Risk-based monitoring (RBM) is a slow uptake in some trial sponsors. There are three main reasons for this. First, there is the fear of making large investments into advanced RBM technology solutions. Second, it is considered that RBM is most suitable for large, complex trials. Third, there is the fear of errors in both critical and non-critical data, appearing as reduced on-site monitoring is being conducted.Our RBM team identified, evaluated, and mitigated trial risks, as well as devised a monitoring strategy. The clinical research associate (CRA) assessed the site risks, and the RBM team conducted central monitoring. We compared all data errors and on-site monitoring time between the partial switching sites [sites that had switched to partial source data verification (SDV) and source data review (SDR)] and the 100% SDV and SDR sites (sites that had implemented 100% SDV and SDR).Partial switching sites did not require any critical data correction and had a smaller number of data corrections through on-site monitoring than the 100% SDV and SDR sites. The RBM strategy reduced the on-site monitoring time by 30%.The results suggest that RBM can be successfully implemented through the use of site risk assessment and central monitoring with practically no additional investment in technology and still produced similar results in terms of subject safety and data quality, as well as the cost savings that have been reported in global complex studies. Risk-based monitoring (RBM) was first introduced into studies in 2011–2012. By the time ICH E6(R2) was issued, RBM was already a well-known concept. The FDA, EMA, and PMDA had included it in their regulations for clinical trials, making it mandatory in their jurisdictions. The upcoming ICH E6(R3) in 2021 is expected to strengthen it even further. However, there has been rather slow uptake by some trial sponsors all over the world. There are three main reasons for this. First, there is a fear of making large investments in advanced RBM technology solutions. Second, it is thought that RBM is only suitable for large complex trials. Third, there is a fear of erroneous data, in both critical and non-critical data when the on-site monitoring is reduced.According to ICH E6(R2), sponsors should develop systems to manage quality throughout all stages of the trial process, and quality management systems should use a risk-based approach (RBA). An RBA process is commonly known as RBM ; this ap. showed that a median of 1.1% of the total eCRF datasets in 1168 phase I–IV biopharmaceutical studies performed with 53 sponsors was corrected by SDV [. reported that in three randomized, double-blind, placebo-controlled, multicenter phase III trials, 100% SDV yielded an error rate of 0.27%, and the error rate for partial SDV was 0.53% [Sheetz et ald by SDV . This anas 0.53% . In the However, no RBM studies have been performed in relation to all errors and deviations of eCRF data and source data as detected by central monitoring, off-site monitoring, and on-site monitoring, including SDV and SDR. No observations have yet been conducted on the combination of central monitoring and site risk assessment as seen in previous studies.Whether a simple RBM without advanced technology will produce satisfactory results in terms of managing data and safety risks.Whether an RBM provides benefits in a low-risk trial with minimal complexity.Whether an RBM can ensure quality regarding all errors in eCRF and source data, minimize protocol deviations, and optimize the monitoring resource utilization.We implemented RBM in our trial with the three-fold objective of investigating the following:We included non-critical data errors to simulate traditional monitoring strategies with 100% SDV and SDR. We compared errors and on-site monitoring time between sites that switched to partial SDV and SDR and sites with 100% SDV and SDR.Our study was an open-label, multicenter trial performed to evaluate 52-week long-term safety, tolerability, and efficacy of tofogliflozin in conjunction with glucagon-like peptide-1 (GLP-1) analogue treatment in type 2 diabetes mellitus. The 67 participants at 11 sites in Japan were randomized. The primary endpoint for this trial was change from baseline in HbA1c. Trial data were collected using electronic data capture (EDC). Data freezing was conducted at each site.The trial sponsors were Kowa Company, Ltd. and Sanofi K.K. The trial was managed and conducted by A2 Healthcare Corporation, a Japanese contract research organization. The members of Kowa Company, Ltd. and A2 Healthcare Corporation discussed and determined the RBM strategy. This trial was registered at ClinicalTrials.gov with number NCT02537834.We identified and assessed trial risk with the TransCelerate Risk Assessment and Categorization Tool (RACT). We formulated a risk mitigation plan for the identified risks. This was performed by the monitoring leader and the RBM team members, including central monitors, data managers (DMs), and statisticians. The risk mitigation plan was adapted to accommodate manuals and/or training for site staff, patient diaries, and discussion of site processes with site staff. The discussions were conducted at all sites, and the results of the discussion were recorded in the process-building sheet, which included an optimized clinical process designed to prevent protocol deviations.We located sites that switched to partial SDV and SDR. These were referred to as partial switching sites, using information related to the previous involvement of the trial sponsor  and the results of the site risk assessments performed by the CRA. The assessed sites were those where the CRA had implemented monitoring in other trials. The CRA determined whether issues had arisen that could affect subject safety or the quality of the trial data, including non-reporting or late reporting of SAEs, late EDC entry, or inadequately trained site staff. Using information on the previous involvement of the sponsor and the site risk assessments, all sites for which information was already present were termed partial switching site.At the beginning of the trial, the CRA discussed the site processes with the site staff at all sites and completed the process-building sheet. At the partial switching sites, where the process-building sheets were completed, the CRA assessed the site risks and switched to partial SDV and SDR at the low-risk sites, using a Monitor-driven Risk Assessment Categorization Tool (MRACT). Until that point, the CRA had performed 100% SDV and SDR at these sites. MRACT included the items necessary to identify the issues and risks that would be difficult to detect with data-driven risk indicators, such as the quality of the source documentation. At the 100% SDV and SDR sites, which referred to all sites that were not partial switching sites and for which there was no information before starting the trial, the CRA also carried out an assessment using MRACT to evaluate the site risks without switching. The implementation details for on-site monitoring, off-site monitoring, and central monitoring activities for this trial are presented in Table After the last patient last visit, the CRA conducted SDV and SDR on the data that had not received SDV and SDR at the partial switching sites during the trial implementation phase Fig. .Figure 1MRACT consists of 17 checklist items, categorized into three groups: critical processes (four items), data quality (three items), and staffing and facilities (ten items). Each checklist item had a risk score from 1 to 3  in accordance with the risk assessment criteria. The CRA began the assessment of the site using MRACT items following the first on-site monitoring. After the first assessment, the CRA carried out monthly assessments at each site, using MRACT. All of the results of the assessments were reviewed and approved by the CRA leader. The RBM team members reviewed the results and queried the CRA leader where necessary. The implementation of the review and the approval minimized the bias and subjectivity of the site risk assessment. The MRACT was not updated during the trial.The CRAs collected all queries to the doctor or clinical research coordinator (CRC) in Microsoft Excel software on a data point basis after on-site monitoring and off-site monitoring. The data collected by the CRAs included corrections of the eCRF and the source data. Where data were corrected, the CRA presented the data and the reason for the error in the spreadsheet file. The reasons for the corrections included lack of understanding of the trial protocol, errors in source documents, transcription errors, lack of data entry, and others. To minimize the human error in data entry by the CRAs, the spreadsheet file for the data collection was set to select and input from the drop-down list, and the CRA leader confirmed the data entered by CRA to allow it to be detected when a human error occurred. A team member of central monitoring collected all errors detected by central monitoring in an Excel spreadsheet. The DM extracted the created query data and the data corrected through the DM queries from the EDC audit trail data at the end of the trial. The dates and times of the beginning and the end of the on-site monitoring were collected by the CRAs. The collection of the data continued from the first patient first visit to the last patient last visit for partial switching sites and the 100% SDV and SDR sites. After the last patient last visit, the CRA conducted SDV and SDR on the data that had not received SDV and SDR at the partial switching sites to collect the error data.The number of corrected eCRF and source data per subject was compared between the 100% SDV and SDR sites and the partial switching sites. The number of corrected eCRF and source data per subject was also compared between monitoring activities. This involved on-site monitoring by the CRA, off-site monitoring by the CRA, off-site monitoring by the DM, central monitoring, and correction by site. The time required for on-site monitoring per completed subject was compared between the 100% SDV and SDR sites and the partial switching sites. The number of corrected eCRF and source data per subject was also compared between the data risk categories, which were determined using the impact of data errors, classified as high, medium, or low. The high-risk category included critical data related to the protection of the human subjects, the reliability of the trial results, and GCP compliance. The high-risk category data were