is included in the very strong category. Several previous studies mentioned that LAB had an antimicrobial ability because it produced a variety of antimicrobial compounds . Some imAs one of the metabolites of the LAB process, organic acids have a level of antimicrobial activity within a broader spectrum than other compounds. This broad-spectrum is known to be a result of a synergistic collaboration between lactic acid and acetic acid that produces a bactericidal for pathogenic bacteria such as Salmonella typhimurium ,9,12. Mossp. casei and L. casei ssp. Pseudoplantarum [In addition, LAB produces 5-carboxylic acid pyrrolidone. This compound is known to have the ability to kill bacteria such as B. subtilis and Enterobacter cloacae. However, this compound is only produced by Lactobacillus casei lantarum . Diacetylantarum ,35. Othe, L. brevis, L. buchneri, L. collinoides,and L. corniformis [One of the compounds produced by LAB is bacteriocin. Bacteriocin is a protein compound excreted by bacteria that inhibits bacterial growth by destroying the bacterial cells, causing development disruption . Anotherniformis . Reuteriniformis , Listeriniformis , and yeaniformis .The antibacterial properties of LAB promote the frequent use of these natural ingredients as biopreservation for food ,41–43. TB. cereus, S. aureus, and E. coli.Based on the test results, LAB isolates taken from Sumba mare’s milk contain compounds that are in the strong and very strong categories of antimicrobial activity against


The aim of this study was to investigate the applicable safety and biomechanical stability of iliosacral triangular osteosynthesis (ITO) through 3D modeling and finite element (FE) analysis.Pelvic CT imaging data from 100 cases were imported into Mimics software for the construction of 3D pelvic models. The S2-alar-iliac (S2AI) screws and S2 sacroiliac screws were placed in the S2 segment with optimal distribution and their compatibility rate on the S2 safe channel was observed and analyzed. In the FE model, the posterior pelvic ring was fixed with two transsacral screws (TTS), triangular osteosynthesis (TO) and ITO, respectively. Four different loading methods were implemented in sequence to simulate the force in standing, flexion, right bending, and left twisting, respectively. The relative displacement and change in relative displacement of the three fixing methods were recorded and analyzed.The theoretical compatibility rate of S2AI screw and S2 sacroiliac screw in S2 segment was 94%, of which 100% were in males and 88% in females. In the FE model, in terms of overall relative displacement, TTS group showed the smallest relative displacement, the ITO group showed the second smallest, and the TO group the largest relative displacement. The change in relative displacement of the TTS group displayed the smaller fluctuations in motion. The change in relative displacement of the TO group under right bending and left twisting displayed larger fluctuations, while the ITO group under flexion displayed larger fluctuations.The simultaneous placement of S2AI screw and S2 sacroiliac screw in the S2 segment is theoretically safe. Although the biomechanical stability of ITO is slightly lower than TTS, it is better than TO, and can be used as a new method for the treatment of posterior pelvic ring injuries.The online version contains supplementary material available at 10.1186/s12891-021-04856-8. Vertical shear pelvic fracture is an unstable injury caused by the complete rupture of the anterior and posterior pelvic ring . Due to Schildhauer et al.  first prTranssacral screw fixation has been considered as an alternative to sacroiliac screw fixation, and has been effectively used in remedying the failure of sacroiliac screw fixation , 15. BioRecently, Lee et al.  proposedWe propose the combination of S2AI-S1 fixation with an S2 sacroiliac screw  for the treatment of sacral fractures. However, it is not yet clear whether simultaneous placement of two screws  in the S2 segment is feasible and the biomechanical properties of ITO are also unclear.The aim of this study was to investigate the applicable safety and biomechanical stability of ITO through 3D modeling and finite element (FE) analysis. This study was approved by the Ethics Committee of the Nanfang Hospital of the Southern Medical University (NFEC-2019-256). Informed consent was obtained from all participants included in the study.The pelvic CT data of 100 patients  from the Nanfang Hospital were saved in DICOM format and then were imported into Mimics 21.0  to reconstruct pelvis model. The transparency of the sacrum and ilium were adjusted in the software to show the S2 safety channel in the lateral view. A tangent line along the upper wall of the S2 safety channel and a line parallel to the upper tangent line through the lowest point of the S2 safety channel were drawn. In this study, the vertical distance between the two parallel lines was defined as the upper and lower width of the S2 safety channel.According to the literature, the S2AI screw  was placed 1-mm inferior and 1-mm lateral to the S1 dorsal foramen and the trajectory for the S2AI screw was aimed at the anterior inferior iliac spine . Under tP<0.05 indicated statistical significance.Statistical analyses were performed using SPSS 20.0 software  and the Student’s t test was used to compare continuous variables. Data are shown as the mean ± standard deviation of the mean. CT data of the lumbar spine and pelvis were collected from a healthy male volunteer . The CT imaging data were processed by Mimics 21.0 , Geomagic Studio 2013 , and Solidworks 2017  for the reconstruction of a model with lumbar spine and complete pelvis. The interpelvic ligaments were simulated as spring structures in finite element (FE) analysis software, ANSYS 17.0 . The Young’s modulus (MPa) and Poisson’s ratio (u) were assigned as mechanical properties to the cortical bone, cancellous bone, articular cartilage, intervertebral disc, interpubic disc, titanium metal, with values that were obtained from the literature , 24. TheThe Denis type II sacral fracture injury model was constructed by grid line segmentation and the ligament was also broken when the fracture occurred. Some ligaments on the right side of the pelvis were removed from the model, including the anterior sacroiliac ligament, the long posterior sacroiliac ligament, the iliolumbar ligament, part of the sacrospinous ligament, and part of the sacrotuberous ligament. Subsequently, the interpubic disc and the corresponding superior pubic ligament and arcuate pubic ligament were removed to complete the construction of the Tile C pelvic injury model. In all models, the anterior pelvic ring was fixed with a plate, and the posterior pelvic ring was fixed with TTS, TO, and ITO, respectively. The TTS model consisted of one S1 transsacral screw and one S2 transsacral screw. The TO model consisted of a unilateral LPF and an S1 sacroiliac screw. The ITO model consisted of a S2AI-S1 and an S2 sacroiliac screw. Iliac screws/S2AI screws, S1/S2 transsacral screws and S1/S2 sacroiliac screws were all fully threaded screws with a diameter of 7.0 mm. The length of the ilium screw/S2AI screw was 80 mm, and the length of the S1/S2 sacroiliac screw was 75 mm .Four pairs of observation points from top to bottom on both sides of the sacral fracture line were selected Fig. a-c. The P = 0.015). This indicates that the upper and lower width of the S2 safety channel is significantly larger in men, rather than in women. Except for 2 patients  who did not have the S2 safety channel, 94 patients were able to accommodate the S2AI screw and S2 sacroiliac screw in the S2 segment, and 4 patients  could not accommodate S2AI screw and S2 sacroiliac screw in the S2 segment. The theoretical overall compatibility rate of S2AI screws and S2 sacroiliac screws in the S2 segment was 94%, of which 100% were males and 88% females. The lateral angulation of the S2AI screw in males was 39.78° ± 4.00° and 41.90° ± 3.79° in females (P = 0.01). These findings indicated that the lateral angulation of S2AI screw in women was significantly larger compared to that in man. The caudal angulation of the S2AI screw in males was 32.69° ± 3.67° and 33.99° ± 3.90° in females (P = 0.10).The upper and lower width of the male S2 safe channel was 14.82 ± 1.81 mm (10.27–18.66 mm) and the upper and lower width of the female S2 safe channel was 13.84 ± 2.14 mm (8.17–17.33 mm)  predicted from the FE analysis of the intact pelvic model under 500 N vertical load