adverse event, primary endpoint, and informed consent. The medium-risk category included secondary endpoint data. The low-risk category included all other data not covered by the high- or medium-risk categories.To summarize the metrics assessed in this investigation, the following definitions were used:The number of eCRF and source data per subject corrected for the 100% SDV and SDR sites and that for the partial switching sites was nearly equal, at 24.3 and 21.8, respectively , the focus on quality management shifted from ensuring the integrity of the trial data to ensuring the reliability of the trial results. That is, it is important to ascertain what approach might be more effective and efficient. This study investigates whether RBM can ensure the protection of human subjects and the reliability of trial results while optimizing monitoring resources.The partial switching sites showed no data corrections in high-risk category items. This means that no critical errors occurred at those sites. Our definition of partial switching site was based on our own information, but we did detect one problem site from the MRACT results and central monitoring during the trial implementation phase. After the detection, we switched it from partial SDV and SDR to 100% SDV and SDR. After the switching, we determined the cause of the critical error and implemented corrective action. These results suggest that the strategy of switching the site monitoring based on the MRACT results and central monitoring is an option for RBM strategy that could ensure the reliability of the trial results.The number of eCRF and source data per subject corrected by off-site monitoring at partial switching sites was higher than that found at 100% SDV and SDR sites. All CRAs were in charge of monitoring the partial switching sites and the 100% SDV and SDR sites. Off-site monitoring activities depended on the CRAs, and all four CRAs stated that the time required and the motivation for off-site monitoring were same for both the partial switching sites and the 100% SDV and SDR sites. These observations suggest that the result cannot be attributed to the differences in the implementation of monitoring among the CRAs. Because the CRAs were not prohibited from conducting on-site monitoring before the weekly off-site monitoring, their on-site monitoring probably detected the errors that the CRAs could detect with weekly off-site monitoring at the 100% SDV and SDR sites.The number of eCRF and source data corrections per subject with on-site monitoring at the partial switching sites was lower than that at the 100% SDV and SDR sites, and the partial switching sites had only low-risk category correction with on-site monitoring. These results suggest that the strategy of switching site monitoring based on the MRACT results and central monitoring effectively detects data error.The partial SDV and SDR reduced the on-site monitoring time by 30%. This suggests that the reduction in time spent on on-site monitoring at the partial switching sites could be attributed to the reduction in the frequency of on-site monitoring from once a month to once every three months.Sheetz et al. showed retrospectively that a median of 1.1% of the total eCRF datasets was corrected by SDV in their data , while tIn the ADAMON study, the monitoring intensities were adjusted, but the issues that affected critical data and processes were identified after completion of the trial . On the It should be noted as a limitation of the study that the trial was conducted with a small sample size. Therefore, its results cannot be generalized. It is unclear whether the same results would be obtained if a more complex trial was conducted, as this trial required few complex or uncommon procedures that go beyond the usual standard of care.We obtained the partial switching sites using prior information. Although this introduces bias, the following two points probably ensured the comparability among the 100% SDV and SDR sites and the partial switching sites.First, we did not assess or select sites for which no information was available. Accordingly, the 100% SDV and SDR sites probably included low-risk sites, which we could probably defined as partial switching sites.Second, the information that we used to assess and select of the partial switching sites was probably insufficient. This is because the partial switching sites included a site that was switched from the partial switching sites to the 100% SDV and SDR sites, following the MRACT results and central monitoring. Furthermore, the CRAs held discussions with the site staff at all sites for risk mitigation, assessed all sites using MRACT, and verified that all sites were low risk at the beginning of the trial.In our study, we suggested that the implementation of RBM can efficiently ensure the quality of trials. Switching strategies are commonly practiced in the industry. However, to our knowledge, this is the first prospective study to demonstrate the effects of RBM, evaluated using all data corrections, adopting a strategy wherein site monitoring can be switched based on the results of site risk assessment and central monitoring.Our study shows that RBM can be successfully implemented with site risk assessment and central monitoring with practically no investment in technology and can still produce similar results in terms of subject safety and data quality, along with showing the savings that have been reported in global complex studies. The time saved by the CRAs can be used to perform additional studies or engage in other activities. We believe that this study will provide a convincing support for the wider spread of RBM studies.


Multiple mechanisms of action towards proteins, DNA, and membranes reduce a risk of pathogen resistance but inevitably cause toxicity for cells and organisms. Silver nanoparticles (AgNP) are known to generate two reactive oxygen species (ROS)-superoxide (•O2−) and hydroxyl (•OH) radicals, which inhibit the cellular antioxidant enzymes  and cause mechanical damage of membranes. Ag+ release and replacement by electrolyte ions with potential formation of insoluble AgCl result in NP instability and interactions of heavy metals with nucleic acids and proteins. Protein shells protect AgNP core from oxidation, dissolution, and aggregation, and provide specific interactions with ligands. These nanoconjugates can be used for immunoassays and diagnostics, but the sensitivity is limited at 10 pg and specificity is restricted by binding with protective proteins . Thus, broad implementation of Ag nanostructures revealed limitations such as instability; binding with major blood proteins; damage of proteins, nucleic acids, and membranes; and immunosuppression of the majority of cytokines.Nanosilver with sizes 1–100 nm at least in one dimension is widely used due to physicochemical, anti-inflammatory, anti-angiogenesis, antiplatelet, antifungal, anticancer, antibacterial, and antiviral properties. Three modes of the nanosilver action were suggested: “Trojan horse”, inductive, and quantum mechanical. The Ag Nanosilver is a generic term that refers to nanoscale Ag materials that have at least one dimension less than 100 nm, and which are commonly in the form of particles called silver nanoparticles (AgNP). They remain the most used engineered nanostructures in approximately ~500 commercialized consumer products with annual production 320 tons  for woun+ by using various plant extracts, bacteria, biodegradable polymers, enzymes, and even microwaves [There are physical, chemical, physicochemical, and biological methods of nanosilver fabrication. Physical methods include thermal evaporation or condensation, laser ablation, arc discharge, metal sputtering and lithography. Chemical methods are citrate method, borohydrate reduction, tollens (silver mirror) reaction, and polyol process. Physicochemical approaches are photoinduced reduction, reduction induced by plasma or by laser irradiation, discharge-induced reduction, thermal decomposition, and electrochemical approaches. The most numerous methods are so-called biological methods by using amino acids, peptides, proteins, nucleic acids, polysaccharides, flavonoids, terpenes, and oils, as well as plant or fungi extracts, whole bacteria, yeast cells, and viruses. Biological approaches are found to be simple, environmental, commercial, and single-step methods that do not require elevated temperature, pressure, force, and chemicals . Recovercrowaves —is graducrowaves ,10,11,12Inevitably, from the rapid growth in its manufacture and utilization follows an increased environmental and human exposure. Despite the evergrowing presence of the nanosilver in the market and extensive research on potential acute and chronic toxicity in vitro and in vivo, exact multiple mechanisms remain uncertain. Remarkably high surface-to-volume ratio of the nanosilver enhances surface reaction properties, thus increasing the possible interaction with biological fluids including blood serum, lymph, saliva, mucus, or lung lining fluid components. AgNP sizes, shape, and surface coating contribute to interactions with biomaterials, organic and inorganic molecules, cells, and viruses .3) and soluble compounds of silver (0.01 mg/m3) [Evident concerns regarding the overuse of the nanosilver with possible interactions with biological systems in new unpredicted ways  and the 1 mg/m3) . Meanwhi1 mg/m3) .Current research is aimed at stability, toxicity, and immunomodulation potential of the nanosilver.