was consistent with the corresponding experimentally measured peak compressive displacements (0.973 to 1.550 mm) reported by Comstock et al.  under th: From observation point 1 to 4, the relative displacement of the TO and ITO groups showed a gradual increasing trend, with the displacement of the former being greater than that of the latter. For the TTS group, the relative displacement was significantly lower than the two other groups, except at observation point 1, at which all groups were close. The relative displacement of the TTS group was less affected by movement. The relative displacement of the TO and ITO groups was increased under flexion and right bending, compared to standing, and the relative displacement was reduced under left twisting, compared to standing : Τhe change in relative displacement of the TTS group at the other observation points was lower than that of the TO and the ITO groups, except at observation point 1, where the displacement change of the TTS group was slightly larger than the other two groups. The change in relative displacement of the TO group under right bending and left twisting was larger than that of the ITO group and the change in relative displacement under flexion was smaller than that of the ITO group Table .Table 2TSeveral past literature studies have measured the safe passage of S2 sacroiliac screws and S2AI screws, also applying 3D-CT technology , 30–32. The factors that affect the compatibility of S2AI screws and S2 sacroiliac screws are summarized into the following points: The first is regarding to the upper and lower width of the S2 safety channel. In theory, the larger the upper and lower width of the S2 safety channel is, the larger the safety channel is. In this study, we showed that when the upper and lower width of the S2 safety channel is less than 12 mm, the risk of the S2 sacroiliac screw passing through the S2 safety channel increases. To ensure safe insertion of the two screws, we recommend the upper and lower width of the S2 safety channel to be 12 mm as the minimum clinically applicable standard for ITO. The second factor concerns the shape of the S2 safety channel. Most individuals (92%) included in the study showed an approximately fan-shaped section of the S2 safety channel, while few showed an approximately triangular (3%) or trapezoidal section (5%). When the length of the upper wall and the front wall of the safety channel is constant, the area of the trapezoidal section is the largest , the sector section is the second largest and the area of the triangular section is the smallest . The final factor is the caudal angulation and the screw diameter of the S2AI screw. The larger the caudal angulation and diameter of the S2AI screw are, the larger the safe channel section of the S2 sacroiliac screw occupied by the S2AI screw is. Therefore, the S2AI screw diameter is recommended not to exceed 7.0 mm. In this study, the average caudal angulation of females was slightly smaller than the results presented by Zhu et al. . This maMin et al.  comparedHu et al.  found thPercutaneous transsacral screw placement has the advantages of less damage, better biomechanical stability, and fewer postoperative complications, making it widely used in clinical practice , 33, 34.This study used the undamaged sacral S2 safety channel as a qualitative analysis model, but anatomical reduction is not always achieved in clinical practice. In addition, the S2AI screw and S2 sacroiliac screw may not be optimally distributed on the pelvis. Therefore, the compatibility rate of S2AI screws and S2 sacroiliac screws obtained in this study may be slightly different from the clinical results. Additionally, only the main ligaments were simulated in the FE analysis, but in reality, other ligaments and muscles may also have an effect . TherefoThe simultaneous placement of S2AI screw and S2 sacroiliac screw in the S2 segment is theoretically safe. Although the biomechanical stability of iliosacral triangular osteosynthesis is slightly lower than two transsacral screws, it is better than triangular osteosynthesis, and can be used as a new method for the treatment of posterior pelvic ring injuries.Additional file 1.Additional file 2.Additional file 3.Additional file 4.Additional file 5.