+ ions release in the process of AgNP dissolving. Replacement of Ag+ by electrolyte ions, potential formation of insoluble AgCl, subsequent catalyzed oxidative corrosion of Ag, and further dissolution of surface layer of Ag2O take place [+ at the particle surface shifts the chemical potential of the particle to a more positive value, and if it approaches that of the electron acceptor , oxidation ceases. The opposite shift in the potential occurs for metallic AgNP with adsorbed nucleophiles , resulting in an increase in the oxidation of Ag(0) [2HPO4/KH2PO4, 0.15 M NaCl/KCl) during 1 h at room temperature  . Therefoof Ag(0) . Howeverperature  due to r K+ ions ,17. To p K+ ions . Coating K+ ions . Recoverrication ,12,18.Staphylococcus aureus protein A is less efficient, whereas a number of proteins  envelope antigen) cannot attach to AgNP at all. Despite known chemical affinity of sulfur atoms to precious metals, direct correlation between cystine disulfide bridge content and binding with AgNP was not observed, perhaps because of strong bonds between two cysteines that stabilize protein conformations.Nanosilver, like other nanostructures immediately after administration into an organism, becomes wrapped by serum and cellular proteins forming protein corona. These natural spontaneous protein shells decrease the efficiency of targeting by directing nanostructures to the reticuloendothelial system by masking the active targeting moieties and decreasing their ability to bind to their target receptor but may re-direct NP towards endogenous targets. Surface of the nanosilver dynamically adsorbs proteins, forming a robust rapidly exchanging “biocorona”. A hard corona with long-term stability can be formed with immunoglobulins IgG/IgM and fibrinogens and may alter NP size, shape, surface charge, and agglomeration state, as well as cellular toxicity and internalization, trafficking, opsonization, and eventually pattern of biodistribution . ColloidThe NP stability depends on the affinity of coating molecules to the particle surface; repulsion from neighboring molecules; loss of chain entropy upon adsorption; and also nonspecific dipole interactions between the macromolecule, the solvent, and the surface. Protein coronaprotects AgNP from dissolution and aggregation . The nanConsequently, AgNP should not be used in microfluidic diagnostics and treatment because of their dissolution and aggregation in electrolyte solutions in any bio-relevant physiological media. Preliminary binding of AgNP with some proteins permits the construction of soft corona, which dynamically exchange with major protective proteins such as immunoglobulins, fibrinogen, and albumins immediately after administration in blood sera or other biological fluids. Different affinity of AgNP binding with proteins determines stability and specificity of the nanoconjugates.+ ions may intercalate between purine and pyramidine base pairs and disrupt the hydrogen bonding between the two anti-parallel strands, thus denaturing the template DNA molecules [+ cations deteriorate their conformations and inhibit surface ligands. Extinction, light scattering, surface plasmon resonance (SPR), and surface-enhanced Raman spectroscopy (SERS) of AgNP exceed those of AuNP in 10–100 times. Relatively low price is also an advantage of the nanosilver.Physicochemical features of the nanosilver with unique plasmon-resonance optical scattering properties determine possible implementation in diagnostics ,19). Higolecules ,21 and dolecules . However2 envelopes with subsequent functionalization with organosilanes. Physisorption of proteins on surfaces of AgNP is reversible, and up to 70% of the attached proteins can be eluted. AgNP possess high affinity for binding with immunoglobulins but not with any protein. SiO2 layer on surfaces of metal NP is suitable for silanization and covalent attachment of any protein. The developed methods of fabrication of AgNP with protein shells permit attaching any protein at different distances from the metal core to avoid possible inactivation of proteins, to reduce fluorescence fading, and to stabilize the nanoconjugates [The stable nanoconjugates of AgNP with immunoglobulins of different origin, classes, and specificity, including both polyclonal and monoclonal antibodies, were constructed by (1) direct binding of AgNP with purified IgG or IgM , (2) nannjugates . Green snjugates .2− and COOH− modified surfaces of chips are not homogenous, causing problems of dot-to-dot reproducibility.To detect binding of immobilized antigens with AgNP conjugated with IgG, the analyzer based on light scattering of dark field laser of total internal reflection with the wavelength 532 nm and corresponding software were used. The sensitivity limit of the nanosilver-based immunodiagnostic systems was nearly 10 pg/dot for direct binding of AgNP with immobilized IgG and 100 pg for 3-layer sandwich immunoassay. For comparison, thresholds of ELISA and xMAP multiplex immunofluorescent analysis with fluorescent magnetic microspheres were 1 pg/mL. Specificity of Ag nanoconjugates is limited due to their binding with the major blood serum proteins: IgM, IgG, fibrinogen, and albumins with high background level. Protein dots on NHTaken together, immunodiagnostics based on AgNP covered with IgG shells remains inferior compared to specificity and sensitivity of the widely used ELISA and xMAP for 10 to 100 times. Specificity of immunodetection and ratio of signal to background are limited because of AgNP binding with blood proteins.Multiple mechanisms of nanosilver toxicity remain uncertain, despite three recently suggested modes: “Trojan horse”, inductive, and quantum mechanical, which may have a collaborative effect .Silver in ionic, nanoparticulate, and bulk forms behave very differently. Due to their large surface area, AgNP are able for rapid oxidation, dissolution, reactive capacity, and binding with inorganic and organic molecules ,16. When+ carriers with release of Ag+ ions through the oxidative dissolution [+ cations have an affinity to amino, thiol, phosphate, and carboxyl groups. Therefore, silver-containing complexes can interact with proteins, DNA, polysaccharides, and phospholipides. Consecutive steps of cytotoxicity include adhesion to cell surface, altering the membrane properties; reactive oxygen species (ROS) formation, damaging cellular, bacterial membranes, and viral envelopes; interactions with DNA; and enzyme deterioration [+ [2), and carboxyl (−COOH) groups, damaging enzyme activity, changing their structure, affecting the normal physiological processes, and ultimately inhibiting the pathogens of different origin [+ antimicrobial action are becoming evident. Ag+ ions may react with phosphorus and sulfur groups of surface proteins after posttranslational modification (phosphorylation and sulfation) on cellular membranes, bacterial cell walls, and virions. Ag+ cations electrostatically interact with membrane phospholipids and proteins, which can cause the depolarization and destabilization of cellular membranes, viral envelopes, and leakage of H+. Thus, the nanosilver increases membrane permeability, reduces mitochondrial membrane potential, and inactivates bacterial or mitochondrial inner membrane-associated respiratory chain including cytochromes. Mitochondria appear to be sensitive targets for the nanosilver toxicity [+ cations alter mitochondrial functions, resulting in the release of apoptogenic signals and subsequent cell death [AgNP can serve as Agsolution ,16,17. Tioration . Besidesation [+ ,26 and nation [+ . The ROSt origin ,28. Additoxicity . Dose-dell death .n-terminal kinase, and cause DNA damage and apoptosis. Interaction of AgNP with DNA hinders DNA replication and leads to cell cycle arrest at the G1, G2/M phase and complete blockage in S phase [AgNP induce ROS and release of cytochrome C into the cytosol and translocation of Bax protein to mitochondria . Increas S phase ,27. Litt S phase . Nanosil S phase ,27 are t3 for 50% of human larynx carcinoma HEp-2 cells (CC50) was 50 μg/mL, whereas for the nanoconjugates of AgNP with protein shells, CC50 was 1.4 μg/mL  data). At present there is no evidence of the efficient uptake or intracellular localization of the citrate-coated AgNP conjugated with fluorescent proteins. Intracellular Ag+ release appears to be responsible for the toxicity since the cultural media after treatment of cells with the nanosilver do not cause any cytotoxicity. Thus, AgNP cytotoxicity is mainly associated with the rate of intracellular Ag release, a “Trojan horse” effect [Noteworthy, that AgNP cytotoxicity exceeds that of Ag+. For instance, cytotoxic concentration of AgNO” effect ,13,27.+ ions electrostatically interact with membrane phospholipids and proteins, which can cause the depolarization and destabilization of cellular membrane and leakage of H+. AgNP induce disorder at the molecular level of lipid bilayers, making them more fluidic and expanded. AgNP adhesion can occur through electrostatic attraction or weak interaction forces [Agn forces . Moreoven forces .Plasmon modes and quantum states of the metallic NPs are the unique light propagation, enhanced reactivity of hot electrons, or the relaxation mechanisms of excited NP. The hot electrons in noble NP can decay through two different actions, namely, electron–electron and electron–phonon interactions. The successful transfer of Ag NP energy, provided by surface plasmon resonance (SPR) through electron–electron interactions requires the direct substrate molecule deposition on the NP surface. The ROS formation under the irradiation was accompanied by the decrease in the superoxide dismutase, catalase, and glutathione peroxidase activity. In contrast, the electron–photon interactions lead to thermal diffusion (heat transfer) outside the NP, which is the basis for photothermal therapy. The NP are more stable under irradiation, and metallic NP have significantly higher extinction coefficient due to SPR, which additionally can be tuned by changes in NP forms and sizes. Ag NP size has a significant impact on their features, which is related to the quantum size effect .Besides short-term or acute toxicity described above and observed within several days after addition of the nanosilver to eukaryotic tissue cultures, bacterial suspensions, and viruses in in vitro experiments, one should not exclude long-term or chronic toxicity . AgNP ha+ ions can generate ROS, leading to DNA damage, protein denaturation, and apoptosis. AgNP of different sizes and shapes tend to accumulate in the mitochondria, thereby inducing mitochondrial dysfunction, i.e., a reduction in mitochondrial membrane potential, and promoting ROS creation [AgNP have been reported to be toxic to human cell lines . Cellulacreation . AgNP cy+ inside the cell, damage of cellular proteins and nucleic acids, and other cytotoxic effects. For instance, the following coatings posses surface charges: (1) positive: polyethylenimine, chitosan, poly-L-lysine, and cetyltrimethylammonium bromide; (2) negative: bovine serum albumin (BSA), citrate, odium bis(2-ethylhexyl)-sulfosuccinate; (3) neutral: polyvinylpyrrolidone. Ag+ ions alter mitochondrial function, resulting in the release of apoptogenic signals and subsequent cell death. They may destroy DNA-dependent DNA replication, RNA transcription, and translation.Surface charge of AgNP stabilized with citrate anions or protein envelopes is a parameter responsible for cellular uptake. In particular, high-level toxicity of positively charged nanoconjugates versus negatively charged coatings has been reported. It can be caused by the adhesion of AgNP onto the negatively charged cell membranes, their consequent entry to the cell, potential release of Ag50 for three human cell lines in a range. However, expression induction of genes involved in cell cycle and apoptosis was noticeable at <1 μg/mL of the nanosilver [3 for any soluble compounds of silver corresponding to 10 pg/mL) in order to reduce a risk of chronic toxicity [Thus, in vitro AgNP are toxic to a variety of examined tissues including lung, liver, brain, vascular system, and reproductive organs. AgNP concentrations used in these studies were 1–200 μg/mL, with most in the 5–50 μg/mL range. The data coincide with our calculations of CCnosilver . Moreovetoxicity .The common mass-only dose metric model employed in toxicology for traditional substances is evidently not convenient for engineered nanomaterials. Alternative dose metrics include particle number, ion release , and the total particle surface area. Nevertheless, polydisperse particle suspensions, the ambiguity in the surface area, and concentrations will obscure the analysis. Therefore, the Organization for Economic Cooperation and Development recommended that particle number, surface area, and mass should all be measured when possible, in order to enable calculation of alternative dose metrics. For AgNP, both surface area and ion release have been reported as effective alternative dose metrics for nanotoxicological assessment. Nanosilver-mediated cytotoxicity in mammalian cells depends greatly on the nanoparticle size, shape, surface charge, dosage, oxidation state, and agglomeration condition, as well as the cell type. Smaller AgNP cause more toxicity than larger ones, owing to their larger surface area and reactivity .Studies in vitro indicated that AgNP are toxic to the mammalian cells derived from skin, liver, lung, brain, vascular system, and reproductive organs. They suggested multiple targeting of the nanosilver in organisms. Bio-distribution and toxicity studies in vivo confirmed that AgNP administered by inhalation, ingestion, or intraperitoneal injections were subsequently detected in blood and damaged several organs, including the brain . MoreoveLong exposure of humans to the nanosilver from cations to NP that can penetrate in living organisms via several routes including inhalation, oral ingestion, intravenous injection, and dermal contacts can lead to argyria, or skin discoloration, and argyrosis, or discoloration of the eyes, as soluble silver incorporates into the tissues with permanent damage of skin microvessels and eyes . StudiesExposure to different forms of the nanosilver leads to distinct outcomes. Whereas elemental silver is not associated with health effects, soluble Ag is associated with lowered blood pressure, diarrhea, respiratory irritation, and fatty degeneration in the liver and kidneys. Furthermore, after different routes of administration including intravenous, intraperitoneal, and intratracheal ways, AgNP can cross the brain–blood barrier in vivo and tends to accumulate in the liver, spleen, kidney, and brain . Respira+.Animal and human studies indicate that it is difficult to remove silver completely once it has been deposited in the body; however, the nanosilver can be excreted through the hair, urine, and feces. Moreover, liver cells may develop a metabolic-based protection against AgNP and Ag3, the main target organs include the liver and spleen, followed by the testes, kidney, brain, and lungs; AgNP are formed in vivo from Ag+ ions and they are probably composed of silver salts. The elimination of silver from brain and testes is extremely slow [2S deposits have been seen in the region of cutaneous nerves, there is no indication of toxic risk of silver to the peripheral nervous system [The nanosilver penetration through the blood–brain barrier is still debatable. Inhaled AgNP may reach the brain through the nasopharyngeal system. They deposit in the olfactory mucosa of the nasopharyngeal region and subsequently are translocated into the brain via the olfactory nerve . Additioely slow . AgNP maely slow . While As system .Nanosilver is able to access the human reproductive system via a variety of commercial products such as contraceptive devices and feminine hygiene products. AgNP cause toxicity to germ line stem cells via reduction in mitochondrial function, induction of membrane leakage, and apoptosis. Examination of the DNA damage response to nanosilver in mammalian embryonic stem cells and embryonic fibroblasts showed apoptosis via upregulation of cell cycle checkpoint protein p53, DNA damage repair protein Rad51, and phosphorylated-H2AX . PolysacEndocytosis and exocytosis of AgNP occur simultaneously and depend on physicochemical properties of NP and protein corona . All nan+ ions that are toxic to aquatic organisms. Later on, Ag+ cations can bind with abundant anions available in the environment with formation of sparingly soluble salts AgCl or Ag2S. Marine inhabitants  are known to be much more vulnerable to the impacts of silver than bacteria [Evergrowing production of nanosilver increases their release into aquatic environments. Once AgNP reach fresh water, the sea, or underground water, they oxidize into Agbacteria . By accuTaken together, the distribution of AgNP after their inhalation, ingestion, and oral and subcutaneous administration involves a variety of target organs including the lungs, liver, and brain. The brain appears to be the most sensitive. The nanosilver causes expression of genes associated with cell cycle progression and related to apoptosis. Therefore, Ag nanostructures remain unsafe, even at non-cytotoxic doses less than 0.5 μg/mL .Various cellular defense mechanisms, innate immunity of vertebrates, and accumulation in certain organs for metabolic-based degradation and subsequent elimination of the nanosilver provide relative protection.The formation of protein corona on NP surfaces upon the in vivo administration is inevitable. Protein shells of all nanostructures after their systemic administration may explain the lack of the in vitro–in vivo correlations and the preclinical to clinical extrapolation. Protein shells provide stability of the nanocongugates, decrease their cytotoxicity, and determine the interaction of NP with the target and non-target cells. The chemical composition of protein corona may serve as a fingerprint for NP of certain types since different NP tend to recruit cellular and serum proteins to variable extents. Vitronectin mediates accumulation in integrin receptor-expressing melanoma cells both in vitro and in vivo, while complement 3 protein (C3), an opsonin and dysopsonin regulate the balance between the reticuloendothelial system uptake and blood circulation .+ ions on mouse lung macrophage cells result in necrotic rather than apoptotic cell death by reducing functional sulfhydryl groups in the cells [The cytotoxic effect and oxidative stress of Aghe cells .Another defense mechanism performed by the most abundant leukocytes, polymorphonuclear neutrophils (PMN), is based on neutrophil extracellular traps (NETs) . NETs ar+ ions, decrease the viability and the cytotoxic potential of natural killer (NK) cells secreting cytokines and killing damaged cells and amplified the expression of the inhibitory receptor CD159a [Nanosilver toxicity results in host defense, including apoptosis, necrosis , and NETr CD159a .Nanosilver possesses anti-inflammatory properties in both animal models and in the clinic. Thus, AgNP inhibit the expression of proinflammatory cytokines transforming growth factor-β and tumor necrosis factor-α. Nanosilver administration attenuates nasal symptoms of allergic rhinitis in mice and inhibits immunoglobulin IgE, IL-4, and IL-10. In clinical study, wound dressing containing AgNP promoted the healing of chronic leg ulcers due to antibacterial effect in the wound and by decreasing inflammatory response. Ability of the nanosilver to reduce cytokine release and matrix metalloproteinases, to decrease lymphocyte and mast cell infiltration, and to induce apoptosis in inflammatory cells may explain their anti-inflammatory mechanisms .3 and AgNP conjugated with the major blood proteins—albumin, fibrinogen, and immunoglobulins—was assayed by Unknown (X) Multi Analyte Profiling (xMAP) using the kit “17 plex” (BioRad) (Innate immunity induction with AgNO(BioRad) .The maximal production of all 17 studied biomarkers including T-helper (Th)1 cytokines: interferon (IFN) γ, tumour necrosis factor (TNF) α, interleukin (IL-1β), IL-12 (p70); Th2 cytokines: IL-2, -4, -5, -6, -7, -8, -10, -13; Th17: IL-17A and other inflammation biomarkers: granulocyte colony-stimulating factor (G-CSF), granulocyte macrophage colony stimulating factor (GM-CSF), monocyte chemotactic protein 1 (monocyte chemotactic and activating factor) (MCP-1 (MCAF)), and macrophage inflammatory protein 1β (MIP-1β) were registered during the first two days posttreatment of human larynx carcinoma HEp-2, oral epithelial carcinoma L41, and colorectal adenocarcinoma HT-29 cells.3  of AgNO3 for HEp-2 cells is 50 µg/mL), the significant upregulation was registered for IL-1β (slight increase of 1.38 times up to 0.08 pg/mL) and IL-8 (significant growth of 3.7 times up to 0.94 pg/mL), whereas steady production of TNF-α (growth of 1.15 times), G-CSF (up at 1.12), and MCP-1  was observed, whereas downregulation was observed for regulatory IL-10 (below the IL-10 production in control intact cells with less than 0.05 pg/mL and therefore undetectable in ELISA with detection limit 1 pg/mL) .In HEp-2 human cell line in 2 days post-treatment with 5 µg/mL AgNO1 pg/mL) . IL prod1 pg/mL) , which i3 addition. However, the growth did not stimulate production of other cytokines (Immunomodulation with nanoconjugates of AgNP covered with the major blood proteins—albumins, fibrinogen, or immunoglobulins—differed . Signifiytokines . Growth ytokines . HoweverLimited stability of Ag nanostructures without stabilizing envelopes in biologically relevant media, cytotoxicity for both eukaryotic and bacterial cells, and negligible cellular uptake restrict their further implementation for combined antiviral and antibacterial therapy. However, spontaneous binding with the major blood proteins and anti-inflammatory properties with inhibition of cytokine production at the early stages after treatment may be helpful in prevention of the cytokine storm caused by RNA-containing viruses.