It is thus not surprising that Nav1.5 mutations have been linked to life-threatening arrhythmias. Interestingly, Nav1.5 activity can also be altered by posttranslational modifications, such as tyrosine phosphorylation. Our combination of protein engineering and molecular modeling has revealed that the detrimental effect of a long QT3 patient mutation is only exposed when a proximal tyrosine is phosphorylated. This suggests a dynamic cross-talk between the genetic mutation and a neighboring phosphorylation, a phenomenon that could be important in other classes of proteins. Additionally, we show that phosphorylation can affect the channel’s sensitivity toward clinically relevant drugs, a finding that may prove important when devising patient-specific treatment plans.The cardiac sodium channel  and two pathogenic long-QT mutant channel backgrounds and decipher functional and pharmacological effects with unique precision. We elucidate the mechanism by which phosphorylation of Y1495 impairs steady-state inactivation in WT Nav1.5. Surprisingly, we find that while the Q1476R patient mutation does not affect inactivation on its own, it enhances the impairment of steady-state inactivation caused by phosphorylation of Y1495 through enhanced unbinding of the inactivation particle. We also show that both phosphorylation and patient mutations can impact Nav1.5 sensitivity toward the clinically used antiarrhythmic drugs quinidine and ranolazine, but not flecainide. The data highlight that functional effects of Nav1.5 phosphorylation can be dramatically amplified by patient mutations. Our work is thus likely to have implications for the interpretation of mutational phenotypes and the design of future drug regimens.The voltage-gated sodium channel Na Each do(DI-IV) 5. The lat(DI-IV) 5–13. Subt(DI-IV) 5.v1.5 and Kv7.1, upon β-adrenergic stimulation, for example   simulations to investigate if the functional effects caused by phosphorylation of Na of SSI) , 24 are  of SSI) , the dis of SSI)  has no sv1.5 Y1495, while a conventional mutagenesis approach can prevent phosphorylation with a tyrosine-to-phenylalanine mutation, it is not possible to control the degree of phosphorylation on the native tyrosine. We overcome this obstacle using a recently developed semisynthetic approach that allows for the insertion of synthetic peptides carrying single or multiple PTMs or PTM mimics into ion channels (REC and CREC) corresponding to partial channel fragments that are recombinantly expressed in Xenopus laevis oocytes and a synthetic peptide (PSYN) containing the site of interest, which is injected into the oocyte cytosol . The covalent linkage of the three fragments is mediated by two orthogonal split inteins: CfaDnaE (split intein A) (SspDnaBM86 (split inteins B) .Heterologous protein expression does not allow precise control over the extent of PTM. In the case of Nachannels . In thisntein A)  and SspDteins B) . Upon asteins B)   or a phosphonylated tyrosine  . However, no voltage-dependent currents were observed within similar incubations times when only N and C fragments were injected, suggesting that the channel fragments alone were unable to noncovalently assemble (nylation at Y1495 (WT phY) results in a roughly 10-mV right-shift in the SSI curve while retaining WT-like values for half-maximal activation .Injection of oocytes expressing N and C fragments with NM peptide (WT NM) results in activation and SSI parameters similar to those obtained when all three channel fragments are expressed recombinantly , 33rec) v1.5 in which the IFM particle is docked to a site between the DIII S4-S5 linker and DIV S6  of N1659 in DIV-S5 helix and F1486 in the IFM particle as a reaction coordinate E. This sv1.5 SSI and accelerating recovery from inactivation.Together, the combined experimental and computational data support the notion that phosphorylation at Y1495 destabilizes the interaction of the IFM motif with its receptor site. Specifically, phosphorylation of Y1495 moves it away from the DIV-S6 and toward the DIII-S6 and DIII-S4-S5 linker, thereby right-shifting NaSYN variants containing the Q1476R mutation on either the Y1495F (Q1476R NM) or Y1495 phY background (Q1476R phY). Insertion of either peptide variant resulted in robust voltage-gated currents within 12 h after injection  was the