Pharmacological inhibition of hERG can be proarrhythmic. Whole-cell patch clamp recordings of hERG current (IhERG) were made from HEK293 cells expressing wild-type (WT) and mutant hERG channels. WT IhERG1a was inhibited by phenanthrene with an IC50 of 17.6 ± 1.7 µM, whilst IhERG1a/1b exhibited an IC50 of 1.8 ± 0.3 µM. WT IhERG block showed marked voltage and time dependence, indicative of dependence of inhibition on channel gating. The inhibitory effect of phenanthrene was markedly impaired by the attenuated inactivation N588K mutation. Remarkably, mutations of S6 domain aromatic amino acids  in the canonical drug binding site did not impair the inhibitory action of phenanthrene; the Y652A mutation augmented IhERG block. In contrast, the F557L (S5) and M651A (S6) mutations impaired the ability of phenanthrene to inhibit IhERG, as did the S624A mutation below the selectivity filter region. Computational docking using a cryo-EM derived hERG structure supported the mutagenesis data. Thus, phenanthrene acts as an inhibitor of the hERG K+ channel by directly interacting with the channel, binding to a distinct site in the channel pore domain.The lipophilic polycyclic aromatic hydrocarbon (PAH) phenanthrene is relatively abundant in polluted air and water and can access and accumulate in human tissue. Phenanthrene has been reported to interact with cardiac ion channels in several fish species. This study was undertaken to investigate the ability of phenanthrene to interact with The online version contains supplementary material available at 10.1007/s00018-021-03967-8. Mor.5 e.g. , 7)..2.5), suEther-à-go-go-Related Gene (ERG) encoded K+ channels as a potential target that might mediate such effects )ley, UK) , 26. Theley, UK) , 29), asley, UK) , 30. ZebThe F656V mutation was made to hERG1a as described in Ref. . F656T wforward-5′-GTATGCTAGCATCACCGGCAACGTGTCG-3′reverse-5′-CGACACGTTGCCGGTGATGCTAGCATAC-3′hERG1a) except for the data in Fig. hERG1a/1b) and Supplementary Fig. 2 which shows data from zERG (IzERG).Experiments were performed on hERG1a current  ).hERG in an open state-dependent fashion, with sensitivity to mutation of S6 helical aromatic residues [hERG exhibited voltage- and time dependence that demonstrate contingency on channel gating for the compound to access its inhibitory binding site. Fourth, the profound reduction in the IhERG inhibitory effect of phenanthrene on inactivation-impaired N588K channels suggests a requirement for intact inactivation gating for optimal access to the inhibitory binding site. Although IhERG carried by hERG1a/1b (which showed enhanced sensitivity to phenanthrene inhibition) has been reported to exhibit a modest (+28 mV) positive shift in voltage dependence of inactivation compared to WT hERG alone [hERG elicited by a command protocol to +20 mV, as used here to evaluate IhERG inhibition. Our data suggest that the profound disturbance of inactivation gating with this mutant adversely affects channel conformation(s) favouring phenanthrene access/binding. Finally, the results of our mutagenesis experiments and docking simulations implicate specific mutations as phenanthrene binding determinants. Thus, the results of this study support a conclusion that phenanthrene acts as a direct hERG channel inhibitor. To our knowledge, the data from this study constitute the most detailed information on the basis of phenanthrene inhibition of any ion channel or electrogenic transporter.Phenanthrene has a simple structure of three fused benzene rings and given its high lipophilicity , a naturresidues , 62. ThiRG alone , the ina modest + mV positRG alone ) and thehERG inhibition (the extent of observed inhibition increased steeply over the range of voltage-dependent activation of the channel), in common with a number of gated-state dependent small molecule inhibitors of hERG that we have studied previously . Thus, the observed facilitation of WT IhERG by phenanthrene at negative test potentials can reasonably be attributed to the leftward shift in voltage dependent activation. A pharmacophore for hERG channel facilitation by inhibitors has been proposed that is comprised of one positively ionizable feature and 3 hydrophobic features [hERG facilitation to occur. It has been recently suggested that facilitation of native IKr by some hERG channel inhibitors may suppress proarrhythmic early afterdepolarizations [Kr and to accelerate deactivation led to a reduction in the native channel’s ability to generate protective outward IKr transients in response to premature stimulation late in repolarization/early in diastole [Phenanthrene exhibited a positive voltage dependence of WT Ily e.g. , 64, 65), 65hERG  protons , 67 or w protons . Intereslleagues –71. Thestivation . Remarkaompounds . Our expion Fig. . Althougizations . Whetherdiastole .hERG(1a) and IzERG deactivation seen here by phenanthrene is unusual, although it is in agreement with recent observations on the effect of phenanthrene on zebrafish native IKr [hERG deactivation precludes a “foot-in-door” inhibitory mechanism in which a compound’s presence in the inner cavity slows closure of the activation gate. The relationship between deactivation acceleration by phenanthrene and the compound’s ability to block the channel appears complex: both N588K and S624A IhERG, which were largely resistant to phenanthrene inhibition, showed little or no effect of the compound on deactivation parameters , consistent with a link between current blocking and deactivation accelerating actions. On the other hand, F557L current was augmented not inhibited by phenanthrene and yet exhibited faster deactivation than in control . hERG1b is identical to hERG1a except for its abbreviated N terminus, which lacks the EAG domain that is known to be important for slow deactivation . The fahERG. Virtually all compounds that have been hitherto investigated have shown a strong dependence on interactions with one or both of S6 Y652 and F656: mutations of these residues typically reduce inhibitory potency [hERG inhibition and the Y652A mutation increased blocking potency. Although Y652A has previously been associated with a modest (+33 mV) positive shift in the voltage dependence inactivation [hERG inactivation at +20 mV (the command voltage used in our standard IhERG protocol) was shown to be similar between WT and Y652A IhERG [50 for capsaicin was four-fold lower for Y652A than for WT IhERG and the F656A mutation did not alter potency [+ channels that hydrophobic pockets can provide inhibitor binding sites away from the K+ permeation path [Perhaps the most surprising results of this study are those pertaining to the likely interaction site through which phenanthrene inhibits I potency , 50. Ind potency . In conttivation , the ext2A IhERG . Consequ2A IhERG . In that potency . Obligat potency . There i modest + mV posit potency , 53, 75.ion path –78.+ permeation path below the selectivity filter is also consistent with the absence of effect of inward K+ current which can suffice to attenuate the effects of blockers that bind within the K+ permeation path [Docking of phenanthrene identifies a site within the side pockets that can accommodate phenanthrene in structures in which the F656 side chain is rotated towards the pore. In other words, the reconfiguration of F656 into a pore-facing orientation creates space for phenanthrene to bind into a site in which interactions with F557 and M651 side chains are made , with substantial inhibition reached by −30 mV and then not further increasing. The voltage dependence of phenanthrene block is thus likely to be associated with a voltage-dependent reorientation of the Y652 side chain [The enhancement of phenanthrene block in the Y652A mutant is less readily explained by the docking analysis although the absence of a requirement for Y652 interactions is consistent with the location for phenanthrene identified by docking guided by mutagenesis Below is the link to the electronic supplementary material.


Cornus mas L.) peel (CCP) was incorporated into a probiotic ice cream formulation containing Bifidobacterium lactis to investigate the potential effect of CCP on the viability of B. lactis in the ice cream after simulated gastrointestinal stress and during 120 days of storage. Furthermore, the effect of the addition of CCP  on bioactive compounds, antioxidant activity, and physicochemical and sensory attributes of the ice cream was evaluated. The results showed that the addition of CCP significantly enhanced vitamin C, total polyphenols, total anthocyanin content, and antioxidant activity of the ice cream. During frozen storage of the ice cream, phenolic compounds and anthocyanins were quite stable, but vitamin C significantly decreased. The addition of CCP had no significant effect on the viability of B. lactis throughout the freezing process, but increments of 6% and 9% CCP increased the viability of B. lactis in the ice cream and after simulated gastrointestinal processes in all storage periods. These findings imply that CCP is a promising candidate to be used for producing functional ice cream.In this study, cornelian cherry ( Ice cream is one of the world’s leading dairy products. It provides vast amounts of calories to users as a frozen dairy dessert with plenty of nutrients . Since iBifidobacterium and Lactobacillus. Bifidobacterium lactis is a probiotic strain of human origin with well-documented beneficial health effects. It promotes the defense against intestinal pathogens and has been consumed largely since 1990 in food products [6 to 109 CFU/g are globally accepted in food [Today, consumers have shown interest in the consumption of functional foods that contain more natural bioactive substances, probiotics, prebiotics, natural flavors, and colorants . As a foproducts . Probiot in food . Incorpo in food .Nowadays, fruit juice industries generate high quantities of by-products and wastes that contain high value-added ingredients with high functionality. Fruit peels are excellent natural sources of phenolic compounds, minerals, vitamins, and fibers, which are important to maintain health status ,10. AmonBifidobacterium lactis. This research assessed the effect of incorporating different concentrations of CCP on the proximate composition, physicochemical and antioxidant activity, and sensory attributes of probiotic ice cream. The survivability of probiotics after freezing and throughout 120 days of storage was determined. Moreover, the protective effect of CCP on the stability and viability of B. lactis to simulated gastrointestinal stress was also investigated.The aim of this investigation was to develop and improve the nutritional value of ice cream using CCP and Bifidobacterium lactis (Bl-04) strain was