voltage required for half-maximal activation. This was significantly left-shifted compared with WT NM but indistinguishable for Q1476R phY and WT phY .SI Appendix, Fig. S4).These data suggest that the phosphorylation-induced destabilization of the IFM particle in its receptor site was starkly exacerbated in the presence of the pathogenic Q1476R mutation. This idea is further supported by our finding that recovery from inactivation was accelerated for Q1476R phY compared with WT phY . Although we observed overall similar trends, both Y1495E and Q1476R/Y1495E resulted in even more pronounced shifts in SSI compared to the semisynthetic WT NM, WT phY, and Q1476R phY constructs . This underscores the advantages of inserting phosphorylation mimics with near identical charge and steric properties via our semisynthetic approach rather than using conventional mutagenesis.Next, we sought to assess if full-length Nav1.5 with both the WT phY and the Q1476R phY systems. Strikingly, the Q1476R mutation causes a break in the DIII-S6 helix, allowing its C-terminal end to move into the IFM binding site. As a consequence, increased contact frequency was observed between G1481/G1482 and the IFM motif in the Q1476R phY system compared to the WT phY system  or the Y1495 phY background (ΔK1500 phY). With both, we observed robust voltage-gated currents  of 86 ± 83 μM for WT NM  and 43 ± 5 μM (ΔK1500 phY), respectively .Next, we turned to inhibition by flecainide, a slightly larger and more hydrophobic AAD B. As expv1.5 by both quinidine and ranolazine is sensitive to phosphorylation at Y1495, while flecainide inhibition is not. Additionally, our data show that the Q1476R mutation abolishes the phosphorylation-induced reduction in apparent affinity for all three tested drugs, while for the ΔK1500 mutation this was only the case for quinidine and flecainide.The above suggests that inhibition of WT Nav1.5. Based on this approach, we 1) outline a detailed molecular mechanism for how phosphorylation of Y1495 modulates Nav1.5 inactivation, 2) demonstrate that the magnitude of the functional effects caused by this modification can vary substantially when we combine it with a patient mutation, and 3) show that phosphorylation can affect the pharmacological sensitivity of Nav1.5 toward clinically relevant AADs.In this study, we use a combination of protein semisynthesis and MD simulations to study the effects of phosphorylation on Y1495 on the DIII-DIV linker of Nav1.5 pathogenicity is often associated with changes in the voltage dependence of SSI. For example, the pronounced right-shifted SSI due to phosphorylation of Y1495 is well established from previous in vitro work  right-shift in the voltage sensitivity of SSI and the significantly accelerated recovery from inactivation due to phosphorylation of Y1495 is caused by a destabilization of the interactions between the IFM particle and its receptor site, which results in a decrease of binding energy of the IFM particle to its binding site. Our simulations illustrate that phosphorylation causes the IFM particle to be displaced from its receptor site, moving it toward DIII-S6 to accommodate the phosphate group of Y1495 in the binding pocket of IFM. In light of the high degree of sequence conservation in the DIII-DIV linker across mammalian Nav channels  alone can be disease-causing  see alsA–C, it htro work , 33. Yetchannels , we specv1.5 SSI likely involves side chains in the C-terminal domain   –53.v1.5 phosphorylation sites are situated within the DI-DII linker. Although multiple lines of evidence suggest that all intracellular linkers can be phosphorylated , we cannot assess the extent to which other PTMs might be present in different parts of the protein or if these would differ in a more relevant mammalian expression system. This is important because the functional impact of Nav1.5 mutations can be cell-type specific   , 70.v1.5 structure determination was heavily engineered, resulting in severe gating shifts and thus prompting us to carefully question this functional assignment. Despite these caveats, our computational data are in remarkable agreement with the functional characterization of the phosphorylation and the patient mutations, leading us to confidently propose a mechanistic model for the effects caused by these modifications.As