obtained from DuPont™ Danisco® .Pasteurized skim cow’s milk powder, UHT milk, and cream of milk (30% fat content) were purchased from Letona Dairy Co., . Cornelian cherry fruit, stabilizer , and white sugar were obtained from a local supermarket . The chemical composition of CCP is presented in v/v) with the addition of cream (30% fat). Afterward, 20 kg of the milk was divided into 4 equal portions. For each mix, 5% skim cow’s milk powder, 15% sugar, 0.75% stabilizer  and 0.25% emulsifier (mono-diglycerides-E471) were added. The mixes were pasteurized using the HTST technique at 85 °C for 25 s in a plate heat exchanger and were quickly cooled to 2 °C. For incorporation of probiotic, B. lactis culture was previously dissolved into UHT milk and activated to obtain 109 CFU/mL of bacteria cells in MRS broth. Then, it was added  to the ice cream mix after pasteurization. Cornelian cherries were washed in distilled water and their seeds and peels were manually separated. Cornelian cherry peel (CCP) was ground by utilizing a Juice Fountain Juicer  to obtain a fine puree. Later on, the CCP was added at three different concentrations  into the ice cream mix. The probiotic mix without CCP was considered as the control sample. The whipping-freezing process was applied with an ice cream maker at−6 °C , and the ice creams were hardened at −23 °C for 24 h and kept at −18 °C.Ice creams were produced in the Pilot Plant of the Good Food Institute . The mixes of ice cream were made by adjusting the cow’s milk fat ratio to 6%  with an RV spindle set (No. 2) was employed to determine the viscosity of melted ice creams. Melted ice cream samples (10 g) were mixed with distilled water (90 mL). The pH was measured with a pH meter  after homogenization. Meltdown behavior was determined following the methodology defined by Martinou-Voulasiki and Zerfiridis  with somFor overrun measurement, a container (300 mL) was filled with the ice cream mix and weighed, and the same volume of hardened ice cream was cut and placed in a container with the same volume capacity. The overrun of ice creams (%) was calculated by applying Equation (1) as presented below:The firmness and cohesiveness of the ice creams were determined by a texture analyzer  with a 50 mm cylinder probe. Frozen ice creams were cut into cubes (2 × 2 × 2 cm³) and were pressed at the speed of 5 mm/s. A Minolta colorimeter  was employed to measure the color of samples in the three-dimensional CIE L* a* b* system .The ascorbic acid content of the ice creams was measured with a reflectometer  and an ascorbic acid tester . Ice creams were melted, homogenized for 1 min, and filtered prior to quantification .2CO3 solution (20% w/v). The blend was maintained at room temperature for 20 min, and then the absorbance was recorded at 735 nm [For phenolic content determination, 25 mL of methanol/water solution (1:1) was used for extracting 25 g of melted ice cream for 12 h. The application of the methanol/water solution was able to extract both water and methanol extractable phenolic compounds. The solution was filtered using a Whatman paper (no. 4) in a 10 mL tube; afterwards, 0.2 mL of the sample was added to 1.8 mL distilled water. Folin–Ciocalteu’s phenol reagent (1 mL) was mixed with 2 mL Nag for 10 min. The supernatant (1 mL) was mixed with 1 mol equiv/l HCl (9 mL). The absorbance was determined at 520 nm. The content of total anthocyanin was quantified as the absorbance at 520 nm × 101 × 18.89 (mg/L). The limit of detection (LOD) and limit of quantification (LOQ) concentrations were set using equations, where σ is the standard deviation of the y-intercept and S is the slope of the calibration curve: LOD = 3.3 × σ/S, LOQ = 10 × σ/S.The method of Hwang, Shyu, and Hsu  with somFirst, 20 g of ice cream was extracted with a 10 mL methanol/water solution (1:1) for 12 h. The blend was filtered with Whatman No. 4 paper. DPPH reagent (0.1 mM) was prepared in methanol, then 3.8 mL of this reagent was added to 100 μL of the extract, vortexed in test tubes for 15 s, and followed by incubation of the tubes in the dark for 24 h at room temperature. The color reduction was measured at 515 nm with a spectrophotometer [3, 0.22 g/L CaCl2, and lysozyme 0.01%) in a Stomacher blender for 3 min. Then, 10 mL of electrolyte mixture including 0.3% pepsin was added to the solution. The pH was set to 2.0 by HCl solution (1.0 mol/L), and this mixture was incubated at 37 °C for 1 h. In the intestinal phase, the pH was increased to 7.5 with a sterile alkaline solution including bile (10 g/L) and pancreatin (1 g/L). Finally, the mixture was incubated under anaerobic conditions at 37 °C for 4 h [Briefly, 1 g of ice cream sample was homogenized with 9 mL of sterile electrolyte solution  agar by the pour plating technique. The plates were incubated anaerobically for 48 h at 37 °C. The results were expressed as log CFU/g [The counts of og CFU/g .The sensory attributes of the ice creams were evaluated by 50 semi-trained panelists. Frozen ice creams were evaluated at a serving temperature of −10 °C. Three-digit random codes were assigned to samples, which were assessed regarding color, taste, odor, texture, and overall acceptability based on a 9-point hedonic scale (9 = like extremely and 1 = dislike extremely). Drinking water was supplied to the panelists for rinsing during evaluation.n = 3), which were analyzed by ANOVA and compared by the Duncan test. Differences were considered to be significant for values of p < 0.05.Statistical analysis was performed using SPSS software 23 . Data were expressed as mean values and standard deviations (p < 0.05). The total solid (33.4–36.5%) and ash (0.96–1.42%) content of ice cream increased significantly with the increase in the levels of CCP (p < 0.05). Conversely, the addition of CCP to probiotic ice creams caused a decrease in protein (4.93 to 3.96%) and fat (5.95 to 4.49%) content. The Ca content of the probiotic ice creams was decreased (from 2481 to 2019 mg/kg) by the augmentation with CCP (p < 0.05) [p > 0.05).As can be seen from with CCP . CorneliViscosity is one of the most important factors in ice cream quality and depends on the ice cream structure. High viscosity causes hardening of the cream in the mouth and adhesion on the palate . The visp < 0.05). Additionally, the b* values of samples decreased significantly, from 1.43 to −4.20. In contrast, the a* values in all samples were increased by increasing the level of CCP.A decrease in the pH value was found when the concentration of CCP was increased. Basically, the pH of ice cream was between 6.3 and 6.5. It is also the most important parameter and depends on the protein in the milk, dissolved gases, and mineral salts. The reduction in pH can be ascribed to the presence of different acid compounds in cornelian cherry, such as ascorbic acid and phenolic substances . Sharma In addition to overrun, the ice cream melting rate is also a significant quality index. Firmness values of the probiotic ice creams varied from 182.5 to 322.6 g. Although CCP considerably reduced the ice cream overrun at 6% and 9%, it did not significantly change the firmness of the ice cream at 3%. The addition of CCP decreased the cohesiveness of the ice creams. Texture profiles were in agreement with the findings of Hwang et al. [p < 0.05). Pantelidis et al. [Bioactive compound content and antioxidant activity of probiotic ice cream mixes (0 day), after freezing (first day) and during storage are listed in s et al.  detectedThe results showed that the increment of CCP significantly improved the total phenolic content in ice cream. Phenolic compounds are secondary metabolites and can be found in fruits and vegetables . Enrichmp < 0.05). The cornelian cherry fruits have been indicated as the highest anthocyanin source among different small fruits (223 mg/100 g fw) [In addition, it did not decrease the total polyphenol content because of the freezing of ice cream and storage. For the ice cream control sample, the total anthocyanin content was not found; however, the anthocyanin level ranged from 0 to 0.42 mg/L and was increased significantly by adding CCP to the ice cream (00 g fw) . An incr00 g fw) . MoreoveThe trends for the results obtained from the DPPH radical scavenging assay  were simB. lactis counts in ice cream mixes and frozen ice creams supplemented by CCP during storage and after simulated passage through the gastrointestinal system. The population of B. lactis decreased by 0.94–1.26 log cycles throughout the freezing process. The oxygen is toxic for most probiotic strains, so air incorporation into ice cream throughout freezing may explain the decrease in B. lactis counts. Additionally, the reduction in the probiotic population during the freezing process may result from thermal shock and injuries to bacterial cells [B. lactis during the freezing process, but the increment of 6% and 9% CCP in ice cream increased the viability of B. lactis during 120-day storage and after gastrointestinal simulation. Öztürk, Demirci and Akin [Myrtus communis augmented the survival of Lactobacillus casei in the ice cream during 8 weeks of storage.B. Lactis during storage [Lb. rhamnosus GG added in Amazonian palm berry ice cream exhibited higher viability under simulated gastrointestinal conditions compared to the fresh culture. In this sense, the presence of the food matrix contributed to the probiotic’s viability. In this regard, the high level of bioactive compounds in CCP  may have even assisted probiotic viability. The survival of B. lactis under in vitro simulated gastrointestinal conditions decreased significantly during storage. However, in ice creams supplemented by 6% and 9% CCP and stored for 120 days at −18 °C, the counts were higher than 106 CFU/g, which indicates a synbiotic ice cream. Balthazar et al. [Likewise, the ice cream formulated with Butiá fruit had cryoprotective characteristics that enhanced the viability of  storage . Costa e storage  observedr et al.  found a p < 0.05) affected sensory acceptability. Although the increment of CCP had no significant effect (p > 0.05) on the odor, the scores for color and taste of the probiotic ice cream improved with the increase in CCP concentration. These attributes of probiotic ice cream with 6% and 9% CCP were statistically different from the other samples (p > 0.05). The lowest texture scores were found to be 7.06 in the sample with 9% CCP. The highest overall acceptance scores were observed in ice cream containing 6% CCP, which was followed by 9%, 3% and control samples, respectively. Karaman et al. [As seen in n et al.  also empB. lactis was developed, and it was indicated that using CCP can improve the viscosity, antioxidant activity, and nutritive value of ice cream. In addition, due to the presence of polyphenol compounds, the survival of B. lactis increased during 120 days of storage and in simulated gastrointestinal conditions. It can be concluded that CCP may be considered as a functional ingredient in the formulation of synbiotic ice cream while maintaining sensory acceptability and probiotic viability.Fruit by-products are gaining great importance for our world today. Fruit peel wastes are used as nutritional additives and structure regulators in many areas of industry. It is very important in terms of by-product evaluation that the by-products remaining after the production of fruit juice can be reutilized in foods, as they contain phenolic and antioxidant components. Ice cream is poor in phenolic substances. Therefore, the present study was carried out to improve the functional properties of ice cream by adding cornelian cherry peel as a by-product of the juice industry. In this study, a functional ice cream containing different concentrations of CCP and


IIbβ3 activation, and α-granule secretion, whereas platelet responses to the GPVI agonist collagen-related peptide (CRP-XL) were significantly enhanced. GSK3 single knock-in lines revealed that this divergence is due to differential roles of GSK3α and GSK3β phosphorylation in regulating platelet function. Expression of phosphorylation-resistant GSK3α resulted in enhanced GPVI-mediated platelet activation, whereas expression of phosphorylation-resistant GSK3β resulted in a reduction in PAR-mediated platelet activation and impaired in vitro thrombus formation under flow. Interestingly, the latter was normalised in double GSK3α/β KI mice, indicating that GSK3α KI can compensate for the impairment in thrombosis caused by GSK3β KI. In conclusion, our data indicate that GSK3α and GSK3β have differential roles in regulating platelet function.One of the mechanisms by which PI3 kinase can regulate platelet function is through phosphorylation of downstream substrates, including glycogen synthase kinase-3 (GSK3)α and GSK3β. Platelet activation results in the phosphorylation of an N-terminal serine residue in GSK3α (Ser21) and GSK3β (Ser9), which competitively inhibits substrate phosphorylation. However, the role of phosphorylation of these paralogs is still largely unknown. Here, we employed GSK3α/β phosphorylation-resistant mouse models to explore the role of this inhibitory phosphorylation in regulating platelet activation. Expression of phosphorylation-resistant GSK3α/β reduced thrombin-mediated platelet aggregation, integrin α Phosphoinositide 3-kinase (PI3K) activation occurs downstream of multiple receptors involved in regulating platelet activation, ultimately controlling both thrombosis and haemostasis ,2,3. Thi2) and phosphatidylinositol 3,4,5-trisphosphate , resulting in protein recruitment and activation of downstream signalling pathways. Proteins recruited in human platelets range from adaptor molecules  and small G-proteins  to kinases   were altered using the intracellular Ca2+ indicator FURA-PE3. Stimulation of mouse platelets with thrombin or CRP-XL elicited concentration-dependent increases in intracellular [Ca2+]; however, we observed no significant alterations in the responses in either platelets expressing phosphorylation-resistant GSK3α . The alterations in platelets expressing either phosphorylation-resistant GSK3α or GSK3β could be due to modifications in either the release/generation of these mediators or the response to them. Monitoring the release of ATP with CHRONO-LUME®, however, revealed no significant alterations in δ-granule secretion in either phosphorylation-resistant GSK3α (αKI) or GSK3β (βKI) platelets  for 2 min over collagen, although this did not reach significance A. HoweveIn this study, we investigated the role of agonist-mediated inhibitory GSK3 phosphorylation in regulating platelet function and thrombosis using a phosphorylation-resistant GSK3 knock-in mouse model. Surprisingly, we found divergent roles for phosphorylation of GSK3α at Ser21 and GSK3β at Ser9. The mutation of GSK3α at Ser21 to Ala enhanced platelet activation, whereas the mutation of GSK3β at Ser9 to Ala supressed platelet activation.+/- platelets were found to be hypersensitive to PAR4-AP and the GSK3β+/- mice had increased sensitivity to thrombotic insult i were measured in washed platelets (2 × 108/mL) loaded with Fura-PE3 in the presence of 1 mM CaCl2. Ratiometric measurements (340/380 nm) were taken using an Infinite® 200 PRO multimode reader .Changes in cytosolic [Ca8/mL) using a luciferin/luciferase reagent . Luminescence was measured using an Infinite® 200 PRO multimode reader .Agonist-stimulated δ-granule secretion was assessed by monitoring ATP release from platelets  as previously described [TxAescribed .® μ-Slide VI0.1 flow chambers  connected to an Aladdin AL-1000 syringe pump . Anticoagulated (40 μM PPACK and 2 U/mL heparin) fluorescently labelled  blood was perfused at a constant shear rate of 1000 s− 1 for 2 min over collagen (50 μg/mL fibrillar HORM® collagen). Samples were fixed, and images were captured on a Leica SP5-II CLSM attached to a Leica DMI 6000 inverted epifluorescence microscope. Quantification of surface coverage and thrombus volume was performed using Volocity® 6.1.1 .Whole blood thrombus formation was performed as previously described  using IbData were analysed and fitted using GraphPad Prism 7.04 . All data are presented as the mean ± s.e.m of at least three independent observations. Data presented with statistical analysis were tested as described in the figure legends.


Background: Effective treatment with tissue plasminogen activator (tPA) critically relies on rapid treatment. Door-to-needle time (DNT) is a key measure of hospital efficiency linked to patient outcomes. Numerous changes can reduce DNT, but they are difficult to trial and implement. Discrete-event simulation (DES) provides a way to model and determine the impact of process improvements.Methods: A conceptual framework was developed to illustrate the thrombolysis process; allowing for treatment processes to be replicated using a DES model developed in ARENA. Activity time duration distributions from three sites  were used. Five scenarios, three process changes, and two reductions in activity durations, were simulated and tested. Scenarios were tested individually and in combinations. The primary outcome measure is median DNT. The study goal is to determine the largest improvement in DNT at each site.Results: Administration of tPA in the imaging area resulted in the largest median DNT reduction for Site 1 and Site 2 for individual test scenarios . Ensuring that patients arriving via emergency medical services (EMS) remain on the EMS stretcher to imaging resulted in the largest median DNT improvement for Site 3 . Reducing both the treatment decision time and tPA preparation time by 35% resulted in a 11.0% (95% CI 10.0–12.0%) maximum reduction in median DNT. The lowest median and 90th percentile DNTs were achieved by combining all test scenarios, with a maximum reduction of 26.7% (95% CI 24.5–28.9%) and 17.1% (95% CI 12.5–21.7%), respectively.Conclusions: The detailed conceptual framework clarifies the intra-hospital logistics of the thrombolysis process. The most significant median DNT improvement at rural hospitals resulted from ensuring patients arriving via EMS remain on the EMS stretcher to imaging, while urban sites benefit more from administering tPA in the imaging area. Reducing the durations of activities on the critical path will provide further DNT improvements. Significant DNT improvements are achievable in urban and rural settings by combining process changes with reducing activity durations. Stroke is a devastating disease, but is treatable with alteplase or tissue plasminogen activator (tPA)  and endoSeveral process changes can reduce DNT , 14, butSeveral studies have illustrated the key activities involved in either the pre-hospital or intra-hospital aspects of acute stroke care –29, 33. A conceptual framework was developed first to provide a generalized model for tasks involved in the thrombolysis process within both urban and rural hospitals. This conceptual model was then used to develop a DES model that can be used for both urban and rural hospitals, based on various inputs. This paper includes descriptions of the conceptual framework, the DES model, as well as the test scenarios applied to the three included sites. The authors declare that all supporting data are available within the article and its Site Context section : Patients arriving via EMS remain on EMS stretcher to imaging : Administration of tPA in imaging area (regular and out of hours) (f hours) , 40–42—TProcess change 3 (P3): Pre-registration of patients arriving via EMS : Reduce treatment decision time by 35%—This scenario models a reduction in the time taken for the physician to decide whether the patient will receive thrombolysis treatment by 35%.Reduction in activity duration 2 (R2): Reduce tPA administration preparation time by 35%—This scenario models a reduction in the time taken to complete the preparation required before administering tPA by 35%. Tissue plasminogen activator administration preparation encompasses activities such as: obtaining the drug, estimating the patient's weight, calculating the correct dosing, mixing the tPA, and programming the tPA administration pump.th percentile DNT for patients treated with thrombolysis. This measure is important as it shows the DNT where most (90% of patients) are treated within, and there has been previous justification for the use of this measure in acute stroke processes . The reduction in IQR was also reported. A critical outcomes measure that was included was 90rocesses . The cure 60 min .p-value of < 0.05 was considered statistically significant.The Mann-Whitney U-test and the Chi-Square Goodness-of-Fit test were performed for continuous and categorical variables, respectively. Minitab Statistical Software for Windows  was used for all statistical analysis. A Section 2 Treatment Process Results section of the qualitative study , their arrival rates were adjusted accordingly. The time and day of a patient's arrival in the system can impact their treatment pathway due to resource availability. Regular hours are defined as 8:00 a.m. to 4:00 p.m., Mondays to Fridays, while out of hours are considered all times outside of regular hours. The schedule generates approximately 35% of arrivals in regular hours and 65% during out of hours as determined from our input data. The schedule specifies that the majority of arrivals occur between 8:00 a.m. and 8:00 p.m., with few arrivals between 12:00 a.m. and 8:00 a.m. Human resource and the resulting treatment