a template for our computational work, we used a Nav1.5 structure that was resolved in a presumably inactivated state. This functional assignment is primarily based on the fact that the IFM particle is docked to a site between the DIII S4-S5 linker and DIV S6. However, we note that the construct used for Nav1.5 patient mutations because PTM levels are subject to variation. Given the enormous (>500) number of disease-associated mutations in Nav1.5 alone  and diluted to the specified concentrations, and the pH value was adjusted to 7.4. The prepared solutions were then stored at room temperature and used for no longer than 20 d.All chemicals were purchased from Sigma-Aldrich, Iris Biotech, Rapp polymere, Combi-Blocks and Chem-Impex unless specified otherwise. AADs were purchased from Sigma-Aldrich  and stored according to product specification. Substances were dissolved in ND96 solution , the sequence derived from the Nav1.5 ion channel, and the C-terminal intein half (IntN-B), with the Nav1.5 ion channel sequence being the only variable one. Regarding the ligation strategy adopted, the three fragments were ligated in a “one-pot” fashion and in a C-to-N direction, exploiting the Thz masking group as previously established (Peptides for Nan detail . Brieflyablished . Note thablished .tBu)-OH, Fmoc-Thr(tBu)-OH, Fmoc-Tyr(tBu)-OH, Fmoc-Asp(tBu)-OH, Fmoc-Glu(tBu)-OH, Fmoc-Met-OH, Fmoc-Val-OH, and Boc-Thz-OH.Unless otherwise stated, the amino acids used for solid-phase peptide synthesis were Fmoc-Ala-OH, Fmoc-Cys(Trt)-OH, Fmoc-Phe-OH, Fmoc-Gly-OH, Fmoc-Ile-OH, Fmoc-Lys(Boc)-OH, Fmoc-Leu-OH, Fmoc-Pro-OH, Fmoc-His(Trt)-OH, Fmoc-Asn(Trt)-OH, Fmoc-Gln(Trt)-OH, Fmoc-Arg(Pbf)-OH, Fmoc-Ser–formic acid , 3 + 12 min. Coupling reactions were performed as double couplings using Fmoc-Xaa-OH , O-(6-Chlorobenzotriazol-1-yl)-N,N,N’,N’-tetramethyluronium hexatuorophosphate , and N,N-diisopropylethylamine  for 40 min for each coupling. All reagents and amino acids used during SPPS were dissolved in N,N-dimethylformamide except i-Pr2NEt, which was dissolved in N-methyl-2-pyrrolidinone. Coupling reactions for nonstandard Fmoc-protected amino acids were performed as outlined for each peptide (SI Appendix).Automated peptide synthesis was carried out on a Biotage Syro Wave peptide synthesizer using standard Fmoc/tBu SPPS chemistry as previously reported . Fmoc deThioesterification of peptides was performed as described , 72 and X. laevis oocytes . Typically, synthetic peptides were injected about 24 h after cRNAs injection. Recordings were conducted 12 to 20 h after injection of synthetic peptides.Stage V-VI oocytes from Note that experimental uncertainties associated with the injection of small amounts of synthetic peptides do not allow us to draw conclusions on expression levels .2, 1.8 CaCl2/BaCl2, 5 HEPES, pH 7.4) during recordings. For pharmacological testing, solutions containing different AADs in ND96 were used. Glass microelectrodes with resistances between 0.1 and 1 MΩ were backfilled with 3 M KCl. To determine values for half-maximal activation, oocytes were held at −100 mV and sodium currents were elicited by voltage steps from −80 mV to +40 mV (in 5-mV increments). SSI curves were determined by applying a 500-ms prepulse from −100 mV to −20 mV (in +5-mV increments) followed by a 25-ms test pulse to −20 mV.Voltage-dependent currents were recorded with a two-electrode voltage clamp using an OC-725C voltage clamp amplifier (Warner Instruments). Oocytes were constantly perfused with ND96 solution   Nav1.5 with Y1495 phosphorylated and Q1476R mutation, and 4) Nav1.5 with Y1495 phosphorylated and ΔK1500 mutation. Phosphorylation and mutation were performed using the CHARMM-GUI Membrane Builder. The system was hydrated by adding two ∼25 Å layers of water to both sides of the membrane. Lastly, the system was ionized with 150 mM NaCl.First, the NaID 6UZ3)  was embeID 6UZ3) . Four diThe CHARMM36 force field was used to describe interactions between protein , lipid , and ion−1 ⋅ nm−2. The weighted histogram analysis method (WHAM)  was restrained throughout the simulation with a restraining potential force constant of 1,000 kJ ⋅ molContacts are defined when the distance between the Cβ atoms of pairs of residues are below 6.7 Å. Those were calculated using MD-TASK .Supplementary File