process differences between regular and out of hours are defined for each site in the ve study . In addive study –6 and move study  can be fThe model activity duration distributions  and arriThe DES has several assumptions and simplifications:Due to the top prioritization of acute stroke patients within a hospital, it is assumed these patients will receive priority for the required resources upon arrival, and that the resources are always available.Patient pathway type assignments (EMS or PV) are independent.The EMS pathway always provides the hospital with pre-notification and pre-identification.Activity durations are independent of each other.All patients in the DES model are eligible to receive thrombolysis treatment.The system may have only a single stroke protocol activation at a time.The model assumes 100% stroke protocol compliance and does not consider personnel dependent variation. Although, it should be noted that waiting for a patient's lab results is not always required to determine the thrombolysis treatment decision, which is reflected in the duration distribution for this activity.There are various reasons based on literature for the established DES assumptions that allow the model to produce meaningful results. Assumption 1 was established due to the Canadian triage and acuity scale (CTAS) level assigned to AIS patients in the qualitative study which provided the foundation for this work . AssumptThe following are model simplifications:Activity durations are independent of the onset to arrival time, meaning durations do not change if a patient is approaching the 4.5-h window.Only AIS patients are included; stroke mimics, and hemorrhagic stroke patients are excluded.Ineligible thrombolysis candidates are not considered.Stroke severity, patient age, and patient sex are not considered.Certain variation in activities may be due to factors included in the assumptions and simplifications listed above; for example, milder stroke patients often have longer treatment times, due to the time taken to determine a diagnosis, and treatment decision. These variations in the associated activities are considered in the distribution of each relevant activity in the DES.The model did not include a warm-up period due to the transient nature of the treatment process being modeled. As randomness exists in all simulation results, a number of replications analysis was conducted to determine the number of runs required to achieve a particular precision of the outcome estimate, summarized in The simulation model was developed using ARENA software .To obtain access to the developed ARENA model, please contact the corresponding author.Ethics approval was obtained from the Nova Scotia Health Research Ethics Board (REB) for this study, with the REB file number 1025975.The model was used to determine the impact of process changes and reduction in activity durations on DNT at each site in comparison to the site-specific baseline DNT. The actual median DNT for Site 1, Site 2, and Site 3 are 50.0, 40.0 and 77.5 min (June 2019–May 2020), with modeled baseline median DNT of 50.0 (IQR 45.4–53.8), 40.1 (IQR 38.7–48.0), and 74.0 (IQR 70.8–82.6) min, respectively. The results of the model baselines and test scenarios are summarized in The results of all scenario experiments are described below and summarized in th percentile DNT results are summarized in Patients Arriving via EMS Remain on EMS Stretcher to Imaging (P1)—As Site 1 and Site 2 were currently implementing this process as their baseline, those sites did not experience an improvement in DNT. This process change did benefit Site 3, and led to the largest improvement for Site 3 across all individual test scenarios. The DNT at Site 3 was reduced to 66.4 (IQR 63.6–75.7) min from a median of 74.0 (IQR 70.8–82.6) min, translating to a 9.2% (95% CI 7.9–10.5%) improvement in DNT compared to the respective site baseline.Administration of tPA in Imaging Area (Regular and Out of Hours) (P2)—Administration of tPA to patients in the imaging area resulted in a reduction of the median DNT for Site 1, Site 2, and Site 3 to 43.7 (IQR 42.2–46.3) min, 36.6 (IQR 34.9–44.6) min, and 71.0 (IQR 66.0–80.3) min, respectively. This scenario was the most impactful individual test result for Site 1 and Site 2, leading to a reduction of 12.6% (95% CI 12.4–12.8%) and 8.2% (95% CI 7.5–9.0%), respectively. It was anticipated that Site 1 would show the largest improvement for this scenario, as Site 1 has the longest travel time to the ED from imaging since it is large tertiary care center.via EMS (P3)Pre-registration of Patients Arriving —As Site 1 and Site 2 include this process in their baseline, those sites did not experience an improvement in DNT. This process change resulted in a DNT of 71.9 (IQR 68.6–80.9) min and a reduction of 1.7% (95% CI 0.3–3.1%) at Site 3.Reduce Treatment Decision Time by 35% (R1)—Physician comfort with treatment with tPA results in a shorter amount of time for making the treatment decision. The reduction in decision time did not reduce Site 1's DNT, highlighting that a bottleneck was present elsewhere. Scenario R1 also had little impact on Site 2, with a 0.5% (95% CI −0.1–1.2%) improvement in DNT. Site 3 experienced a 1.8% (95% CI 1.0–2.7%) improvement, with a DNT of 72.3 (IQR 70.0–76.0) min.Reduce tPA Administration Preparation Time by 35% (R2)—This reduction in activity duration scenario benefitted Site 1 and Site 2 to a greater degree than did R1. The DNT was reduced for Site 1 by 8.6% (95% CI 8.2–9.0%) with a DNT of 45.7 (IQR 42.0–49.1) min. Site 2 improved their DNT by 5.3% (95% CI 4.2–6.5%) with an output of 37.8 (IQR 35.9–48.0) min. The impact of R2 was comparable to R1 for Site 3, with DNT reduction of 1.6% (95% CI −0.2–3.5%) and a DNT of 71.8 (IQR 66.6–81.4) min.Combination of P1, P2, P3—When combining all process change scenarios, Site 3 saw a 15.4% (95% CI 13.1–17.7%) reduction with a DNT of 61.3 (IQR 56.3–72.6) min from a baseline median of 74.0 (IQR 70.8–82.6) min. As Site 1 and Site 2 were currently implementing P1 and P3, their respective results are identical to their P2 results as that was the only new process change for those sites.Combination of R1, R2—Combining the two reductions of activity duration scenarios benefited Site 3 far more than Site 1 and Site 2, whose improvements in this case were largely attributable to R2. The combination of R1 and R2 was equally, or more, effective in terms of improving DNT when compared to being individually tested, due to the close relationship of these activities and the bottleneck formed when adjusted individually. The resulting DNT for Site 1, Site 2, and Site 3 were 45.7 (IQR 42.0– 49.1) min, 36.7 (IQR 35.4–48.0) min, and 65.3 (IQR 62.8–70.6) min, respectively.Combination of P1, P2, P3, R1, R2—As anticipated, the lowest DNT for each site was achieved by combining all test scenarios, which resulted in the following DNTs: Site 1 was reduced by 18.9% (95% CI 18.6–19.1%) to 40.6 (IQR 39.1–43.2) min, Site 2 by 15.9% (95% CI 15.3–16.4%) to 33.6 (IQR 32.4–44.6) min, and Site 3 by 26.7% (95% CI 24.5–28.9) to 52.9 (IQR 49.8–61.2) min.th percentile DNT reduction percentages results which further define the spread of the DNT results. As shown in th percentile DNT experienced in individual test scenarios for Site 1, Site 2 and Site 3, respectively, as shown in th percentile DNT results when considering all individual and combinations of test scenarios were achieved by combining all three process changes and two reduction in activity durations for all sites. When combining all test scenarios, the following 90th percentile DNT improvements were experienced: Site 1 was reduced from 71.3 to 63.0 min , Site 2 was reduced from 62.8 to 56.2 min , and Site 3 was reduced from 92.9 to 82.7 min .In addition to median DNT and DNT reduction percentages results, The developed conceptual framework expands upon published works  to incluth percentile DNT  modelers must understand clinical concepts and have the ability to grasp the pathway logistics; and (2) translate that knowledge into a model for use of testing . This hiA limitation of this study is that the conceptual framework was based on only three hospitals with a small sample size of participants involved at each site in a single Canadian province . Furtherth percentile DNT in urban and rural settings. Our modeling shows that of the three included process changes, the most significant median DNT improvement at rural hospitals resulted from ensuring patients arriving via EMS remain on the EMS stretcher to imaging, while urban sites benefit greater from administering tPA in the imaging area. Reducing the durations of activities found on the critical path will result in further DNT improvements. The lowest median DNTs and 90th percentile DNTs results were achieved by combining all three process changes and two reduction in activity durations for all sites. Significant DNT improvements are achievable in urban and rural settings by combining process changes and reducing activity durations. Based on the results of this study, similar sites can feel confident in achieving desired outcomes when implementing these process improvements. Discrete-event simulation modeling of acute stroke processes can be expanded to develop more accurate models to reveal the ideal processes to achieve the most efficient treatment for patients.The conceptual framework developed in this study defines treatment pathways for AIS patients receiving thrombolysis treatment in urban or rural hospitals. The detail of the framework aims to reduce the gap between clinical knowledge and modeler perceptions regarding the logistics of the intra-hospital aspect of the thrombolysis process. Several process improvements were shown to have a positive impact on median DNT and 90The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author/s.TB: study design, DES modeling, data analysis, preparation of figures and tables, preparation of the first and revised drafts of the manuscript, as well as final editing, and formatting. DV: revision of manuscript for intellectual content. JB: input into the following areas: data analysis, model verification, sensitivity analysis, statistical analysis, as well as revision of manuscript for intellectual content. NK: study design, input into data analysis, editing, formatting, and revision of manuscript for intellectual content. All authors contributed to the article and approved the submitted version.This work was funded by Canadian Institutes of Health Research (CIHR) Project Grant (PJT-169124) held by NK.NK: Founder and part equity owner of DESTINE Health. Principal Investigator for CIHR grant that funded this work. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.